Innovation platform

Abstract

A method is provided that includes posting, on a platform, an idea of a first user and rewards offered in exchange for posting comments that add value to the idea. The method further includes posting a comment that relates to the idea, the comment posted by a second user that accepts the rewards offered. The method further includes receiving a comment evaluation indicating that the second user that posted the comment is to be compensated in a manner compliant with terms of the rewards offered. The method further includes orchestrating delivery of compensation for the second user and notifying an account of the second user that compensation for the comment has been made.

Description

INNOVATION PLATFORMRELATED APPLICATION

[0001] This application claims priority to U.S. Provisional Patent Application Serial No. 63 / 573,170, filed April 2, 2024, entitled “Innovation Platform”, the disclosure of which is hereby incorporated by reference, in its entirety.BACKGROUND

[0002] In today's interconnected world, the exchange of ideas has become a cornerstone of innovation and progress. From online forums to social media platforms, individuals harness the power of the Internet to share insights and perspectives relating to a wide variety of topics.

[0003] However, in the context of sharing these insights and perspectives, existing platforms do not adequately incentivize meaningful contributions from users, nor do these platforms adequately compensate contributors for their valuable input. While most social media platforms allow collaboration and for the sharing of ideas, many of these platforms do not compensate users for exchanging ideas. Some traditional social media platforms rely on non-monetary forms of recognition, such as likes, upvotes, and the like, which fail to translate into tangible benefits for the creators. This absence of tangible incentive discourages individuals from actively sharing ideas, limiting the growth and development of science and technology.

[0004] Moreover, existing social media platforms often lack mechanisms to facilitate collaboration and refinement of ideas. While initial contributions may spark inspiration, the true value often lies in the iterative process of feedback and improvement. Without a structured framework for collaboration, promising ideas may stagnate or remain underdeveloped, depriving society of potentially transformative innovations.

[0005] Further, traditional systems do not provide secure, time-stamped, verifiable records of ideas shared over the Internet. This makes it difficult to determine which of multiple different users were first to disclose an idea, thereby disincentivizing users from sharing ideas.Furthermore, without a secure, verifiable way of creating records of ideas shared over the Internet, traditional systems are unable to implement a system for compensating users for sharing ideas and comments to ideas over the Internet.

[0006] Still further, traditional systems do not provide an efficient and / or effective way ofmanaging version control as between different versions of ideas being shared over the Internet. For example, a user may post an idea at a first time period, and as additional users begin to post comments about the idea over time, the originally posting user may update his or her idea (i.e., update the original post to reflect a second version of the idea). In this situation, even if the original post includes a time stamp indicating the time at which the user updated the idea, there may be no way to tell whether the commenting users posted comments about the first version, or the second version, of the idea. This makes it difficult to provide proper compensation for comments posted to add value to the idea, given the comments are only linked to the most recently updated version of the idea.

[0007] Moreover, traditional systems do not provide an efficient and / or effective way of authenticating access and viewership of an online forum used to share these ideas. For example, a user may have access to a registered profile used to post an idea or a comment about an existing idea. However, traditional systems do not provide a mechanism for authenticating that the person logged in under the registered account is in fact the registered user. Additionally, in some situations, such as when an authorized user is sharing an idea in a public space, traditional systems do not provide a way to verify that there are no additional unauthorized users present in the vicinity of the authorized user. Without this verification, it is difficult to prove that the registered account that posts an idea or a comment is actually being posted by the authorized user,

[0008] What is needed is a platform for sharing ideas that encourages active participation while ensuring equitable compensation for valuable contributions. It is an object of the present invention to overcome one or more of the problems described above.SUMMARY

[0009] In an aspect of the invention, a method is provided. The method includes receiving, by a server device, a request from a first registered account of a user to post an idea on a platform designed to manage an exchange of ideas and idea compensation packages. The platform is supported by the server device. The request includes idea data describing the idea and reward offer data describing one or more idea sharing rewards packages (ISRPs) being offered in exchange for comments determined to add value to the idea. The method further includes causing, by the server device, the idea data and the reward offer data to be posted in amanner that is accessible to a group of registered accounts via the platform. The method further includes receiving, by the server device, a request to post a comment that relates to the idea. The request to post the comment is made by a second user associated with a second registered account. The request to post the comment includes comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted. The method further includes causing, by the server device, the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform.

[0010] The method further includes receiving, by the server device, comment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP of the ISRPs. The method further includes generating, by the server device, cryptographic hashes of the idea data, the comment data, and the comment evaluation data. The method further includes storing, by the server device, the cryptographic hashes as blocks in a blockchain such that blockchain provides a time- stamped, immutable record of the idea and time-stamped, immutable records of interactions that users have with the platform that involve the idea. The method further includes orchestrating, by the server device, delivery of compensation for the second user in the manner that complies with the terms of the ISRP. The method further includes notifying, by the server device, the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

[0011] In an embodiment of the invention, the method further includes generating a smart contract that defines compensation rules for the ISRP. In this embodiment, when orchestrating the delivery of the compensation for the second user, the method includes executing the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP are satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user. In another embodiment of the invention, the method further includes generating a cryptographic hash of the smart contract. In this embodiment, the method further includes storing the cryptographic hash as a block on the blockchain. The method further includes generating a cryptographic hash of a transaction which approves the compensation of the second user. The method further includes storing the cryptographic hash of the transaction as another block on the blockchain.

[0012] In another embodiment of the invention, the user is an authorized user that has abiometric identification profile that includes data identifying a set of baseline facial features. In this embodiment, the method further includes processing image data depicting an area around a user device of the authorized user to identify facial features for one or more faces found in the image data. The method further includes determining whether the facial features for the one or more faces include a set of facial features that match the baseline facial features of the authorized user. The method further includes determining whether the facial features for the one or more faces include a set of additional facial features of one or more unauthorized users. In response to the set of facial features matching the set of baseline facial features and excluding the set of additional facial features of the one or more unauthorized users, the method further includes permitting access to a user interface of the platform. In response to the set of facial features not matching the set of baseline facial features or including the additional facial features of the one or more unauthorized users, the method further includes blurring the user interface of the platform as it is shown on the user device to prevent unauthorized access.

