Market orchestration system for facilitating electronic marketplace transactions

Abstract

Systems and methods for configuring and launching a marketplace are described. A method may include identifying an opportunity for a new marketplace, receiving marketplace opportunity data, determining configuration parameters, and determining a feasibility of implementing the new marketplace configuration. An architecture of the new marketplace may be determined, and marketplace objects configured. Data resources and their configuration in a model may be determined and the data resources connected to marketplace objects. The new marketplace may then be launched.

Description

MARKET ORCHESTRATION SYSTEM FOR FACILITATING ELECTRONIC MARKETPLACE TRANSACTIONSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority to PCT Application No.: PCT / US2021 / 042050 (SFTX-0018-WO), filed July 16, 2021, entitled “SYSTEMS AND METHODS FOR CONTROLLING RIGHTS RELATED TO DIGITAL KNOWLEDGE.”

[0002] This application claims the benefit of priority to the following U.S. Provisional Applications: Serial No. 63 / 127,980 (Attorney Docket No. SFTX-0016-P01), filed December 18, 2020, entitled “MARKET ORCHESTRATION SYSTEM FOR FACILITATING ELECTRONIC MARKETPLACE TRANSACTIONS”; Serial No. 63 / 137,690 (SFTX-0019- P01), filed January 14, 2021, entitled “METHODS AND SYSTEMS FOR MANAGEMENT OF DIGITAL KNOWLEDGE”; and Serial No. 63 / 221,903 (Attorney Docket No. SFTX-0019-P02), filed July 14, 2021, entitled “METHODS AND SYSTEMS FOR MANAGEMENT OF DIGITAL KNOWLEDGE.”

[0003] Each of the foregoing applications is incorporated herein by reference in its entirety. BACKGROUND

[0004] Exchanges and other marketplaces provide a range of critical functions for their stakeholders, including the ability to find counterparties who are willing to engage in transactions involving a wide range of asset classes. Among other things, exchange transactions allow parties to unlock liquidity, execute financial strategies (such as with arbitrage), manage risk (such as with options and futures contracts), aggregate capital, convert value from one asset class to another, participate in gains from trade, influence behavior, and obtain insight (such as from data streams about transactions). Successful marketplaces like the New York Stock Exchange (NYSE) and the Chicago Mercantile Exchange (CME) are fundamental components of the global economy, and new exchanges emerge regularly for new categories. Exchanges rely increasingly on information technology infrastructure capabilities for a wide range of core capabilities for trading, presentation, execution, reporting, analytics, reconciliation and other functions, including distributed storage, caching, high speed networking, algorithmic trading, big data, data integration, modeling and analytics, robotic process automation, distributed ledger technologies (DLTs), smart contracts, real-time data collection, search, asset digitization and others. There exists a need in the art to provide intelligent orchestration of markets for a broad and expanding range of asset classes and involving an increasingly diverse set of stakeholders.

[0005] An incredible amount of information is digitally exchanged on a regular basis, and the amount is increasing each day. This information can include valuable and sensitive information, such as trade secrets, know how, patented material, and works of authorship. Some of theinformation is subject to access and control restrictions, such as restrictions on who can view, edit, change, use, transmit, sell, buy, rent, review, license, and source the digital information (e.g., vis-a-vis patent licenses, trademark licenses, contract agreements, copyright licenses, and the like). Setting and enforcing access and control restrictions is difficult, as any computer- based system for doing so has potential flaws, such as risks of impropriety or unreliability of an owner or maintainer of the system, or risks of other parties gaining unauthorized access and illegitimately accessing, copying, editing, or otherwise tampering with the digital knowledge. As such, there is a need for a cryptographically secure blockchain for knowledge system capable of storing digital knowledge and providing convenient and secure control of the same.

[0006] Lending transactions provide financing for a wide variety of needs, ranging from housing and education to corporate and government projects, among many others, while enabling lenders to earn financial returns. However, lending transactions are plagued by a number of problems, including opacity and asymmetry of information, moral hazard induced by shifting of the consequences of risky or inappropriate behavior, complexity of application and negotiation processes, burdensome regulatory and policy regimes, difficulty in determining the value of property that is used as collateral or backing for obligations, difficulty in determining the reliability or financial health of entities, and others.

[0007] Machines and automated agents are increasingly involved in market activities, including for data collection, forecasting, planning, transaction execution, and other activities. This includes increasingly high-performance systems, such as used in high-speed trading. A need exists for methods and systems that improve the machines that enable markets, including for increased efficiency, speed, reliability, and the like for participants in such markets.

[0008] Many markets are increasingly distributed, rather than centralized, with distributed ledgers like Blockchain, peer-to-peer interaction models, and micro-transactions replacing or complementing traditional models that involve centralized authorities or intermediaries. A need exists for improved machines that enable distributed transactions to occur at scale among large numbers of participants, including human participants and automated agents.

[0009] Operations on blockchains, such as ones using cryptocurrency, increasingly require energy-intensive computing operations, such as calculating very large hash functions on growing chains of blocks. Systems using proof-of-work, proof-of-stake, and the like have led to “mining” operations by which computer processing power is applied at a large scale in order to perform calculations that support collective trust in transactions that are recorded in blockchains.

[0010] Many applications of artificial intelligence also require energy-intensive computing operations, such as where very large neural networks, with very large numbers ofinterconnections, perform operations on large numbers of inputs to produce one or more outputs, such as a prediction, classification, optimization, control output, or the like.

[0011] The growth of the Internet of Things and cloud computing platforms have also led to the proliferation of devices, applications, and connections among them, such that data centers, housing servers and other IT components, consume a significant fraction of the energy consumption of the United States and other developed countries.

[0012] As a result of these and other trends, energy consumption has become a major factor in utilization of computing resources, such that energy resources and computing resources (or simply “energy and compute”) have begun to converge from various standpoints, such as requisitioning, purchasing, provisioning, configuration, and management of inputs, activities, outputs, and the like. Projects have been undertaken, for example, to place large scale computing resource facilities, such as Bitcoin™ or other cryptocurrency mining operations, in close proximity to large-scale hydropower sources, such as Niagara Falls.

[0013] A major challenge for facility owners and operators is the uncertainty involved in optimizing a facility, such as resulting from volatility in the cost and availability of inputs (in particular where less stable renewable resources are involved), variability in the cost and availability of computing and networking resources (such as where network performance varies), and volatility and uncertainty in various end markets to which energy and compute resources can be applied (such as volatility in cryptocurrencies, volatility in energy markets, volatility in pricing in various other markets, and uncertainty in the utility of artificial intelligence in a wide range of applications), among other factors.SUMMARY

[0014] Provided herein are methods, systems, and other elements, optionally organized as a platform, for intelligent and automated orchestration of markets, applicable in various embodiments for a broad range of asset classes involving various stakeholders. Market orchestration enables the identification, configuration, and execution of a wide range of marketplace types where goods, services or other items or assets are exchanged. These marketplaces may support traditional asset classes (such as equities, commodities, and bonds) and nontraditional asset classes (such as human-delivered services and entertainment experiences). While traditional marketplaces are established for long periods of time and operate with a consistent set of assets, market orchestration allows for the configuration and execution of a variety of marketplaces with customizable parameters, bringing much needed flexibility to trading.

[0015] Aspects of the present disclosure relates to a method for configuring and launching a marketplace. The method may include identifying, by a processing system, an opportunity tofacilitate a new marketplace. The method may include receiving, by the processing system, marketplace opportunity data. The marketplace opportunity data may include information related to one or more assets. The method may include determining, by the processing system, configuration parameters to be implemented in the new marketplace. The method may include determining, by the processing system, the feasibility of implementing the configuration parameters in the new marketplace. The method may include determining, by the processing system, databases to support the new marketplace. The method may include determining, by the processing system, architecture of the new marketplace. The method may include determining, by the processing system, the design of data within the selected database environment. The method may include configuring, by the processing system, a marketplace object. The method may include connecting, by the processing system, the new marketplace

[0016] Other aspects of the present disclosure relate to a method for configuring role-based market orchestration digital twins. The method may include generating, by a processing system, a digital twin of a marketplace. The digital twin may be a digital representation of the structure of the marketplace. The method may include determining, by the processing system, a set of relationships between different roles within the set of roles based on the marketplace. The method may include determining, by the processing system, a set of settings for a role from the set of roles based on the inferred relationships. The method may include using the inferred relationships within the marketplace structure to provide a set of settings for a set of roles. The method may include linking a set of identities to roles. The method may include determining, by the processing system, a configuration of a presentation layer of a role-based market orchestration digital twin corresponding to the role based on the settings of the at least one role that is linked to the identity. The configuration system of the presentation layer may define a set of states that is depicted in the role-based market orchestration digital twin associated with the role. The method may include determining, by a processing system, a set of data sources that provide data corresponding to the set of states. Each data source may provide one or more respective types of data. The method may include configuring one or more data structures that store the data that is received from the one or more data sources. The one or more data structures may be configured to provide data used to populate one or more of the set of states in the role-based market orchestration digital twin. The method may include linking a set of identities to the set of roles. In embodiments, each identity may correspond to a respective role from the set of roles. In embodiments, a role-based market orchestration digital twin may integrate with a market orchestration platform that operates on the role-based market orchestration digital twin such that changes in the market orchestration platform are automatically reflected in the role-based market orchestration digital twin. In embodiments, the set of settings for the set of roles includes role-based permission settings. Inembodiments, the set of settings for the set of roles includes role-based preference settings. In embodiments, the role-based preference settings are configured based on a set of role-specific templates. In embodiments, the set of templates includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, and a seller template. In embodiments, the set of settings for the set of roles includes role-based taxonomy settings. In embodiments, the taxonomy settings identify a taxonomy that is used to characterize data that is presented in the role-based digital twin, such that the data is presented in a taxonomy that is linked to the role corresponding to the role-based digital twin. In embodiments, the set of taxonomies includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, and a seller template. In embodiments, at least one role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the at least one role is selected from among a market maker role, a market analyst role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role. In embodiments, the role is selected from among a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role.

[0017] Other aspects of the present invention relate to a method for configuring an intelligent agent. The method may include receiving digital twin data from a set of data sources. The digital data may include sensor data that is received from a set of sensors that monitor a set of monitored physical entities associated with a marketplace, the sensor data transported by a set of network entities. The digital data may include marketplace data streams generated by a set of marketplace assets, wherein the marketplace assets include at least one of physical entities associated with the marketplace and digital entities associated with the marketplace. The method may include structuring the digital twin data into a set of digital twin data structures that are configured to serve a plurality of different role-based digital twins. The method may include receiving a request for a role-based digital twin from a client application. In embodiments, the role-based digital twin is configured with respect to a defined role within the marketplace. The method may include determining a subset of the structured digital twin data to corresponds to a set of states that are depicted in the role-based digital twin. The method may include providing the subset of the structured digital twin data to the client application. The method may include receiving intelligent agent training data sets from the client application, each intelligent agent training data set indicating a respective action taken by a user using the client application and one or more featuresthat correspond to the respective action. The method may include training an intelligent agent on behalf of the user based on the intelligent agent training data sets. In embodiments, the intelligent agent is configured to determine actions to be performed on behalf of the user. In embodiments, the determined actions are either recommended to the user or automatically performed on behalf of the user. In embodiments, the role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the role is selected from among a market maker role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role. In embodiments, the role is selected from among a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role. In embodiments, the intelligent agent training data includes interactions training data that indicates a set of interactions with a set of experts by the user during performance of the role. In embodiments, the set of interactions used to train the intelligent agent includes interactions of the user with the physical entities. In embodiments, the set of interactions used to train the intelligent agent includes interactions of the user with the role-based digital twin. In embodiments, wherein the set of interactions used to train the intelligent agent includes interactions of the user with the sensor data as depicted in the role-based digital twin. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the experts with the data streams generated by the physical entities. In embodiments, the set of interactions used to train the intelligent agent system includes interactions of the experts with one or more computational entities. In embodiments, the set of interactions used to train the intelligent agent includes interactions of the user with one or more network entities. In embodiments, the intelligent agent is trained to determine an action selected from the group comprising: selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying the need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset, physically retrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, and order matching. In embodiments, the intelligent agent is trained on a training set of outcomes resulting from the actions taken by the user. In embodiments, the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, afault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome. In embodiments, the intelligent agent is trained to perform an action selected from among determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber-securing a device, cyber- securing a process, cyber-securing a network, cyber-securing a computational resource, cyber- securing equipment, cyber- securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware, configuring a system, configuring a device, configuring a process, configuring a network, configuring a computational resource, configuring equipment, and configuring hardware. In embodiments, the intelligent agent is at least one of trained and configured via feedback from at least one expert in the defined role regarding a set of outputs of the intelligent agent. In embodiments, the set of outputs of the intelligent agent upon which the expert provides feedback includes at least one of a recommendation, a classification, a prediction, a control instruction, an input selection, a protocol selection, a communication, an alert, a target selection for a communication, a data storage selection, a computational selection, a configuration, an event detection, and a forecast. In embodiments, the feedback of the at least one expert is solicited to train the intelligent agent to replicate the expertise of the expert in the role. In embodiments, the feedback of the at least one expert is used to modify the set of inputs to the intelligent agent. In embodiments, the feedback of the at least one expert is used to identify and characterize at leastone error by the intelligent agent. In embodiments, a report on a set of errors is provided to a user of the intelligent agent to enable reconfiguring of the intelligent agent based on the feedback from the expert. In embodiments, the artificial intelligence system includes at least one of removing an input that is the source of the error, reconfiguring a set of nodes of the artificial intelligence system, reconfiguring a set of weights of the artificial intelligence system, reconfiguring a set of outputs of the artificial intelligence system, reconfiguring a processing flow within the artificial intelligence system, and augmenting the set of inputs to the artificial intelligence system. In embodiments, the intelligent agent is trained upon a training set of outcomes and to provide at least one of training and guidance to an individual who performs a defined role in a marketplace. In embodiments, the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome. In embodiments, the method further includes parsing the training data set of interactions to identify a type of processing undertaken by the user in analyzing the set of interactions. In embodiments, the type of processing is selected from the set of audio processing in analyzing audio information, tactile processing, textual information processing, motion processing, visual processing, spatiotemporal processing, mathematical processing, and analytic processing.

[0018] Other aspects of the present disclosure relate to a method for rewarding an expert worker. The method may include taking an information technology architecture that supports a digital twin of a set of physical entities. In embodiments, the information technology architecture includes a set of sensors that provide sensor data about the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing data and a set of network entities for transporting data that is derived from the set of sensors and the set of data streams; and a set of data processing systems for extracting. The method may include transforming and loading the data that is transported by the network entities into a set of resources that are sources for the digital twin. The method may include integrating an artificial intelligence system with the information technology architecture, wherein the artificial intelligence system is configured to operate as a double of an expert worker for a defined role of marketplace. In embodiments, the expert worker is provided with a benefit for training the artificial intelligence system. In embodiments, the benefit is a reward based on the outcomes of the use of the artificial intelligence system. In embodiments, the benefit is a reward based on the productivity of the artificial intelligence system. In embodiments, the benefit is a reward based on a measure of the expertise of the artificial intelligence system. In embodiments, the benefit is ashare of revenue or profit generated by the work of the artificial intelligence system. In embodiments, the reward is administered via a smart contract operating on the blockchain. In embodiments, the artificial intelligence system is trained upon a training set of data that includes a set of interactions by a specific expert worker during performance of the defined role. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the digital twin. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the sensor data. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the data streams generated by the physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the computational entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the expert with the network entities. In embodiments, the artificial intelligence system is trained based on the interactions to determine an action selected from the group consisting of selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying the need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset, physically retrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, and order matching. In embodiments, the training set of interactions is parsed to identify a chain of reasoning of the expert worker upon a set of information and the chain of reasoning is embodied in the configuration of the artificial intelligence system. In embodiments, the chain of reasoning is parsed to identify a type of reasoning of the expert worker and the type of reasoning is used as a basis for configuration of the artificial intelligence system. In embodiments, the chain of reasoning is a deductive chain of reasoning from a set of data. In embodiments, the artificial intelligence system is trained to perform an action selected from among determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing anetwork, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber-securing a device, cyber-securing a process, cyber- securing a network, cyber- securing a computational resource, cyber-securing equipment, cyber-securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware, configuring a system, configuring a device, configuring a process, configuring a network, configuring a computational resource, configuring equipment, and configuring hardware.

[0019] Other aspects of the present disclosure relate to the method of integrating an AI- embodied workforce double into a digital twin data processing architecture. The method may include taking an information technology architecture that supports a digital twin of a set of physical entities. In embodiments, the architecture includes a set of sensors that provide sensor data about the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing data and a set of network entities for transporting data that is derived from the set of sensors and the set of data streams; and a set of data processing systems for extracting, transforming and loading the data that is transported by the network entities into a set of resources that are sources for the digital twin. The method may include integrating an artificial intelligence system with the information technology architecture. In embodiments, the artificial intelligence system is configured to operate as a double of a defined market orchestration workforce involving a defined set of roles of a marketplace. In embodiments, the artificial intelligence system is trained upon a training set of data that includes a set of interactions by members of the defined workforce during performance of the defined set of roles. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the digital twin. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the sensor data. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforcewith the data streams generated by the physical entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the computational entities. In embodiments, the set of interactions used to train the artificial intelligence system includes interactions of the workforce with the network entities. In embodiments, the training set of interactions is parsed to identify a chain of operations of the workforce upon a set of information and the chain of reasoning is embodied in the configuration of the artificial intelligence system. In embodiments, the training set of interactions is parsed to identify a type of processing of the workforce upon a set of information and the type of processing is embodied in the configuration of the artificial intelligence system. In embodiments, the artificial intelligence system is trained based on the interactions to determine an action selected from the group consisting of selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying the need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset, physically retrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, and order matching. In embodiments, the artificial intelligence system is trained on a training set of outcomes. In embodiments, the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome. In embodiments, the artificial intelligence system is at least one of trained and configured via feedback from members of the workforce regarding a set of outputs of the artificial intelligence system. In embodiments, the set of outputs of the artificial intelligence system upon which the workforce members provide feedback includes at least one of a recommendation, a classification, a prediction, a control instruction, an input selection, a protocol selection, a communication, an alert, a target selection for a communication, a data storage selection, a computational selection, a configuration, an event detection, and a forecast. In embodiments, the feedback of the workforce members is solicited to train the artificial intelligence system to replicate the operation of the workforce in the defined set of roles. In embodiments, the feedback of the workforce members is used to modify the set of inputs to the artificial intelligence system. In embodiments, the feedback of the workforce members is used to identify and characterize at least one error by the artificial intelligence system. In embodiments, a report on a set of errors is provided to a manager of the artificial intelligence system to enable reconfiguringof the artificial intelligence system based on the feedback. In embodiments, reconfiguring the artificial intelligence system includes at least one of removing an input that is the source of the error, reconfiguring a set of nodes of the artificial intelligence system, reconfiguring a set of weights of the artificial intelligence system, reconfiguring a set of outputs of the artificial intelligence system, reconfiguring a processing flow within the artificial intelligence system, and augmenting the set of inputs to the artificial intelligence system. In embodiments, the artificial intelligence system is configured to provide at least one of training and guidance to enable the other worker to perform a role within the defined set of roles of the workforce. In embodiments, the artificial intelligence system learns on a training set of outcomes to enhance the training and guidance. In embodiments, the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome. In embodiments, the artificial intelligence system is trained to perform an action selected from among determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber-securing a device, cyber-securing a process, cyber- securing a network, cyber- securing a computational resource, cyber-securing equipment, cyber-securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware, configuring a system, configuring a device, configuring a process, configuring a network,configuring a computational resource, configuring equipment, and configuring hardware. In embodiments, the artificial intelligence system is configured to provide at least one of training and guidance to the workforce to enable the workforce to perform the defined role. In embodiments, the artificial intelligence system learns on a training set of outcomes to enhance the training and guidance. In embodiments, the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome. In embodiments, outcomes are compared between a set of actions of the workforce and a set of outputs of the artificial intelligence system. In embodiments, the comparison is used to train the workforce. In embodiments, the comparison is used to improve the artificial intelligence system. In embodiments, at least one role within the set of roles of the workforce is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, the workforce is a supply chain management workforce. In embodiments, the workforce is a demand planning workforce. In embodiments, the workforce is a logistics planning workforce. In embodiments, the workforce is a vendor management workforce. In embodiments, the workforce is a brokering workforce for a marketplace. In embodiments, the workforce is a trading workforce for a marketplace. In embodiments, the workforce is a trade reconciliation workforce for a marketplace. In embodiments, the workforce is a transactional execution workforce for a marketplace. In embodiments, the computational entities and the network entities are integrated as a converged computational and network entity.

[0020] Other aspects of the present invention relate to a method for configuring a workforce digital twin. The method may include representing an enterprise organizational structure in a digital twin of a digital marketplace orchestration enterprise. The method may include parsing the structure to infer relationships among a set of roles within the organizational structure, the relationships and the roles defining a workforce of the digital marketplace orchestration enterprise. The method may include configuring the presentation layer of a digital twin to represent the digital marketplace orchestration enterprise as a set of workforces having a set of attributes and relationships. In embodiments, the digital twin integrates with a market orchestration platform that operates on a data structure representing a set of roles in the marketplace, such that changes in the market orchestration platform are automatically reflected in the digital twin. In embodiments, the workforce is a brokering workforce for a marketplace. In embodiments, the workforce is a trading workforce for a marketplace. In embodiments, the workforce is a trade reconciliation workforce for a marketplace. In embodiments, the workforceis a transactional execution workforce for a marketplace. In embodiments, at least one workforce role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role. In embodiments, at least one workforce role is selected from among a market maker role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role. In embodiments, the digital twin represents a recommendation for training for the workforce. In embodiments, the digital twin provides a recommendation for augmentation of the workforce. In embodiments, the digital twin provides a recommendation for configuration of a set of operations involving the workforce. In embodiments, the digital twin provides a recommendation for configuration of the workforce.

[0021] Other aspects of the present invention relate to a market orchestration platform that leverages machine learning and artificial intelligence trained to recognize the stage of a marketplace. In embodiments, a machine learning system trains a set of machine-learned models to output a determination related to the stage of a marketplace using training data comprising marketplace features and outcomes. In embodiments, an artificial intelligence system receives a request for a determination related to the stage of the marketplace and generates the determination related to the stage of the marketplace based on the set of machine-learned models and the request. In embodiments, the determination related to the stage of the marketplace is leveraged, at least in part, to automatically adjust parameters of the marketplace. In embodiments, the set of machine- learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term / short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing.

[0022] Other aspects of the present invention relate to a method for updating the properties of market orchestration digital twins. The method may include receiving a request to update one or more properties of one or more digital twins. The method may include retrieving the one or more digital twins required to fulfill the request. The method may include selecting data sources from a set of available data sources. The method may include retrieving data from selected data sources. The method may include updating one or more properties of the one or more digital twins based on the retrieved data. In embodiments, the digital twins are selected from the set of marketplace digital twins, asset digital twins, trader digital twins, broker digital twins, environment digital twins, and marketplace host digital twins. In embodiments, the one or more properties of the one or more digital twins relates to asset ownership. In embodiments, the data source is selected from the set of an Internet of Things connected device, a machine vision system, an analog vibration sensor, a digital vibration sensor, a fixed digital vibration sensor, a tri-axial vibration sensor, a single axis vibration sensor, an optical vibration sensor, and a crosspoint switch.

[0023] Another aspect of the invention relates to a method for generating a fairness score for a set of transactions. The method may include receiving, by a fairness engine, transaction data from an execution engine. The method may include calculating, by the fairness engine, a fairness score representing the fairness of a transaction. In embodiments, the fairness engine may include an execution timing fairness engine that determines or receives a set of measures of latency for a set of users. In embodiments, the execution timing fairness engine automatically orchestrates a set of configuration parameters or other features that mitigate unfairness that may be caused by disparate latency. In embodiments, the set of measures of latency are determined by testing network return times. In embodiments, testing network return times may include determining a ping, an upload speed, or a download speed. In embodiments, the set of transactions are executed based upon the fairness score exceeding a predetermined threshold.

[0024] Other aspects of the present invention relate to a quantum computing system. In embodiments, the quantum computing system is configured to determine a rate of exchange between, among, or across a set of marketplaces by simulating a set of trading activities involving the set of marketplaces. In embodiments, the quantum computing system supports models selected from the set of quantum circuit model, quantum Turing model, adiabatic quantum computer, oneway quantum computer, quantum annealing, quantum cellular autonoma, and hybrids and combinations of the foregoing.

[0025] Another aspect of the invention relates to a counterparty strategy engine. In embodiments, the counterparty strategy engine includes a machine learning system that trains a set of machine- learned models to output a determination related to trading strategies employed by a set of counterparties using training data comprising marketplace features and outcomes. In embodiments, the counterparty strategy engine includes an artificial intelligence system that receives a request for a determination related to the trading strategies employed by the set of counterparties and generates the determination related to the strategies employed by the set of counterparties based on the set of machine-learned models and the request. In embodiments, the trading strategies are selected from the set of buy and hold, long / short equity, asset allocation, intertemporal portfolio choice, pairs trading, swing trading, scalping, day trading, news-based, market timing, social trading, front-running, chart-based, computer- science based, automated / algorithmic, and hybrids and combinations of the foregoing.

[0026] Another aspect of the present disclosure relates to machine learning and / or artificial intelligence systems trained to group similar buyers into a cohort-targeted marketplace. In embodiments, a machine learning system trains a set of machine-learned models to identify a set of similar buyers for a cohort-targeted marketplace using training data comprising marketplace features and outcomes. In embodiments, an artificial intelligence system receives a request toidentify the group of similar buyers, identifies the group of similar buyers, and generates the cohort-targeted marketplace based on the identification. In embodiments, the set of machine- learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term / short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing. In embodiments, content from a set of product websites may be fed to the set of machine-learned models, which are trained to identify new product or service offerings relevant to the cohort-targeted marketplace.

[0027] Another aspect of the present disclosure relates to the quantum computing system configured to connect and direct a neural network development or selection process. In embodiments, the quantum computing system directly programs the weights of a neural network such that the neural network produces desired outputs. In embodiments, the quantum computing system supports models selected from the set of quantum circuit model, quantum Turing model, adiabatic quantum computer, one-way quantum computer, quantum annealing, quantum cellular autonoma, and hybrids and combinations of the foregoing.

[0028] Example embodiments herein disclose systems, procedures, and aspects that provide cryptographically secure blockchains for knowledge systems capable of storing digital knowledge for providing convenient and secure control of the same. Example methods and systems herein provide for improvements in determining property valuation, reliability of financial health of entities, transparency, symmetry of information, and application and negotiation processes in the lending environment. Example methods and systems herein provide for improvements to the machines that enable markets, providing for increased efficiency, speed, and / or reliability for participants in such markets. Example methods and systems herein provide for improvements to data collection, storage and processing, automated configuration of inputs, resource, and outputs, and means for facility optimization for an energy and compute facility.

[0029] In one or more example embodiments, a knowledge distribution system for controlling rights related to digital knowledge is disclosed. The knowledge distribution system may be a blockchain for knowledge system that allows for storage of digital knowledge, buying and selling of digital knowledge, tokenization of digital knowledge, and / or reviewing / auditing of the digital knowledge via a cryptographically secure distributed ledger. Smart contracts may be implemented on the distributed ledger and controlling of rights to digital knowledge, transferring digital knowledge, and adherence of parties to agreements related to the digital knowledge. The blockchain for knowledge system can also facilitate third parties reviewing, auditing, or verifying information related to digital knowledge.

[0030] There can be a number of practical obstacles to the sharing of knowledge such as the absence of trust between parties that could potentially benefit from sharing of the knowledge. Aplatform exists for a digital knowledge distribution system that facilitates orchestration of the sharing of knowledge by providing a high degree of control over the extent to which counterparties can access shared knowledge. Even where knowledge is secure and well- controlled, some types of knowledge are so sensitive that an owner may be unwilling to share the entire set of knowledge with a single counterparty. In embodiments, a platform is disclosed for a digital knowledge distribution system that facilitates handling and control of subsets of knowledge, including automated handling of aggregation of knowledge, or related outputs, that result from division of knowledge subsets.

[0031] The knowledge distribution system may include a ledger management system configured to create and manage a distributed ledger where the distributed ledger may be distributed over nodes of a network and may include blocks linked via cryptography. A smart contract system may be communication with the distributed ledger and may be configured to implement and manage a smart contract via the distributed ledger. The smart contract may be stored in the distributed ledger and may include a triggering event. The smart contract may be configured to perform a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event. The knowledge distribution system may be configured to receive from a user an instance of the digital knowledge. The digital knowledge may be tokenized such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of parties to the smart contract may be processed. The knowledge distribution system may be configured to manage rights of control of and access to the tokenized digital knowledge according to the smart contract and manage the smart contract action in response to the triggering event.

[0032] One or more of the following example features may be included. The digital knowledge may include intellectual property where the smart contract embeds intellectual property licensing terms for intellectual property embedded in the distributed ledger, and where executing an operation on the distributed ledger may provide access to the intellectual property and may process a commitment of a party to the smart contract to the intellectual property licensing terms. A smart contract wrapper on the distributed ledger may allow an operation on the ledger to add intellectual property to an aggregate stack of intellectual property, may allow an operation on the ledger to add intellectual property to agree to an apportionment of royalties among the parties in the ledger, may allow an operation on the ledger to add intellectual property to an aggregate stack of intellectual property, and / or may allow an operation on the ledger to process a commitment of a party to a contract term. The tokenized digital knowledge may include an instruction set. The distributed ledger may be configured to provide provableaccess to the instruction set and execute the instruction set on a system resulting in recording a transaction in the distributed ledger. The tokenized digital knowledge may include executable algorithmic logic, a three-dimensional (3D) printer instruction set, an instruction set for a coating process, an instruction set for a semiconductor fabrication process, a firmware program, an instruction set for a field-programmable gate array, serverless code logic, an instruction set for a crystal fabrication system, an instruction set for a food preparation process, an instruction set for a polymer production process, an instruction set for a chemical synthesis process, an instruction set for a biological production process, a data set for a digital twin, and / or a trade secret with an expert wrapper. The system may be configured to aggregate views of a trade secret into a chain that proves which knowledge recipients of the parties have viewed the trade secret. The knowledge distribution system may include a reporting system configured to report an analytic result based on operations performed on the distributed ledger or the digital knowledge. The distributed ledger may be configured to aggregate a set of instructions where an operation on the distributed ledger may add at least one instruction to a pre-existing set of instructions to provide a modified set of instructions. The smart contract may be configured to manage allocation of instruction sub-sets to the distributed ledger and access to the instruction sub-sets. The distributed ledger may be configured to log parties who have contributed to an instance of the digital knowledge by storing data related to the parties in at least one of the blocks. The knowledge distribution system may be configured to log a source of an instance of the digital knowledge by storing data related to the source in at least one of the blocks. The distributed ledger may be configured such that a private network of authorized participants may establish cryptography-based consensus required for verification of new blocks to be added to the blocks. The ledger management system may be configured to facilitate crowdsourcing of information added to a block of the blocks of the distributed ledger. The distributed ledger may be configured such to store a review of an instance of the digital knowledge by a crowdsourcer in a block of the blocks. The distributed ledger may be configured such to store a signature of an instance of the digital knowledge by a crowdsourcer in a block of the blocks. The distributed ledger may be configured such to store a verification of an instance of the digital knowledge by a crowdsourcer in a block of the blocks. The ledger management system may be configured to establish cryptographic currency tokens that may be tradeable among users of the distributed ledger. The knowledge distribution system may include an account management system in communication with the distributed ledger that may be configured to facilitate creation and management of user accounts related to users of the knowledge distribution system. The knowledge distribution system may include a user interface system in communication with the distributed ledger and may be configured to present a user interface to a user of the knowledgedistribution system where the user interface allows the user to view data related to an instance of the digital knowledge. The knowledge distribution system may include a marketplace system in communication with the distributed ledger and may be configured to establish and maintain a digital marketplace that may be configured to visually present data related to an instance of the digital knowledge to a user of the knowledge distribution system. The knowledge distribution system may include a knowledge datastore in communication with the distributed ledger and may be configured to store data related to the digital knowledge. The knowledge distribution system may include a client datastore in communication with the distributed ledger and may be configured to store data related to users of the knowledge distribution system. The knowledge distribution system may include a smart contract datastore in communication with the distributed ledger and may be configured to store data related to the smart contract. The knowledge distribution system may include a reporting system in communication with the distributed ledger and may be configured to analyze said tokenized digital knowledge and report an analytic result based on the analysis of the tokenized digital knowledge. The smart contract may be generated using a parameterizable smart contract template. The smart contract may include parameters based on type of digital knowledge to be tokenized. The parameters may include financial parameters, royalty parameters, usage parameters, output produced parameters, allocation of consideration parameters, identity parameters, and / or access condition parameters.

[0033] In other example embodiments, a knowledge distribution system may use a distributed ledger and smart contracts to facilitate management and exchange of access, licensing, and ownership rights of digital knowledge.

[0034] In other example embodiments, a computer-implemented method for controlling rights related to digital knowledge is disclosed. The method may include creating and managing a distributed ledger that is distributed over nodes of a network and includes blocks linked via cryptography. A smart contract may be implemented and managed via the distributed ledger where the smart contract may be stored in the distributed ledger and may include a triggering event. A smart contract action may be performed with respect to the digital knowledge in response to an occurrence of the triggering event. An instance of the digital knowledge may be received. The digital knowledge may be tokenized such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of parties to the smart contract may be processed. The method may include management of rights over control of and access to the tokenized digital knowledge according to the smart contract and management of the smart contract action in response to the triggering event.

[0035] One or more of the following example features may be included. A knowledge exchange for the exchange of the tokenized digital knowledge based on the smart contract may be orchestrated. The knowledge exchange of the tokenized digital knowledge may be integrated with another exchange where the knowledge exchange facilitates exchange of valuable and / or sensitive knowledge related to a subject matter of the other exchange.

[0036] In other example embodiments, a knowledge distribution system for controlling rights related to digital knowledge is disclosed. The knowledge distribution system may include a ledger management system configured to create and manage a distributed ledger. The distributed ledger may be distributed over nodes of a network and may include blocks linked via cryptography. A smart contract system may be in communication with the distributed ledger and may be configured to implement and manage a smart contract via the distributed ledger. The smart contract may be stored in the distributed ledger and may include a triggering event. The smart contract may be configured to perform a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event. The knowledge distribution system may be configured to receive from a knowledge provider device an instance of the digital knowledge including a three-dimensional (3D) printer instruction set for 3D printing an object. The digital knowledge may be tokenized such that the instance of the digital knowledge may be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of the knowledge provider and a knowledge recipient of the 3D printer instruction set to the smart contract may be processed. The knowledge distribution system may be configured to manage rights of control of and access to the tokenized digital knowledge according to the smart contract and may manage the smart contract action according to a condition and the triggering event.

[0037] One or more of the following example features may be included. The 3D printer instruction set may include a 3D printing schematic. The object may be at least one of a custom part, a custom product, a manufacturing part, a replacement part, a toy, a medical device, and a tool. The knowledge recipient may use a knowledge recipient device to download and use the 3D printer instruction set. The knowledge recipient device may be at least one of a computing device, a server, a 3D printer, and a manufacturing device. The knowledge recipient may use a knowledge recipient device to purchase the tokenized digital knowledge corresponding to the 3D printer instruction set. The knowledge distribution system may include an event listener configured to listen to an application programming interface (API) that may provide a connection between the knowledge distribution system and a knowledge recipient device of the knowledge recipient. The smart contract may be configured to trigger the condition of the knowledge recipient to make a payment when the 3D printer instruction set may be transferredor used based on the rights of control of and access to the tokenized digital knowledge. The rights of control of and access to the tokenized digital knowledge may include a permission for a user to 3D print using multiple instances of the 3D printer instruction set. The rights of control of and access to the tokenized digital knowledge may include at least one of 3D printer requirements, a time period during which the object can be 3D printed, whether the tokenized digital knowledge is transferred to a downstream knowledge recipient, warranties, disclaimers, indemnifications, and certifications with respect to the object. Information related to the 3D printer instruction set of the tokenized digital knowledge may be modified on the distributed ledger when the 3D printer instruction set is at least one of purchased, downloaded, and used. In examples, information related to the 3D printer instruction set may include at least one of origin, date of creation, names of one or more contributing individuals, groups, and / or companies, pricing, market trends for related schematics, serial numbers, and part identifiers. The smart contract action may be one of an assignment of a serial number to the object that is 3D printed, monitoring for the triggering event, verifying fulfillment of an obligation based on the condition, verifying payment and / or transfer of the tokenized digital knowledge, transferring the tokenized digital knowledge, logging one or more transactions in the distributed ledger, performing one or more operations with respect to the distributed ledger, and creating one or more new blocks in the distributed ledger. The smart contract action may include verifying that the condition is met as defined in the smart contract where the condition may be one of printer requirements, payment received or currency transferred from a knowledge recipient device of the knowledge recipient, and transfer of the tokenized digital knowledge to the knowledge recipient device. When the tokenized digital knowledge may be transferred to a knowledge recipient device of a knowledge recipient, a 3D printer may be configured to print the object according to the 3D printer instruction set. The knowledge distribution system may include a smart contract generator that may be configured to parametrize a smart contract template based on at least one of information provided by the knowledge provider, the condition, and the triggering event.

[0038] In other example embodiments, a computer-implemented method for controlling rights related to digital knowledge is disclosed. The method may include creating and managing a distributed ledger that is distributed over nodes of a network and includes blocks linked via cryptography. A smart contract may be implemented and managed via the distributed ledger where the smart contract may be stored in the distributed ledger and may include a triggering event. A smart contract action may be performed with respect to the digital knowledge in response to an occurrence of the triggering event. The method may include receiving from a knowledge provider device an instance of the digital knowledge that includes a three-dimensional (3D) printer instruction set for 3D printing an object. The digital knowledge may be tokenized such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger. The tokenized digital knowledge may be stored via the distributed ledger. Commitments of the knowledge provider and a knowledge recipient of the 3D printer instruction set to the smart contract may be processed. The method may include management of rights of control of and access to the tokenized digital knowledge according to the smart contract, and management of the smart contract action according to a condition and the triggering event.

[0039] One or more of the following example features may be included. An element of the instance of the digital knowledge via the smart contract may be crowdsourced. The element of the instance of the digital knowledge may be managed by a smart contract system according to the smart contract.

[0040] Provided herein is a lending transaction enablement platform having a set of data- integrated microservices including data collection and monitoring services, blockchain services, and smart contract services for handling lending entities and transactions. The platform is capable of enabling a wide range of dedicated solutions, which may share data collection and storage infrastructure, and which may share or exchange inputs, events, activities, and outputs, such as to reinforce learning, enable automation, and enable adaptive intelligence across the various solutions.

[0041] Aspects of the present disclosure relate to a method for electronically facilitating licensing of one or more personality rights of a licensor. The method may include receiving an access request from a licensee to obtain approval to license personality rights from a set of available licensors. The method may include selectively granting access to the licensee based on the access request. The method may include receiving confirmation of a deposit of an amount of funds from the licensee. The method may include issuing an amount of cryptocurrency corresponding to the amount of funds deposited by the licensee to an account of the licensee. The method may include receiving a smart contract request to create a smart contract governing the licensing of the one or more personality rights of the licensor by the licensee. The smart contract request may indicate one or more terms including a consideration amount of cryptocurrency to be paid to the licensor in exchange for one or more obligations on the licensor. The method may include generating the smart contract based on the smart contract request. The method may include escrowing the consideration amount of cryptocurrency from the account of the licensee. The method may include deploying the smart contract to a distributed ledger. The method may include verifying, by the smart contract, that the licensor has performed the one or more obligations. The method may include, in response to receivingverification that the licensor has performed the one or more obligations, releasing at least a portion of the consideration amount of cryptocurrency into a licensor account of the licensor. The method may include outputting a record indicating a completion of a licensing transaction defined by the smart contract to the distributed ledger.

[0042] Other aspects of the present disclosure relate to a system configured for electronically facilitating licensing of one or more personality rights of a licensor. The system may include one or more hardware processors configured by machine-readable instructions. The processor(s) may be configured to receive an access request from a licensee to obtain approval to license personality rights from a set of available licensors. The processor(s) may be configured to selectively grant access to the licensee based on the access request. The processor(s) may be configured to receive confirmation of a deposit of an amount of funds from the licensee. The processor(s) may be configured to issue an amount of cryptocurrency corresponding to the amount of funds deposited by the licensee to an account of the licensee. The processor(s) may be configured to receive a smart contract request to create a smart contract governing the licensing of the one or more personality rights of the licensor by the licensee. The smart contract request may indicate one or more terms including a consideration amount of cryptocurrency to be paid to the licensor in exchange for one or more obligations on the licensor. The processor(s) may be configured to generate the smart contract based on the smart contract request. The processor(s) may be configured to escrow the consideration amount of cryptocurrency from the account of the licensee. The processor(s) may be configured to deploy the smart contract to a distributed ledger. The processor(s) may be configured to verify, by the smart contract, that the licensor has performed the one or more obligations. The processor(s) may be configured to, in response to receiving verification that the licensor has performed the one or more obligations, release at least a portion of the consideration amount of cryptocurrency into a licensor account of the licensor. The processor(s) may be configured to output a record indicating a completion of a licensing transaction defined by the smart contract to the distributed ledger.

[0043] These and other features, and characteristics of the present technology, as well as the methods of operation and functions of the related elements of structure and the combination of parts and economies of manufacturer, will become more apparent upon consideration of the following description and the appended claims with reference to the accompanying drawings, all of which form a part of this specification, wherein like reference numerals designate corresponding parts in the various figures. It is to be expressly understood, however, that the drawings are for the purpose of illustration and description only and are not intended as a definition of the limits of the invention. As used in the specification and in the claims, the singular form of 'a', 'an', and 'the' include plural referents unless the context clearly dictates otherwise. Amore complete understanding of the disclosure will be appreciated from the description and accompanying drawings and the claims, which follow.BRIEF DESCRIPTION OF THE FIGURES

[0044] The disclosure and the following detailed description of certain embodiments thereof may be understood by reference to the following figures:

[0045] Fig. 1 is a schematic diagram of components of a platform for enabling intelligent transactions in accordance with embodiments of the present disclosure.

[0046] Figs. 2 A and 2B are schematic diagrams of additional components of a platform for enabling intelligent transactions in accordance with embodiments of the present disclosure.

[0047] Fig. 3 is a schematic diagram of additional components of a platform for enabling intelligent transactions in accordance with embodiments of the present disclosure.

[0048] Figs. 4 to Fig. 31 are schematic diagrams of embodiments of neural net systems that may connect to, be integrated in, and be accessible by the platform for enabling intelligent transactions including ones involving expert systems, self-organization, machine learning, artificial intelligence and including neural net systems trained for pattern recognition, for classification of one or more parameters, characteristics, or phenomena, for support of autonomous control, and other purposes in accordance with embodiments of the present disclosure.

[0049] Fig. 32 is a schematic diagram of components of an environment including an intelligent energy and compute facility, a host intelligent energy and compute facility resource management platform, a set of data sources, a set of expert systems, interfaces to a set of market platforms and external resources, and a set of user or client systems and devices in accordance with embodiments of the present disclosure.

[0050] Fig. 33 depicts components and interactions of a transactional, financial and marketplace enablement system.

[0051] Fig. 34 depicts components and interactions of a set of data handling layers of a transactional, financial and marketplace enablement system.

[0052] Fig. 35 depicts adaptive intelligence and robotic process automation capabilities of a transactional, financial and marketplace enablement system.

[0053] Fig. 36 depicts opportunity mining capabilities of a transactional, financial and marketplace enablement system.

[0054] Fig. 37 depicts adaptive edge computation management and edge intelligence capabilities of a transactional, financial and marketplace enablement system.

[0055] Fig. 38 depicts protocol adaptation and adaptive data storage capabilities of a transactional, financial and marketplace enablement system.

[0056] Fig. 39 depicts robotic operational analytic capabilities of a transactional, financial and marketplace enablement system.

[0057] Fig. 40 depicts a blockchain and smart contract platform for a forward market for access rights to events.

[0058] Fig. 41 depicts an algorithm and a dashboard of a blockchain and smart contract platform for a forward market for access rights to events.

[0059] Fig. 42 depicts a blockchain and smart contract platform for forward market demand aggregation.

[0060] Fig. 43 depicts an algorithm and a dashboard of a blockchain and smart contract platform for forward market demand aggregation.

[0061] Fig. 44 depicts a blockchain and smart contract platform for crowdsourcing for innovation.

[0062] Fig. 45 depicts an algorithm and a dashboard of a blockchain and smart contract platform for crowdsourcing for innovation.

[0063] Fig. 46 depicts a blockchain and smart contract platform for crowdsourcing for evidence.

[0064] Fig. 47 depicts an algorithm and a dashboard of a blockchain and smart contract platform for crowdsourcing for evidence.

[0065] Fig. 48 depicts components and interactions of an embodiment of a lending platform having a set of data-integrated microservices including data collection and monitoring services for handling lending entities and transactions.

[0066] Fig. 49 depicts components and interactions of an embodiment of a lending platform in which a set of lending solutions are supported by a data-integrated set of data collection and monitoring services, adaptive intelligent systems, and data storage systems.

[0067] Fig. 50 depicts components and interactions of an embodiment of a lending platform having a set of data integrated blockchain services, smart contract services, social network analytic services, crowdsourcing services and Internet of Things data collection and monitoring services for collecting, monitoring, and processing information about entities involved in or related to a lending transaction.

[0068] Fig. 51 depicts components and interactions of a lending platform having an Internet of Things and sensor platform for monitoring at least one of a set of assets, a set of collateral, and a guarantee for a loan, a bond, or a debt transaction.

[0069] Fig. 52 depicts components and interactions of a lending platform having a crowdsourcing system for collecting information related to entities involved in a lending transaction.

[0070] Fig. 53 depicts an embodiment of a crowdsourcing workflow enabled by a lending platform.

[0071] Fig. 54 depicts components and interactions of an embodiment of a lending platform having a smart contract system that automatically adjusts an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services.

[0072] Fig. 55 depicts components and interactions of an embodiment of a lending platform having a smart contract that automatically restructures debt based on a monitored condition.

[0073] Fig. 56 depicts components and interactions of a lending platform having a set of data collection and monitoring systems for validating the reliability of a guarantee for a loan, including an Internet of Things system and a social network analytics system.

[0074] Fig. 57 depicts components and interactions of a lending platform having a robotic process automation system for negotiation of a set of terms and conditions for a loan.

[0075] Fig. 58 depicts components and interactions of a lending platform having a robotic process automation system for loan collection.

[0076] Fig. 59 depicts components and interactions of a lending platform having a robotic process automation system for consolidating a set of loans.

[0077] Fig. 60 depicts components and interactions of a lending platform having a robotic process automation system for managing a factoring loan.

[0078] Fig. 61 depicts components and interactions of a lending platform having a robotic process automation system for brokering a mortgage loan.

[0079] Fig. 62 depicts components and interactions of a lending platform having a crowdsourcing and automated classification system for validating condition of an issuer for a bond, a social network monitoring system with artificial intelligence for classifying a condition about a bond, and an Internet of Things data collection and monitoring system with artificial intelligence for classifying a condition about a bond.

[0080] Fig. 63 depicts components and interactions of a lending platform having a system that manages the terms and conditions of a loan based on a parameter monitored by the loT, by a parameter determined by a social network analytic system, or a parameter determined by a crowdsourcing system.

[0081] Fig. 64 depicts components and interactions of a lending platform having an automated blockchain custody service for managing a set of custodial assets.

[0082] Fig. 65 depicts components and interactions of a lending platform having an underwriting system for a loan with a set of data-integrated microservices including datacollection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for underwriting lending entities and transactions.

[0083] Fig. 66 depicts components and interactions of a lending platform having a loan marketing system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services and smart contract services for marketing a loan to a set of prospective parties.

[0084] Fig. 67 depicts components and interactions of a lending platform having a rating system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for rating a set of loan-related entities.

[0085] Fig. 68 depicts components and interactions of a lending platform having a regulatory and / or compliance system with a set of data-integrated microservices including data collection and monitoring services, blockchain services, artificial intelligence services, and smart contract services for automatically facilitating compliance with at least one of a law, a regulation and a policy that applies to a lending transaction.

[0086] Fig. 69, depicts a system for automated loan management.

[0087] Fig. 70 depicts a system.

[0088] Fig. 71 depicts a method for handling a loan.

[0089] Fig. 72 depicts a system for adaptive intelligence and robotic process automation capabilities of a transactional, financial and marketplace enablement.

[0090] Fig. 73 depicts a method for automated smart contract creation and collateral assignment.

[0091] Fig. 74 depicts a system for handling a loan.

[0092] Fig. 75 depicts a method for handling a loan.

[0093] Fig. 76 depicts a system for adaptive intelligence and robotic process automation.

[0094] Fig. 77 depicts a method for loan creation and management.

[0095] Fig. 78 depicts a system for adaptive intelligence and robotic process automation capabilities of a transactional, financial and marketplace enablement.

[0096] Fig. 79 depicts a method for robotic process automation of transactional, financial and marketplace activities.

[0097] Fig. 80 depicts a system for adaptive intelligence and robotic process automation.

[0098] Fig. 81 depicts a method for automated transactional, financial and marketplace activities.