[0013] In another embodiment of the invention, the user is an authorized user that has a biometric identification profile that includes data identifying a set of baseline facial features. In this embodiment, the method further includes receiving image data depicting an area around a user device associated with the authorized user. The user device provides the image data to the server device based on determining that one or more system parameters fail to satisfy one or more corresponding system performance thresholds. The method further includes processing the image data to identify facial features for one or more faces found in the image data. The method further includes determining whether the facial features include a set of facial features that match the baseline facial features of the authorized user. The method further includes determining whether the facial features for the one or more faces include a set of additional facial features of one or more unauthorized users. In response to the set of facial features matching the set of baseline facial features and excluding the additional facial features of one or more unauthorized users, the method further includes permitting access to the user device for a user interface of the platform. In response to the set of facial features not matching the set of baseline facial features or including the additional facial features of the one or more unauthorized users, the method further includes blurring the user interface of the platform as it is shown on the user device to prevent unauthorized access.

[0014] In another embodiment of the invention, a vector database stores idea embeddings fora collection of ideas shared over the platform. In this embodiment, the method further includes generating idea embeddings for the idea by using a data model trained using machine loaming to process the idea data. The method further includes identifying one or more previously posted ideas that are similar to the idea provided by the user by performing a similarity analysis that compares the idea embeddings for the idea and the idea embeddings for the collection of ideas shared over the platform. The method further includes providing idea data for the one or more previously posted ideas to a user device associated with the user. The method further includes receiving, from the user device, an instruction to post the idea as a comment to a previously posted idea of the one or more previously posted ideas. The method further includes providing the user device with reward offer data for the previously posted idea. The method further includes receiving, from the user device, reward acceptance data for the previously posted idea. In this embodiment, causing the idea data to be posted includes causing the idea data to be posted as comment data relating to the previously posted idea.

[0015] In another embodiment of the invention, a graph data structure stores the idea as a first version of the idea using a first set of nodes and edges, receiving another request from the first registered account of the user to post a modified idea that includes at least one change relative to the idea. In this embodiment, the method further includes determining a degree of semantic similarity between the idea data and modified idea data for the modified idea. The method further includes updating the graph data structure to store the modified idea data as a second version of the idea using a second set of nodes and edges. A position in which the second set of nodes and edges are placed in the graph data structure is based on the degree of semantic similarity between the idea data and the modified idea data.

[0016] In another embodiment of the invention, the method further includes receiving a request to merge the modified idea and the original idea into a merged idea that represents a third version of the idea. The method further includes identifying one or more conflicts by analyzing the idea data and the modified idea data using machine learning. The method further includes resolving the one or more conflicts using an automated or semi- automated conflict resolution technique. The method further includes updating the graph data structure to include a third set of nodes and edges for the merged idea.

[0017] In another aspect of the invention, a device is provided. The device includes one or more memories and one or more processors operatively coupled to the one or more memories.The one or more processors are to receive a request from a first registered account of a user to post an idea on a platform designed to manage an exchange of ideas and idea compensation packages. The platform is supported by the server device. The request includes idea data describing the idea and reward offer data describing one or more idea sharing rewards packages (ISRPs) being offered in exchange for comments determined to add value to the idea. The one or more processors are to cause the idea data and the reward offer data to be posted in a manner that is accessible to a group of registered accounts via the platform. The one or more processors are to receive a second request from the first registered account to post a modified idea that includes at least one change relative to the idea. The one or more processors are to receive a request to post a comment that relates to the idea. The request to post the comment is made by a second user associated with a second registered account. The request to post the comment includes comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted. The one or more processors are to cause the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform. The one or more processors are to receive comment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP, of the ISRPs. The one or more processors are to associate different versions of the idea by using a graph data structure that includes a set of nodes and edges for each respective version of the idea, wherein the comment data and the comment evaluation data is linked to a particular version of the different versions. The one or more processors are to orchestrate delivery of compensation for the second user in the manner that complies with the terms of the ISRP. The one or more processors arc to notify the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

[0018] In an embodiment of the invention, the one or more processors are further to generate cryptographic hashes of the idea data, modified idea data for the modified idea, the comment data, and the comment evaluation data. The one or more processors are further to store the cryptographic hashes as blocks in a blockchain such that blockchain provides time-stamped, immutable, versioned records of the idea and time- stamped, immutable records of interactions that users have with the platform that involve the idea.

[0019] In another embodiment of the invention, the one or more processors are further togenerate a smart contract that defines compensation rules for the ISRP. In this embodiment, the one or more processors, when orchestrating the delivery of the compensation for the second user, are to execute the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP are satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user.

[0020] In another embodiment of the invention, the one or more processors, when associating the different versions of the idea, are to generate a first set of nodes and edges for the idea, wherein one or more nodes, of the first set of nodes, represent paragraphs of content describing the idea. In this embodiment, the one or more processors are also to generate a second set of nodes and edges for the modified idea. One or more nodes, of the second set of nodes, represent paragraphs of content describing the modified idea. A position of the second set of nodes and edges in the graph data structure is selected based on classifying one or more changes between the idea data and the modified idea data. In another embodiment, the one or more processors are to generate a cryptographic hash of each paragraph of content describing the idea and each paragraph of content describing the modified idea. In this embodiment, the one or more processors are to store each respective cryptographic hash as a block in a blockchain to establish an immutable record of versioned pieces of paragraph- specific content.

[0021] In another embodiment of the invention, a vector database stores idea embeddings for a collection of ideas shared over the platform. In this embodiment, the one or more processors are further to generate idea embeddings for the idea by using a data model trained using machine learning to process the idea data. The one or more processors are further to identify one or more previously posted ideas that are similar to the idea provided by the user by performing a similarity analysis that compares the idea embeddings for the idea and the idea embeddings for the collection of ideas shared over the platform. The one or more processors are further to provide idea data for the one or more previously posted ideas to a user device associated with the user. The one or more processors are further to receive, from the user device, an instruction to post the idea as a comment to a previously posted idea of the one or more previously posted ideas. The one or more processors are further to provide the user device with reward offer data for the previously posted idea. The one or more processors are further to receive, from the user device, reward acceptance data for the previously posted idea. In this embodiment, when causing the idea data to be posted, the one or more processors are to cause the idea data to beposted as comment data relating to the previously posted idea.

[0022] In another aspect of the invention, a non-transitory, computer-readable medium storing instructions is provided. The instructions include one or more instructions that, when executed by one or more processors, cause the one or more processors to receive image data depicting an area around a user device of a user who has a first registered account with a platform designed to manage an exchange of ideas and idea compensation packages. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to process the image data to identify facial features for one or more faces found in the image data. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to determine whether the facial features for the one or more faces match baseline facial features of the user. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to permit or deny access to a user interface of the platform based on whether the facial features for the one or more faces match the baseline facial features of the user. In response to permitting access to the user interface, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to receive a request from a first registered account of the user to post an idea on the platform. The request includes idea data describing the idea and reward offer data describing one or more idea sharing rewards packages (ISRPs) being offered in exchange for comments determined to add value to the idea. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to cause the idea data and the reward offer data to be posted in a manner that is accessible to a group of registered accounts via the platform.

[0023] The one or more instructions, when executed by the one or more processors, further cause the one or more processors to receive a request to post a comment that relates to the idea. The request to post the comment is made by a second user associated with a second registered account. The request to post the comment includes comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to cause the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to receivecomment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP of the ISRPs. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to orchestrate delivery of compensation for the second user in the manner that complies with the terms of the ISRP. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to notify the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

[0024] In an embodiment of the invention, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to associate different versions of the idea by using a graph data structure that includes a set of nodes and edges for each respective version of the idea, wherein the comment data and the comment evaluation data is linked to a particular version of the different versions.

[0025] In another embodiment of the invention, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to generate a cryptographic hash of each paragraph of content included in each respective version of the idea. In this embodiment, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to store each respective cryptographic hash as a block in a blockchain to establish an immutable record of versioned pieces of paragraph-specific content included in each respective version of the idea.

[0026] In another embodiment of the invention, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to generate a smart contract that defines compensation rules for the ISRP. In this embodiment, the one or more instructions, that cause the one or more processors to orchestrate the delivery of the compensation for the second user, cause the one or more processors to execute the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP are satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user.

[0027] In another embodiment of the invention, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to generate a graph data structure that includes a set of nodes to associate the idea data, the comment data, and the comment evaluation data. Respective nodes, in the set of nodes, represent versioned pieces ofcontent described in in the idea data, the comment data, or the comment evaluation data.

[0028] In another embodiment of the invention, a graph data structure stores the idea as a first version of the idea using a first set of nodes and edges. In this embodiment, the one or more instructions, when executed by the one or more processors, further cause the one or more processors to receive another request from the first registered account of the user to post a modified idea that includes at least one change relative to the idea. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to determine a degree of semantic similarity between the idea data and modified idea data for the modified idea. The one or more instructions, when executed by the one or more processors, further cause the one or more processors to update the graph data structure to store the modified idea data as a second version of the idea using a second set of nodes and edges. A position in which the second set of nodes and edges are placed in the graph data structure is based on the degree of semantic similarity between the idea data and the modified idea data.

[0029] The above and other objects and advantages of the present invention shall be made apparent from the accompanying drawings and the description thereof.BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Fig. 1 is a diagram of an example process for creating an account with an innovation platform.

[0031] Fig. 2A is a diagram showing a user posting an idea on a forum of the innovation platform.

[0032] Fig. 2B is a diagram showing a second user posting a comment about the idea on the forum.

[0033] Fig. 2C is a diagram showing comment evaluation data being provided to the innovation platform.

[0034] Fig. 2D is a diagram showing the second user being compensated for the comment about the idea.

[0035] Fig. 3A is a diagram showing the innovation platform storing idea data using a distributed file system and storing a cryptographic hash of the idea data using a blockchain.

[0036] Fig. 3B is a diagram showing the innovation platform storing comment data on the distributed file system and storing a cryptographic hash of the comment data using theblockchain.

[0037] Fig. 3C is a diagram showing the innovation platform storing comment evaluation data using the distributed file system and storing a cryptographic hash of comment evaluation data using the blockchain.

[0038] Fig. 3D is a diagram showing the innovation platform generating a smart contract, storing smart contract using the distributed file system, and storing a cryptographic hash of the smart contract using the blockchain.

[0039] Fig. 3E is a diagram showing execution of the smart contract so as to implement an idea sharing rewards package (ISRP).

[0040] Fig. 3F is a diagram showing the innovation platform storing approved transaction data using the distributed file system and storing a cryptographic hash of the approved transaction data using the blockchain.

[0041] Fig. 3G is a diagram showing an electronic wallet of a commenting user being provided with compensation for posting the comment about the idea of the user.

[0042] Fig. 4A is a diagram showing the user configuring biometric identification to enable screen-blurring.

[0043] Fig. 4B is a diagram showing a camera capturing image data of the user while a user device filters the image data and identifies one or more faces in the filtered image data.

[0044] Fig. 4C is a diagram showing the user device blurring a screen of the user by using computer vision techniques to verify that only the authorized user is in a vicinity of user device.

[0045] Fig. 4D is the innovation platform storing security event data using the distributed file system and storing a cryptographic hash of the security event data on the blockchain.

[0046] Fig. 4E is a diagram showing the innovation platform determining whether facial features included in the image data match stored facial features of the user.

[0047] Fig. 4F is a diagram showing screen-blur being applied to a user interface display of the innovation platform during a period where a feed of the camera experiences an interruption.

[0048] Fig. 5A is a diagram showing the user requesting to post an idea and the innovation platform pre-processing text and / or image data describing and / or depicting the idea.

[0049] Fig. 5B is a diagram showing the innovation platform generating idea embeddings for the text and / or image data and storing the idea embeddings in a vector database.

[0050] Fig. 5C is a diagram showing the innovation platform identifying previously postedideas that are similar to the idea submitted by the user and further showing the user providing instructions to post the idea as a comment to one of the previously posted similar ideas.

[0051] Fig. 5D is a diagram showing the innovation platform posting the idea as the comment of the previously posted similar idea.

[0052] Fig. 5E is a diagram showing comment evaluation data being provided to the innovation platform.

[0053] Fig. 5F is a diagram showing the user being compensated for the comment about the previously posted idea.

[0054] Fig. 6A is a diagram showing the user inputting a modification to an existing idea and the innovation platform performing one or more pre-processing operations on modified idea data.

[0055] Fig. 6B is a diagram showing the innovation platform classifying one or more changes between the idea and the modified idea and updating a graph data structure based on the one or more classified changes.

[0056] Fig. 6C is a diagram showing the innovation platform storing modified idea data using the distributed file system and storing a cryptographic hash of the modified idea data using the blockchain.

[0057] Fig. 6D is a diagram showing part of a process for requesting a merge of the idea and the modified idea.

[0058] Fig. 6E is a diagram showing another part of the process for requesting the merge of the idea and the modified idea.

[0059] Fig. 6F is a diagram showing the innovation platform storing merged idea data using the distributed file system and storing a cryptographic hash of the merged idea data using the blockchain.

[0060] Fig. 7 is a diagram of an example environment in which systems and / or methods described herein may be implemented.

[0061] Fig. 8 is a diagram of example components of one or more devices of Fig. 7.DETAILED DESCRIPTION

[0062] The following detailed description of example embodiments refers to the accompanying drawings. The same reference numbers in different drawings may identify thesame or similar elements.