[0099] Fig. 82 depicts a system for adaptive intelligence and robotic process.[000100] Fig. 83 depicts a method for performing loan related actions.[000101] Fig. 84 depicts a system for adaptive intelligence and robotic process.[000102] Fig. 85 depicts a method for performing loan related actions.[000103] Fig. 86 depicts a system for adaptive intelligence and robotic process.[000104] Fig. 87 depicts a method for performing loan related actions.[000105] Fig. 88 depicts a smart contract system for managing collateral for a loan.[000106] Fig. 89 depicts a smart contract method for managing collateral for a loan.[000107] Fig. 90 depicts a system for validating conditions of collateral or a guarantor for a loan.[000108] Fig. 91 depicts a crowdsourcing method for validating conditions of collateral or a guarantor for a loan.[000109] Fig. 92 depicts a smart contract system for modifying a loan.[000110] Fig. 93 depicts a smart contract method for modifying a loan.[000111] Fig. 94 depicts a smart contract system for modifying a loan.[000112] Fig. 95 depicts a smart contract method for modifying a loan.[000113] Fig. 96 depicts a smart contract system for modifying a loan.[000114] Fig. 97 depicts a smart contract method for modifying a loan.[000115] Fig. 98 depicts a monitoring system for validating conditions of a guarantee for a loan.[000116] Fig. 99 depicts a monitoring method for validating conditions of a guarantee for a loan.[000117] Fig. 100 depicts a robotic process automation system for negotiating a loan.[000118] Fig. 101 depicts a robotic process automation method for negotiating a loan.[000119] Fig. 102 depicts a system for adaptive intelligence and robotic process automation.[000120] Fig. 103 depicts a loan collection method.[000121] Fig. 104 depicts a system for adaptive intelligence and robotic process automation.[000122] Fig. 105 depicts a loan refinancing method.[000123] Fig. 106 depicts a system for adaptive intelligence and robotic process automation.[000124] Fig. 107 depicts a for loan consolidation method.[000125] Fig. 108 depicts a system for adaptive intelligence and robotic process automation.[000126] Fig. 109 depicts a loan factoring method.[000127] Fig. 110 depicts a system for adaptive intelligence and robotic process automation.[000128] Fig. Ill depicts a mortgage brokering method.[000129] Fig. 112 depicts a system for adaptive intelligence and robotic process automation.[000130] Fig. 113 depicts a method for debt management.[000131] Fig. 114 depicts a system for adaptive intelligence and robotic process automation.[000132] Fig. 115 depicts a method for bond management.[000133] Fig. 116 depicts a system for monitoring a condition of an issuer for a bond.[000134] Fig. 117 depicts a method for monitoring a condition of an issuer for a bond[000135] Fig. 118 depicts a system for monitoring a condition of an issuer for a bond.[000136] Fig. 119 depicts a method for monitoring a condition of an issuer for a bond.[000137] Fig. 120 depicts a system for automatic subsidized loan management.[000138] Fig. 121 depicts a method for automatically modifying subsidized loan terms and conditions.[000139] Fig. 122 depicts a system to automatically modify terms and conditions of a loan.[000140] Fig. 123 depicts a method for collecting social network information about an entity involved in a subsidized loan transaction.[000141] Fig. 124 depicts a system for automating handling of a subsidized loan using crowdsourcing.[000142] Fig. 125 depicts a method for automating handling of a subsidized loan.[000143] Fig. 126 depicts a system for asset access control.[000144] Fig. 127 depicts a method for asset access control.[000145] Fig. 128 depicts a system automated handling of loan foreclosure.[000146] Fig. 129 depicts a method for facilitating foreclosure on collateral.[000147] Fig. 130 depicts an example energy and computing resource platform.[000148] Fig. 131 depicts an example facility data record.[000149] Fig. 132 depicts an example schema of a person data record.[000150] Fig. 133 depicts a cognitive processing system.[000151] Fig. 134 depicts a process for a lead generation system to generate a lead list.[000152] Fig. 135 depicts a process for a lead generation system to determine facility outputs for identified leads.[000153] Fig. 136 depicts a process to generate and output personalized content.[000154] Fig. 137 depicts a schematic illustrating an example of a portion of an information technology system for transaction artificial intelligence leveraging digital twins according to some embodiments of the present disclosure.[000155] Fig. 138 depicts a schematic illustrating a compliance system that facilitates the licensing of personality rights according to some embodiments of the present disclosure.[000156] Fig. 139 depicts a schematic illustrating an example set of components of a compliance system according to some embodiments of the present disclosure.[000157] Fig. 140 depicts a set of operations of a method for vetting a potential licensee for purposes of licensing personality rights of a licensor according to some embodiments of the present disclosure.[000158] Fig. 141 depicts a set of operations of a method for facilitating the licensing of personality rights of a licensor by a licensee according to some embodiments of the present disclosure.[000159] Fig. 142 depicts a set of operations of a method for detecting potential circumvention of rules or regulations by a licensor and / or licensee according to some embodiments of the present disclosure.[000160] Fig. 143 depicts a method for selecting an Al solution.[000161] Fig. 144 depicts a method for selecting an Al solution.[000162] Fig. 145 depicts an example of an assembled Al solution.[000163] Fig. 146 depicts a method for selecting an Al solution.[000164] Fig. 147 depicts a method for selecting an Al solution.[000165] Fig. 148 depicts an Al solution selection and configuration system.[000166] Fig. 149 depicts an Al solution selection and configuration system.[000167] Fig. 150 depicts an Al solution selection and configuration system.[000168] Fig. 151 depicts a component configuration circuit.[000169] Fig. 152 depicts an Al solution selection and configuration system.[000170] Fig. 153 depicts a system for selecting and configuring an artificial intelligence model. [000171] Fig. 154 depicts a method of selecting and configuring an artificial intelligence model. [000172] Fig. 155 is a schematic illustrating examples of architecture of a digital twin system according to embodiments of the present disclosure.[000173] Fig. 156 is a schematic illustrating exemplary components of a digital twin management system according to embodiments of the present disclosure.[000174] Fig. 157 is a schematic illustrating examples of a digital twin I / O system that interfaces with an environment, the digital twin system, and / or components thereof to provide bidirectional transfer of data between coupled components according to embodiments of the present disclosure.[000175] Fig. 158 is a schematic illustrating an example set of identified states related to industrial environments that the digital twin system may identify and / or store for access by intelligent systems (e.g., a cognitive intelligence system) or users of the digital twin system according to embodiments of the present disclosure.[000176] Fig. 159 is a schematic illustrating example embodiments of methods for updating a set of properties of a digital twin of the present disclosure on behalf of a client application and / or one or more embedded digital twins.[000177] Fig. 160 illustrates example embodiments of a display interface of the present disclosure that renders a digital twin of a dryer centrifuge with information relating to the dryer centrifuge.[000178] Fig. 161 is a schematic illustrating an example embodiment of a method for updating a set of vibration fault level states of machine components such as bearings in the digital twin of an industrial machine, on behalf of a client application.[000179] Fig. 162 is a schematic illustrating an example embodiment of a method for updating a set of vibration severity unit values of machine components such as bearings in the digital twin of a machine on behalf of a client application.[000180] Fig. 163 is a schematic illustrating an example embodiment of a method for updating a set of probability of failure values in the digital twins of machine components on behalf of a client application.[000181] Fig. 164 is a schematic illustrating an example embodiment of a method for updating a set of probability of downtime values of machines in the digital twin of a manufacturing facility on behalf of a client application.[000182] Fig. 165 is a schematic illustrating an example embodiment of a method for updating a set of probability of shutdown values of manufacturing facilities in the digital twin of an enterprise on behalf of a client application.[000183] Fig. 166 is a schematic illustrating an example embodiment of a method for updating a set of cost of downtime values of machines in the digital twin of a manufacturing facility.[000184] Fig. 167 is a schematic illustrating an example embodiment of a method for updating one or more manufacturing KPI values in a digital twin of a manufacturing facility, on behalf of a client application.[000185] Fig. 168 is a schematic diagram of components of a knowledge distribution system and a communication network for facilitating management of digital knowledge in accordance with embodiments of the present disclosure.[000186] Fig. 169 is a schematic diagram of a ledger network of the knowledge distribution system in accordance with embodiments of the present disclosure.[000187] Fig. 170 is a schematic diagram of the knowledge distribution system of FIG. 168 including details of a smart contract and a smart contract system of the knowledge distribution system in accordance with embodiments of the present disclosure.[000188] Fig. 171 is a schematic diagram of a plurality of datastores of the knowledge distribution system in accordance with embodiments of the present disclosure.[000189] Fig. 172 illustrates a method of deploying a knowledge token and related smart contract via the knowledge distribution system in accordance with embodiments of the present disclosure.[000190] Fig. 173 illustrates a method of performing high level process flow of a smart contract that distributes digital knowledge via the knowledge distribution system in accordance with embodiments of the present disclosure.[000191] Fig. 174 is a schematic diagram of another embodiment of components of the knowledge distribution system and a communication network for facilitating management of digital knowledge in accordance with embodiments of the present disclosure.[000192] Fig. 175 depicts a knowledge distribution system for controlling rights related to digital knowledge.[000193] Fig. 176 depicts a computer-implemented method for controlling rights related to digital knowledge.[000194] Fig. 177 depicts a computer-implemented method for controlling rights related to digital knowledge.[000195] Fig. 178 depicts a knowledge distribution system for controlling rights related to digital knowledge.[000196] Fig. 179 depicts possible components of a 3D printer instruction set.[000197] Fig. 180 depicts possible content of tokenized digital knowledge.[000198] Fig. 181 depicts possible smart contract actions.[000199] Fig. 182 depicts possible conditions relating to triggering events.[000200] Fig. 183 depicts possible control and access rights.[000201] Fig. 184 depicts possible triggering events.[000202] Fig. 185 depicts a computer-implemented method for controlling rights related to digital knowledge.[000203] Fig. 186 depicts a computer-implemented method for controlling rights related to digital knowledge.[000204] Fig. 187 depicts possible crowdsourced information.[000205] Fig. 188 depicts possible contents of a distributed ledger.[000206] Fig. 189 depicts possible parameters.[000207] Fig. 190 depicts an embodiment of a knowledge distribution system for controlling rights related to digital knowledge.[000208]Figs. 191-196 depict embodiments of operations for controlling rights related to digital knowledge.[000209] Fig. 197 is a diagrammatic view illustrating an example implementation of the knowledge distribution system including a trust network for identifying the likelihood of fraudulent transactions using a consensus trust score and preventing such fraudulent transactions according to some embodiments of the present disclosure.[000210] FIG. 198 illustrates an example method that describes operation of an example trust network illustrated in FIG. 197 according to some embodiments of the present disclosure. [000211] FIG. 199 is a diagrammatic view illustrating a transaction being processed by the ledger network including a plurality of node computing devices according to some embodiments of the present disclosure.[000212] Fig. 200 is a diagrammatic view illustrating an example implementation of the knowledge distribution system including a digital marketplace configured to provide an environment allowing knowledge providers and knowledge recipients to engage in commerce relating to the transfer of digital knowledge according to some embodiments of the present disclosure.[000213] Fig. 201 is a diagrammatic view illustrating an example user interface of a digital marketplace configured to enable transactions and commerce between various users of the knowledge distribution system according to some embodiments of the present disclosure. [000214] FIG. 202 is a schematic view of an exemplary embodiment of the market orchestration system according to some embodiments of the present disclosure.[000215] FIG. 203 is a schematic view of an exemplary embodiment of the market orchestration system including a marketplace configuration system for configuring and launching a marketplace.[000216] FIG. 204 is a schematic illustrating an example embodiment of a method of configuring and launching a marketplace according to some embodiments of the present disclosure.[000217] FIG. 205 is a schematic view of an exemplary embodiment of the market orchestration system including a robotic process automation system configured to automate internal marketplace workflows based on robotic process automation.[000218] FIG. 206 is a schematic view of an exemplary embodiment of the market orchestration system including an edge device configured to perform edge computation and intelligence.[000219] FIG. 207 is a schematic view of an exemplary embodiment of the market orchestration system including a digital twin system configured to integrate a set of adaptive edge computing systems with a market orchestration digital twin.[000220] FIG. 208 is a schematic view of a digital twin system.DETAILED DESCRIPTION[000221] The term services / microservices (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a service / microservice includes any system (or platform) configured to functionally perform the operations of the service, where the system may be data-integrated, including data collection circuits, blockchain circuits, artificial intelligence circuits, and / or smart contract circuits for handling lending entities and transactions. Services / microservices may facilitate data handling and may include facilities for data extraction, transformation and loading; data cleansing and deduplication facilities; data normalization facilities; data synchronization facilities; data security facilities; computational facilities (e.g., for performing pre-defined calculation operations on data streams and providing an output stream); compression and decompression facilities; analytic facilities (such as providing automated production of data visualizations), data processing facilities, and / or data storage facilities (including storage retention, formatting, compression, migration, etc.), and others.[000222] Services / microservices may include controllers, processors, network infrastructure, input / output devices, servers, client devices (e.g., laptops, desktops, terminals, mobile devices, and / or dedicated devices), sensors (e.g., loT sensors associated with one or more entities, equipment, and / or collateral), actuators (e.g., automated locks, notification devices, lights, camera controls, etc.), virtualized versions of any one or more of the foregoing (e.g., outsourced computing resources such as a cloud storage, computing operations; virtual sensors; subscribed data to be gathered such as stock or commodity prices, recordal logs, etc.), and / or include components configured as computer readable instructions that, when performed by a processor, cause the processor to perform one or more functions of the service, etc. Services may be distributed across a number of devices, and / or functions of a service may be performed by one or more devices cooperating to perform the given function of the service.[000223] Services / microservices may include application programming interfaces that facilitate connection among the components of the system performing the service (e.g., microservices) and between the system to entities (e.g., programs, web sites, user devices, etc.) that are external to the system. Without limitation to any other aspect of the present disclosure, example microservices that may be present in certain embodiments include (a) a multi-modal set of data collection circuits that collect information about and monitor entities related to a lending transaction; (b) blockchain circuits for maintaining a secure historical ledger of events related to a loan, the blockchain circuits having access control features that govern access by a set of parties involved in a loan; (c) a set of application programming interfaces, data integration services, data processing workflows and user interfaces for handling loan-related events andloan-related activities; and (d) smart contract circuits for specifying terms and conditions of smart contracts that govern at least one of loan terms and conditions, loan-related events, and loan-related activities. Any of the services / microservices may be controlled by or have control over a controller. Certain systems may not be considered to be a service / microservice. For example, a point of sale device that simply charges a set cost for a good or service may not be a service. In another example, a service that tracks the cost of a good or service and triggers notifications when the value changes may not be a valuation service itself, but may rely on valuation services, and / or may form a portion of a valuation service in certain embodiments. It can be seen that a given circuit, controller, or device may be a service or a part of a service in certain embodiments, such as when the functions or capabilities of the circuit, controller, or device are configured to support a service or microservice as described herein, but may not be a service or part of a service for other embodiments (e.g., where the functions or capabilities of the circuit, controller, or device are not relevant to a service or microservice as described herein). In another example, a mobile device being operated by a user may form a portion of a service as described herein at a first point in time (e.g., when the user accesses a feature of the service through an application or other communication from the mobile device, and / or when a monitoring function is being performed via the mobile device), but may not form a portion of the service at a second point in time (e.g., after a transaction is completed, after the user uninstalls an application, and / or when a monitoring function is stopped and / or passed to another device). Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes or systems, and any such processes or systems may be considered a service (or a part of a service) herein.[000224] One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems from the present disclosure to construct, provide performance characteristics (e.g., bandwidth, computing power, time response, etc.), and / or provide operational capabilities (e.g., time between checks, up-time requirements including longitudinal (e.g., continuous operating time) and / or sequential (e.g., time-of-day, calendar time, etc.), resolution and / or accuracy of sensing, data determinations (e.g., accuracy, timing, amount of data), and / or actuator confirmation capability) of components of the service that are sufficient to provide a given embodiment of a service, platform, and / or microservice as described herein. Certain considerations for the person of skill in the art, in determining the configuration of components, circuits, controllers, and / or devices to implement a service, platform, and / or microservice ("service" in the listing following) as described herein include, without limitation: the balance of capital costs versus operatingcosts in implementing and operating the service; the availability, speed, and / or bandwidth of network services available for system components, service users, and / or other entities that interact with the service; the response time of considerations for the service (e.g., how quickly decisions within the service must be implemented to support the commercial function of the service, the operating time for various artificial intelligence or other high computation operations) and / or the capital or operating cost to support a given response time; the location of interacting components of the service, and the effects of such locations on operations of the service (e.g., data storage locations and relevant regulatory schemes, network communication limitations and / or costs, power costs as a function of the location, support availability for time zones relevant to the service, etc.); the availability of certain sensor types, the related support for those sensors, and the availability of sufficient substitutes (e.g., a camera may require supportive lighting, and / or high network bandwidth or local storage) for the sensing purpose; an aspect of the underlying value of an aspect of the service (e.g., a principal amount of a loan, a value of collateral, a volatility of the collateral value, a net worth or relative net worth of a lender, guarantor, and / or borrower, etc.) including the time sensitivity of the underlying value (e.g., if it changes quickly or slowly relative to the operations of the service or the term of the loan); a trust indicator between parties of a transaction (e.g., history of performance between the parties, a credit rating, social rating, or other external indicator, conformance of activity related to the transaction to an industry standard or other normalized transaction type, etc.); and / or the availability of cost recovery options (e.g., subscriptions, fees, payment for services, etc.) for given configurations and / or capabilities of the service, platform, and / or microservice. Without limitation to any other aspect of the present disclosure, certain operations performed by services herein include: performing real-time alterations to a loan based on tracked data; utilizing data to execute a collateral-backed smart contract; re-evaluating debt transactions in response to a tracked condition or data, and the like. While specific examples of services / microservices and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000225] Without limitation, services include a financial service (e.g., a loan transaction service), a data collection service (e.g., a data collection service for collecting and monitoring data), a blockchain service (e.g., a blockchain service to maintain secure data), data integration services (e.g., a data integration service to aggregate data), smart contract services (e.g., a smart contract service to determine aspects of smart contracts), software services (e.g., a software service to extract data related to the entities from publicly available information sites),crowdsourcing services (e.g., a crowdsourcing service to solicit and report information), Internet of Things services (e.g., an Internet of Things service to monitor an environment), publishing services (e.g., a publishing services to publish data), microservices (e.g., having a set of application programming interfaces that facilitate connection among the microservices), valuation services (e.g., that use a valuation model to set a value for collateral based on information), artificial intelligence services, market value data collection services (e.g., that monitor and report on marketplace information), clustering services (e.g., for grouping the collateral items based on similarity of attributes), social networking services (e.g., that enables configuration with respect to parameters of a social network), asset identification services (e.g., for identifying a set of assets for which a financial institution is responsible for taking custody), identity management services (e.g., by which a financial institution verifies identities and credentials), and the like, and / or similar functional terminology. Example services to perform one or more functions herein include computing devices; servers; networked devices; user interfaces; inter-device interfaces such as communication protocols, shared information and / or information storage, and / or application programming interfaces (APIs); sensors (e.g., loT sensors operationally coupled to monitored components, equipment, locations, or the like); distributed ledgers; circuits; and / or computer readable code configured to cause a processor to execute one or more functions of the service. One or more aspects or components of services herein may be distributed across a number of devices, and / or may consolidated, in whole or part, on a given device. In embodiments, aspects or components of services herein may be implemented at least in part through circuits, such as, in non-limiting examples, a data collection service implemented at least in part as a data collection circuit structed to collect and monitor data, a blockchain service implemented at least in part as a blockchain circuit structured to maintain secure data, data integration services implemented at least in part as a data integration circuit structured to aggregate data, smart contract services implemented at least in part as a smart contract circuit structed to determine aspects of smart contracts, software services implemented at least in part as a software service circuit structured to extract data related to the entities from publicly available information sites, crowdsourcing services implemented at least in part as a crowdsourcing circuit structured to solicit and report information, Internet of Things services implemented at least in part as an Internet of Things circuit structured to monitor an environment, publishing services implemented at least in part as a publishing services circuit structured to publish data, microservice service implemented at least in part as a microservice circuit structured to interconnect a plurality of service circuits, valuation service implemented at least in part as valuation services circuit structured to access a valuation model to set a value for collateral based on data, artificial intelligence service implemented at least in part as an artificialintelligence services circuit, market value data collection service implemented at least in part as market value data collection service circuit structured to monitor and report on marketplace information, clustering service implemented at least in part as a clustering services circuit structured to group collateral items based on similarity of attributes, a social networking service implemented at least in part as a social networking analytic services circuit structured to configure parameters with respect to a social network, asset identification services implemented at least in part as an asset identification service circuit for identifying a set of assets for which a financial institution is responsible for taking custody, identity management services implemented at least in part as an identity management service circuit enabling a financial institution to verify identities and credentials, and the like. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to items and services herein, while in certain embodiments a given system may not be considered with respect to items and services herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and / or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Among the considerations that one of skill in the art may contemplate to determine a configuration for a particular service include: the distribution and access devices available to one or more parties to a particular transaction; jurisdictional limitations on the storage, type, and communication of certain types of information; requirements or desired aspects of security and verification of information communication for the service; the response time of information gathering, inter-party communications, and determinations to be made by algorithms, machine learning components, and / or artificial intelligence components of the service; cost considerations of the service, including capital expenses and operating costs, as well as which party or entity will bear the costs and availability to recover costs such as through subscriptions, service fees, or the like; the amount of information to be stored and / or communicated to support the service; and / or the processing or computing power to be utilized to support the service.[000226] The terms items and services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, items and service include any items and service, including, without limitation, items and services used as a reward, used as collateral, become the subject of a negotiation, and the like, such as, without limitation, an application for a warranty or guarantee with respect to an item that is the subject of a loan, collateral for a loan, or the like, such as a product, a service, an offering, a solution, a physical product, software, a level of service, quality of service, afinancial instrument, a debt, an item of collateral, performance of a service, or other items. Without limitation to any other aspect or description of the present disclosure, items and service include any items and service, including, without limitation, items and services as applied to physical items (e.g., a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property), a financial item (e.g., a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency), a consumable item (e.g., an edible item, a beverage), a highly valued item (e.g., a precious metal, an item of jewelry, a gemstone), an intellectual item (e.g., an item of intellectual property, an intellectual property right, a contractual right), and the like. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered with respect to items and services herein, while in certain embodiments a given system may not be considered with respect to items and services herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and / or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system.[000227] The terms agent, automated agent, and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an agent or automated agent may process events relevant to at least one of the value, the condition, and the ownership of items of collateral or assets. The agent or automated agent may also undertake an action related to a loan, debt transaction, bond transaction, subsidized loan, or the like to which the collateral or asset is subject, such as in response to the processed events. The agent or automated agent may interact with a marketplace for purposes of collecting data, testing spot market transactions, executing transactions, and the like, where dynamic system behavior involves complex interactions that a user may desire to understand, predict, control, and / or optimize. Certain systems may not be considered an agent or an automated agent. For example, if events are merely collected but not processed, the system may not be an agent or automated agent. In some embodiments, if a loan-related action is undertaken not in response to a processed event, it may not have been undertaken by an agent or automated agent. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure include and / or benefit from agents or automated agent. Certain considerations for the person of skill in the art, or embodiments of the present disclosure withrespect to an agent or automated agent include, without limitation: rules that determine when there is a change in a value, condition or ownership of an asset or collateral, and / or rules to determine if a change warrants a further action on a loan or other transaction, and other considerations. While specific examples of market values and marketplace information are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure. [000228] The term marketplace information, market value and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, marketplace information and market value describe a status or value of an asset, collateral, food, or service at a defined point or period in time. Market value may refer to the expected value placed on an item in a marketplace or auction setting, or pricing or financial data for items that are similar to the item, asset, or collateral in at least one public marketplace. For a company, market value may be the number of its outstanding shares multiplied by the current share price. Valuation services may include market value data collection services that monitor and report on marketplace information relevant to the value (e.g., market value) of collateral, the issuer, a set of bonds, and a set of assets, a set of subsidized loans, a party, and the like. Market values may be dynamic in nature because they depend on an assortment of factors, from physical operating conditions to economic climate to the dynamics of demand and supply. Market value may be affected by, and marketplace information may include, proximity to other assets, inventory or supply of assets, demand for assets, origin of items, history of items, underlying current value of item components, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity. In certain embodiments, a market value may include information such as a volatility of a value, a sensitivity of a value (e.g., relative to other parameters having an uncertainty associated therewith), and / or a specific value of the valuated object to a particular party (e.g., an object may have more value as possessed by a first party than as possessed by a second party).[000229] Certain information may not be marketplace information or a market value. For example, where variables related to a value are not market-derived, they may be a value-in-useor an investment value. In certain embodiments, an investment value may be considered a market value (e.g., when the valuating party intends to utilize the asset as an investment if acquired), and not a market value in other embodiments (e.g., when the valuating party intends to immediately liquidate the investment if acquired). One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from marketplace information or a market value. Certain considerations for the person of skill in the art, in determining whether the term market value is referring to an asset, item, collateral, good, or service include: the presence of other similar assets in a marketplace, the change in value depending on location, an opening bid of an item exceeding a list price, and other considerations. While specific examples of market values and marketplace information are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure. [000230] The term apportion value or apportioned value and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, apportion value describes a proportional distribution or allocation of value proportionally, or a process to divide and assign value according to a rule of proportional distribution. Apportionment of the value may be to several parties (e.g., each of the several parties is a beneficiary of a portion of the value), to several transactions (e.g., each of the transactions utilizes a portion of the value), and / or in a many-to-many relationship (e.g., a group of objects has an aggregate value that is apportioned between a number of parties and / or transactions). In some embodiments, the value may be a net loss and the apportioned value is the allocation of a liability to each entity. In other embodiments, apportioned value may refer to the distribution or allocation of an economic benefit, real estate, collateral, or the like. In certain embodiments, apportionment may include a consideration of the value relative to the parties - for example, a $10 million asset apportioned 50 / 50 between two parties, where the parties have distinct value considerations for the asset, may result in one party crediting the apportionment differing resulting values from the apportionment. In certain embodiments, apportionment may include a consideration of the value relative to given transactions - for example, a first type of transaction (e.g., a long-term loan) may have a different valuation of a given asset than a second type of transaction (e.g., a short-term line of credit).[000231] Certain conditions or processes may not relate to apportioned value. For example, the total value of an item may provide its inherent worth, but not how much of the value is held by each identified entity. One of skill in the art, having the benefit of the disclosure herein andknowledge about apportioned value, can readily determine which aspects of the present disclosure will benefit a particular application for apportioned value. Certain considerations for the person of skill in the art, or embodiments of the present disclosure with respect to an apportioned value include, without limitation: the currency of the principal sum, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction / loan amount, the amount of the principal sum, the number of entities owed, the value of the collateral, and the like. While specific examples of apportioned values are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000232] The term financial condition and similar terms as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, financial condition describes a current status of an entity's assets, liabilities, and equity positions at a defined point or period in time. The financial condition may be memorialized in financial statement. The financial condition may further include an assessment of the ability of the entity to survive future risk scenarios or meet future or maturing obligations. Financial condition may be based on a set of attributes of the entity selected from among a publicly stated valuation of the entity, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition of an entity, a foreclosure status of an entity, a contractual default status of an entity, a regulatory violation status of an entity, a criminal status of an entity, an export controls status of an entity, an embargo status of an entity, a tariff status of an entity, a tax status of an entity, a credit report of an entity, a credit rating of an entity, a website rating of an entity, a set of customer reviews for a product of an entity, a social network rating of an entity, a set of credentials of an entity, a set of referrals of an entity, a set of testimonials for an entity, a set of behavior of an entity, a location of an entity, and a geolocation of an entity. A financial condition may also describe a requirement or threshold for an agreement or loan. For example, conditions for allowing a developer to proceed may be various certifications and their agreement to a financial payout. That is, the developer's ability to proceed is conditioned upon a financial element, among others. Certain conditions may not be a financial condition. For example, a credit card balance alone may be a clue as to the financial condition, but may not be the financial condition on its own. In another example, a payment schedule may determine how long a debt may be on an entity's balance sheet, but in a silo may not accurately provide a financial condition. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to thatperson, can readily determine which aspects of the present disclosure include and / or will benefit from a financial condition. Certain considerations for the person of skill in the art, in determining whether the term financial condition is referring to a current status of an entity's assets, liabilities, and equity positions at a defined point or period in time and / or for a given purpose include: the reporting of more than one financial data point, the ratio of a loan to value of collateral, the ratio of the collateral to the loan, the gross trans action / loan amount, the credit scores of the borrower and the lender, and other considerations. While specific examples of financial conditions are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000233] The term interest rate and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, interest rate includes an amount of interest due per period, as a proportion of an amount lent, deposited, or borrowed. The total interest on an amount lent or borrowed may depend on the principal sum, the interest rate, the compounding frequency, and the length of time over which it is lent, deposited, or borrowed. Typically, interest rate is expressed as an annual percentage but can be defined for any time period. The interest rate relates to the amount a bank or other lender charges to borrow its money, or the rate a bank or other entity pays its savers for keeping money in an account. Interest rate may be variable or fixed. For example, an interest rate may vary in accordance with a government or other stakeholder directive, the currency of the principal sum lent or borrowed, the term to maturity of the investment, the perceived default probability of the borrower, supply and demand in the market, the amount of collateral, the status of an economy, or special features like call provisions. In certain embodiments, an interest rate may be a relative rate (e.g., relative to a prime rate, an inflation index, etc.). In certain embodiments, an interest rate may further consider costs or fees applied (e.g., "points") to adjust the interest rate. A nominal interest rate may not be adjusted for inflation while a real interest rate takes inflation into account. Certain examples may not be an interest rate for purposes of particular embodiments. For example, a bank account growing by a fixed dollar amount each year, and / or a fixed fee amount, may not be an example of an interest rate for certain embodiments. One of skill in the art, having the benefit of the disclosure herein and knowledge about interest rates, can readily determine the characteristics of an interest rate for a particular embodiment. Certain considerations for the person of skill in the art, or embodiments of the present disclosure with respect to an interest rate include, without limitation: the currency of the principal sum, variables for setting an interest rate, criteria for modifying an interest rate, the anticipatedtransaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross transaction / loan amount, the amount of the principal sum, the appropriate lifespans of transactions and / or collateral for a particular industry, the likelihood that a lender will sell and / or consolidate a loan before the term, and the like. While specific examples of interest rates are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000234] The term valuation services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a valuation service includes any service that sets a value for a good or service. Valuation services may use a valuation model to set a value for collateral based on information from data collection and monitoring services. Smart contract services may process output from the set of valuation services and assign items of collateral sufficient to provide security for a loan and / or apportion value for an item of collateral among a set of lenders and / or transactions. Valuation services may include artificial intelligence services that may iteratively improve the valuation model based on outcome data relating to transactions in collateral. Valuation services may include market value data collection services that may monitor and report on marketplace information relevant to the value of collateral. Certain processes may not be considered to be a valuation service. For example, a point of sale device that simply charges a set cost for a good or service may not be a valuation service. In another example, a service that tracks the cost of a good or service and triggers notifications when the value changes may not be a valuation service itself, but may rely on valuation services and / or form a part of a valuation service. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a valuation service herein, while in certain embodiments a given service may not be considered a valuation service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to enhance operations of the contemplated system and / or to provide a valuation service. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a valuation service and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: perform real-time alterations to a loan based on a value of a collateral; utilize marketplace data to execute a collateral-backed smart contract; re-evaluate collateral based on a storage condition orgeolocation; the tendency of the collateral to have a volatile value, be utilized, and / or be moved; and the like. While specific examples of valuation services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000235] The term collateral attributes (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, collateral attributes include any identification of the durability (ability of the collateral to withstand wear or the useful life of the collateral), value, identification (does the collateral have definite characteristics that make it easy to identify or market), stability of value (does the collateral maintain value over time), standardization, grade, quality, marketability, liquidity, transferability, desirability, trackability, deliverability (ability of the collateral be delivered or transfer without a deterioration in value), market transparency (is the collateral value easily verifiable or widely agreed upon), physical or virtual. Collateral attributes may be measured in absolute or relative terms, and / or may include qualitative (e.g., categorical descriptions) or quantitative descriptions. Collateral attributes may be different for different industries, products, elements, uses, and the like. Collateral attributes may be assigned quantitative or qualitative values. Values associated with collateral attributes may be based on a scale (such as 1-10) or a relative designation (high, low, better, etc.). Collateral may include various components; each component may have collateral attributes. Collateral may, therefore, have multiple values for the same collateral attribute. In some embodiments, multiple values of collateral attributes may be combined to generate one value for each attribute. Some collateral attributes may apply only to specific portions of collateral. Some collateral attributes, even for a given component of the collateral, may have distinct values depending upon the party of interest (e.g., a party that values an aspect of the collateral more highly than another party) and / or depending upon the type of transaction (e.g., the collateral may be more valuable or appropriate for a first type of loan than for a second type of loan). Certain attributes associated with collateral may not be collateral attributes as described herein depending upon the purpose of the collateral attributes herein. For example, a product may be rated as durable relative to similar products; however, if the life of the product is much lower than the term of a particular loan in consideration, the durability of the product may be rated differently (e.g., not durable) or irrelevant (e.g., where the current inventory of the product is attached as the collateral, and is expected to change out during the term of the loan). Accordingly, the benefits of the present disclosure may be applied to a variety of attributes, and any such attributes may be considered collateral attributes herein, while in certain embodiments a given attribute may not beconsidered a collateral attribute herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated collateral attributes ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular collateral attribute. Certain considerations for the person of skill in the art, in determining whether a contemplated attribute is a collateral attribute and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the source of the attribute and the source of the value of the attribute (e.g. does the attribute and attribute value comes from a reputable source), the volatility of the attribute (e.g. does the attribute values for the collateral fluctuate, is the attribute a new attribute for the collateral), relative differences in attribute values for similar collateral, exceptional values for attributes (e.g., some attribute values may be high, such as, in the 98th percentile or very low, such as in the 2nd percentile, compared to similar class of collateral), the fungibility of the collateral, the type of transaction related to the collateral, and / or the purpose of the utilization of collateral for a particular party or transaction. While specific examples of collateral attributes and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000236] The term blockchain services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, blockchain services include any service related to the processing, recordation, and / or updating of a blockchain, and may include services for processing blocks, computing hash values, generating new blocks in a blockchain, appending a block to the blockchain, creating a fork in the blockchain, merging of forks in the blockchain, verifying previous computations, updating a shared ledger, updating a distributed ledger, generating cryptographic keys, verifying transactions, maintaining a blockchain, updating a blockchain, verifying a blockchain, generating random numbers. The services may be performed by execution of computer readable instructions on local computers and / or by remote servers and computers. Certain services may not be considered blockchain services individually but may be considered blockchain services based on the final use of the service and / or in a particular embodiment - for example, a computing a hash value may be performed in a context outside of a blockchain such in the context of secure communication. Some initial services may be invoked without first being applied to blockchains, but further actions or services in conjunction with the initial services may associate the initial service with aspects of blockchains. For example, a random number may be periodically generated and stored in memory; the random numbers may initially not begenerated for blockchain purposes but may be utilized for blockchains. Accordingly, the benefits of the present disclosure may be applied in a wide variety of services, and any such services may be considered blockchain services herein, while in certain embodiments a given service may not be considered a blockchain service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated blockchain service ordinarily available to that person, can readily determine which aspects of the present disclosure can be configured to implement, and / or will benefit, a particular blockchain service. Certain considerations for the person of skill in the art, in determining whether a contemplated service is a blockchain service and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the application of the service, the source of the service (e.g., if the service is associated with a known or verifiable blockchain service provider), responsiveness of the service (e.g., some blockchain services may have an expected completion time, and / or may be determined through utilization), cost of the service, the amount of data requested for the service, and / or the amount of data generated by the service (blocks of blockchain or keys associated with blockchains may be a specific size or a specific range of sizes). While specific examples of blockchain services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000237] The term blockchain (and variations such as cryptocurrency ledger, and the like) as utilized herein may be understood broadly to describe a cryptocurrency ledger that records, administrates, or otherwise processes online transactions. A blockchain may be public, private, or a combination thereof, without limitation. A blockchain may also be used to represent a set of digital transactions, agreement, terms, or other digital value. Without limitation to any other aspect or description of the present disclosure, in the former case, a blockchain may also be used in conjunction with investment applications, token-trading applications, and / or digital / cryptocurrency based marketplaces. A blockchain can also be associated with rendering consideration, such as providing goods, services, items, fees, access to a restricted area or event, data, or other valuable benefit. Blockchains in various forms may be included where discussing a unit of consideration, collateral, currency, cryptocurrency, or any other form of value. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the value symbolized or represented by a blockchain. While specific examples of blockchains are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerationsunderstood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000238] The terms ledger and distributed ledger (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a ledger may be a document, file, computer file, database, book, and the like which maintains a record of transactions. Ledgers may be physical or digital. Ledgers may include records related to sales, accounts, purchases, transactions, assets, liabilities, incomes, expenses, capital, and the like. Ledgers may provide a history of transactions that may be associated with time. Ledgers may be centralized or decentralized / distributed. A centralized ledger may be a document that is controlled, updated, or viewable by one or more selected entities or a clearinghouse and wherein changes or updates to the ledger are governed or controlled by the entity or clearinghouse. A distributed ledger may be a ledger that is distributed across a plurality of entities, participants or regions which may independently, concurrently, or consensually, update, or modify their copies of the ledger. Ledgers and distributed ledgers may include security measures and cryptographic functions for signing, concealing, or verifying content. In the case of distributed ledgers, blockchain technology may be used. In the case of distributed ledgers implemented using blockchain, the ledger may be Merkle trees comprising a linked list of nodes in which each node contains hashed or encrypted transactional data of the previous nodes. Certain records of transactions may not be considered ledgers. A file, computer file, database, or book may or may not be a ledger depending on what data it stores, how the data is organized, maintained, or secured. For example, a list of transactions may not be considered a ledger if it cannot be trusted or verified, and / or if it is based on inconsistent, fraudulent, or incomplete data. Data in ledgers may be organized in any format such as tables, lists, binary streams of data, or the like which may depend on convenience, source of data, type of data, environment, applications, and the like. A ledger that is shared among various entities may not be a distributed ledger, but the distinction of distributed may be based on which entities are authorized to make changes to the ledger and / or how the changes are shared and processed among the different entities. Accordingly, the benefits of the present disclosure may be applied in a wide variety of data, and any such data may be considered ledgers herein, while in certain embodiments a given data may not be considered a ledger herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated ledgers and distributed ledger ordinarily available to that person, can readily determine which aspects of the present disclosure can be utilized to implement, and / or will benefit a particular ledger. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a ledger and / or whether aspects of the present disclosure can benefit or enhance the contemplatedledger include, without limitation: the security of the data in the ledger (can the data be tampered or modified), the time associated with making changes to the data in the ledger, cost of making changes (computationally and monetarily), detail of data, organization of data (does the data need to be processed for use in an application), who controls the ledger (can the party be trusted or relied to manage the ledger), confidentiality of the data (who can see or track the data in the ledger), size of the infrastructure, communication requirements (distributed ledgers may require a communication interface or specific infrastructure), resiliency. While specific examples of blockchain services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000239] The term loan (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan may be an agreement related to an asset that is borrowed, and that is expected to be returned in kind (e.g., money borrowed, and money returned) or as an agreed transaction (e.g., a first good or service is borrowed, and money, a second good or service, or a combination, is returned). Assets may be money, property, time, physical objects, virtual objects, services, a right (e.g., a ticket, a license, or other rights), a depreciation amount, a credit (e.g., a tax credit, an emissions credit, etc.), an agreed assumption of a risk or liability, and / or any combination thereof. A loan may be based on a formal or informal agreement between a borrower and a lender wherein a lender may provide an asset to the borrower for a predefined amount of time, a variable period of time, or indefinitely. Lenders and borrowers may be individuals, entities, corporations, governments, groups of people, organizations, and the like. Loan types may include mortgage loans, personal loans, secured loans, unsecured loans, concessional loans, commercial loans, microloans, and the like. The agreement between the borrower and the lender may specify terms of the loan. The borrower may be required to return an asset or repay with a different asset than was borrowed. In some cases, a loan may require interest to be repaid on the borrowed asset. Borrowers and lenders may be intermediaries between other entities and may never possess or use the asset. In some embodiments, a loan may not be associated with direct transfer of goods but may be associated with usage rights or shared usage rights. In certain embodiments, the agreement between the borrower and the lender may be executed between the borrower and the lender, and / or executed between an intermediary (e.g., a beneficiary of a loan right such as through a sale of the loan). In certain embodiment, the agreement between the borrower and the lender may be executed through services herein, such as through a smart contract service that determines at least a portion of the terms and conditions of the loans, and in certainembodiments may commit the borrower and / or the lender to the terms of the agreement, which may be a smart contract. In certain embodiments, the smart contract service may populate the terms of the agreement, and present them to the borrower and / or lender for execution. In certain embodiments, the smart contract service may automatically commit one of the borrower or the lender to the terms (at least as an offer) and may present the offer to the other one of the borrower or the lender for execution. In certain embodiments, a loan agreement may include multiple borrowers and / or multiple lenders, for example where a set of loans includes a number of beneficiaries of payment on the set of loans, and / or a number of borrowers on the set of loans. In certain embodiments, the risks and / or obligations of the set of loans may be individualized (e.g., each borrower and / or lender is related to specific loans of the set of loans), apportioned (e.g., a default on a particular loan has an associated loss apportioned between the lenders), and / or combinations of these (e.g., one or more subsets of the set of loans is treated individually and / or apportioned).[000240] Certain agreements may not be considered a loan. An agreement to transfer or borrow assets may not be a loan depending on what assets are transferred, how the assets were transferred, or the parties involved. For example, in some cases, the transfer of assets may be for an indefinite time and may be considered a sale of the asset or a permanent transfer. Likewise, if an asset is borrowed or transferred without clear or definite terms or lack of consensus between the lender and the borrower it may, in some cases, not be considered a loan. An agreement may be considered a loan even if a formal agreement is not directly codified in a written agreement as long as the parties willingly and knowingly agreed to the arrangement, and / or ordinary practices (e.g., in a particular industry) may treat the transaction as a loan. Accordingly, the benefits of the present disclosure may be applied in a wide variety of agreements, and any such agreement may be considered a loan herein, while in certain embodiments a given agreement may not be considered a loan herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about contemplated loans ordinarily available to that person, can readily determine which aspects of the present disclosure implement a loan, utilize a loan, or benefit a particular loan transaction. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan and / or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the value of the assets involved, the ability of the borrower to return or repay the loan, the types of assets involved (e.g., whether the asset is consumed through utilization), the repayment time frame associated with the loan, the interest on the loan, how the agreement of the loan was arranged, formality of the agreement, detail of the agreement, the detail of the agreements of the loan, the collateral attributes associated with the loan, and / or the ordinary business expectations of any ofthe foregoing in a particular context. While specific examples of loans and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000241] The term loan related event(s) (and similar terms, including loan-related events) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan related events may include any event related to terms of the loan or events triggered by the agreement associated with the loan. Loan-related events may include default on loan, breach of contract, fulfillment, repayment, payment, change in interest, late fee assessment, refund assessment, distribution, and the like. Loan-related events may be triggered by explicit agreement terms; for example - an agreement may specify a rise in interest rate after a time period has elapsed from the beginning of the loan; the rise in interest rate triggered by the agreement may be a loan related event. Loan-related events may be triggered implicitly by related loan agreement terms. In certain embodiments, any occurrence that may be considered relevant to assumptions of the loan agreement, and / or expectations of the parties to the loan agreement, may be considered an occurrence of an event. For example, if collateral for a loan is expected to be replaceable (e.g., an inventory as collateral), then a change in inventory levels may be considered an occurrence of a loan related event. In another example, if review and / or confirmation of the collateral is expected, then a lack of access to the collateral, the disablement or failure of a monitoring sensor, etc. may be considered an occurrence of a loan related event. In certain embodiments, circuits, controllers, or other devices described herein may automatically trigger the determination of a loan-related events. In some embodiments, loan-related events may be triggered by entities that manage loans or loan-related contracts. Loan-related events may be conditionally triggered based on one or more conditions in the loan agreement. Loan related events may be related to tasks or requirements that need to be completed by the lender, borrower, or a third party. Certain events may be considered loan- related events in certain embodiments and / or in certain contexts, but may not be considered a loan-related event in another embodiment or context. Many events may be associated with loans but may be caused by external triggers not associated with a loan. However, in certain embodiments, an externally triggered event (e.g., a commodity price change related to a collateral item) may be loan-related events. For example, renegotiation of loan terms initiated by a lender may not be considered a loan related event if the terms and / or performance of the existing loan agreement did not trigger the renegotiation. Accordingly, the benefits of the present disclosure may be applied in a wide variety of events, and any such event may be considered a loan related event herein, while in certain embodiments given events may not beconsidered a loan related event herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure may be considered a loan- related event for the contemplated system and / or for particular transactions supported by the system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan related event and / or whether aspects of the present disclosure can benefit or enhance the contemplated transaction system include, without limitation: the impact of the related event on the loan (events that cause default or termination of the loan may have higher impact), the cost (capital and / or operating) associated with the event, the cost (capital and / or operating) associated with monitoring for an occurrence of the event, the entities responsible for responding to the event, a time period and / or response time associated with the event (e.g., time required to complete the event and time that is allotted from the time the event is triggered to when processing or detection of the event is desired to occur), the entity responsible for the event, the data required for processing the event (e.g., confidential information may have different safeguards or restrictions), the availability of mitigating actions if an undetected event occurs, and / or the remedies available to an at-risk party if the event occurs without detection. While specific examples of loan-related events and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000242] The term loan-related activities (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan related activity may include activities related to the generation, maintenance, termination, collection, enforcement, servicing, billing, marketing, ability to perform, or negotiation of a loan. Loan-related activity may include activities related to the signing of a loan agreement or a promissory note, review of loan documents, processing of payments, evaluation of collateral, evaluation of compliance of the borrower or lender to the loan terms, renegotiation of terms, perfection of security or collateral for the loan, and / or a negation of terms. Loan- related activities may relate to events associated with a loan before formal agreement on the terms, such as activities associated with initial negotiations. Loan-related activities may relate to events during the life of the loan and after the termination of a loan. Loan-related activities may be performed by a lender, borrower, or a third party. Certain activities may not be considered loan related activities services individually but may be considered loan related activities based on the specificity of the activity to the loan lifecycle- for example, billing or invoicing related to outstanding loans may be considered a loan related activity, however when the invoicing orbilling of loans is combined with billing or invoicing for non loan-related elements the invoicing may not be considered a loan related activity. Some activities may be performed in relation to an asset regardless of whether a loan is associated with the asset; in these cases, the activity may not be considered a loan related activity. For example, regular audits related to an asset may occur regardless of whether the asset is associated with a loan and may not be considered a loan related activity. In another example, a regular audit related to an asset may be required by a loan agreement and would not typically occur but for the association with a loan, in this case, the activity may be considered a loan related activity. In some embodiments, activities may be considered loan-related activities if the activity would otherwise not occur if the loan is not active or present, but may still be considered a loan-related activity in some instances (e.g., if auditing occurs normally, but the lender does not have the ability to enforce or review the audit, then the audit may be considered a loan-related activity even though it already occurs otherwise). Accordingly, the benefits of the present disclosure may be applied in a wide variety of events, and any such event may be considered a loan related event herein, while in certain embodiments given events may not be considered a loan related events herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine a loan related activity for the purposes of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan related activity and / or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the necessity of the activity for the loan (can the loan agreement or terms be satisfied without the activity), the cost of the activity, the specificity of the activity to the loan (is the activity similar or identical to other industries), time involved in the activity, the impact of the activity on a loan life cycle, entity performing the activity, amount of data required for the activity (does the activity require confidential information related to the loan, or personal information related to the entities), and / or the ability of parties to enforce and / or review the activity. While specific examples of loan-related events and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000243] The terms loan-terms, loan terms, terms for a loan, terms and conditions, and the like as utilized herein should be understood broadly ("loan terms"). Without limitation to any other aspect or description of the present disclosure, loan terms may relate to conditions, rules, limitations, contract obligations, and the like related to the timing, repayment, origination, and other enforceable conditions agreed to by the borrower and the lender of the loan. Loan termsmay be specified in a formal contract between a borrower and the lender. Loan terms may specify aspects of an interest rate, collateral, foreclose conditions, consequence of debt, payment options, payment schedule, a covenant, and the like. Loan terms may be negotiable or may change during the life of a loan. Loan terms may be change or be affected by outside parameters such as market prices, bond prices, conditions associated with a lender or borrower, and the like. Certain aspects of a loan may not be considered loan terms. In certain embodiments, aspects of loan that have not been formally agreed upon between a lender and a borrower, and / or that are not ordinarily understood in the course of business (and / or the particular industry) may not be considered loan terms. Certain aspects of a loan may be preliminary or informal until they have been formally agreed or confirmed in a contract or a formal agreement. Certain aspects of a loan may not be considered loan terms individually but may not be considered loan terms based on the specificity of the aspect to a specific loan. Certain aspects of a loan may not be considered loan terms at a particular time during the loan, but may be considered loan terms at another time during the loan (e.g., obligations and / or waivers that may occur through the performance of the parties, and / or expiration of a loan term). For example, an interest rate may generally not be considered a loan term until it is defined in relation of a loan and defined as to how the interest compounded (annual, monthly), calculated, and the like. An aspect of a loan may not be considered a term if it is indefinite or unenforceable. Some aspects may be manifestations or related to terms of a loan but may themselves not be the terms. For example, a loan term may be the repayment period of a loan, such as one year. The term may not specify how the loan is to be repaid in the year. The loan may be repaid with 12 monthly payments or one annual payment. A monthly payment plan in this case may not be considered a loan term as it can be just one or many options for repayment not directly specified by a loan. Accordingly, the benefits of the present disclosure may be applied in a wide variety of loan aspects, and any such aspect may be considered a loan term herein, while in certain embodiments given aspects may not be considered loan terms herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure are loan terms for the contemplated system. [000244] Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan term and / or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the enforceability of the terms (can the conditions be enforced by the lender or the lender or the borrower), the cost of enforcing the terms (amount of time, or effort required ensure the conditions are being followed), the complexity of the terms (how easily can they be followed or understood by the parties involved, are the terms error prone or easily misunderstood), entities responsible for the terms, fairness ofthe terms, stability of the terms (how often do they change), observability of the terms (can the terms be verified by a another party), favorability of the terms to one party (do the terms favor the borrower or the lender), risk associated with the loan (terms may depend on the probability that the loan may not be repaid), characteristics of the borrower or lender (their ability to meet the terms), and / or ordinary expectations for the loan and / or related industry.[000245] While specific examples of loan terms are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000246] The term loan conditions, loan-conditions, conditions for a loan, terms and conditions, and the like as utilized herein should be understood broadly ("loan conditions"). Without limitation to any other aspect or description of the present disclosure, loan conditions may relate to rules, limits, and / or obligations related to a loan. Loan conditions may relate to rules or necessary obligations for obtaining a loan, for maintaining a loan, for applying for a loan, for transferring a loan, and the like. Loan conditions may include principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, treatment of collateral, access to collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, conditions related to other debts of the borrower, and a consequence of default.[000247] Certain aspects of a loan may not be considered loan conditions. Aspects of loan that have not been formally agreed upon between a lender and a borrower, and / or that are not ordinarily understood in the course of business (and / or the particular industry), may not be considered loan conditions. Certain aspects of a loan may be preliminary or informal until they have been formally agreed or confirmed in a contract or a formal agreement. Certain aspects of a loan may not be considered loan conditions individually but may be considered loan conditions based on the specificity of the aspect to a specific loan. Certain aspects of a loan may not be considered loan conditions at a particular time during the loan, but may be considered loan conditions at another time during the loan (e.g., obligations and / or waivers that may occur through the performance of the parties, and / or expiration of a loan condition). Accordingly, the benefits of the present disclosure may be applied in a wide variety of loan aspects, and any such aspect may be considered loan conditions herein, while in certain embodiments given aspects may not be considered loan conditions herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to thatperson, can readily determine which aspects of the present disclosure are loan conditions for the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated data is a loan condition and / or whether aspects of the present disclosure can benefit or enhance the contemplated loan include, without limitation: the enforceability of the condition (can the conditions be enforced by the lender or the lender or the borrower), the cost of enforcing the condition (amount of time, or effort required ensure the conditions are being followed), the complexity of the condition (how easily can they be followed or understood by the parties involved, are the conditions error prone or easily misunderstood), entities responsible for the conditions, fairness of the conditions, observability of the conditions (can the conditions be verified by a another party), favorability of the conditions to one party (do the conditions favor the borrower or the lender), risk associated with the loan (conditions may depend on the probability that the loan may not be repaid), and / or ordinary expectations for the loan and / or related industry.[000248] While specific examples of loan conditions are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000249] The term loan collateral, collateral, item of collateral, collateral item, and the like as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a loan collateral may relate to any asset or property that a borrower promises to a lender as backup in exchange for a loan, and / or as security for the loan. Collateral may be any item of value that is accepted as an alternate form of repayment in case of default on a loan. Collateral may include any number of physical or virtual items such as a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Collateral may include more than one item or types of items.[000250] A collateral item may describe an asset, a property, a value, or other item defined as a security for a loan or a transaction. A set of collateral items may be defined, and within that set substitution, removal or addition of collateral items may be affected. For example, a collateral item may be, without limitation: a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory,a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, or an item of personal property, or the like. If a set or plurality of collateral items is defined, substitution, removal or addition of collateral items may be affected, such as substituting, removing, or adding a collateral item to or from a set of collateral items. Without limitation to any other aspect or description of the present disclosure, a collateral item or set of collateral items may also be used in conjunction with other terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. In certain embodiments, a smart contract may calculate whether a borrower has satisfied conditions or covenants and in cases where the borrower has not satisfied such conditions or covenants, may enable automated action, or trigger another conditions or terms that may affect the status, ownership, or transfer of a collateral item, or initiate the substitution, removal, or addition of collateral items to a set of collateral for a loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about collateral items, can readily determine the purposes and use of collateral items in various embodiments and contexts disclosed herein, including the substitution, removal, and addition thereof.[000251] While specific examples of loan collateral are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000252] The term smart contract services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a smart contract service includes any service or application that manages a smart contract or a smart lending contract. For example, the smart contract service may specify terms and conditions of a smart contract, such as in a rules database, or process output from a set of valuation services and assign items of collateral sufficient to provide security for a loan. Smart contract services may automatically execute a set of rules or conditions that embody the smart contract, wherein the execution may be based on or take advantage of collected data. Smart contract services may automatically initiate a demand for payment of a loan, automatically initiate a foreclosure process, automatically initiate an action to claim substitute or backupcollateral or transfer ownership of collateral, automatically initiate an inspection process, automatically change a payment, or interest rate term that is based on the collateral, and may also configure smart contracts to automatically undertake a loan-related action. Smart contracts may govern at least one of loan terms and conditions, loan-related events, and loan-related activities. Smart contracts may be agreements that are encoded as computer protocols and may facilitate, verify, or enforce the negotiation or performance of a smart contract. Smart contracts may or may not be one or more of partially or fully self-executing, or partially or fully selfenforcing.[000253] Certain processes may not be considered to be smart-contract related individually, but may be considered smart-contract related in an aggregated system - for example automatically undertaking a loan-related action may not be smart contract-related in one instance, but in another instance, may be governed by terms of a smart contract. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a smart contract or smart contract service herein, while in certain embodiments a given service may not be considered a smart contract service herein. [000254] One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement a smart contract service and / or enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system includes a smart contract service or smart contract and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to transfer ownership of collateral automatically in response to an event; automated actions available upon a finding of covenant compliance (or lack of compliance); the amenity of the collateral to clustering, re-balancing, distribution, addition, substitution, and removal of items from collateral; the modification parameters of an aspect of a loan in response to an event (e.g., timing, complexity, suitability for the loan type, etc.); the complexity of terms and conditions of loans for the system, including benefits from rapid determination and / or predictions of changes to entities (e.g., in the collateral, a financial condition of a party, offset collateral, and / or in an industry related to a party) related to the loan; the suitability of automated generation of terms and conditions and / or execution of terms and conditions for the types of loans, parties, and / or industries contemplated for the system; and the like. While specific examples of smart contract services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein,and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000255] The term loT system (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, an loT system includes any system of uniquely identified and interrelated computing devices, mechanical and digital machines, sensors, and objects that are able to transfer data over a network without intervention. Certain components may not be considered an loT system individually, but may be considered an loT system in an aggregated system - for example, a single networked.[000256] The sensor, smart speaker, and / or medical device may be not an loT system, but may be a part of a larger system and / or be accumulated with a number of other similar components to be considered an loT system and / or a part of an loT system. In certain embodiments, a system may be considered an loT system for some purposes but not for other purposes - for example, a smart speaker may be considered part of an loT system for certain operations, such as for providing surround sound, or the like, but not part of an loT system for other operations such as directly streaming content from a single, locally networked source. Additionally, in certain embodiments, otherwise similar looking systems may be differentiated in determining whether such systems are loT systems, and / or which type of loT system. For example, one group of medical devices may not, at a given time, be sharing to an aggregated HER database, while another group of medical devices may be sharing data to an aggregate HER for the purposes of a clinical study, and accordingly one group of medical devices may be an loT system, while the other is not. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered an loT system herein, while in certain embodiments a given system may not be considered an loT system herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, how to combine processes and systems from the present disclosure to enhance operations of the contemplated system, and which circuits, controllers, and / or devices include an loT system for the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is an loT system and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: the transmission environment of the system (e.g., availability of low power, inter-device networking); the shared data storage of a group of devices; establishment of a geofence by a group of devices; service as blockchain nodes; the performance of asset, collateral, or entity monitoring; the relay of data between devices; ability to aggregate data froma plurality of sensors or monitoring devices, and the like. While specific examples of loT systems and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000257] The term data collection services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a data collection service includes any service that collects data or information, including any circuit, controller, device, or application that may store, transmit, transfer, share, process, organize, compare, report on and / or aggregate data. The data collection service may include data collection devices (e.g., sensors) and / or may be in communication with data collection devices. The data collection service may monitor entities, such as to identify data or information for collection. The data collection service may be event-driven, run on a periodic basis, or retrieve data from an application at particular points in the application's execution. Certain processes may not be considered to be a data collection service individually, but may be considered a data collection service in an aggregated system - for example, a networked storage device may be a component of a data collection service in one instance, but in another instance, may have stand-alone functionality. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a data collection service herein, while in certain embodiments a given service may not be considered a data collection service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure implement a data collection service and / or to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a data collection service and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to modify a business rule on the fly and alter a data collection protocol; perform real-time monitoring of events; connection of a device for data collection to a monitoring infrastructure, execution of computer readable instructions that cause a processor to log or track events; use of an automated inspection system; occurrence of sales at a networked point-of-sale; need for data from one or more distributed sensors or cameras; and the like. While specific examples of data collection services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefitof the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000258] The term data integration services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a data integration service includes any service that integrates data or information, including any device or application that may extract, transform, load, normalize, compress, decompress, encode, decode, and otherwise process data packets, signals, and other information. The data integration service may monitor entities, such as to identify data or information for integration. The data integration service may integrate data regardless of required frequency, communication protocol, or business rules needed for intricate integration patterns.Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a data integration service herein, while in certain embodiments a given service may not be considered a data integration service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement a data integration service and / or enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a data integration service and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: ability to modify a business rule on the fly and alter a data integration protocol; communication with third party databases to pull in data to integrate with; synchronization of data across disparate platforms; connection to a central data warehouse; data storage capacity, processing capacity, and / or communication capacity distributed throughout the system; the connection of separate, automated workflows; and the like. While specific examples of data integration services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000259] The term computational services (and similar terms) as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, computational services may be included as a part of one or more services, platforms, or microservices, such as blockchain services, data collection services, data integration services, valuation services, smart contract services, data monitoring services, data mining, and / or any service that facilitates collection, access, processing, transformation, analysis, storage,visualization, or sharing of data. Certain processes may not be considered to be a computational service. For example, a process may not be considered a computational service depending on the sorts of rules governing the service, an end product of the service, or the intent of the service. Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes systems, and any such processes or systems may be considered a computational service herein, while in certain embodiments a given service may not be considered a computational service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system and how to combine processes and systems from the present disclosure to implement one or more computational service, and / or to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a computational service and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: agreement-based access to the service; mediate an exchange between different services; provides on demand computational power to a web service; accomplishes one or more of monitoring, collection, access, processing, transformation, analysis, storage, integration, visualization, mining, or sharing of data. While specific examples of computational services and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000260] The term sensor as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, a sensor may be a device, module, machine, or subsystem that detects or measures a physical quality, event, or change. In embodiments, may record, indicate, transmit, or otherwise respond to the detection or measurement. Examples of sensors may be sensors for sensing movement of entities, for sensing temperatures, pressures or other attributes about entities or their environments, cameras that capture still or video images of entities, sensors that collect data about collateral or assets, such as, for example, regarding the location, condition (health, physical, or otherwise), quality, security, possession, or the like. In embodiments, sensors may be sensitive to, but not influential on, the property to be measured but insensitive to other properties. Sensors may be analog or digital. Sensors may include processors, transmitters, transceivers, memory, power, sensing circuit, electrochemical fluid reservoirs, light sources, and the like. Further examples of sensors contemplated for use in the system include biosensors, chemical sensors, black silicon sensor, IR sensor, acoustic sensor, induction sensor, motion sensor, optical sensor, opacity sensor,proximity sensor, inductive sensor, Eddy-current sensor, passive infrared proximity sensor, radar, capacitance sensor, capacitive displacement sensor, hall-effect sensor, magnetic sensor, GPS sensor, thermal imaging sensor, thermocouple, thermistor, photoelectric sensor, ultrasonic sensor, infrared laser sensor, inertial motion sensor, MEMS internal motion sensor, ultrasonic 3D motion sensor, accelerometer, inclinometer, force sensor, piezoelectric sensor, rotary encoders, linear encoders, ozone sensor, smoke sensor, heat sensor, magnetometer, carbon dioxide detector, carbon monoxide detector, oxygen sensor, glucose sensor, smoke detector, metal detector, rain sensor, altimeter, GPS, detection of being outside, detection of context, detection of activity, object detector (e.g. collateral), marker detector (e.g. geo-location marker), laser rangefinder, sonar, capacitance, optical response, heart rate sensor, or an RF / micropower impulse radio (MIR) sensor. In certain embodiments, a sensor may be a virtual sensor - for example determining a parameter of interest as a calculation based on other sensed parameters in the system. In certain embodiments, a sensor may be a smart sensor - for example reporting a sensed value as an abstracted communication (e.g., as a network communication) of the sensed value. In certain embodiments, a sensor may provide a sensed value directly (e.g., as a voltage level, frequency parameter, etc.) to a circuit, controller, or other device in the system. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit from a sensor. Certain considerations for the person of skill in the art, in determining whether a contemplated device is a sensor and / or whether aspects of the present disclosure can benefit from or be enhanced by the contemplated sensor include, without limitation: the conditioning of an activation / deactivation of a system to an environmental quality; the conversion of electrical output into measured quantities; the ability to enforce a geofence; the automatic modification of a loan in response to change in collateral; and the like. While specific examples of sensors and considerations are described herein for purposes of illustration, any system benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000261] The term storage condition and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, storage condition includes an environment, physical location, environmental quality, level of exposure, security measures, maintenance description, accessibility description, and the like related to the storage of an asset, collateral, or an entity specified and monitored in a contract, loan, or agreement or backing the contract, loan or other agreement, and the like. Based on a storage condition of a collateral, an asset, or entity, actions may be taken to, maintain, improve, and / orconfirm a condition of the asset or the use of that asset as collateral. Based on a storage condition, actions may be taken to alter the terms or conditions of a loan or bond. Storage condition may be classified in accordance with various rules, thresholds, conditional procedures, workflows, model parameters, and the like and may be based on self-reporting or on data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analytic services and a set of algorithms for querying network domains, social media data, crowdsourced data, and the like. The storage condition may be tied to a geographic location relating to the collateral, the issuer, the borrower, the distribution of the funds or other geographic locations. Examples of loT data may include images, sensor data, location data, and the like. Examples of social media data or crowdsourced data may include behavior of parties to the loan, financial condition of parties, adherence to a party’s a term or condition of the loan, or bond, or the like. Parties to the loan may include issuers of a bond, related entities, lender, borrower, 3rd parties with an interest in the debt. Storage condition may relate to an asset or type of collateral such as a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a cryptocurrency, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an item of intellectual property, an intellectual property right, a contractual right, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. The storage condition may include an environment where environment may include an environment selected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the storage condition of a collateral, an asset or an entity may include managing, reporting on, altering, syndicating, consolidating, terminating, maintaining, modifying terms and / or conditions, foreclosing an asset, or otherwise handling a loan, contract, or agreement. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated storage condition, can readily determine which aspects of the present disclosure will benefit a particular application for a storage condition. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate storage condition to manage and / or monitor, include, without limitation: the legality of the condition given the jurisdiction of the transaction, the data available for a given collateral, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross trans action / loan amount, the credit scores of the borrower and the lender, ordinarypractices in the industry, and other considerations. While specific examples of storage conditions are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000262] The term geolocation and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, geolocation includes the identification or estimation of the real-world geographic location of an object, including the generation of a set of geographic coordinates (e.g. latitude and longitude) and / or street address. Based on a geolocation of a collateral, an asset, or entity, actions may be taken to maintain or improve a condition of the asset or the use of that asset as collateral. Based on a geolocation, actions may be taken to alter the terms or conditions of a loan or bond. Based on a geolocation, determinations or predictions related to a transaction may be performed - for example based upon the weather, civil unrest in a particular area, and / or local disasters (e.g., an earthquake, flood, tornado, hurricane, industrial accident, etc.). Geolocations may be determined in accordance with various rules, thresholds, conditional procedures, workflows, model parameters, and the like and may be based on self-reporting or on data from Internet of Things devices, data from a set of environmental condition sensors, data from a set of social network analytic services and a set of algorithms for querying network domains, social media data, crowdsourced data, and the like. Examples of geolocation data may include GPS coordinates, images, sensor data, street address, and the like. Geolocation data may be quantitative (e.g., longitude / latitude, relative to a plat map, etc.) and / or qualitative (e.g., categorical such as "coastal", "rural", etc.; "within New York City", etc.). Geolocation data may be absolute (e.g., GPS location) or relative (e.g., within 100 yards of an expected location). Examples of social media data or crowdsourced data may include behavior of parties to the loan as inferred by their geolocation, financial condition of parties inferred by geolocation, adherence of parties to a term or condition of the loan, or bond, or the like. Geolocation may be determined for an asset or type of collateral such as a municipal asset, a vehicle, a ship, a plane, a building, a home, real estate property, undeveloped land, a farm, a crop, a municipal facility, a warehouse, a set of inventory, a commodity, a security, a currency, a token of value, a ticket, a consumable item, an edible item, a beverage, a precious metal, an item of jewelry, a gemstone, an antique, a fixture, an item of furniture, an item of equipment, a tool, an item of machinery, and an item of personal property. Geolocation may be determined for an entity such as one of the parties, a third-party (e.g., an inspection service, maintenance service, cleaning service, etc. relevant to a transaction), or any other entity related to a transaction. The geolocation may include an environmentselected from among a municipal environment, a corporate environment, a securities trading environment, a real property environment, a commercial facility, a warehousing facility, a transportation environment, a manufacturing environment, a storage environment, a home, and a vehicle. Actions based on the geolocation of a collateral, an asset or an entity may include managing, reporting on, altering, syndicating, consolidating, terminating, maintaining, modifying terms and / or conditions, foreclosing an asset, or otherwise handling a loan, contract, or agreement. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system, can readily determine which aspects of the present disclosure will benefit a particular application for a geolocation, and which location aspect of an item is a geolocation for the contemplated system. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate geolocation to manage, include, without limitation: the legality of the geolocation given the jurisdiction of the transaction, the data available for a given collateral, the anticipated transaction type (loan, bond or debt), the specific type of collateral, the ratio of the loan to value, the ratio of the collateral to the loan, the gross trans action / loan amount, the frequency of travel of the borrower to certain jurisdictions and other considerations, the mobility of the collateral, and / or a likelihood of location-specific event occurrence relevant to the transaction (e.g., weather, location of a relevant industrial facility, availability of relevant services, etc.). While specific examples of geolocation are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000263] The term jurisdictional location and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure, jurisdictional location refers to the laws and legal authority governing a loan entity. The jurisdictional location may be based on a geolocation of an entity, a registration location of an entity (e.g. a ship's flag state, a state of incorporation for a business, and the like), a granting state for certain rights such as intellectual priority, and the like. In certain embodiments, a jurisdictional location may be one or more of the geolocations for an entity in the system. In certain embodiments, a jurisdictional location may not be the same as the geolocation of any entity in the system (e.g., where an agreement specifies some other jurisdiction). In certain embodiments, a jurisdictional location may vary for entities in the system (e.g., borrower at A, lender at B, collateral positioned at C, agreement enforced at D, etc.). In certain embodiments, a jurisdictional location for a given entity may vary during the operations of the system (e.g., due to movement of collateral, related data, changes in terms and conditions, etc.). In certainembodiments, a given entity of the system may have more than one jurisdictional location (e.g., due to operations of the relevant law, and / or options available to one or more parties), and / or may have distinct jurisdictional locations for different purposes. A jurisdictional location of an item of collateral, an asset, or entity, actions may dictate certain terms or conditions of a loan or bond, and / or may indicate different obligations for notices to parties, foreclosure and / or default execution, treatment of collateral and / or debt security, and / or treatment of various data within the system. While specific examples of jurisdictional location are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein are specifically contemplated within the scope of the present disclosure.[000264] The terms token of value, token, and variations such as cryptocurrency token, and the like, as utilized herein, in the context of increments of value, may be understood broadly to describe either: (a) a unit of currency or cryptocurrency (e.g. a cryptocurrency token), and (b) may also be used to represent a credential that can be exchanged for a good, service, data or other valuable consideration (e.g. a token of value). Without limitation to any other aspect or description of the present disclosure, in the former case, a token may also be used in conjunction with investment applications, token-trading applications, and token-based marketplaces. In the latter case, a token can also be associated with rendering consideration, such as providing goods, services, fees, access to a restricted area or event, data, or other valuable benefit. Tokens can be contingent (e.g. contingent access token) or not contingent. For example, a token of value may be exchanged for accommodations, (e.g. hotel rooms), dining / food goods and services, space (e.g. shared space, workspace, convention space, etc.), fitness / wellness goods or services, event tickets or event admissions, travel, flights or other transportation, digital content, virtual goods, license keys, or other valuable goods, services, data, or consideration. Tokens in various forms may be included where discussing a unit of consideration, collateral, or value, whether currency, cryptocurrency, or any other form of value such as goods, services, data, or other benefits. One of skill in the art, having the benefit of the disclosure herein and knowledge about a token, can readily determine the value symbolized or represented by a token, whether currency, cryptocurrency, good, service, data, or other value. While specific examples of tokens are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [000265] The term pricing data as utilized herein may be understood broadly to describe a quantity of information such as a price or cost, of one or more items in a marketplace. Without limitation to any other aspect or description of the present disclosure, pricing data may also beused in conjunction with spot market pricing, forward market pricing, pricing discount information, promotional pricing, and other information relating to the cost or price of items. Pricing data may satisfy one or more conditions, or may trigger application of one or more rules of a smart contract. Pricing data may be used in conjunction with other forms of data such as market value data, accounting data, access data, asset and facility data, worker data, event data, underwriting data, claims data or other forms of data. Pricing data may be adjusted for the context of the valued item (e.g., condition, liquidity, location, etc.) and / or for the context of a particular party. One of skill in the art, having the benefit of the disclosure herein and knowledge about pricing data, can readily determine the purposes and use of pricing data in various embodiments and contexts disclosed herein.[000266] Without limitation to any other aspect or description of the present disclosure, a token includes any token including, without limitation, a token of value, such as collateral, an asset, a reward, such as in a token serving as representation of value, such as a value holding voucher that can be exchanged for goods or services. Certain components may not be considered tokens individually, but may be considered tokens in an aggregated system - for example, a value placed on an asset may not be in itself be a token, but the value of an asset may be placed in a token of value, such as to be stored, exchanged, traded, and the like. For instance, in a nonlimiting example, a blockchain circuit may be structured to provide lenders a mechanism to store the value of assets, where the value attributed to the token is stored in a distributed ledger of the blockchain circuit, but the token itself, assigned the value, may be exchanged, or traded such as through a token marketplace. In certain embodiments, a token may be considered a token for some purposes but not for other purposes - for example, a token may be used as an indication of ownership of an asset, but this use of a token would not be traded as a value where a token including the value of the asset might. Accordingly, the benefits of the present disclosure may be applied in a wide variety of systems, and any such systems may be considered a token herein, while in certain embodiments a given system may not be considered a token herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system ordinarily available to that person, can readily determine which aspects of the present disclosure will benefit a particular system, and / or how to combine processes and systems from the present disclosure to enhance operations of the contemplated system. Certain considerations for the person of skill in the art, in determining whether a contemplated system is a token and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation, access data such as relating to rights of access, tickets, and tokens; use in an investment application such as for investment in shares, interests, and tokens; a token-trading application; a token-based marketplace; forms ofconsideration such as monetary rewards and tokens; translating the value of a resources in tokens; a cryptocurrency token; indications of ownership such as identity information, event information, and token information; a blockchain-based access token traded in a marketplace application; pricing application such as for setting and monitoring pricing for contingent access rights, underlying access rights, tokens, and fees; trading applications such as for trading or exchanging contingent access rights or underlying access rights or tokens; tokens created and stored on a blockchain for contingent access rights resulting in an ownership (e.g., a ticket); and the like.[000267] The term financial data as utilized herein may be understood broadly to describe a collection of financial information about an asset, collateral or other item or items. Financial data may include revenues, expenses, assets, liabilities, equity, bond ratings, default, return on assets (ROA), return on investment (ROI), past performance, expected future performance, earnings per share (EPS), internal rate of return (IRR), earnings announcements, ratios, statistical analysis of any of the foregoing (e.g. moving averages), and the like. Without limitation to any other aspect or description of the present disclosure, financial data may also be used in conjunction with pricing data and market value data. Financial data may satisfy one or more conditions, or may trigger application of one or more rules of a smart contract. Financial data may be used in conjunction with other forms of data such as market value data, pricing data, accounting data, access data, asset and facility data, worker data, event data, underwriting data, claims data or other forms of data. One of skill in the art, having the benefit of the disclosure herein and knowledge about financial data, can readily determine the purposes and use of pricing data in various embodiments and contexts disclosed herein.[000268] The term covenant as utilized herein may be understood broadly to describe a term, agreement, or promise, such as performance of some action or inaction. For example, a covenant may relate to behavior of a party or legal status of a party. Without limitation to any other aspect or description of the present disclosure, a covenant may also be used in conjunction with other related terms to an agreement or loan, such as a representation, a warranty, an indemnity, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. A covenant or lack of performance of a covenant may satisfy one or more conditions, or may trigger collection, breach or other terms and conditions. In certain embodiments, a smart contract may calculate whether a covenant is satisfied and in cases where the covenant is not satisfied, may enable automated action, or trigger other conditions or terms. One of skill in theart, having the benefit of the disclosure herein and knowledge about covenants, can readily determine the purposes and use of covenants in various embodiments and contexts disclosed herein.[000269] The term entity as utilized herein may be understood broadly to describe a party, a third-party (e.g., an auditor, regulator, service provider, etc.), and / or an identifiable related object such as an item of collateral related to a transaction. Example entities include an individual, partnership, corporation, limited liability company or other legal organization. Other example entities include an identifiable item of collateral, offset collateral, potential collateral, or the like. For example, an entity may be a given party, such as an individual, to an agreement or loan. Data or other terms herein may be characterized as having a context relating to an entity, such as entity-oriented data. An entity may be characterized with a specific context or application, such as a human entity, physical entity, transactional entity, or a financial entity, without limitation. An entity may have representatives that represent or act on its behalf. Without limitation to any other aspect or description of the present disclosure, an entity may also be used in conjunction with other related entities or terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. An entity may have a set of attributes such as: a publicly stated valuation, a set of property owned by the entity as indicated by public records, a valuation of a set of property owned by the entity, a bankruptcy condition, a foreclosure status, a contractual default status, a regulatory violation status, a criminal status, an export controls status, an embargo status, a tariff status, a tax status, a credit report, a credit rating, a website rating, a set of customer reviews for a product of an entity, a social network rating, a set of credentials, a set of referrals, a set of testimonials, a set of behavior, a location, and a geolocation, without limitation. In certain embodiments, a smart contract may calculate whether an entity has satisfied conditions or covenants and in cases where the entity has not satisfied such conditions or covenants, may enable automated action, or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about entities, can readily determine the purposes and use of entities in various embodiments and contexts disclosed herein.[000270] The term party as utilized herein may be understood broadly to describe a member of an agreement, such as an individual, partnership, corporation, limited liability company or other legal organization. For example, a party may be a primary lender, a secondary lender, a lendingsyndicate, a corporate lender, a government lender, a bank lender, a secured lender, a bond issuer, a bond purchaser, an unsecured lender, a guarantor, a provider of security, a borrower, a debtor, an underwriter, an inspector, an assessor, an auditor, a valuation professional, a government official, an accountant or other entities having rights or obligations to an agreement, transaction or loan. A party may characterize a different term, such as transaction as in the term multi-party transaction, where multiple parties are involved in a transaction, or the like, without limitation. A party may have representatives that represent or act on its behalf. In certain embodiments, the term party may reference a potential party or a prospective party - for example, an intended lender or borrower interacting with a system, that may not yet be committed to an actual agreement during the interactions with the system. Without limitation to any other aspect or description of the present disclosure, an party may also be used in conjunction with other related parties or terms to an agreement or loan, such as a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, an entity, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. A party may have a set of attributes such as: an identity, a creditworthiness, an activity, a behavior, a business practice, a status of performance of a contract, information about accounts receivable, information about accounts payable, information about the value of collateral, and other types of information, without limitation. In certain embodiments, a smart contract may calculate whether a party has satisfied conditions or covenants and in cases where the party has not satisfied such conditions or covenants, may enable automated action, or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about parties, can readily determine the purposes and use of parties in various embodiments and contexts disclosed herein.[000271] The term party attribute, entity attribute, or party / entity attribute as utilized herein may be understood broadly to describe a value, characteristic, or status of a party or entity. For example, attributes of a party or entity may be, without limitation: value, quality, location, net worth, price, physical condition, health condition, security, safety, ownership, identity, creditworthiness, activity, behavior, business practice, status of performance of a contract, information about accounts receivable, information about accounts payable, information about the value of collateral, and other types of information, and the like. In certain embodiments, a smart contract may calculate values, status or conditions associated with attributes of a party or entity, and in cases where the party or entity has not satisfied such conditions or covenants, may enable automated action, or trigger other conditions or terms. One of skill in the art, having thebenefit of the disclosure herein and knowledge about attributes of a party or entity, can readily determine the purposes and use of these attributes in various embodiments and contexts disclosed herein.[000272] The term lender as utilized herein may be understood broadly to describe a party to an agreement offering an asset for lending, proceeds of a loan, and may include an individual, partnership, corporation, limited liability company, or other legal organization. For example, a lender may be a primary lender, a secondary lender, a lending syndicate, a corporate lender, a government lender, a bank lender, a secured lender, an unsecured lender, or other party having rights or obligations to an agreement, transaction or loan offering a loan to a borrower, without limitation. A lender may have representatives that represent or act on its behalf. Without limitation to any other aspect or description of the present disclosure, an party may also be used in conjunction with other related parties or terms to an agreement or loan, such as a borrower, a guarantor, a representation, a warranty, an indemnity, a covenant, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a security, a personal guarantee, a lien, a duration, a foreclose condition, a default condition, and a consequence of default. In certain embodiments, a smart contract may calculate whether a lender has satisfied conditions or covenants and in cases where the lender has not satisfied such conditions or covenants, may enable automated action, a notification or alert, or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about a lender, can readily determine the purposes and use of a lender in various embodiments and contexts disclosed herein.[000273] The term crowdsourcing services as utilized herein may be understood broadly to describe services offered or rendered in conjunction with a crowdsourcing model or transaction, wherein a large group of people or entities supply contributions to fulfill a need, such as a loan, for the transaction. Crowdsourcing services may be provided by a platform or system, without limitation. A crowdsourcing request may be communicated to a group of information suppliers and by which responses to the request may be collected and processed to provide a reward to at least one successful information supplier. The request and parameters may be configured to obtain information related to the condition of a set of collateral for a loan. The crowdsourcing request may be published. In certain embodiments, without limitation, crowdsourcing services may be performed by a smart contract, wherein the reward is managed by a smart contract that processes responses to the crowdsourcing request and automatically allocates a reward to information that satisfies a set of parameter configured for the crowdsourcing request. One of skill in the art, having the benefit of the disclosure herein and knowledge about crowdsourcingservices, can readily determine the purposes and use of crowdsourcing services in various embodiments and contexts disclosed herein.[000274] The term publishing services as utilized herein may be understood to describe a set of services to publish a crowdsourcing request. Publishing services may be provided by a platform or system, without limitation. In certain embodiments, without limitation, publishing services may be performed by a smart contract, wherein the crowdsourcing request is published, or publication is initiated by the smart contract. One of skill in the art, having the benefit of the disclosure herein and knowledge about publishing services, can readily determine the purposes and use of publishing services in various embodiments and contexts disclosed herein.[000275] The term interface as utilized herein may be understood broadly to describe a component by which interaction or communication is achieved, such as a component of a computer, which may be embodied in software, hardware, or a combination thereof. For example, an interface may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: an application programming interface, a graphic user interface, user interface, software interface, marketplace interface, demand aggregation interface, crowdsourcing interface, secure access control interface, network interface, data integration interface or a cloud computing interface, or combinations thereof. An interface may serve to act as a way to enter, receive or display data, within the scope of lending, refinancing, collection, consolidation, factoring, brokering or foreclosure, without limitation. An interface may serve as an interface for another interface. Without limitation to any other aspect or description of the present disclosure, an interface may be used in conjunction with applications, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, an interface may be embodied in software, hardware, or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge about an interface, can readily determine the purposes and use of an interface in various embodiments and contexts disclosed herein.[000276] The term graphical user interface as utilized herein may be understood as a type of interface to allow a user to interact with a system, computer, or other interfaces, in which interaction or communication is achieved through graphical devices or representations. A graphical user interface may be a component of a computer, which may be embodied in computer readable instructions, hardware, or a combination thereof. A graphical user interface may serve a number of different purposes or be configured for different applications or contexts. Such an interface may serve to act as a way to receive or display data using visual representation, stimulus or interactive data, without limitation. A graphical user interface mayserve as an interface for another graphical user interface or other interfaces. Without limitation to any other aspect or description of the present disclosure, a graphical user interface may be used in conjunction with applications, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, a graphical user interface may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or in memory. Graphical user interfaces may be configured for any input types, including keyboards, a mouse, a touch screen, and the like. Graphical user interfaces may be configured for any desired user interaction environments, including for example a dedicated application, a web page interface, or combinations of these. One of skill in the art, having the benefit of the disclosure herein and knowledge about a graphical user interface, can readily determine the purposes and use of a graphical user interface in various embodiments and contexts disclosed herein.[000277] The term user interface as utilized herein may be understood as a type of interface to allow a user to interact with a system, computer, or other apparatus, in which interaction or communication is achieved through graphical devices or representations. A user interface may be a component of a computer, which may be embodied in software, hardware, or a combination thereof. The user interface may be stored on a medium or in memory. User interfaces may include drop-down menus, tables, forms, or the like with default, templated, recommended, or pre-configured conditions. In certain embodiments, a user interface may include voice interaction. Without limitation to any other aspect or description of the present disclosure, a user interface may be used in conjunction with applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. User interfaces may serve a number of different purposes or be configured for different applications or contexts. For example, a lender-side user interface may include features to view a plurality of customer profiles, but may be restricted from making certain changes. A debtor-side user interface may include features to view details and make changes to a user account. A 3rd party neutral-side interface (e.g. a 3rd party not having an interest in an underlying transaction, such as a regulator, auditor, etc.) may have features that enable a view of company oversight and anonymized user data without the ability to manipulate any data, and may have scheduled access depending upon the 3rd party and the purpose for the access. A 3rd party interested-side interface (e.g. a 3rd party that may have an interest in an underlying transaction, such as a collector, debtor advocate, investigator, partial owner, etc.) may include features enabling a view of particular user data with restrictions on making changes. Many more features of these user interfaces may be available to implements embodiments of the systems and / or procedures described throughout the present disclosure.Accordingly, the benefits of the present disclosure may be applied in a wide variety of processes and systems, and any such processes or systems may be considered a service herein. One of skill in the art, having the benefit of the disclosure herein and knowledge about a user interface, can readily determine the purposes and use of a user interface in various embodiments and contexts disclosed herein. Certain considerations for the person of skill in the art, in determining whether a contemplated interface is a user interface and / or whether aspects of the present disclosure can benefit or enhance the contemplated system include, without limitation: configurable views, ability to restrict manipulation or views, report functions, ability to manipulate user profile and data, implement regulatory requirements, provide the desired user features for borrowers, lenders, and 3rd parties, and the like.[000278] Interfaces and dashboards as utilized herein may further be understood broadly to describe a component by which interaction or communication is achieved, such as a component of a computer, which may be embodied in software, hardware, or a combination thereof. Interfaces and dashboards may acquire, receive, present, or otherwise administrate an item, service, offering or other aspects of a transaction or loan. For example, interfaces and dashboards may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: an application programming interface, a graphic user interface, user interface, software interface, marketplace interface, demand aggregation interface, crowdsourcing interface, secure access control interface, network interface, data integration interface or a cloud computing interface, or combinations thereof. An interface or dashboard may serve to act as a way to receive or display data, within the context of lending, refinancing, collection, consolidation, factoring, brokering or foreclosure, without limitation. An interface or dashboard may serve as an interface or dashboard for another interface or dashboard. Without limitation to any other aspect or description of the present disclosure, an interface may be used in conjunction with applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, sub-systems, interfaces, connections, or as part of a system. In certain embodiments, an interface or dashboard may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of interfaces and / or dashboards in various embodiments and contexts disclosed herein. [000279] The term domain as utilized herein may be understood broadly to describe a scope or context of a transaction and / or communications related to a transaction. For example, a domain may serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a domain for execution, a domain for a digital asset, domains towhich a request will be published, domains to which social network data collection and monitoring services will be applied, domains to which Internet of Things data collection and monitoring services will be applied, network domains, geolocation domains, jurisdictional location domains, and time domains. Without limitation to any other aspect or description of the present disclosure, one or more domains may be utilized relative to any applications, circuits, controllers, processes, modules, services, layers, devices, components, machines, products, subsystems, interfaces, connections, or as part of a system. In certain embodiments, a domain may be embodied in computer readable instructions, hardware, or a combination thereof, as well as stored on a medium or in memory. One of skill in the art, having the benefit of the disclosure herein and knowledge about a domain, can readily determine the purposes and use of a domain in various embodiments and contexts disclosed herein.[000280] The term request (and variations) as utilized herein may be understood broadly to describe the action or instance of initiating or asking for a thing (e.g. information, a response, an object, and the like) to be provided. A specific type of request may also serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a formal legal request (e.g. a subpoena), a request to refinance (e.g. a loan), or a crowdsourcing request. Systems may be utilized to perform requests as well as fulfill requests. Requests in various forms may be included where discussing a legal action, a refinancing of a loan, or a crowdsourcing service, without limitation. One of skill in the art, having the benefit of the disclosure herein and knowledge about a contemplated system, can readily determine the value of a request implemented in an embodiment. While specific examples of requests are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [000281] The term reward (and variations) as utilized herein may be understood broadly to describe a thing or consideration received or provided in response to an action or stimulus. Rewards can be of a financial type, or non- financial type, without limitation. A specific type of reward may also serve a number of different purposes or be configured for different applications or contexts, such as, without limitation: a reward event, claims for rewards, monetary rewards, rewards captured as a data set, rewards points, and other forms of rewards. Rewards may be triggered, allocated, generated for innovation, provided for the submission of evidence, requested, offered, selected, administrated, managed, configured, allocated, conveyed, identified, without limitation, as well as other actions. Systems may be utilized to perform the aforementioned actions. Rewards in various forms may be included where discussing a particular behavior, or encouragement of a particular behavior, without limitation. In certainembodiments herein, a reward may be utilized as a specific incentive (e.g., rewarding a particular person that responds to a crowdsourcing request) or as a general incentive (e.g., providing a reward responsive to a successful crowdsourcing request, in addition to or alternatively to a reward to the particular person that responded). One of skill in the art, having the benefit of the disclosure herein and knowledge about a reward, can readily determine the value of a reward implemented in an embodiment. While specific examples of rewards are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure. [000282] The term robotic process automation system as utilized herein may be understood broadly to describe a system capable of performing tasks or providing needs for a system of the present disclosure. For example, a robotic process automation system, without limitation, can be configured for: negotiation of a set of terms and conditions for a loan, negotiation of refinancing of a loan, loan collection, consolidating a set of loans, managing a factoring loan, brokering a mortgage loan, training for foreclosure negotiations, configuring a crowdsourcing request based on a set of attributes for a loan, setting a reward, determining a set of domains to which a request will be published, configuring the content of a request, configuring a data collection and monitoring action based on a set of attributes of a loan, determining a set of domains to which the Internet of Things data collection and monitoring services will be applied, and iteratively training and improving based on a set of outcomes. A robotic process automation system may include: a set of data collection and monitoring services, an artificial intelligence system, and another robotic process automation system which is a component of the higher level robotic process automation system. The robotic process automation system may include: at least one of the set of mortgage loan activities and the set of mortgage loan interactions includes activities among marketing activity, identification of a set of prospective borrowers, identification of property, identification of collateral, qualification of borrower, title search, title verification, property assessment, property inspection, property valuation, income verification, borrower demographic analysis, identification of capital providers, determination of available interest rates, determination of available payment terms and conditions, analysis of existing mortgage, comparative analysis of existing and new mortgage terms, completion of application workflow, population of fields of application, preparation of mortgage agreement, completion of schedule to mortgage agreement, negotiation of mortgage terms and conditions with capital provider, negotiation of mortgage terms and conditions with borrower, transfer of title, placement of lien and closing of mortgage agreement. Example and non-limiting robotic process automation systems may include one or more user interfaces, interfaces with circuits and / or controllersthroughout the system to provide, request, and / or share data, and / or one or more artificial intelligence circuits configured to iteratively improve one or more operations of the robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated robotic process automation system, can readily determine the circuits, controllers, and / or devices to include to implement a robotic process automation system performing the selected functions for the contemplated system. While specific examples of robotic process automation systems are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood.[000283] The term loan-related action (and other related terms such as loan-related event and loan-related activity) are utilized herein and may be understood broadly to describe one or multiple actions, events or activities relating to a transaction that includes a loan within the transaction. The action, event or activity may occur in many different contexts of loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, administration, negotiating, collecting, procuring, enforcing and data processing (e.g. data collection), or combinations thereof, without limitation. A loan-related action may be used in the form of a noun (e.g. a notice of default has been communicated to the borrower with formal notice, which could be considered a loan-related action). A loan-related action, event, or activity may refer to a single instance, or may characterize a group of actions, events, or activities. For example, a single action such as providing a specific notice to a borrower of an overdue payment may be considered a loan-related action. Similarly, a group of actions from start to finish relating to a default may also be considered a single loan-related action. Appraisal, inspection, funding, and recording, without limitation, may all also be considered loan-related actions that have occurred, as well as events relating to the loan, and may also be loan-related events. Similarly, these activities of completing these actions may also be considered loan-related activities (e.g. appraising, inspecting, funding, recording, etc.), without limitation. In certain embodiments, a smart contract or robotic process automation system may perform loan-related actions, loan- related events, or loan-related activities for one or more of the parties, and process appropriate tasks for completion of the same. In some cases the smart contract or robotic process automation system may not complete a loan-related action, and depending upon such outcome this may enable an automated action or may trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions, events, and activities can readily determine the purposes and use of this term in various forms and embodiments as described throughout the present disclosure.[000284] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for calling of a loan. A calling of a loan is an action wherein the lender can demand the loan be repaid, usually triggered by some other condition or term, such as delinquent payment(s). For example, a loan-related action for calling of the loan may occur when a borrower misses three payments in a row, such that there is a severe delinquency in the loan payment schedule, and the loan goes into default. In such a scenario, a lender may be initiating loan-related actions for calling of the loan to protect its rights. In such a scenario, perhaps the borrower pays a sum to cure the delinquency and penalties, which may also be considered as a loan-related action for calling of the loan. In some circumstances, a smart contract or robotic process automation system may initiate, administrate, or process loan- related actions for calling of the loan, which without limitation, may including providing notice, researching, and collecting payment history, or other tasks performed as a part of the calling of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for calling of the loan, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein.[000285] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for payment of a loan. Typically in transactions involving loans, without limitation, a loan is repaid on a payment schedule. Various actions may be taken to provide a borrower with information to pay back the loan, as well as actions for a lender to receive payment for the loan. For example, if a borrower makes a payment on the loan, a loan-related action for payment of the loan may occur. Without limitation, such a payment may comprise several actions that may occur with respect to the payment on the loan, such as: the payment being tendered to the lender, the loan ledger or accounting reflecting that a payment has been made, a receipt provided to the borrower of the payment made, and the next payment being requested of the borrower. In some circumstances, a smart contract or robotic process automation system may initiate, administrate, or process such loan-related actions for payment of the loan, which without limitation, may including providing notice to the lender, researching and collecting payment history, providing a receipt to the borrower, providing notice of the next payment due to the borrower, or other actions associated with payment of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for payment of a loan, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein.[000286] The term loan-related action, events, and activities, as noted herein, may also more specifically be utilized to describe a context for a payment schedule or alternative payment schedule. Typically in transactions involving loans, without limitation, a loan is repaid on a payment schedule, which may be modified over time. Or, such a payment schedule may be developed and agreed in the alternative, with an alternative payment schedule. Various actions may be taken in the context of a payment schedule or alternate payment schedule for the lender or the borrower, such as: the amount of such payments, when such payments are due, what penalties or fees may attach to late payments, or other terms. For example, if a borrower makes an early payment on the loan, a loan-related action for payment schedule and alternative payment schedule of the loan may occur; in such case, perhaps the payment is applied as principal, with the regular payment still being due. Without limitation, loan-related actions for a payment schedule and alternative payment schedule may comprise several actions that may occur with respect to the payment on the loan, such as: the payment being tendered to the lender, the loan ledger or accounting reflecting that a payment has been made, a receipt provided to the borrower of the payment made, a calculation if any fees are attached or due, and the next payment being requested of the borrower. In certain embodiments, an activity to determine a payment schedule or alternative payment schedule may be a loan-related action, event, or activity. In certain embodiments, an activity to communicate the payment schedule or alternative payment schedule (e.g., to the borrower, the lender, or a 3rd party) may be a loan- related action, event, or activity. In some circumstances, a smart contract circuit or robotic process automation system may initiate, administrate, or process such loan-related actions for payment schedule and alternative payment schedule, which without limitation, may include providing notice to the lender, researching and collecting payment history, providing a receipt to the borrower, calculating the next due date, calculating the final payment amount and date, providing notice of the next payment due to the borrower, determining the payment schedule or an alternate payment schedule, communicating the payment scheduler or an alternate payment schedule, or other actions associated with payment of the loan. One of skill in the art, having the benefit of the disclosure herein and knowledge about loan-related actions for payment schedule and alternative payment schedule, or other forms of the term and its various forms, can readily determine the purposes and use of this term in the context of an event or other various embodiments and contexts disclosed herein.