[0063] Fig. 1 is a diagram of an example process 10 for creating an account with an innovation platform. The innovation platform may be supported by an innovation platform server (IPS) 12. As used herein, the term “innovation platform” is to refer to one or more applications used to facilitate and compensate the exchange of ideas between users.

[0064] As shown by reference number 14, a user may create an account with the innovation platform. For example, a user may, via user device 16, interact with a user interface of the innovation platform to create an account. This may include creating a username and password for accessing a web-based or application-based interface of the innovation platform.

[0065] In some embodiments, creating the account may include completing a verification process. For example, the user may provide personally identifiable information (PII) data (e.g., a driver’s license, a birth certificate, etc.) as part of a verification process that must be completed to create the account. Additionally, or alternatively, the user may provide contact information, such as a phone number, an email address, a mailing address, and / or the like. In some embodiments, verification may require a third party background check. In this case, the user may consent to the background check and the IPS 12 may notify the user once the result of the background check has been received.

[0066] Additionally, or alternatively, creating the account may include agreeing to the terms of one or more contracts. For example, the account creation process may involve providing the user with a terms of use (ToS) agreement that must be agreed to by the user to use the innovation platform. As another example, the user may be provided with a non-disclosure agreement that must be reviewed and signed.

[0067] As shown by reference number 18, creating the account causes the user device 16 to transmit account information to the IPS 12. The account information may include the username and password, PII data of the user, and / or any other information provided while creating the account. The account information may be transmitted over a network, such as the Internet.

[0068] As shown by reference number 20, the IPS 12 may store the account information of the user. As shown by reference number 22, the user device 16 may receive, from the IPS 12, an acknowledgement that the account has been created.

[0069] As indicated above, Fig. 1 is provided merely as an example. Other examples may differ from what is described with regard to Fig. 1. For example, there may be additional devicesand / or networks, fewer devices and / or networks, different devices and / or networks, or differently arranged devices and / or networks than those shown in Fig. 1. Furthermore, two or more devices shown in Fig. 1 may be implemented within a single device, or a single device shown in Fig. 1 may be implemented as multiple and / or distributed devices. Additionally, or alternatively, a set of devices (e.g., one or more devices) of example process 10 may perform one or more functions described as being performed by another set of devices of example process 10.

[0070] Figs. 2A-2D are diagrams of an example process 24 for using the innovation platform to facilitate the sharing of ideas and for providing compensation for the sharing of ideas. An idea may be posted to a forum that is part of the innovation platform. As will be explained, other users may post reply comments to make recommendations or suggestions on ways to improve upon the original idea and may be compensated if those reply comments are determined to add value to the original idea.

[0071] As shown in Fig. 2A, and by reference number 26, a user may input an idea that is to be posted on the forum of the innovation platform. For example, the user, who is logged into the innovation platform forum as a registered user, may interact with a user interface of the forum to describe the idea that is to be posted.

[0072] In some embodiments, the user may select a button or icon on the user interface of the forum for posting a new idea. Next, the user may provide content describing the idea, such as by inputting a title of the idea, a description of the idea, and / or by uploading one or more files describing the idea. The post (sometimes referred to herein as an idea posting, or the posted idea) may include text data, image data, and / or video data.

[0073] In the example shown by reference number 28, the user may input a title indicating that the idea is for a fast check-out concept to be used while grocery shopping. In the description field, the user may input that the idea involves having customers at a grocery store push a shopping cart through a scanner shaped like a metal detector. This causes the scanner to analyze the contents of the shopping cart, and to transmit data to the cashier’ s check out computer so as to automatically populate the checkout computer screen with the bill.

[0074] In some embodiments, the user may interact with a user interface to select a category and / or one or more sub-categories to which the idea applies. Continuing with the example above, the user may select a category such as shopping, a sub-category relating to shopping (e.g., shopping check-out processes) and / or may select one or more categories of related technologies,such as scanner technology, video or imaging analysis technology (e.g., computer vision, etc.), and / or the like.

[0075] In some embodiments, the user may be prompted to select one or more idea sharing rewards packages (ISPRs) that are linked to the idea. An ISRP refers to a rewards package that defines one or more ways in which other users may be compensated for posting comments that are determined to be valuable contributions to the user’s original idea. The ISRP may include one or more fixed fee rewards packages, one or more equity-based rewards packages (e.g., a tier based package, a future value based package, etc.), one or more hybrid rewards packages (e.g., combining one or more fixed fee and equity-based reward packages), and / or the like.

[0076] A fixed fee reward package may include a range of different fixed fees that are to be offered to users who post comments, where the amount awarded is based on the determined value of a given reply comment. An equity-based rewards package may include a value that reflects an equity or ownership percentage in an interest or future interest of the user posting the idea. The interest or future interest may be equity in a company that is created (or that ends up being created) based on the idea, equity in the form of stocks and / or bonds, royalties stemming from a patent filed on the idea, and / or the like. The specific fixed fee amount or equity value awarded for posting a comment is described in the ISRP but ultimately is awarded by a panel of experts as is discussed in connection with Fig. 2C. In some embodiments, a user may recommend specific reward amount, or a specific reward range, subject to approval by the panel of experts.

[0077] In some embodiments, the user may be provided with a template of suggested details to include when posting the idea. For example, the template may specify that the user should describe a problem that the idea is solving, a summary of the solution to the problem, a list of any hardware or devices used to carry out the solution, a list of software services used to carry out the solution, how the idea could be implemented from a business perspective, and / or any other implementation details that may be useful to include when posting the idea. In some embodiments, the template provided may be one of a group of templates from which the user is able to select a preferred template. Additionally, or alternatively, the user may be able to utilize a free form idea posting structure, so as to provide the user with more freedom when posting the idea.

[0078] As shown by reference number 30, the user device 16-1 may provide, to theinnovation platform 14, a request to post the idea. For example, the user may interact with the user interface of the forum by clicking on a submit button that causes the user device 16-1 to provide, to the innovation platform 14, a request to post (e.g., publish) the idea. The request may include an account identifier of the account of the user, idea data describing the idea, and / or reward offer data describing one or more ISRPs being offered in exchange for comments determined to add value to the idea.

[0079] The idea data may include text data identifying a title of the idea, text data identifying one or more paragraphs describing the idea, image and / or video depicting the idea, idea metadata (e.g., data identifying a timestamp for a time at which the idea data is submitted), and / or the like. Reward offer data describing an ISRP may include data identifying a type of reward package, rules defining how comments become eligible for a reward, parameters describing when and how compensation will be distributed, and / or the like.