[000287] The term regulatory notice requirement (and any derivatives) as utilized herein may be understood broadly to describe an obligation or condition to communicate a notification or message to another party or entity. The regulatory notice requirement may be required under one or more conditions that are triggered, or generally required. For example, a lender may havea regulatory notice requirement to provide notice to a borrower of a default of a loan, or change of an interest rate of a loan, or other notifications relating to a transaction or loan. The regulatory aspect of the term may be attributed to jurisdiction-specific laws, rules, or codes that require certain obligations of communication. In certain embodiments, a policy directive may be treated as a regulatory notice requirement - for example where a lender has an internal notice policy that may exceed the regulatory requirements of one or more of the jurisdictional locations related to a transaction. The notice aspect generally relates to formal communications, which may take many different forms, but may specifically be specified as a particular form of notice, such as a certified mail, facsimile, email transmission, or other physical or electronic form, a content for the notice, and / or a timing requirement related to the notice. The requirement aspect relates to the necessity of a party to complete its obligation to be in compliance with laws, rules, codes, policies, standard practices, or terms of an agreement or loan. In certain embodiments, a smart contract may process or trigger regulatory notice requirements and provide appropriate notice to a borrower. This may be based on location of at least one of: the lender, the borrower, the funds provided via the loan, the repayment of the loan, and the collateral of the loan, or other locations as designated by the terms of the loan, transaction, or agreement. In cases where a party or entity has not satisfied such regulatory notice requirements, certain changes in the rights or obligations between the parties may be triggered - for example where a lender provides a non-compliant notice to the borrower, an automated action or trigger based on the terms and conditions of the loan, and / or based on external information (e.g., a regulatory prescription, internal policy of the lender, etc.) may be affected by a smart contract circuit and / or robotic process automation system may be implemented. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory notice requirements in various embodiments and contexts disclosed herein.[000288] The term regulatory notice requirement may also be utilized herein to describe an obligation or condition to communicate a notification or message to another party or entity based upon a general or specific policy, rather than based on a particular jurisdiction, or laws, rules, or codes of a particular location (as in regulatory notice requirement that may be jurisdiction-specific). The regulatory notice requirement may be prudent or suggested, rather than obligatory or required, under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory notice requirement that is policy based to provide notice to a borrower of a new informational website, or will experience a change of an interest rate of a loan in the future, or other notifications relating to a transaction or loan that are advisory or helpful, rather than mandatory (although mandatory notices may also fall under apolicy basis). Thus, in policy based uses of the regulatory notice requirement term, a smart contract circuit may process or trigger regulatory notice requirements and provide appropriate notice to a borrower which may or may not necessarily be required by a law, rule, or code. The basis of the notice or communication may be out of prudence, courtesy, custom, or obligation. [000289] The term regulatory notice may also be utilized herein to describe an obligation or condition to communicate a notification or message to another party or entity specifically, such as a lender or borrower. The regulatory notice may be specifically directed toward any party or entity, or a group of parties or entities. For example, a particular notice or communication may be advisable or required to be provided to a borrower, such as on circumstances of a borrower's failure to provide scheduled payments on a loan resulting in a default. As such, such a regulatory notice directed to a particular user, such as a lender or borrower, may be as a result of a regulatory notice requirement that is jurisdiction-specific or policy-based, or otherwise. Thus, in some circumstances a smart contract may process or trigger a regulatory notice and provide appropriate notice to a specific party such as a borrower, which may or may not necessarily be required by a law, rule, or code, but may otherwise be provided out of prudence, courtesy or custom. In cases where a party or entity has not satisfied such regulatory notice requirements to a specific party or parties, it may create circumstances where certain rights may be forgiven by one or more parties or entities, or may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory notice requirements based in various embodiments and contexts disclosed herein. [000290] The term regulatory foreclosure requirement (and any derivatives) as utilized herein may be understood broadly to describe an obligation or condition in order to trigger, process or complete default of a loan, foreclosure, or recapture of collateral, or other related foreclosure actions. The regulatory foreclosure requirement may be required under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory foreclosure requirement to provide notice to a borrower of a default of a loan, or other notifications relating to the default of a loan prior to foreclosure. The regulatory aspect of the term may be attributed to jurisdiction-specific laws, rules, or codes that require certain obligations of communication. The foreclosure aspect generally relates to the specific remedy of foreclosure, or a recapture of collateral property and default of a loan, which may take many different forms, but may be specified in the terms of the loan. The requirement aspect relates to the necessity of a party to complete its obligation in order to be in compliance or performance of laws, rules, codes or terms of an agreement or loan. In certain embodiments, a smart contract circuit may process or trigger regulatory foreclosure requirements and process appropriate tasksrelating to such a foreclosure action. This may be based on a jurisdictional location of at least one of the lender, the borrower, the fund provided via the loan, the repayment of the loan, and the collateral of the loan, or other locations as designated by the terms of the loan, transaction, or agreement. In cases where a party or entity has not satisfied such regulatory foreclosure requirements, certain rights may be forgiven by the party or entity (e.g. a lender), or such a failure to comply with the regulatory notice requirement may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of regulatory foreclosure requirements in various embodiments and contexts disclosed herein.[000291] The term regulatory foreclosure requirement may also be utilized herein to describe an obligation or in order to trigger, process or complete default of a loan, foreclosure, or recapture of collateral, or other related foreclosure actions, based upon a general or specific policy rather than based on a particular jurisdiction, or laws, rules, or codes of a particular location (as in regulatory foreclosure requirement that may be jurisdiction-specific). The regulatory foreclosure requirement may be prudent or suggested, rather than obligatory or required, under one or more conditions that are triggered, or generally required. For example, a lender may have a regulatory foreclosure requirement that is policy based to provide notice to a borrower of a default of a loan, or other notifications relating to a transaction or loan that are advisory or helpful, rather than mandatory (although mandatory notices may also fall under a policy basis). Thus, in policy based uses of the regulatory foreclosure requirement term, a smart contract may process or trigger regulatory foreclosure requirements and provide appropriate notice to a borrower which may or may not necessarily be required by a law, rule, or code. The basis of the notice or communication may be out of prudence, courtesy, custom, industry practice, or obligation.[000292] The term regulatory foreclosure requirements may also be utilized herein to describe an obligation or condition that is to be performed with regard to a specific user, such as a lender or a borrower. The regulatory notice may be specifically directed toward any party or entity, or a group of parties or entities. For example, a particular notice or communication may be advisable or required to be provided to a borrower, such as on circumstances of a borrower's failure to provide scheduled payments on a loan resulting in a default. As such, such a regulatory foreclosure requirement is directed to a particular user, such as a lender or borrower, and may be a result of a regulatory foreclosure requirement that is jurisdiction-specific or policy-based, or otherwise. For example, the foreclosure requirement may be related to a specific entity involved with a transaction (e.g., the current borrower has been a customer for 30 years, so s / he receives unique treatment), or to a class of entities (e.g., "preferred" borrowers, or "first time default"borrowers). Thus, in some circumstances a smart contract circuit may process or trigger an obligation or action that must be taken pursuant to a foreclosure, where the action is directed or from a specific party such as a lender or a borrower, which may or may not necessarily be required by a law, rule, or code, but may otherwise be provided out of prudence, courtesy, or custom. In certain embodiments, the obligation or condition that is to be performed with regard to the specific user may form a part of the terms and conditions or otherwise be known to the specific user to which it applies (e.g., an insurance company or bank that advertises a specific practice with regard to a specific class of customers, such as first-time default customers, firsttime accident customers, etc.), and in certain embodiments the obligation or condition that is to be performed with regard to the specific user may be unknown to the specific user to which it applies (e.g., a bank has a policy relating to a class of users to which the specific user belongs, but the specific user is not aware of the classification).[000293] The terms value, valuation, valuation model (and similar terms) as utilized herein should be understood broadly to describe an approach to evaluate and determine the estimated value for collateral. Without limitation to any other aspect or description of the present disclosure, a valuation model may be used in conjunction with: collateral (e.g. a secured property), artificial intelligence services (e.g. to improve a valuation model), data collection and monitoring services (e.g. to set a valuation amount), valuation services (e.g. the process of informing, using, and / or improving a valuation model), and / or outcomes relating to transactions in collateral (e.g. as a basis of improving the valuation model). "Jurisdiction-specific valuation model" is also used as a valuation model used in a specific geographic / jurisdictional area or region; wherein, the jurisdiction can be specific to jurisdiction of the lender, the borrower, the delivery of funds, the payment of the loan or the collateral of the loan, or combinations thereof. In certain embodiments, a jurisdiction-specific valuation model considers jurisdictional effects on a valuation of collateral, including at least: rights and obligations for borrowers and lenders in the relevant jurisdiction(s); jurisdictional effects on the ability to move, import, export, substitute, and / or liquidate the collateral; jurisdictional effects on the timing between default and foreclosure or collection of collateral; and / or jurisdictional effects on the volatility and / or sensitivity of collateral value determinations. In certain embodiments, a geolocation-specific valuation model considers geolocation effects on a valuation of the collateral, which may include a similar list of considerations relative jurisdictional effects (although the jurisdictional location(s) may be distinct from the geolocation(s)), but may also include additional effects, such as: weather-related effects; distance of the collateral from monitoring, maintenance, or seizure services; and / or proximity of risk phenomenon (e.g., fault lines, industrial locations, a nuclear plant, etc.). A valuation model may utilize a valuation of offset collateral (e.g., a similaritem of collateral, a generic value such as a market value of similar or fungible collateral, and / or a value of an item that correlates with a value of the collateral) as a part of the valuation of the collateral. In certain embodiments, an artificial intelligence circuit includes one or more machine learning and / or artificial intelligence algorithms, to improve a valuation model, including, for example, utilizing information over time between multiple transactions involving similar or offset collateral, and / or utilizing outcome information (e.g., where loan transactions are completed successfully or unsuccessfully, and / or in response to collateral seizure or liquidation events that demonstrate real- world collateral valuation determinations) from the same or other transactions to iteratively improve the valuation model. In certain embodiments, an artificial intelligence circuit is trained on a collateral valuation data set, for example previously determined valuations and / or through interactions with a trainer (e.g., a human, accounting valuations, and / or other valuation data). In certain embodiments, the valuation model and / or parameters of the valuation model (e.g., assumptions, calibration values, etc.) may be determined and / or negotiated as a part of the terms and conditions of the transaction (e.g., a loan, a set of loans, and / or a subset of the set of loans). One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine which aspects of the present disclosure will benefit a particular application for a valuation model, and how to choose or combine valuation models to implement an embodiment of a valuation model. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate valuation model, include, without limitation: the legal considerations of a valuation model given the jurisdiction of the collateral; the data available for a given collateral; the anticipated transaction / loan type(s); the specific type of collateral; the ratio of the loan to value; the ratio of the collateral to the loan; the gross transaction / loan amount; the credit scores of the borrower; accounting practices for the loan type and / or related industry; uncertainties related to any of the foregoing; and / or sensitivities related to any of the foregoing. While specific examples of valuation models and considerations are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure[000294] The term market value data, or marketplace information, (and other forms or variations) as utilized herein may be understood broadly to describe data or information relating to the valuation of a property, asset, collateral, or other valuable items which may be used as the subject of a loan, collateral, or transaction. Market value data or marketplace information may change from time to time, and may be estimated, calculated, or objectively or subjectivelydetermined from various sources of information. Market value data or marketplace information may be related directly to an item of collateral or to an off-set item of collateral. Market value data or marketplace information may include financial data, market ratings, product ratings, customer data, market research to understand customer needs or preferences, competitive intelligence re. competitors, suppliers, and the like, entities sales, transactions, customer acquisition cost, customer lifetime value, brand awareness, chum rate, and the like. The term may occur in many different contexts of contracts or loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and data processing (e.g. data collection), or combinations thereof, without limitation. Market value data or marketplace information may be used as a noun to identify a single figure or a plurality of figures or data. For example, market value data or marketplace information may be utilized by a lender to determine if a property or asset will serve as collateral for a secured loan, or may alternatively be utilized in the determination of foreclosure if a loan is in default, without limitation to these circumstances in use of the term. Marketplace value data or marketplace information may also be used to determine loan-to-value figures or calculations. In certain embodiments, a collection service, smart contract circuit, and / or robotic process automation system may estimate or calculate market value data or marketplace information from one or more sources of data or information. In some cases market data value or marketplace information, depending upon the data / information contained therein, may enable automated action, or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system and available relevant marketplace information, can readily determine the purposes and use of this term in various forms, embodiments and contexts disclosed herein.[000295] The terms similar collateral, similar to collateral, off-set collateral, and other forms or variations as utilized herein may be understood broadly to describe a property, asset or valuable item that may be like in nature to a collateral (e.g. an article of value held in security) regarding a loan or other transaction. Similar collateral may refer to a property, asset, collateral or other valuable item which may be aggregated, substituted, or otherwise referred to in conjunction with other collateral, whether the similarity comes in the form of a common attribute such as type of item of collateral, category of the item of collateral, an age of the item of collateral, a condition of the item of collateral, a history of the item of collateral, an ownership of the item of collateral, a caretaker of the item of collateral, a security of the item of collateral, a condition of an owner of the item of collateral, a lien on the item of collateral, a storage condition of the item of collateral, a geolocation of the item of collateral, and a jurisdictional location of the item of collateral, and the like. In certain embodiments, an offset collateral references an item that has avalue correlation with an item of collateral - for example, an offset collateral may exhibit similar price movements, volatility, storage requirements, or the like for an item of collateral. In certain embodiments, similar collateral may be aggregated to form a larger security interest or collateral for an additional loan or distribution, or transaction. In certain embodiments, offset collateral may be utilized to inform a valuation of the collateral. In certain embodiments, a smart contract circuit or robotic process automation system may estimate or calculate figures, data or information relating to similar collateral, or may perform a function with respect to aggregating similar collateral. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of similar collateral, offset collateral, or related terms as they relate to collateral in various forms, embodiments, and contexts disclosed herein.[000296] The term restructure (and other forms such as restructuring) as utilized herein may be understood broadly to describe a modification of terms or conditions, properties, collateral, or other considerations affecting a loan or transaction. Restructuring may result in a successful outcome where amended terms or conditions are adopted between parties, or an unsuccessful outcome where no modification or restructure occurs, without limitation. Restructuring can occur in many contexts of contracts or loans, such as application, lending, refinancing, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. Debt may also be restructured, which may indicate that debts owed to a party are modified as to timing, amounts, collateral, or other terms. For example, a borrower may restructure debt of a loan to accommodate a change of financial conditions, or a lender may offer to a borrower the restructuring of a debt for its own needs or prudence. In certain embodiments, a smart contract circuit or robotic process automation system may automatically or manually restructure debt based on a monitored condition, or create options for restructuring a debt, administrate the process of negotiating or effecting the restructuring of a debt, or other actions in connection with restructuring or modifying terms of a loan or transaction. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of this term, whether in the context of debt or otherwise, in various embodiments and contexts disclosed herein.[000297] The term social network data collection, social network monitoring services, and social network data collection and monitoring services (and its various forms or derivatives) as utilized herein may be understood broadly to describe services relating to the acquisition, organizing, observing, or otherwise acting upon data or information derived from one or more social networks. The social network data collection and monitoring services may be a part of a related system of services or a standalone set of services. Social network data collection and monitoringservices may be provided by a platform or system, without limitation. Social network data collection and monitoring services may be used in a variety of contexts such as lending, refinancing, negotiation, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. Requests of social network data collection and monitoring, with configuration parameters, may be requested by other services, automatically initiated, or triggered to occur based on conditions or circumstances that occur. An interface may be provided to configure, initiate, display, or otherwise interact with social network data collection and monitoring services. Social networks, as utilized herein, reference any mass platform where data and communications occur between individuals and / or entities, where the data and communications are at least partially accessible to an embodiment system. In certain embodiments, the social network data includes publicly available (e.g., accessible without any authorization) information. In certain embodiments, the social network data includes information that is properly accessible to an embodiment system, but may include subscription access or other access to information that is not freely available to the public, but may be accessible (e.g., consistent with a privacy policy of the social network with its users). A social network may be primarily social in nature, but may additionally or alternatively include professional networks, alumni networks, industry related networks, academically oriented networks, or the like. In certain embodiments, a social network may be a crowdsourcing platform, such as a platform configured to accept queries or requests directed to users (and / or a subset of users, potentially meeting specified criteria), where users may be aware that certain communications will be shared and accessible to requestors, at least a portion of users of the platform, and / or publicly available. In certain embodiments, without limitation, social network data collection and monitoring services may be performed by a smart contract circuit or a robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of social network data collection and monitoring services in various embodiments and contexts disclosed herein.[000298] The term crowdsource and social network information as utilized herein may further be understood broadly to describe information acquired or provided in conjunction with a crowdsourcing model or transaction, or information acquired or provided on or in conjunction with a social network. Crowdsource and social network information may be provided by a platform or system, without limitation. Crowdsource and social network information may be acquired, provided, or communicated to or from a group of information suppliers and by which responses to the request may be collected and processed. Crowdsource and social network information may provide information, conditions or factors relating to a loan or agreement.Crowdsource and social network information may be private or published, or combinations thereof, without limitation. In certain embodiments, without limitation, crowdsource and social network information may be acquired, provided, organized, or processed, without limitation, by a smart contract circuit, wherein the crowdsource and social network information may be managed by a smart contract circuit that processes the information to satisfy a set of configured parameters. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine the purposes and use of this term in various embodiments and contexts disclosed herein.[000299] The term negotiate (and other forms such as negotiating or negotiation) as utilized herein may be understood broadly to describe discussions or communications to bring about or obtain a compromise, outcome, or agreement between parties or entities. Negotiation may result in a successful outcome where terms are agreed between parties, or an unsuccessful outcome where the parties do not agree to specific terms, or combinations thereof, without limitation. A negotiation may be successful in one aspect or for a particular purpose, and unsuccessful in another aspect or for another purpose. Negotiation can occur in many contexts of contracts or loans, such as lending, refinancing, collection, consolidation, factoring, brokering, foreclosure, and combinations thereof, without limitation. For example, a borrower may negotiate an interest rate or loan terms with a lender. In another example, a borrower in default may negotiate an alternative resolution to avoid foreclosure with a lender. In certain embodiments, a smart contract circuit or robotic process automation system may negotiate for one or more of the parties, and process appropriate tasks for completing or attempting to complete a negotiation of terms. In some cases negotiation by the smart contract or robotic process automation system may not complete or be successful. Successful negotiation may enable automated action or trigger other conditions or terms to be implemented by the smart contract circuit or robotic process automation system. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of negotiation in various embodiments and contexts disclosed herein.[000300] The term negotiate in various forms may more specifically be utilized herein in verb form (e.g. to negotiate) or in noun forms (e.g. a negotiation), or other forms to describe a context of mutual discussion leading to an outcome. For example, a robotic process automation system may negotiate terms and conditions on behalf of a party, which would be a use as a verb clause. In another example, a robotic process automation system may be negotiating terms and conditions for modification of a loan, or negotiating a consolidation offer, or other terms. As a noun clause, a negotiation (e.g. an event) may be performed by a robotic process automation system. Thus, in some circumstances a smart contract circuit or robotic process automationsystem may negotiate (e.g. as a verb clause) terms and conditions, or the description of doing so may be considered a negotiation (e.g. as a noun clause). One of skill in the art, having the benefit of the disclosure herein and knowledge about negotiating and negotiation, or other forms of the word negotiate, can readily determine the purposes and use of this term in various embodiments and contexts disclosed herein.[000301] The term negotiate in various forms may also specifically be utilized to describe an outcome, such as a mutual compromise or completion of negotiation leading to an outcome. For example, a loan may, by robotic process automation system or otherwise, be considered negotiated as a successful outcome that has resulted in an agreement between parties, where the negotiation has reached completion. Thus, in some circumstances a smart contract circuit or robotic process automation system may have negotiated to completion a set of terms and conditions, or a negotiated loan. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available for a contemplated system, can readily determine the purposes and use of this term as it relates to a mutually agreed outcome through completion of negotiation in various embodiments and contexts disclosed herein.[000302] The term negotiate in various forms may also specifically be utilized to characterize an event such as a negotiating event, or an event negotiation, including reaching a set of agreeable terms between parties. An event requiring mutual agreement or compromise between parties may be considered a negotiating event, without limitation. For example, during the procurement of a loan, the process of reaching a mutually acceptable set of terms and conditions between parties could be considered a negotiating event. Thus, in some circumstances a smart contract circuit or robotic process automation system may accommodate the communications, actions, or behaviors of the parties for a negotiated event.[000303] The term collection (and other forms such as collect or collecting) as utilized herein may be understood broadly to describe the acquisition of a tangible (e.g. physical item), intangible (e.g. data, a license, or a right), or monetary (e.g. payment) item, or other obligation or asset from a source. The term generally may relate to the entire prospective acquisition of such an item from related tasks in early stages to related tasks in late stages or full completion of the acquisition of the item. Collection may result in a successful outcome where the item is tendered to a party, or may or an unsuccessful outcome where the item is not tendered or acquired to a party, or combinations thereof (e.g., a late or otherwise deficient tender of the item), without limitation. Collection may occur in many different contexts of contracts or loans, such as lending, refinancing, consolidation, factoring, brokering, foreclosure, and data processing (e.g. data collection), or combinations thereof, without limitation. Collection may be used in the form of a noun (e.g. data collection or the collection of an overdue payment where itrefers to an event or characterizes an event), may refer as a noun to an assortment of items (e.g. a collection of collateral for a loan where it refers to a number of items in a transaction), or may be used in the form of a verb (e.g. collecting a payment from the borrower). For example, a lender may collect an overdue payment from a borrower through an online payment, or may have a successful collection of overdue payments acquired through a customer service telephone call. In certain embodiments, a smart contract circuit or robotic process automation system may perform collection for one or more of the parties, and process appropriate tasks for completing or attempting collection for one or more items (e.g., an overdue payment). In some cases negotiation by the smart contract or robotic process automation system may not complete or be successful, and depending upon such outcomes this may enable automated action or trigger other conditions or terms. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of collection in various forms, embodiments, and contexts disclosed herein.[000304] The term collection in various forms may also more specifically be utilized herein in noun form to describe a context for an event or thing, such as a collection event, or a collection payment. For example, a collection event may refer to a communication to a party or other activity that relates to acquisition of an item in such an activity, without limitation. A collection payment, for example, may relate to a payment made by a borrower that has been acquired through the process of collection, or through a collection department with a lender. Although not limited to an overdue, delinquent, or defaulted loan, collection may characterize an event, payment or department, or other noun associated with a transaction or loan, as being a remedy for something that has become overdue. Thus, in some circumstances a smart contract circuit or robotic process automation system may collect a payment or installment from a borrower, and the activity of doing so may be considered a collection event, without limitation.[000305] The term collection in various forms may also more specifically be utilized herein as an adjective or other forms to describe a context relating to litigation, such as the outcome of a collection litigation (e.g. litigation regarding overdue or default payments on a loan). For example, the outcome of a collection litigation may be related to delinquent payments which are owed by a borrower or other party, and collection efforts relating to those delinquent payments may be litigated by parties. Thus, in some circumstances a smart contract circuit or robotic process automation system may receive, determine, or otherwise administrate the outcome of collection litigation.[000306] The term collection in various forms may also more specifically be utilized herein as an adjective or other forms to describe a context relating to an action of acquisition, such as a collection action (e.g. actions to induce tendering or acquisition of overdue or default paymentson a loan or other obligation). The terms collection yield, financial yield of collection, and / or collection financial yield may be used. The result of such a collection action may or may not have a financial yield. For example, a collection action may result in the payment of one or more outstanding payments on a loan, which may render a financial yield to another party such as the lender. Thus, in some circumstances a smart contract circuit or robotic process automation system may render a financial yield from a collection action, or otherwise administrate or in some manner assist in a financial yield of a collection action. In embodiments, a collection action may include the need for collection litigation.[000307] The term collection in various forms (collection ROI, ROI on collection, ROI on collection activity, collection activity ROI, and the like) may also more specifically be utilized herein to describe a context relating to an action of receiving value, such as a collection action (e.g. actions to induce tendering or acquisition of overdue or default payments on a loan or other obligation), wherein there is a return on investment (ROI). The result of such a collection action may or may not have an ROI, either with respect to the collection action itself (as an ROI on the collection action) or as an ROI on the broader loan or transaction that is the subject of the collection action. For example, an ROI on a collection action may be prudent or not with respect to a default loan, without limitation, depending upon whether the ROI will be provided to a party such as the lender. A projected ROI on collection may be estimated, or may also be calculated given real events that transpire. In some circumstances, a smart contract circuit or robotic process automation system may render an estimated ROI for a collection action or collection event, or may calculate an ROI for actual events transpiring in a collection action or collection event, without limitation. In embodiments, such a ROI may be a positive or negative figure, whether estimated or actual.[000308] The term reputation, measure of reputation, lender reputation, borrower reputation, entity reputation, and the like may include general, widely held beliefs, opinions, and / or perceptions that are generally held about an individual, entity, collateral, and the like. A measure for reputation may be determined based on social data including likes / dislikes, review of entity or products and services provided by the entity, rankings of the company or product, current and historic market and financial data include price, forecast, buy / sell recommendations, financial news regarding entity, competitors, and partners. Reputations may be cumulative in that a product reputation and the reputation of a company leader or lead scientist may influence the overall reputation of the entity. Reputation of an institute associated with an entity (e.g. a school being attended by a student) may influence the reputation of the entity. In some circumstances, a smart contract circuit or robotic process automation system may collect, or initiate collection of data related to the above and determine a measure or ranking of reputation. A measure orranking of an entity's reputation may be used by a smart contract circuit or robotic process automation system in determining whether to enter into an agreement with the entity, determination of terms and conditions of a loan, interest rates, and the like. In certain embodiments, indicia of a reputation determination may be related to outcomes of one or more transactions (e.g., a comparison of "likes" on a particular social media data set to an outcome index, such as successful payments, successful negotiation outcomes, ability to liquidate a particular type of collateral, etc.) to determine the measure or ranking of an entity's reputation. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system, can readily determine the purposes and use of the reputation, a measure or ranking of the reputation, and / or utilization of the reputation in negotiations, determination of terms and conditions, determination of whether to proceed with a transaction, and other various embodiments and contexts disclosed herein.[000309] The term collection in various forms (e.g. collector) may also more specifically be utilized herein to describe a party or entity that induces, administrates, or facilitates a collection action, collection event, or other collection related context. The measure of reputation of a party involved, such as a collector, or during the context of a collection, may be estimated or calculated using objective, subjective, or historical metrics or data. For example, a collector may be involved in a collection action, and the reputation of that collector may be used to determine decisions, actions, or conditions. Similarly, a collection may be also used to describe objective, subjective or historical metrics or data to measure the reputation of a party involved, such as a lender, borrower, or debtor. In some circumstances, a smart contract circuit or robotic process automation system may render a collection or measures, or implement a collector, within the context of a transaction or loan.[000310] The term collection and data collection in various forms, including data collection systems, may also more specifically be utilized herein to describe a context relating to the acquisition, organization, or processing of data, or combinations thereof, without limitation. The result of such a data collection may be related or wholly unrelated to a collection of items (e.g., grouping of the items, either physically or logically), or actions taken for delinquent payments (e.g., collection of collateral, a debt, or the like), without limitation. For example, a data collection may be performed by a data collection system, wherein data is acquired, organized, or processed for decision-making, monitoring, or other purposes of prospective or actual transaction or loan. In some circumstances, a smart contract or robotic process automation system may incorporate data collection or a data collection system, to perform portions or entire tasks of data collection, without limitation. One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available for a contemplated system, can readilydetermine and distinguish the purposes and use of collection in the context of data or information as used herein.[000311] The terms refinance, refinancing activity(ies), refinancing interactions, refinancing outcomes, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure refinance and refinancing activities include replacing an existing mortgage, loan, bond, debt transaction, or the like with a new mortgage, loan, bond, or debt transaction that pays off or ends the previous financial arrangement. In certain embodiments, any change to terms and conditions of a loan, and / or any material change to terms and conditions of a loan, may be considered a refinancing activity. In certain embodiments, a refinancing activity is considered only those changes to a loan agreement that result in a different financial outcome for the loan agreement. Typically, the new loan should be advantageous to the borrower or issuer, and / or mutually agreeable (e.g., improving a raw financial outcome of one, and a security or other outcome for the other). Refinancing may be done to reduce interest rates, lower regular payments, change the loan term, change the collateral associated with the loan, consolidate debt into a single loan, restructure debt, change a type of loan (e.g. variable rate to fixed rate), pay off a loan that is due, in response to an improved credit score, to enlarge the loan, and / or in response to a change in market conditions (e.g. interest rates, value of collateral, and the like).[000312] Refinancing activity may include initiating an offer to refinance, initiating a request to refinance, configuring a refinancing interest rate, configuring a refinancing payment schedule, configuring a refinancing balance in a response to the amount or terms of the refinanced loan, configuring collateral for a refinancing including changes in collateral used, changes in terms and conditions for the collateral, a change in the amount of collateral and the like, managing use of proceeds of a refinancing, removing or placing a lien on different items of collateral as appropriate given changes in terms and conditions as part of a refinancing, verifying title for a new or existing item of collateral to be used to secure the refinanced loan, managing an inspection process title for a new or existing item of collateral to be used to secure the refinanced loan, populating an application to refinance a loan, negotiating terms and conditions for a refinanced loan and closing a refinancing. Refinance and refinancing activities may be disclosed in the context of data collection and monitoring services that collect a training set of interactions between entities for a set of loan refinancing activities. Refinance and refinancing activities may be disclosed in the context of an artificial intelligence system that is trained using the collected training set of interactions that includes both refinancing activities and outcomes. The trained artificial intelligence may then be used to recommend a refinance activity, evaluate a refinance activity, make a prediction around an expected outcome of refinancing activity, andthe like. Refinance and refinancing activities may be disclosed in the context of smart contract systems which may automate a subset of the interactions and activities of refinancing. In an example, a smart contract system may automatically adjust an interest rate for a loan based on information collected via at least one of an Internet of Things system, a crowdsourcing system, a set of social network analytic services and a set of data collection and monitoring services. The interest rate may be adjusted based on rules, thresholds, model parameters that determine, or recommend, an interest rate for refinancing a loan based on interest rates available to the lender from secondary lenders, risk factors of the borrower (including predicted risk based on one or more predictive models using artificial intelligence), marketing factors (such as competing interest rates offered by other lenders), and the like. Outcomes and events of a refinancing activity may be recorded in a distributed ledger. Based on the outcome of a refinance activity, a smart contract for the refinance loan may be automatically reconfigured to define the terms and conditions for the new loan such as a principal amount of debt, a balance of debt, a fixed interest rate, a variable interest rate, a payment amount, a payment schedule, a balloon payment schedule, a specification of collateral, a specification of substitutability of collateral, a party, a guarantee, a guarantor, a security, a personal guarantee, a lien, a duration, a covenant, a foreclose condition, a default condition, and a consequence of default.[000313] One of skill in the art, having the benefit of the disclosure herein and knowledge ordinarily available about a contemplated system can readily determine which aspects of the present disclosure will benefit from a particular application of a refinance activity, how to choose or combine refinance activities, how to implement systems, services, or circuits to automatically perform of one or more (or all) aspects of a refinance activity, and the like. Certain considerations for the person of skill in the art, or embodiments of the present disclosure in choosing an appropriate training sets of interactions with which to train an artificial intelligence to take action, recommend or predict the outcome of certain refinance activities. While specific examples of refinance and refinancing activities are described herein for purposes of illustration, any embodiment benefitting from the disclosures herein, and any considerations understood to one of skill in the art having the benefit of the disclosures herein, are specifically contemplated within the scope of the present disclosure.[000314] The terms consolidate, consolidation activity(ies), loan consolidation, debt consolidation, consolidation plan, and similar terms, as utilized herein should be understood broadly. Without limitation to any other aspect or description of the present disclosure consolidate, consolidation activity(ies), loan consolidation, debt consolidation, or consolidation plan are related to the use of a single large loan to pay off several smaller loans, and / or the use of o...

Claims

What is claimed is1. A method for configuring and launching a marketplace, comprising: identifying an opportunity to facilitate configuration of a new marketplace; receiving marketplace opportunity data, wherein the marketplace opportunity data includes information related to a set of assets of one or more types; determining configuration parameters to be implemented in the new marketplace; determining a feasibility of implementing the configuration parameters in the new marketplace; determining data resources to support the new marketplace; determining an architecture of the new marketplace; determining the configuration of the data resources in a data model for the marketplace; configuring a marketplace object; connecting selected data resources to populate the marketplace object; and launching the new marketplace.

2. The method of claim 1, further comprising recording features of the configuration.

3. The method of claim 2, wherein the features of configuration include at least one of: a type of asset supported, an anonymity rule, a listing requirement, a fee, a supported trading type, a shipping rule, or a delivery rule.

4. The method of claim 1, wherein the marketplace opportunity data include at least one of: an asset, an asset type, asset data, or asset demand data.

5. The method of claim 4, wherein the asset demand data includes at least one of: a demand quantity, a demand location, a demand demographics, or a demand indicator.

6. The method of claim 1, further comprising prioritizing an implementation of the marketplace based on a set of desired outcomes.

7. The method of claim 6, wherein the set of desired outcomes include at least one of: overall profitability of the marketplace, efficiency of the marketplace, generation of threshold levels of overall participation, participation by parties of desired types, or generation of threshold levels of trading activity.7838. A method for configuring and launching a marketplace, comprising: taking an identified type of asset and defining an exchangeable marketplace object that represents a set of rights to control the identified type of asset, wherein defining the exchangeable marketplace object includes specifying a data model for the exchangeable marketplace object and a set of data resources for populating instances of the exchangeable marketplace object; configuring a mechanism for exchange of instances of the exchangeable marketplace object, wherein the mechanism for exchange includes a set of interfaces whereby instances of the exchangeable marketplace objects may be exchanged in defined quantities for defined units of value; and configuring a set of computational and connectivity resources to support a marketplace by which the defined exchangeable marketplace objects are exchanged; wherein at least one of: defining the exchangeable marketplace object, configuring the mechanism of exchange, or configuring the set of computational and connectivity resources, is performed by robotic process automation that is trained on a training set of interactions by a set of human users.

9. The method of claim 8, wherein marketplace object further comprises a set of metadata that defines overall market operational parameters.

10. The method of claim 8, further comprises enabling exchange opportunities between different market environments.

11. The method of claim 8, wherein configuring the mechanism for exchange comprises setting exchange rates for trading between native currencies of different market environments.

12. The method of claim 8, further comprising identifying a set of legal rights to control a type of asset for which an online marketplace or exchange is not active.

13. The method of claim 8, further comprising prioritizing an implementation of the marketplace based on a set of desired outcomes.

14. The method of claim 13, wherein the set of desired outcomes include at least one of: overall profitability of the marketplace, efficiency of the marketplace, generation of threshold levels of784overall participation, participation by parties of desired types, or generation of threshold levels of trading activity.

15. A method for configuring and launching a marketplace, comprising: identifying a set of legal rights to control a type of asset for which an online marketplace or exchange is not active; defining an exchangeable marketplace object that represents the set of legal rights to control the type of asset, wherein defining the exchangeable marketplace object includes specifying a data model for the exchangeable marketplace object and a set of data resources for populating instances of the exchangeable marketplace object; configuring a mechanism for exchange of instances of the exchangeable marketplace object, wherein the mechanism for exchange includes a set of interfaces whereby instances of exchangeable marketplace objects may be exchanged in defined quantities for defined units of value; and configuring a set of computational and connectivity resources to support a marketplace by which the defined exchangeable marketplace objects are exchanged.

16. The method of claim 15, wherein identifying the set of legal rights includes automatically monitoring changes in law.

17. The method of claim 15, wherein at least one of: defining the exchangeable marketplace object, configuring the mechanism of exchange, or configuring the set of computational and connectivity resources, is performed by robotic process automation that is trained on a training set of interactions by a set of human users.

18. The method of claim 15, further comprises enabling exchange opportunities between different market environments.

19. The method of claim 18, wherein configuring the mechanism for exchange comprises setting exchange rates for trading between native currencies of different market environments.

20. The method of claim 15, wherein marketplace object further comprises a set of metadata that defines overall market operational parameters.78521. A method for configuring role-based digital twins, comprising: generating, by a processing system, a digital twin of a marketplace, wherein the digital twin is a digital representation of a structure of the marketplace, the structure having a set of entities of the marketplace that include assets and roles; determining, by the processing system, a set of relationships between different roles with respect to the set of entities of the marketplace; determining, by the processing system, a set of settings for a role from a set of roles based on the set of determined relationships; using the set of determined relationships within the marketplace structure to provide a set of settings for the set of roles; linking a set of identities to roles; determining, by the processing system, a configuration of a presentation layer of a rolebased market orchestration digital twin corresponding to each respective role based on the set of settings of the role that is linked to an identity of the set of identities, wherein the configuration of the presentation layer defines a set of states that is depicted in the role-based market orchestration digital twin associated with the role; determining, by the processing system, a set of data sources that provide data corresponding to the set of states, wherein each data source provides one or more respective types of data; and configuring one or more data structures that store the data that is received from the set of data sources, wherein the one or more data structures are configured to provide data used to populate one or more of the set of states in the role-based market orchestration digital twin.

22. The method of claim 21, further comprising linking the set of identities to the set of roles, wherein each identity corresponds to a respective role from the set of roles.

23. The method of claim 21, wherein the role-based market orchestration digital twin integrates with a market orchestration platform that operates on the role-based market orchestration digital twin such that changes in the market orchestration platform are automatically reflected in the role-based market orchestration digital twin.

24. The method of claim 21, wherein the set of settings for the set of roles includes rolebased permission settings.78625. The method of claim 21, wherein the set of settings for the set of roles includes rolebased preference settings.

26. The method of claim 25, wherein the role-based preference settings are configured based on a set of role-specific templates.

27. The method of claim 26, wherein the set of role-specific templates includes at least one of a trader template, a marketplace host template, a broker template, a buyer template, or a seller template.

28. The method of claim 21, wherein the set of settings for the set of roles includes a set of role-based taxonomy settings.

29. The method of claim 28, wherein the role-based taxonomy settings identify a taxonomy that is used to characterize data that is presented in the role-based market orchestration digital twin, such that the data is presented in a taxonomy that is linked to the role corresponding to the role-based market orchestration digital twin.

30. The method of claim 29, wherein the set of role-based taxonomies includes at least one of: a trader template, a marketplace host template, a broker template, a buyer template, or a seller template.

31. The method of claim 21, wherein at least one role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role.

32. The method of claim 21, wherein at least one role includes: a market maker role, a market analyst role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, or a contract configuration role.

33. The method of claim 21, wherein the role is selected from among a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role.78734. A method for training an intelligent agent, comprising: receiving digital twin data from a set of data sources, the digital twin data including: physical entity data that is received from a set of data resources that monitor a set of monitored physical entities associated with a marketplace, the physical entity data transported by a set of network entities; and marketplace data streams generated by a set of marketplace assets, wherein the set of marketplace assets include at least one of physical entities associated with the marketplace or digital entities associated with the marketplace; structuring the digital twin data into a set of digital twin data structures that are configured to serve a plurality of different role-based digital twins; receiving a request for a role-based digital twin from a client application, wherein the role-based digital twin is configured with respect to a role within the marketplace; determining a subset of the structured digital twin data to corresponds to a set of states that are depicted in the role-based digital twin; providing the subset of the structured digital twin data to the client application; receiving intelligent agent training data sets from the client application, each intelligent agent training data set indicating a respective action taken by a user using the client application and one or more features that correspond to the respective action; and training an intelligent agent on behalf of the user based on the intelligent agent training data sets, wherein the intelligent agent is configured to determine actions to be performed on behalf of the user, wherein the determined actions to be performed are either recommended to the user or automatically performed on behalf of the user.

35. The method of claim 34, wherein the role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role.

36. The method of claim 34, wherein the role is selected from among a market maker role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role.

37. The method of claim 34, wherein the role is selected from among a chief marketing officer role, a product development role, a supply chain manager role, a customer role, a supplier role, a vendor role, a demand management role, a marketing manager role, a sales788manager role, a service manager role, a demand forecasting role, a retail manager role, a warehouse manager role, a salesperson role, and a distribution center manager role.

38. The method of claim 34, wherein the intelligent agent training data sets include interactions training data that indicates a set of interactions with a set of experts by the user during performance of the role.

39. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of the user with the physical entities.

40. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of the user with the role-based digital twin.

41. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of the user with sensor data as depicted in the role-based digital twin.

42. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of at least one of the set of experts with the marketplace data streams generated by the physical entities.

43. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of at least a subset of the set of experts with one or more computational entities.

44. The method of claim 38, wherein the set of interactions used to train the intelligent agent includes interactions of the user with one or more network entities.

45. The method of claim 38, wherein the intelligent agent is trained to determine an action including at least one of: selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying a need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset, physicallyretrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, or order matching.

46. The method of claim 38, wherein the intelligent agent is trained on a training set of outcomes resulting from the actions taken by the user.

47. The method of claim 46 wherein the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, and a production outcome.

48. The method of claim 38, wherein the intelligent agent is trained to perform an action including at least one of: determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber- securing a device, cyber-securing a process, cyber- securing a network, cyber- securing a computational resource, cyber-securing equipment, cyber-securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware, configuring a system, configuring a device, configuring a process, configuring a network, configuring a computational resource, configuring equipment, or configuring hardware.

49. The method of claim 34, wherein the intelligent agent is at least one of trained or configured via feedback from at least one expert in a defined role regarding a set of outputs of intelligent agent.

50. The method of claim 49, wherein the set of outputs of the intelligent agent upon which the at least one expert provides feedback includes at least one of a recommendation, a classification, a prediction, a control instruction, an input selection, a protocol selection, a communication, an alert, a target selection for a communication, a data storage selection, a computational selection, a configuration, an event detection, or a forecast.

51. The method of claim 50, wherein the feedback of the at least one expert is solicited to train the intelligent agent to replicate expertise of an expert in the role.

52. The method of claim 51, wherein the feedback of the at least one expert is used to modify a set of inputs to the intelligent agent.

53. The method of claim 52, wherein the feedback of the at least one expert is used to identify and characterize at least one error by the intelligent agent.

54. The method of claim 53, wherein a report on a set of errors is provided to a user of the intelligent agent to enable reconfiguring of the intelligent agent based on the feedback from the expert.

55. The method of claim 54, wherein reconfiguring the intelligent agent includes at least one of removing an input that is a source of the at least one error, reconfiguring a set of nodes of the intelligent agent, reconfiguring a set of weights of the intelligent agent, reconfiguring a set of outputs of the intelligent agent, reconfiguring a processing flow within the intelligent agent, or augmenting the set of inputs to the intelligent agent.

56. The method of claim 34, wherein the intelligent agent is trained upon a training set of outcomes and to provide at least one of training or guidance to an individual who performs a defined role in a marketplace.

57. The method of claim 56, wherein the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, aperformance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, or a production outcome.

58. The method of claim 38, wherein the method further includes parsing the training data set of interactions to identify a type of processing undertaken by the user in analyzing the set of interactions.

59. The method of claim 58, wherein the type of processing includes at least one of: audio processing, analyzing audio information, tactile processing, textual information processing, motion processing, visual processing, spatiotemporal processing, mathematical processing, or analytic processing.

60. A method, comprising: taking an information technology architecture that supports a digital twin of a set of physical entities; and integrating an artificial intelligence system with the information technology architecture, wherein the artificial intelligence system is configured to operate as an intelligent agent double of an expert worker for a defined role, wherein the expert worker is provided with a benefit for training the artificial intelligence system, wherein the benefit is based on a set of outcomes of an operation of the intelligent agent double within the information technology architecture.

61. The method of claim 60, wherein the information technology architecture comprises: a set of sensors that provide sensor data about the set of physical entities; and a set of data streams generated by at least a subset of the set of physical entities.

62. The method of claim 61, wherein the information technology architecture further comprises: a set of computational entities for processing data and a set of network entities for transporting data that is derived from the set of sensors and the set of data streams; and a set of data processing systems for extracting, transforming, and loading the data that is transported by a subset of the set of network entities into a set of resources that are sources for the digital twin.

63. The method of claim 60, wherein the benefit is a reward based on the set of outcomes of a use of the artificial intelligence system.

64. The method of claim 63, further comprising: tracking the reward via a distributed ledger on a blockchain that captures information associated with a set of actions and events involving the artificial intelligence system; and administering the reward via a smart contract operating on the blockchain.

65. A method, comprising: taking an information technology architecture that supports a digital twin of a set of physical entities, the information technology architecture including: a set of sensors that provide sensor data about the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing data and a set of network entities for transporting data that is derived from the set of sensors and the set of data streams; a set of data processing systems for extracting, transforming, and loading the data that is transported by the set of network entities into a set of resources that are sources for the digital twin; and integrating an artificial intelligence system with the information technology architecture, wherein the artificial intelligence system is configured to operate as a double of an expert worker for a defined role of marketplace and wherein the expert worker is provided with a benefit for training the artificial intelligence system.

66. The method of claim 65, wherein the benefit is a reward based on outcomes of a use of the artificial intelligence system.

67. The method of claim 65, wherein the benefit is a reward based on productivity of the artificial intelligence system.

68. The method of claim 65, wherein the benefit is a reward based on a measure of expertise of the artificial intelligence system.

69. The method of claim 65, wherein the benefit is a share of revenue or profit generated by work of the artificial intelligence system.

70. The method of claim 66, wherein the reward is tracked via a distributed ledger on a blockchain that captures information associated with a set of actions and events involving the artificial intelligence system.79371. The method of claim 70, wherein the reward is administered via a smart contract operating on the blockchain.

72. The method of claim 65, wherein the artificial intelligence system is trained upon a training set of data that includes a set of interactions by a specific expert worker during performance of the defined role.

73. The method of claim 72, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with physical entities.

74. The method of claim 72, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with the digital twin.

75. The method of claim 72, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with the sensor data.

76. The method of claim 73, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with the set of data streams generated by the physical entities.

77. The method of claim 72, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with the set of computational entities.

78. The method of claim 72, wherein the set of interactions used to train the artificial intelligence system includes interactions of the specific expert worker with the set of network entities.

79. The method of claim 73, wherein the artificial intelligence system is trained based on the set of interactions to determine an action including at least one of: selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying a need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset,794physically retrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, or order matching.

80. The method of claim 72, wherein the training set of interactions is parsed to identify a chain of reasoning of the expert worker upon a set of information and the chain of reasoning is embodied in the configuration of the artificial intelligence system.

81. The method of claim 80, wherein the chain of reasoning is parsed to identify a type of reasoning of the expert worker and the type of reasoning is used as a basis for configuration of the artificial intelligence system.

82. The method of claim 80, wherein the chain of reasoning is a deductive chain of reasoning from a set of data.

83. The method of claim 65, wherein the artificial intelligence system is trained to perform an action including at least one of: determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber- securing a device, cyber-securing a process, cyber- securing a network, cyber- securing a computational resource, cyber-securing equipment, cyber-securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware,795configuring a system, configuring a device, configuring a process, configuring a network, configuring a computational resource, configuring equipment, or configuring hardware.

84. A method, comprising: taking an information technology architecture that supports a digital twin of a set of physical entities; and integrating an artificial intelligence system with the information technology architecture, wherein the artificial intelligence system is configured to operate as an intelligent agent double of a defined market orchestration workforce that performs a defined set of roles of a marketplace.

85. The method of claim 84, wherein the information technology architecture includes: a set of sensors that provide sensor data about the set of physical entities; a set of data streams generated by at least a subset of the set of physical entities; a set of computational entities for processing data and a set of network entities for transporting data that is derived from the set of sensors and the set of data streams; and a set of data processing systems for extracting, transforming, and loading the data that is transported by network entities into a set of resources that are sources for the digital twin.

86. The method of claim 85, wherein the artificial intelligence system is trained upon a training set of data that includes a set of interactions by members of a defined workforce during performance of the defined set of roles.

87. The method of claim 86, wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with the set of physical entities.

88. The method of claim 86, wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with the digital twin.

89. The method of claim 86, wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with sensor data.

90. The method of claim 86, wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with a subset of the set of data streams generated by the set of physical entities.79691. The method of claim 86 wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with a subset of the set of computational entities.

92. The method of claim 86, wherein the set of interactions used to train the artificial intelligence system includes interactions of the defined workforce with a subset of the set of network entities.

93. The method of claim 86, wherein the training set of interactions is parsed to identify a chain of operations of the defined workforce upon a set of information and the chain of reasoning is embodied in the configuration of the artificial intelligence system.

94. The method of claim 86, wherein the training set of interactions is parsed to identify a type of processing of the defined workforce upon a set of information and the type of processing is embodied in the configuration of the artificial intelligence system.

95. The method of claim 86, wherein the artificial intelligence system is trained, based on the training set of interactions, to determine an action, wherein the action comprises one of selection of an asset, pricing of an asset, configuring a marketplace, listing an asset in a marketplace, uploading information related to an asset listed in a marketplace, identifying counterparties, selecting counterparties, identifying opportunities, selecting opportunities, performing a negotiation, identifying a need for a new marketplace, digitally inspecting an asset, physically inspecting an asset, configuring a digital twin, placing an order request, generating a smart contract, physically delivering an asset, physically retrieving an asset, selection of a trading strategy, brokering a trade, valuation of an asset, or order matching.

96. The method of claim 86, wherein the artificial intelligence system is trained on a training set of outcomes.

97. The method of claim 96, wherein the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, or a production outcome.79798. The method of claim 96, wherein the artificial intelligence system is at least one of trained or configured via feedback from members of the defined workforce regarding a set of outputs of the artificial intelligence system.

99. The method of claim 98, wherein the set of outputs of the artificial intelligence system upon which the members of the defined workforce provide feedback includes at least one of a recommendation, a classification, a prediction, a control instruction, an input selection, a protocol selection, a communication, an alert, a target selection for a communication, a data storage selection, a computational selection, a configuration, an event detection, or a forecast.

100. The method of claim 98, wherein the feedback of the members of the defined workforce is solicited to train the artificial intelligence system to replicate the operation of the workforce in the defined set of roles.

101. The method of claim 98, wherein the feedback of the members of the defined workforce is used to modify a training set of inputs to the artificial intelligence system.

102. The method of claim 98, wherein the feedback of the members of the defined workforce is used to identify and characterize at least one error by the artificial intelligence system.

103. The method of claim 86, wherein a report on a set of errors is provided to a manager of the artificial intelligence system to enable reconfiguring of the artificial intelligence system based on feedback.

104. The method of claim 103, wherein reconfiguring the artificial intelligence system includes at least one of removing an input that is a source of an error, reconfiguring a set of nodes of the artificial intelligence system, reconfiguring a set of weights of the artificial intelligence system, reconfiguring a set of outputs of the artificial intelligence system, reconfiguring a processing flow within the artificial intelligence system, or augmenting the set of inputs to the artificial intelligence system.

105. The method of claim 84, wherein the artificial intelligence system is configured to provide at least one of training or guidance to enable the other worker to perform a role within the defined set of roles of the defined workforce.798106. The method of claim 105, wherein the artificial intelligence system is further configured to learn, on a training set of outcomes, to enhance the training and guidance.

107. The method of claim 106, wherein the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, or a production outcome.

108. The method of claim 86, wherein the artificial intelligence system is trained to perform an action selected from among determining an architecture for a system, reporting on a status, reporting on an event, reporting on a context, reporting on a condition, determining a model, configuring a model, populating a model, designing a system, designing a process, designing an apparatus, engineering a system, engineering a device, engineering a process, engineering a product, maintaining a system, maintaining a device, maintaining a process, maintaining a network, maintaining a computational resource, maintaining equipment, maintaining hardware, repairing a system, repairing a device, repairing a process, repairing a network, repairing a computational resource, repairing equipment, repairing hardware, assembling a system, assembling a device, assembling a process, assembling a network, assembling a computational resource, assembling equipment, assembling hardware, setting a price, physically securing a system, physically securing a device, physically securing a process, physically securing a network, physically securing a computational resource, physically securing equipment, physically securing hardware, cyber- securing a system, cyber- securing a device, cyber-securing a process, cyber- securing a network, cyber- securing a computational resource, cyber-securing equipment, cyber-securing hardware, detecting a threat, detecting a fault, tuning a system, tuning a device, tuning a process, tuning a network, tuning a computational resource, tuning equipment, tuning hardware, optimizing a system, optimizing a device, optimizing a process, optimizing a network, optimizing a computational resource, optimizing equipment, optimizing hardware, monitoring a system, monitoring a device, monitoring a process, monitoring a network, monitoring a computational resource, monitoring equipment, monitoring hardware, configuring a system, configuring a device, configuring a process, configuring a network, configuring a computational resource, configuring equipment, and configuring hardware.799109. The method of claim 86, wherein the artificial intelligence system is configured to provide at least one of training or guidance to the defined workforce to enable the defined workforce to perform the defined role.

110. The method of claim 109, wherein the artificial intelligence system is configured to learn, on a training set of outcomes, to enhance the at least one of training or guidance.

111. The method of claim 110, wherein the training set of outcomes includes data relating to at least one of a financial outcome, an operational outcome, a fault outcome, a success outcome, a performance indicator outcome, an output outcome, a consumption outcome, an energy utilization outcome, a resource utilization outcome, a cost outcome, a profit outcome, a revenue outcome, a sales outcome, or a production outcome.

112. The method of claim 108, wherein outcomes are compared between a set of actions of the defined workforce and a set of outputs of the artificial intelligence system.

113. The method of claim 112, wherein the output comparison is used to train the defined workforce.

114. The method of claim 112, wherein the output comparison is used to improve the artificial intelligence system.

115. The method of claim 85, wherein at least one role within the set of roles of the defined workforce is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role.

116. The method of claim 85, wherein the defined workforce is a supply chain management workforce.

117. The method of claim 85, wherein the defined workforce is a demand planning workforce.

118. The method of claim 85, wherein the defined workforce is a logistics planning workforce.

119. The method of claim 85, wherein the defined workforce is a vendor management workforce.800120. The method of claim 85, wherein the defined workforce is a brokering workforce for a marketplace.

121. The method of claim 85, wherein the defined workforce is a trading workforce for a marketplace.

122. The method of claim 85, wherein the defined workforce is a trade reconciliation workforce for a marketplace.

123. The method of claim 85, wherein the defined workforce is a transactional execution workforce for a marketplace.

124. The method of claim 85, wherein the set of computational entities and the set of network entities are integrated as a converged computational and network entity.

125. A method for configuring a digital twin of a workforce, comprising: representing an enterprise organizational structure in a digital twin of a digital marketplace orchestration enterprise; parsing the enterprise organizational structure to infer relationships among a set of roles within the organizational structure, the relationships and the set of roles defining a workforce of the digital marketplace orchestration enterprise; and configuring a presentation layer of a digital twin to represent the digital marketplace orchestration enterprise as a set of workforces having a set of attributes and relationships.

126. The method of claim 125, wherein the digital twin integrates with a digital market orchestration platform that operates on a data structure representing a set of roles in the digital marketplace, such that changes in the digital marketplace orchestration enterprise are automatically reflected in the digital twin.

127. The method of claim 125, wherein the workforce is a brokering workforce for a marketplace.

128. The method of claim 125, wherein the workforce is a trading workforce for a marketplace.801129. The method of claim 125, wherein the workforce is a trade reconciliation workforce for a marketplace.

130. The method of claim 125, wherein the workforce is a transactional execution workforce for a marketplace.

131. The method of claim 125, wherein at least one workforce role is selected from among a trader role, a marketplace host role, a broker role, a buyer role, and a seller role.

132. The method of claim 125, wherein at least one workforce role is selected from among a market maker role, an exchange manager role, a broker-dealer role, a trading role, a reconciliation role, a contract counterparty role, an exchange rate setting role, a market orchestration role, a market configuration role, and a contract configuration role.

133. The method of claim 125, wherein the digital twin represents a recommendation for training for the workforce.

134. The method of claim 125, wherein the digital twin provides a recommendation for augmentation of the workforce.

135. The method of claim 125, wherein the digital twin provides a recommendation for configuration of a set of operations involving the workforce.

136. The method of claim 125, wherein the digital twin provides a recommendation for configuration of the workforce.

137. A market orchestration platform, comprising: a machine learning system that trains a set of machine-learned models to output a determination related to a stage of a marketplace using training data comprising marketplace features and outcomes; and an artificial intelligence system that receives a request for a determination related to the stage of the marketplace and generates the determination related to the stage of the marketplace based on the set of machine-learned models and the request.802138. The market orchestration platform of claim 137, wherein the determination related to the stage of the marketplace is leveraged, at least in part, to automatically adjust parameters of the marketplace.