[0080] A reward package may be fixed fee, equity-based, tiered incentive (e.g., $x for minor comments, $y for large contributions), a royalty-based structure, etc. Rules defining how comments become eligible for a reward may include a rule indicating whether compensation eligibility is based on a vote from the original poster or approval by a board of experts, a rule indicating whether a comment must be referenced in a patent filing, used in a prototype, and / or merged into the idea thread, a rule indicating minimum standards relating to originality, technical relevance, and / or feasibility. In some embodiments, rules defining comment eligibility for rewards may be implemented using a smart contract. Parameters describing when and how compensation will be distributed may, for example, indicate that compensation is to be distributed immediately after expert approval, deferred until a trigger event such as a product launch occurs, or distributed or deferred based on another trigger condition. These parameters may further specify whether payments are made via a crypto wallet, bank account, or platform credit. These parameters may further specify a multi- signature requirement for releasing compensation.

[0081] In some embodiments, prior to posting the idea, the IPS 12 may determine whether the user’s idea is similar to one or more ideas have already been posted on the innovation platform. For example, the IPS 12 may analyze data for previously submitted ideas and comments to those ideas and may determine whether any similar- ideas have been posted based on that analysis. In some embodiments, the analysis may include performing a keyword searchthat compares keywords included in the title and / or description of the user’s idea to words included in titles and / or descriptions of ideas that have been previously posted to the forum.

[0082] In some embodiments, the IPS 12 may determine that the user’s idea is identical to or similar to an idea that has been previously posted to the forum. In this case, the IPS 12 may provide the user with one or more options, depending on the degree to which the user’s idea matches a previously posted idea. For example, if the user’ s idea is a direct (or near direct) match to a previously posted idea, the IPS 12 may provide the user with a link to the previous posting, so as to give the user the opportunity to review the post, and to post a reply comment. If the user’s idea is only a partial match with the previously posted idea, the IPS 12 may post the user’s idea, and / or may provide the user with the link to the previously posted idea. As would be understood by one skilled in the art, the IPS 12 may determine a degree of similarly between idea postings by analyzing text data and / or image data for respective ideas using natural language processing and / or machine learning techniques. This is described in further detail in connection with Figs. 5A-5F.

[0083] As is described above, in some embodiments, the user may interact with a user interface to select a category and / or one or more sub-categories to which the idea applies. In other embodiments, the IPS 12 may determine one or more categories and / or sub-categories to which the idea applies. For example, the IPS 12 may use one or more natural language processing techniques, one or more machine learning techniques, and / or one or more computer vision techniques to process the idea data to determine one or more categories and / or subcategories to which the idea applies.

[0084] As shown by reference number 32, the IPS 12 may post the idea on the forum of the innovation platform. For example, the IPS 12 may post the idea on a forum of the innovation platform, such that the posted idea is made available to other registered users.

[0085] In some embodiments, the post may include the reward offer data describing the one or more ISRPs being offered. In this case, when users click on the posted idea, a user interface that displays the contents of the idea may also display the ISRP offer data. In some embodiments, the user interface that displays the idea may include a hyperlink to an offer page that includes the ISRP offer data.

[0086] In some embodiments, the IPS 12 may provide the user with an indication that the idea has been posted. For example, the IPS 12 may provide the user device 16-1 with aconfirmation message indicating that the idea has been posted, which may cause the user device 16-1 to update a user interface to display the idea that has been posted.

[0087] In some embodiments, the IPS 12 may store a record of the time and date at which the idea is posted. This record may be stored using any data structure known in the art, such as an array, a linked list, a database table, a blockchain, and / or the like.

[0088] In some embodiments, the record may be stored on a blockchain. A blockchain is a distributed database that maintains a continuously growing list of records, called blocks, that may be linked together to form a chain. Each block in the blockchain may contain a set of transactions (e.g., data entries), a timestamp, and a link to a previous block and / or transaction. The blocks may be secured from tampering and revision. A distributed file system, or distributed ledger, is a decentralized record-keeping system where multiple parties maintain and synchronize a shared database across different nodes in a network. The distributed file system enables fault tolerance, redundancy, and efficient access to large datasets. Embodiments involving the use of a distributed file system and / or block are shown and described in connection with Figs. 3A-3G. By implementing the forum using the blockchain, an immutable, independently verified cryptographic record of the time and date at which idea, comments, and / or idea evaluations are posted is stored. This may, for example, be useful when there arc doubts as to which of multiple users is first to conceive of an idea.

[0089] As shown in Fig. 2B, and by reference number 34, a second user may input a comment relating to the idea. For example, a user device 16-2 may display a user interface of the forum which shows the post describing the original idea and the second user may interact with the user interface to input a comment relating to the idea. To provide a specific example, the user may first select a button or icon on the user interface of the forum for posting a comment relating to the idea. Next, the user may input the comment, such as by inputting a title of the comment and / or a description of the comment. The comment may include text data, image data, and / or video data.

[0090] In the example shown by reference number 36, the second user may input a comment that provides a partial way of implementing the original idea. Specifically, the comment includes text indicating that the scanner can be used to generate imaging data of the food items in the shopping cart. The imaging data can be provided to the cashier’s computer, which could run image analysis software to identify which items are bananas, apples, etc. If each product can beidentified with a threshold confidence level (e.g., -100%), then the bill for those products may be automatically populated on the computer screen of the cashier. It is to be understood that this is provided by way of example, and that in practice, a comment might provide useful insight into any matter relating to the original idea, such as a comment providing a different way to implement idea, a comment providing a way to monetize or sell the idea, a business development strategy including information pertaining to start-up financing, product manufacturing, and / or scaling, and / or any other comment relating to the original idea.

[0091] In some embodiments, prior to inputting the comment, the second user may search for subject matter on which to comment. For example, the forum may include a search feature that allows users to search for posts relating to particular subject matter. The search feature may include a drop-down menu of categories, free form text, and / or any other type of search feature known in the art. Performing a search may cause a list of relevant idea postings to be displayed on the user interface of the forum. The second user may then select an idea from the list, causing the post on the selected idea to be displayed on the user interface.

[0092] In some embodiments, to input a comment about the idea, the second user may first be prompted to sign one or more agreements. For example, to view the idea, the posting user may require commenters to sign a non-disclosure agreement (ND A), a non-compete (NC) agreement, and / or a related type of agreement. In this case, the agreement may be displayed on a user interface, and viewed and signed by the second user.

[0093] In some embodiments, to input a comment about the idea, the second user may first be prompted to select one of the ISRPs. For example, the user device 16-2 may provide, for display on the user interface of the forum, a list identifying the one or more ISRPs. The user may then be prompted to select one of the ISRPs, or may be prompted to consent to the terms outlined in a specified ISRP. Selection of an ISRP may create a legal contract between the first and second user, where the second user’s comment is provided in exchange for a promise that proper compensation for that comment will be provided if the comment is later determined to add value to the idea. In this way, when another user posts a comment with his or her own follow-up thoughts about the idea, the commenting user has a clear understanding of the ranges and / or types of ISRPs that may be available as compensation for adding value to the original idea.

[0094] In addition to inputting a comment, in some embodiments, the second user mayinteract with the idea posting by liking or disliking the idea, thereby increasing or decreasing the exposure of the idea to other users on the forum. For example, the IPS 12 may be configured to sort postings of ideas based on one or more criterion, including a quantity of likes, a quantity of dislikes, a date on which a post is submitted, a date on which a most recent comment to a post is submitted, and / or the like. In this way, the order in which postings of ideas are displayed on the forum may be sorted to prioritize the most popular and / or most recent ideas.

[0095] As shown by reference number 38, when the user submits the comment relating to the idea, the user device 16-2 transmits a request to post the comment to the IPS 12. The request may include an account identifier of the account of the second user, comment data describing the comment, an identifier to the idea data describing the idea, and / or ISRP acceptance data describing one or more ISRPs that have been selected by the second user.

[0096] As shown by reference number 40, the IPS 12 may post the comment on the forum of the innovation platform. The comment may be posted such that it is available to other registered users. In some embodiments, the comment may be posted such that it is visible under the original description of the idea.

[0097] In some embodiments, the IPS 12 may store a record of the time and date at which the comment is posted. This record may be stored using any data structure known in the art, such as an array, a linked list, etc. In some embodiments, the record may be stored on a blockchain. In this way, the blockchain creates an immutable, independently verified cryptographic record of the time and date at which the comment is posted. This may be useful when there are doubts as to which of multiple users was first to conceive of an idea or a feature of an idea.

[0098] In some embodiments, other users may interact with the comment provided by the second user. For example, other users may provide follow-up comments, like / dislike the comment, etc.

[0099] As shown in Fig. 2C, a panel of experts may determine a value of an ISRP that has been approved by the original posting user. In some embodiments, the user who posted the original idea may identify (or select) the second user’s comment as being eligible for an ISRP. In other embodiments, the second user’s comment may be determined to be eligible for an ISRP by the panel of experts, using a rules-based automation computation performed by the IPS 12, and / or using a semi-automated approach.

[0100] In some embodiments, the second user’ s comment may be eligible for an ISRP if theoriginal posting user is utilizing the subject matter described in the second user’s comment to make, use, distribute, and / or sell a product that incorporates the suggestion made in the comment by the second user. Continuing with the example described in connection with Figs. 2 A and 2B, assume the user decides to build a checkout system for grocery stores, and relies on the second user’ s idea to capture image data of the items included in the shopping cart, and to analyze the image data to identify which items were selected by the shopper. In this case, the second user’s comment may be determined to be eligible to receive an ISRP. This may cause ISRP data and / or related data to be made accessible to the panel of experts.

[0101] In some embodiments, the evaluation may be triggered by one or more other events. For example, the evaluation may be triggered by a configurable event, such as a certain amount of time passing. In this case, the original posting user may be prompted with a comment review interface that requires the user to indicate, for each posted comment, whether that comment is identified as eligible to receive an ISRP. When the user submits the review, data identifying any eligible ISRPs may be provided to the panel of experts.

[0102] The panel of experts may have accounts with the innovation platform and may access a review interface via a group of evaluation devices 42 (shown as evaluation device 42- 1 , evaluation device 42-2, ..., evaluation device 42-N). In some embodiments, the panel of experts may, using the review interface, evaluate a comment to determine the proper compensation to award for that comment. The panel of experts may be trained to assess the value of comments provided by registered users. For example, an expert may assess the value of a comment based on a degree to which the content of the comment is being relied upon by the original posting user, a degree to which the comment improves the quality or financial value of a product made using the idea, and / or the like. This ensures that a fair and impartial decision is made on the amount of value to assign to a particular comment.

[0103] As shown by reference number 44, respective evaluation devices 42 may provide, to the IPS 12, comment evaluation data identifying the ISRP that has been approved based on the evaluation performed by the experts. The comment evaluation data may be provided to the IPS 12, along with an account identifier linked to the user that posted the idea, and an account identifier linked to the second user who posted the comment.

[0104] In some embodiments, the IPS 12 may receive multiple ISRP recommendations from the panel of experts. In this case, the IPS 12 may be configured with one or more configurablerules designed to address situations where the same number of experts recommend two separate ISRPs. For example, assume that a panel of ten experts subject ISRP data, where five experts suggest a first ISRP recommendation and five experts suggest a second ISRP recommendation. The one or more configurable rules may include a weight-driven tie breaker rule, a rule indicating that the user posting the original idea is to select between the two ISRP recommendations, a rule indicating to select a random ISRP, a rule indicating that the board re- evaluation is required, a rule indicating that a hybrid split payment is to be utilized (e.g., 50% from the first ISRP recommendation, 50% from the second ISRP recommendation), and / or the like.

[0105] In some embodiments, the IPS 12 may store the comment evaluation data and / or may store specific comment evaluation data pertaining to the ISRP that has been approved.

[0106] Fig. 2D illustrates the IPS 12 orchestrating the process of compensating the second user based on the terms of the approved ISRP. In the example that follows, the IPS 12 may orchestrate compensation of the second user when the terms of the ISRP provide for compensation in the form of a fixed fee. In practice, the IPS 12 may orchestrate compensation for a user for any number of different types of compensation, depending on the terms identified in the ISRP.

[0107] As shown by reference number 46, the IPS 12 may provide a payment interface link to the user device 16-1, such that the payment interface link is provided for display on a user interface of the forum. In other embodiments, the payment interface may be provided directly on the user interface of the forum.

[0108] As shown by reference number 48, the user may interact with the user device 16-1 to cause transaction information to be provided to the transaction server 50-1. Transaction server 50-1 may, for example, be associated with a bank of the user. As shown by reference number 52, transaction server 50-1 may provide the transaction information to transaction server 50-2, which may, for example, be associated with a bank of the second user.

[0109] As shown by reference numbers 54, 56, 58, and 60, a confirmation message indicating that the transaction was successfully processed may be provided from transaction server 50-2 to transaction server 50-1, to user device 16-2, to IPS 12, and / or to user device 16-2. As shown by reference number 62, the user device 16-1 may provide the confirmation message for display on a user interface.