139. The market orchestration platform of claim 137, wherein the set of machine-learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term / short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing.

140. The market orchestration platform of claim 137, wherein a digital twin of a workflow of the marketplace is configured to depict, for at least one state, a status, an input, an output, an outcome, or a processing operation.

141. A method for updating one or more properties of one or more market orchestration digital twins, comprising: receiving a request to update one or more properties of one or more digital twins; retrieving the one or more digital twins required to fulfill the request; selecting data sources from a set of available data sources; retrieving data from selected data sources; and updating one or more properties of the one or more digital twins based on the retrieved data.

142. The method of claim 141, wherein the one or more digital twins include at least one of: marketplace digital twins, asset digital twins, trader digital twins, broker digital twins, environment digital twins, or marketplace host digital twins.

143. The method of claim 141, wherein the one or more properties of the one or more digital twins relates to asset ownership.

144. The method of claim 141, wherein the selected data source includes at least one of: an Internet of Things connected device, a machine vision system, an analog vibration sensor, a digital vibration sensor, a fixed digital vibration sensor, a tri-axial vibration sensor, a single axis vibration sensor, or an optical vibration sensor.803145. The method of claim 141, wherein the digital twin comprises a data-based digital twin, and wherein the data-based digital twin comprises a data structure including a set of parameters that are parametrized to represent a state of a thing.

146. The method of claim 143, further comprising: tracking, using a digital twin, a physical item whose ownership rights are to be traded in a marketplace; and representing a condition of the physical item.

147. A method for generating a fairness score for a transaction: receiving, by a fairness engine, transaction data from a set of transactions from an execution engine; and calculating, by the fairness engine, the fairness score representing a fairness of the transaction.

148. The method of claim 147, wherein the fairness engine includes an execution timing fairness engine that determines or receives a set of measures of latency for a set of users.

149. The method of claim 148, wherein the execution timing fairness engine automatically orchestrates a set of configuration parameters or other features that mitigate unfairness that may be caused by disparate latency.

150. The method of claim 148, wherein the set of measures of latency is determined by testing network return times.

151. The method of claim 150, wherein testing network return times includes determining a ping, an upload speed, or a download speed.

152. The method of claim 147, wherein the set of transactions are executed based upon the fairness score exceeding a predetermined threshold.804153. A market orchestration platform, comprising: a quantum computing system that determines a rate of exchange among a set of marketplaces by simulating a set of trading activities involving the set of marketplaces.

154. The market orchestration platform of claim 153, wherein the quantum computing system supports models including at least one of: a quantum circuit model, quantum Turing model, adiabatic quantum computer, one-way quantum computer, quantum annealing, quantum cellular autonoma, or hybrids and combinations of the foregoing.

155. The market orchestration platform of claim 153, wherein the quantum computing system comprises a quantum annealing module configured to find a global minimum or maximum of an objective function over a set of candidate solutions.

156. The market orchestration platform of claim 155, wherein the quantum annealing module is further configured to provide optimized asset pricing.

157. The market orchestration platform of claim 153, wherein the quantum computing system further comprises a trapped ion quantum computer module configured to apply trapped ions to solve complex problems.

158. The market orchestration platform of claim 153, wherein the quantum computing system is simulated by a computer program executed by a traditional computer.

159. The market orchestration platform of claim 153, wherein the quantum computing system comprises quantum output filters configured to select a solution from a set of solutions provided by a plurality of neural networks.

160. The market orchestration platform of claim 153, wherein the quantum computing system further comprises a quantum database engine configured to assist with recognition of individuals and identities across market platforms.

161. The market orchestration platform of claim 160, wherein the quantum database engine is further configured to establish a single identity for a trader that is valid across interactions.805162. The market orchestration platform of claim 161, wherein the quantum computing system is further configured to optimize an individualized marketplace experience.

163. The market orchestration platform of claim 153, wherein the quantum computing system is further configured to solve arbitrage-related optimization problems across marketplaces.

164. The market orchestration platform of claim 153, wherein the quantum computing system is further configured to predict volatility in assets and / or markets and identify a risk profile for investment strategies.

165. The market orchestration platform of claim 164, wherein the quantum computing system is further configured to manage risk factors.

166. The market orchestration platform of claim 165, wherein the quantum computing system is further configured to assign an optimization weight for an asset class.

167. The market orchestration platform of claim 166, wherein weight comprises a percentage of a portfolio that concentrates in the asset class.

168. A market orchestration platform, comprising: a counterparty strategy engine including: a machine learning system that trains a set of machine-learned models to output a determination related to trading strategies employed by a set of counterparties using a training data set comprising at least one of: marketplace features, activities, or outcomes; and an artificial intelligence system that receives a request for a determination related to the trading strategies employed by the set of counterparties and generates the determination related to the strategies employed by the set of counterparties based on the set of machine-learned models and the request.

169. The market orchestration platform of claim 168, wherein the trading strategies include at least one of: buy and hold, long / short equity, asset allocation, intertemporal portfolio choice, pairs trading, swing trading, scalping, day trading, news-based, market timing, social trading, front-running, chart-based, computer- science based, automated / algorithmic, or hybrids or combinations of the foregoing.806170. The market orchestration platform of claim 168, wherein the counterparty strategy engine is configured to identify a counterparty user.

171. The market orchestration platform of claim 170, wherein the counterparty strategy engine is further configured to facilitate automated recommendations to a counterparty user.

172. The market orchestration platform of claim 171, wherein the machine learning system is further configured to identify complementary or competitive trading strategies for a counterparty user.

173. A market orchestration platform, comprising:A machine learning system that trains a set of machine-learned models to identify a set of similar parties for a cohort-targeted marketplace using a training data set comprising at least one of: marketplace features, activities, or outcomes; and an artificial intelligence system that receives a request to identify a group of similar parties, identifies the group of similar parties, and generates the cohort-targeted marketplace based on an identification of the group of similar parties.

174. The market orchestration platform of claim 173, wherein the group of similar parties are selected from a set of buyers, sellers, brokers, and investors.

175. The market orchestration platform of claim 173, wherein the set of machine-learned models employ a convolutional neural network, a recurrent neural network, a feed forward neural network, a long-term / short-term memory (LTSM) neural network, a self-organizing neural network, and hybrids and combinations of the foregoing.

176. The market orchestration platform of claim 173, wherein content from a set of product websites may be fed to the set of machine-learned models, which are trained to identify new product or service offerings relevant to the cohort-targeted marketplace.

177. A market orchestration platform, comprising: a quantum computing system configured to directly program weights of a neural network such that the neural network produces desired outputs.807178. The market orchestration platform of claim 177, wherein the quantum computing system supports at least one: of a quantum circuit model, a quantum Turing model, an adiabatic quantum computer, a one-way quantum computer, a quantum annealing, a quantum cellular autonoma, or hybrids and combinations of the foregoing.

179. The market orchestration platform of claim 177, wherein the quantum computing system is further configured to determine a rate of exchange among a set of marketplaces by simulating a set of trading activities involving the set of marketplaces.

180. The market orchestration platform of claim 177, wherein the quantum computing system comprises a quantum annealing module configured to find a global minimum or maximum of an objective function over a set of candidate solutions.

181. The market orchestration platform of claim 180, wherein the quantum annealing module is further configured to provide optimized asset pricing.

182. The market orchestration platform of claim 177, wherein the quantum computing system further comprises a trapped ion quantum computer module configured to apply trapped ions to solve complex problems.

183. The market orchestration platform of claim 177, wherein the quantum computing system is simulated by a computer program executed by a traditional computer.

184. The market orchestration platform of claim 177, wherein the quantum computing system is further configured to optimize an individualized marketplace experience.

185. The market orchestration platform of claim 178, wherein the quantum computing system comprises quantum output filters configured to select a solution from a set of solutions provided by a plurality of neural networks.

186. The market orchestration platform of claim 177, wherein the quantum computing system further comprises a quantum database engine configured to assist with recognition of individuals and identities across market platforms.808187. The market orchestration platform of claim 186, wherein the quantum database engine is further configured to establish a single identity for a trader that is valid across interactions.

188. The market orchestration platform of claim 177, wherein the quantum computing system is further configured to solve arbitrage-related optimization problems across marketplaces.

189. The market orchestration platform of claim 177, wherein the quantum computing system is further configured to predict volatility in assets and / or markets and identify a risk profile for investment strategies.

190. The market orchestration platform of claim 189, wherein the quantum computing system is further configured to manage risk factors.

191. The market orchestration platform of claim 189, wherein the quantum computing system is further configured to assign an optimization weight for an asset class.

192. The market orchestration platform of claim 191, wherein weight comprises a percentage of a portfolio that concentrates in the asset class.

193. A knowledge distribution system for controlling rights related to digital knowledge, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and including a plurality of cryptographically linked blocks linked via cryptography; and a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and including a triggering event, and being configured to perform a smart contract action with respect to said digital knowledge in response to an occurrence of said triggering event, wherein the knowledge distribution system is configured to: receive an instance of said digital knowledge from a user; tokenize said digital knowledge such that said instance of said digital knowledge can be manipulated as a token on the distributed ledger; store said tokenized digital knowledge via the distributed ledger; process commitments of a plurality of parties to the smart contract; and809manage rights of control of and access to the tokenized digital knowledge according to the smart contract and manage the smart contract action in response to the triggering event.

194. The knowledge distribution system of claim 193, wherein said digital knowledge includes intellectual property of one or more intellectual property rights holders, wherein the smart contract embeds intellectual property licensing terms for intellectual property embedded in the distributed ledger, and wherein executing an operation on the distributed ledger provides access to the intellectual property and process a commitment of a party to the smart contract to said intellectual property licensing terms.

195. The knowledge distribution system of claim 193, wherein the smart contract includes a smart contract wrapper that performs an operation to add intellectual property to an aggregate stack of intellectual property.

196. The knowledge distribution system of claim 193, wherein the smart contract includes a smart contract wrapper that performs an operation on the distributed ledger to add intellectual property to agree to an apportionment of royalties among the plurality of parties in the distributed ledger.

197. The knowledge distribution system of claim 193, wherein the smart contract includes a smart contract wrapper that performs an operation on the distributed ledger to add intellectual property to an aggregate stack of intellectual property.

198. The knowledge distribution system of claim 193, wherein the smart contract includes a smart contract wrapper that performs an operation on the distributed ledger to process a commitment of a party to a contract term.

199. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set.

200. The knowledge distribution system of claim 199, wherein the distributed ledger is configured to provide, by recording a transaction in the distributed ledger, provable access to the instruction set and provable execution of the instruction set on a system.810201. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes executable algorithmic logic.

202. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes a three-dimensional (3D) printer instruction set.

203. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a coating process.

204. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a semiconductor fabrication process.

205. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes a firmware program.

206. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a field-programmable gate array.

207. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes serverless code logic.

208. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a crystal fabrication system.

209. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a food preparation process.

210. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a polymer production process.

211. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a chemical synthesis process.

212. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set for a biological production process.811213. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes a data set for a digital twin.

214. The knowledge distribution system of claim 193, wherein said tokenized digital knowledge includes an instruction set to perform a trade secret.

215. The knowledge distribution system of claim 193, wherein said system is configured to aggregate views of a trade secret into a chain that proves which knowledge recipients of the plurality of parties have viewed the trade secret.

216. The knowledge distribution system of claim 193, further comprising a reporting system configured to report an analytic result based on operations performed on the distributed ledger or said digital knowledge.

217. The knowledge distribution system of claim 193, wherein the distributed ledger is configured to aggregate a set of instructions, where an operation on the distributed ledger adds at least one instruction to a pre-existing set of instructions to provide a modified set of instructions.

218. The knowledge distribution system of claim 217, wherein the smart contract is configured to manage allocation of instruction sub-sets to the distributed ledger and access to the instruction sub-sets.

219. The knowledge distribution system of claim 193, wherein the distributed ledger is configured to log a plurality of parties who have contributed to an instance of said digital knowledge by storing data related to said plurality of parties in at least one of the plurality of cryptographically linked blocks.

220. The knowledge distribution system of claim 193, wherein the knowledge distribution system is configured to log a source of an instance of said digital knowledge by storing data related to said source in at least one of the plurality of cryptographically linked blocks.

221. The knowledge distribution system of claim 193, wherein the distributed ledger is configured such that a private network of authorized participants may establish cryptography-812based consensus required for verification of new blocks to be added to the plurality of cryptographically linked blocks.

222. The knowledge distribution system of claim 193, wherein the ledger management system is configured to facilitate crowdsourcing of information added to a block of the plurality of cryptographically linked blocks of the distributed ledger.

223. The knowledge distribution system of claim 193, wherein the distributed ledger is configured to store a review of an instance of the digital knowledge by a crowdsource in a block of the plurality of cryptographically linked blocks.

224. The knowledge distribution system of claim 193, wherein the distributed ledger is configured to store a signature of an instance of the digital knowledge by a crowdsource in a block of the plurality of cryptographically linked blocks.

225. The knowledge distribution system of claim 193, wherein the distributed ledger is configured to store a verification of an instance of the digital knowledge by a crowdsource in a block of the plurality of cryptographically linked blocks.

226. The knowledge distribution system of claim 193, wherein the ledger management system is configured to establish a plurality of cryptographic currency tokens, wherein the plurality of cryptographic currency tokens is tradeable among users of the distributed ledger.

227. The knowledge distribution system of claim 193, including an account management system in communication with the distributed ledger and configured to facilitate creation and management of user accounts related to users of the knowledge distribution system.

228. The knowledge distribution system of claim 193, further comprising a user interface system in communication with the distributed ledger and configured to present a user interface to a user of the knowledge distribution system, the user interface allowing the user to view data related to an instance of said digital knowledge.

229. The knowledge distribution system of claim 193, further comprising a marketplace system in communication with the distributed ledger and configured to establish and maintain a digital813marketplace, the digital marketplace being configured to visually present data related to an instance of said digital knowledge to a user of the knowledge distribution system.

230. The knowledge distribution system of claim 193, further comprising a knowledge datastore in communication with the distributed ledger and configured to store data related to said digital knowledge.

231. The knowledge distribution system of claim 193, further comprising a client datastore in communication with the distributed ledger and configured to store data related to a plurality of users of the knowledge distribution system.

232. The knowledge distribution system of claim 193, further comprising a smart contract datastore in communication with the distributed ledger and configured to store data related to the smart contract.

233. The knowledge distribution system of claim 193, further comprising a reporting system in communication with the distributed ledger and configured to analyze the tokenized digital knowledge and report an analytic result based on an analysis of the tokenized digital knowledge.

234. The knowledge distribution system of claim 193, wherein the smart contract is generated using a parameterizable smart contract template.

235. The knowledge distribution system of claim 193, wherein the smart contract includes parameters based on a type of digital knowledge to be tokenized.

236. The knowledge distribution system of claim 235, wherein the parameters include at least one of financial parameters, royalty parameters, usage parameters, output produced parameters, allocation of consideration parameters, identity parameters, and access condition parameters.

237. A computer-implemented method for controlling rights related to digital knowledge comprising: creating and managing a distributed ledger that is distributed over a plurality of nodes of a network and includes a plurality of blocks linked via cryptography; implementing and managing a smart contract via the distributed ledger, wherein the smart contract is stored in the distributed ledger and includes a triggering event;814performing a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event; receiving an instance of the digital knowledge; tokenizing the digital knowledge such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger; storing the tokenized digital knowledge via the distributed ledger; processing commitments of a plurality of parties to the smart contract; and managing rights of control of and access to the tokenized digital knowledge according to the smart contract and managing the smart contract action in response to the triggering event.

238. The computer- implemented method of claim 237 further comprising orchestrating a knowledge exchange for an exchange of the tokenized digital knowledge based on the smart contract.

239. The computer-implemented method of claim 238 further comprising integrating the knowledge exchange of the tokenized digital knowledge with another exchange where the knowledge exchange facilitates exchange of at least one of valuable and sensitive knowledge related to a subject matter of the exchange.

240. A knowledge distribution system for controlling rights related to digital knowledge, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and includes a plurality of cryptographically linked blocks; and a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and includes a triggering event, and the smart contract is configured to perform a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event; wherein the knowledge distribution system is configured to: receive from a knowledge provider device an instance of the digital knowledge including a three-dimensional (3D) printer instruction set for 3D printing an object; tokenize the digital knowledge such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger; store the tokenized digital knowledge via the distributed ledger;815process commitments of the knowledge provider and a knowledge recipient of the 3D printer instruction set to the smart contract; and manage rights of control of and access to the tokenized digital knowledge according to the smart contract, and manage the smart contract action according to a condition and the triggering event.

241. The knowledge distribution system of claim 240, wherein the 3D printer instruction set includes a 3D printing schematic.

242. The knowledge distribution system of claim 240, wherein the object is at least one of a custom part, a custom product, a manufacturing part, a replacement part, a toy, a medical device, and a tool.

243. The knowledge distribution system of claim 240, wherein the knowledge recipient uses a knowledge recipient device to download and use the 3D printer instruction set, and wherein the knowledge recipient device is at least one of a computing device, a server, a 3D printer, and a manufacturing device.

244. The knowledge distribution system of claim 240, wherein the knowledge recipient uses a knowledge recipient device to purchase the tokenized digital knowledge corresponding to the 3D printer instruction set.

245. The knowledge distribution system of claim 240, further comprising an event listener configured to listen to an application programming interface (API) that provides a connection between the knowledge distribution system and a knowledge recipient device of the knowledge recipient.

246. The knowledge distribution system of claim 240, wherein the smart contract is configured to trigger the condition of the knowledge recipient to make a payment when the 3D printer instruction set is transferred or used based on the rights of control of and access to the tokenized digital knowledge.

247. The knowledge distribution system of claim 240, wherein the rights of control of and access to the tokenized digital knowledge include a permission for a user to 3D print using multiple instances of the 3D printer instruction set.816248. The knowledge distribution system of claim 240, wherein the rights of control of and access to the tokenized digital knowledge include at least one of 3D printer requirements, a time period during which the object can be 3D printed, whether the tokenized digital knowledge is transferred to a downstream knowledge recipient, warranties, disclaimers, indemnifications, and certifications with respect to the object.

249. The knowledge distribution system of claim 240, wherein information related to the 3D printer instruction set of the tokenized digital knowledge is modified on the distributed ledger when the 3D printer instruction set is at least one of purchased, downloaded, and used.

250. The knowledge distribution system of claim 240, wherein information related to the 3D printer instruction set includes at least one of origin, date of creation, names of one or more contributing individuals, groups, and / or companies, pricing, market trends for related schematics, serial numbers, and part identifiers.

251. The knowledge distribution system of claim 240, wherein the smart contract action is one of an assignment of a serial number to the object that is 3D printed, monitoring for the triggering event, verifying fulfillment of an obligation based on the condition, verifying payment and / or transfer of the tokenized digital knowledge, transferring the tokenized digital knowledge, logging one or more transactions in the distributed ledger, performing one or more operations with respect to the distributed ledger, and creating one or more new blocks in the distributed ledger.

252. The knowledge distribution system of claim 240, wherein the smart contract action includes verifying that the condition is met as defined in the smart contract, wherein the condition is one of printer requirements, payment received, currency transferred from a knowledge recipient device of the knowledge recipient, or transfer of the tokenized digital knowledge to the knowledge recipient device.

253. The knowledge distribution system of claim 240, wherein when the tokenized digital knowledge is transferred to a knowledge recipient device of a knowledge recipient, a 3D printer is configured to print the object according to the 3D printer instruction set.817254. The knowledge distribution system of claim 240, further comprising a smart contract generator configured to parametrize a smart contract template based on at least one of information provided by the knowledge provider, the condition, and the triggering event.

255. A computer-implemented method for controlling rights related to digital knowledge comprising: creating and managing a distributed ledger that is distributed over a plurality of nodes of a network and includes a plurality of blocks linked via cryptography; implementing and managing a smart contract via the distributed ledger, wherein the smart contract is stored in the distributed ledger and includes a triggering event; performing a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event; receiving from a knowledge provider device an instance of the digital knowledge that includes a three-dimensional (3D) printer instruction set for 3D printing an object; tokenizing the digital knowledge such that the instance of the digital knowledge can be manipulated as a token on the distributed ledger; storing the tokenized digital knowledge via the distributed ledger; processing commitments of the knowledge provider and a knowledge recipient of the 3D printer instruction set to the smart contract; and managing rights of control of and access to the tokenized digital knowledge according to the smart contract, and managing the smart contract action according to a condition and the triggering event.

256. The computer-implemented method of claim 255 further comprising crowdsourcing an element of the instance of the digital knowledge via the smart contract, wherein the element of the instance of the digital knowledge is managed by a smart contract system according to the smart contract.

257. A knowledge distribution system for managing digital knowledge assets, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and including a plurality of cryptographically linked blocks linked via cryptography; and a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and including a triggering event, and being configured to818perform a smart contract action with respect to the digital knowledge assets in response to an occurrence of the triggering event; wherein the knowledge distribution system is configured to: tokenize the digital knowledge assets in the form of non-fungible tokens; store the non-fungible tokens via the distributed ledger; process commitments of a plurality of parties to the smart contract; and manage rights of control of and access to the digital knowledge assets based on the smart contract and manage the smart contract action in response to the triggering event.

258. The knowledge distribution system of claim 257, wherein the digital knowledge assets are tokenized as static non-fungible tokens.

259. The knowledge distribution system of claim 257, wherein the digital knowledge assets are tokenized as dynamic non-fungible tokens.

260. The knowledge distribution system of claim 257, wherein the digital knowledge assets include intellectual property of one or more intellectual property rights holders, wherein the smart contract embeds intellectual property licensing terms for intellectual property embedded in the distributed ledger, and wherein executing an operation on the distributed ledger provides access to the intellectual property and process a commitment of a party to the smart contract to the intellectual property licensing terms.

261. The knowledge distribution system of claim 260, wherein the intellectual property is a patent.

262. The knowledge distribution system of claim 261, wherein the patent is tokenized as a dynamic non-fungible token wherein a value / price of the patent is dynamic during a lifetime of the patent and can change based on real- world events.

263. The knowledge distribution system of claim 262, wherein the real- world events comprise legal or transactional events including prosecution events, invalidity or litigation events, and licensing or sale events.819264. A knowledge distribution system for controlling rights related to digital knowledge, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and including a plurality of cryptographically linked blocks linked via cryptography; a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and including a triggering event, and being configured to perform a smart contract action with respect to said digital knowledge in response to an occurrence of said triggering event; and a trust network configured to identify a likelihood of fraudulent transactions on the distributed ledger by generating and tracking a consensus trust score for all the nodes of the network, the consensus trust score indicating the likelihood that the node is involved in a fraudulent activity, wherein the knowledge distribution system is configured to: receive an instance of said digital knowledge from a user; tokenize said digital knowledge such that said instance of said digital knowledge can be manipulated as a non-fungible token on said distributed ledger; store said tokenized digital knowledge via the distributed ledger; process commitments of a plurality of parties to the smart contract; and manage rights of control of and access to the tokenized digital knowledge according to the smart contract and manage the smart contract action in response to the triggering event.

265. The knowledge distribution system of claim 264, wherein the trust network is configured to notify the plurality of parties of potentially fraudulent nodes that have a consensus trust score below a threshold level as set by a user.

266. The knowledge distribution system of claim 264, wherein the smart contract monitors a consensus trust score for the plurality of parties and provides alerts and notifications based on a set of business rules defined by the user.

267. The knowledge distribution system of claim 264, wherein the smart contract is configured to temporarily lock funds with a mediator and unlock the funds upon meeting certain conditions of the transaction between the plurality of parties.820268. The knowledge distribution system of claim 264, wherein the smart contract is a multisignature contract requiring signature from multiple parties.

269. The knowledge distribution system of claim 264, wherein the distributed ledger is configured such that a private network of authorized participants may establish cryptographic consensus for validation of new blocks to be added to the plurality of blocks.

270. The knowledge distribution system of claim 264, wherein the cryptographic consensus is based on a proof of stake consensus (PoS) protocol.

271. The knowledge distribution system of claim 264, wherein the cryptographic consensus is based on a Proof of Authority (PoA) consensus protocol.

272. The knowledge distribution system of claim 271, wherein the authority of a node is a function of the consensus trust score for the node.

273. The knowledge distribution system of claim 271, wherein the authority of a node is a function of a reputation for the node.

274. A patent asset management system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and includes a plurality of cryptographically linked blocks; and a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and includes a triggering event, and the smart contract is configured to perform a smart contract action with respect to the patent in response to an occurrence of the triggering event; wherein the patent asset management system is configured to: tokenize a patent received from a patent assignee in the form of a dynamic non- fungible token (NFT); store the NFT via the distributed ledger and offer the NFT for monetization via an NFT marketplace; process commitments of the patent assignee and a buyer of the patent NFT set to the smart contract; and821manage rights of control of and access to the patent according to the smart contract, and manage the smart contract action according to a condition and the triggering event.

275. The patent management system of claim 274, wherein the smart contract embeds intellectual property licensing terms for the patent.

276. The patent management system of claim 274, wherein a value / price of the patent is dynamic during a lifetime of the patent and can change based on real-world events.

277. The patent management system of claim 276, wherein the real-world events comprise legal or transactional events including prosecution events, invalidity or litigation events, or licensing or sale events.

278. A knowledge distribution system for controlling rights related to digital knowledge, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and including a plurality of cryptographically linked blocks linked via cryptography; a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and including a triggering event, and being configured to perform a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event; and a trust network configured to identify a likelihood of fraudulent transactions on the distributed ledger by generating and tracking a consensus trust score for each node of the plurality of nodes of the network, the consensus trust score indicating the likelihood that a given node of the plurality of nodes is involved in a fraudulent activity, wherein the knowledge distribution system is configured to: receive an instance of the digital knowledge from a user; tokenize the digital knowledge such that the instance of the digital knowledge can be manipulated as a non-fungible token on the distributed ledger; store the tokenized digital knowledge via the distributed ledger; process commitments of a plurality of parties to the smart contract; and822manage rights of control of and access to the tokenized digital knowledge according to the smart contract and manage the smart contract action in response to the triggering event.

279. The knowledge distribution system of claim 278. further comprising a digital marketplace for facilitating buying and selling of non-fungible tokens based on the digital knowledge.

280. The knowledge distribution system of claim 279 wherein the digital marketplace includes a web based user interface for searching of NFTs based on the digital knowledge.

281. A knowledge distribution system for controlling rights related to digital knowledge, the system comprising: a ledger management system configured to create and manage a distributed ledger, the distributed ledger being distributed over a plurality of nodes of a network and including a plurality of cryptographically linked blocks linked via cryptography; a smart contract system in communication with the distributed ledger and configured to implement and manage a smart contract via the distributed ledger, the smart contract being stored in the distributed ledger and including a triggering event, and being configured to perform a smart contract action with respect to the digital knowledge in response to an occurrence of the triggering event; and a trust network configured to generate a consensus trust score for the plurality of nodes of the network wherein the consensus trust score determines an authority of a node in the network; wherein the knowledge distribution system is configured to: tokenize an instance of the digital knowledge received from a knowledge provider as a non-fungible token; store the tokenized digital knowledge via the distributed ledger; orchestrate transactions between the knowledge provider and a knowledge recipient, wherein such orchestration and validation of transactions in the network is enabled by a set of nodes with a high value of authority; process commitments of the knowledge provider and the knowledge recipient to the smart contract; and manage rights of control of and access to the tokenized digital knowledge according to the smart contract and manage the smart contract action in response to the triggering event.823282. The knowledge distribution system of claim 281, wherein a value / price of the digital knowledge is dynamic during a lifetime of the digital knowledge and can change based on real- world events.

283. The knowledge distribution system of claim 282, wherein the real- world events comprise legal or transactional events, or licensing or sale events.

284. A computer-implemented method for controlling rights related to intellectual property comprising: creating and managing a distributed ledger that is distributed over a plurality of nodes of a network and includes a plurality of blocks linked via cryptography; implementing and managing a smart contract via the distributed ledger, wherein the smart contract is stored in the distributed ledger and includes a triggering event; performing a smart contract action with respect to the intellectual property in response to an occurrence of the triggering event; receiving from a knowledge provider an instance of the intellectual property that includes a patent document; tokenizing the intellectual property in the form of a dynamic non- fungible token (NFT) such that the instance of the intellectual property can be manipulated as a token on the distributed ledger; storing the NFT via the distributed ledger; processing commitments of the knowledge provider and a knowledge recipient of the intellectual property to the smart contract; and managing rights of control of and access to the NFT according to the smart contract, and managing the smart contract action according to a condition and the triggering event.

285. The method for controlling rights related to intellectual property of claim 284, further comprising embedding patent licensing terms in the smart contract.

286. The method for controlling rights related to intellectual property of claim 284, further comprising dynamically varying a value / price of the intellectual property based on real- world events.824287. The method for controlling rights of related to intellectual property of claim 286, wherein the real-world events comprise legal or transactional events including prosecution events, invalidity or litigation events, or licensing or sale events.825

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