[0110] In some embodiments, the IPS 12 may perform one or more other actions relating to the accepted ISRP. For example, assume the terms of the ISRP indicate that the second user is to have 5% equity in a future company established by the user. In this case, the IPS 12 may generate a contract or contract outline indicating that the second user is to have 5% equity in any future company that uses, makes, sells and / or distributes the product corresponding to the idea. Additionally, or alternatively, the IPS 12 may perform one or more other actions, such as notifying the first and second users that the ISRP has been accepted, recommending nearby law firms for preparing a contract that includes the second user’s share of 5%, and / or the like.

[0111] As indicated above, 2A-2D are provided merely as an example. Other examples may differ from what is described with regard to 2A-2D. For example, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or differently arranged devices and / or networks than those shown in 2A-2D. Furthermore, two or more devices shown in 2A-2D may be implemented within a single device, or a single device shown in 2A-2D may be implemented as multiple and / or distributed devices. Additionally, or alternatively, a set of devices (e.g., one or more devices) used in example process 24 may perform one or more functions described as being performed by another set of devices used in example process 24.

[0112] Figs. 3A-3G are diagrams showing an example process 64 for facilitating the sharing of ideas and for providing compensation for the sharing of comments related to those ideas. Furthermore, one or more embodiments described here involve the use of a distributed file system, a blockchain, and / or one or more smart contracts. By using a distributed file system, the innovation platform provides efficient and decentralized storage of large quantities of idea- related data, ensuring scalability and accessibility. By using a blockchain, the innovation platform ensures that idea-related postings and data are securely recorded and time stamped in an immutable manner. By using one or more smart contracts, the innovation platform is able to provide automated reward distribution when users are compensated for providing comments that add value to an idea posting.

[0113] As shown in Fig. 3A, and by reference number 66, the user may interact with a user interface of the innovation platform to input an idea. As shown by reference number 68, when the user submits the idea, the user device 16-1 provides a request to post the idea to the IPS 12. The request may include idea data and / or reward offer data which are defined in connection withFigs. 2A-2D.

[0114] As shown by reference number 70, the IPS 12 may generate a cryptographic hash of the idea data and / or the reward offer data. For example, the IPS 12 may generate a cryptographic hash of the idea data and / or the reward offer data by executing a hash function that converts this data into a fixed-length hash value. In the examples that follow, secure hash algorithm (SHA)-256 is implemented. In practice, other hash functions may be implemented, such as SHA-3, SHA-1, BLAKE2, and / or the like.

[0115] The cryptographic hash may, for example, be a SHA-256 hash value (shown as SHA- 256 Hash Value A) that hashes the idea data and / or the reward offer data. Furthermore, metadata relating to the idea data and / or the reward offer data may be hashed, such as an account identifier for an account of the user, a timestamp, and / or other types of metadata. As can be appreciated by one of ordinary skill in the art, the value A for provided for sake of simplicity. To provide a practical example, assume the user has an account identifier of user_123, that the idea text is “a solar-powered retractable pool cover that adjusts based on weather conditions”, and that the timestamp is 2025-03-27T15:03:00Z. In this example, the IPS 12 may process these values to generate a cryptographic hash of “752f42571f5cd869blf9f08594d9695f9f887dl3963de428b2”.

[0116] As shown by reference number 72, the IPS 12 may store the idea data using a distributed file system 74. For example, the IPS 12 may store the idea data as a first record in the distributed file system 74. In some embodiments, the IPS 12 may also store the reward offer data, either as part of the first record or as a second record in the distributed file system 74. In some embodiments, the IPS 12 may also store idea metadata and / or reward offer metadata in the distributed file system 74. In some embodiments, data stored in the distributed file system 74 may be stored only after obtaining user consent and after obtaining the data in a manner compliant with any applicable data privacy laws and regulations. In some embodiments, data stored may be encrypted. In some embodiments, data stored may be modified to exclude certain personally identifiable information (PII).

[0117] As shown by reference number 76, the IPS 12 may store the cryptographic hash using a blockchain 78. For example, the IPS 12 may store the cryptographic hash as a first block in the blockchain 78. In some embodiments, the blockchain 78 may be a permissioned blockchain. In this case, roles may be assigned to specific users and access to the blockchain 78 may be based on the assigned role. For example, a user submitting an idea may be allowed to write to theblockchain 78 to post an idea, write to the blockchain 78 to post a modified post, write to the blockchain to post a merged idea, write to the blockchain 78 to accept or reject reward evaluations, and / or the like. The user may also be given read permissions to view blockchain 78 entries. A second user posting a comment may be given similar read / write permissions.Notably, the user and the second user are not permitted to edit postings on the blockchain 78, as these records are immutable. Instead, a new block on the chain is recorded to reflect any modifications or changes that are made. An expert reviewer / evaluator may also be given read / write permissions. A platform administrator may be given read-only access to the blockchain 78. Blockchain node operators may be given read access and may validate transactions occurring on the blockchain, but may be unable to access raw content stored in the distributed file system 74.

[0118] In some embodiments, the IPS 12 may generate a content identifier (e.g., CID A) for the first record. In some embodiments, the IPS 12 may store the CID as part of the first record in the blockchain 78. The CID may serve as a point to a memory location at which the corresponding idea data and / or reward offer data is stored via the distributed file system 74. For example, assume a second user enters a keyword “solar-powered pool cover” in the search bar. The IPS 12 may query a backend database and obtain the corresponding collection of idea data which may have been indexed by one of: title, description, user-submitted tags, and / or a vectorbased semantic similar search powered by machine learning. When the second user clicks on an idea, the IPS 12 is provided with a cryptographic hash for that idea. The cryptographic hash is stored in association with the CID which allows the IPS 12 to then use the COD to obtain the idea data and / or the reward offer data from the distributed file system 74.

[0119] As shown by reference number 80, the IPS 12 may post the idea on the forum of the innovation platform, thereby making the idea accessible to other registered users.

[0120] As shown in Fig. 3B, and by reference number 82, a second user may input a comment relating to the idea. For example, a user device 16-2 may display a user interface of the innovation platform and the second user may interact with the user interface to input the comment. The second user may also accept the one or more ISRPs offered by the user posting the idea.

[0121] As shown by reference number 84, when the second user submits the comment, the user device 16-2 provides a request to post the comment to the IPS 12. The request may includecomment data and / or reward acceptance data indicating that the second user has accepted the one or more ISRPs.

[0122] As shown by reference number 86, the IPS 12 may generate a cryptographic hash of the comment data. For example, the IPS 12 may generate a cryptographic hash of comment data describing the comment by executing the hash function to convert the comment data into a fixed- length hash value. In some embodiments, the cryptographic hash may also be generated for the reward acceptance data, comment metadata, and / or reward acceptance metadata. In the examples shown, the cryptographic hash is represented as SHA-256 hash value B.

[0123] As shown by reference number 88, the IPS 12 may store the comment data as part of the distributed file system 74. For example, the IPS 12 may store the comment data as a second record in the distributed file system 74. In some embodiments, the IPS 12 may also store the reward acceptance data, either as part of the second record or as a separate record in the distributed file system 74.

[0124] As shown by reference number 90, the IPS 12 may store the cryptographic hash (e.g., SHA-256 hash value B) using the blockchain 78. For example, the IPS 12 may store the cryptographic hash (e.g., SHA-256 hash value B) as a second block in the blockchain 78.

[0125] In some embodiments, the IPS 12 may generate a content identifier (e.g., CID B) for the second record. In some embodiments, the IPS 12 may store the CID for the second record as part of the second block in the blockchain 78. In this case, the CID serves as a pointer to a memory location in which the comment data is stored in the distributed file system 74.

[0126] As shown by reference number 92, the IPS 12 may post the comment on the forum of the innovation platform, thereby making the comment accessible to other registered users.

[0127] As shown in Fig. 3C, and by reference number 94, one or more evaluation devices 42 (shown as evaluation device 42-1, evaluation device 42-2, ..., evaluation device 42-N) may provide comment evaluation data to the IPS 12. As described in Fig. 2C, the panel of experts may, using a review interface, evaluate the comment to determine the proper compensation to award for that comment. Comment evaluation data may include data indicating whether the comment is eligible for compensation, an approved compensation value (e.g., a fixed fee amount, a percent ownership share in a company that uses, sells, makes, and / or distributes a product relating to the idea, etc.), notes data explaining how the evaluation was performed and / or how the approved compensation value is determined, and / or the like. After this review, commentevaluation data that identifies an ISRP that has been approved by the panel of experts is provided to the IPS 12.

[0128] As shown by reference number 96, the IPS 12 may generate a cryptographic hash of the comment evaluation data. For example, the IPS 12 may generate a cryptographic hash of the comment evaluation data (e.g., which includes content describing the evaluation and / or an evaluation decision) by executing the hash function to convert the comment evaluation data into a fixed-length hash value. In some embodiments, comment evaluation metadata is also hashed, including an account identifier of each respective panel member and a timestamp indicating a time during which the comment evaluation data is received. In the example shown, the cryptographic hash is represented as SHA-256 hash value C.

[0129] As shown by reference number 98, the IPS 12 may store the comment evaluation data using the distributed file system 74. For example, the IPS 12 may store the comment evaluation data as a third record in the distributed file system 74.

[0130] As shown by reference number 100, the IPS 12 may store the cryptographic hash of the comment evaluation data using the blockchain 78. For example, the IPS 12 may store the cryptographic hash as a third block in the blockchain 78. In some embodiments, the IPS 12 may generate a CID (e.g., CID C) for the comment evaluation data. This may be stored as part of the third block in the blockchain 78 and serve as a pointer to a memory location in which the comment evaluation data is stored in the distributed file system 74.

[0131] As shown by reference number 101, the IPS 12 post the evaluation on the forum of the innovation platform, thereby allowing other registered users to view the evaluation.

[0132] As will be shown in Figs. 3D-3G, a small contract may be used to automatically distribute compensation to the second user for posting the comment. As shown by in Fig. 3D, and by reference number 102, the IPS 12 may generate a smart contract. The smart contract may include an address for an electronic wallet of the user, an address for an electronic wallet of the second user, the cryptographic hashes and corresponding CIDs for the idea data, the comment data, and / or comment evaluation data. The comment evaluation data may include data identifying an approved compensation amount and / or data identifying a compensation status. The smart contract may further include smart contract metadata including an account identifier of the user, an account identifier of the second user, a timestamp indicating a time at which the smart contract is created, and / or the like.

[0133] The smart contract may further include a function defining a set of compensation rules, a function defining a process to initiate payment to compensate the second user, a function verifying the integrity of the comment, and / or a function creating an audit log of a compensation transaction history. The function defining the set of compensation rules may include one or more rules defining one or more corresponding compensation amounts based on an approved contribution level of the comment to the original idea. The function defining the process to initiate payment may include a feature to verify that the comment evaluation data includes an approved compensation amount, a feature to verify that the compensation status is pending (e.g., compensation has not previously been processed), and / or another type of feature.

[0134] The function verifying the integrity of the comment ensures that the comment has not been altered before payment is made. This function obtains comment data from the distributed file system 74, hashes the comment data, compares the hash with a stored cryptographic hash of the comment data on the blockchain 78, and if the hash matches the cryptographic hash on the blockchain 78, determines that the comment is authentic and has not been altered. The function creating the audit log creates an on-chain audit trail of all payments and evaluations.

[0135] As shown by reference number 104, the IPS 12 may generate a cryptographic hash of the smart contract. For example, the IPS 12 may generate a cryptographic hash of the smart contract by executing the hash function to convert the smart contract into a fixed-length hash value. In the example shown, the hash value is SHA-256 hash value D. Notably, smart contract metadata may also be hashed by the IPS 12. Smart contract metadata may include an account identifier of the user, an account identifier of the second user, a timestamp indicating a time during which the smart contract is created, and / or the like.

[0136] As shown by reference number 106, the IPS 12 may store the smart contract using the distributed file system 74. For example, the IPS 12 may store the smart contract as a fourth record in the distributed file system 74. In some embodiments, the distributed file system 74 may only store metadata pertaining to the smart contract and the smart contract itself may be stored on the IPS 12 or another node with access to the distributed file system 74 and / or blockchain 78. As shown by reference number 108, the IPS 12 may store the cryptographic hash of the smart contract using the blockchain 78. For example, the cryptographic hash (e.g., SHA- 256 hash value D) may be stored as a fourth block in the blockchain 78.

[0137] In some embodiments, the IPS 12 may generate a content identifier (e.g., CID D) forthe fourth record. In some embodiments, the IPS 12 may store the CID for the fourth record as part of the fourth block in the blockchain 78. This allows the CID to serve as a pointer to a memory location in which the smart contract is stored in the distributed file system 74.

[0138] As shown in Fig. 3E, and by reference number 112, an event triggers execution of the smart contract (shown as smart contract 110). A smart contract may be executed to distribute funds, allocate equity, record a milestone, mint tokens, log an immutable event, and / or the like. The event may, for example, be an event such as obtaining (or receiving) comment evaluation data indicating that the comment has been approved for compensation. In other embodiments, another event may trigger execution of the smart contract. For example, execution of the smart contract may be triggered based on validation criteria being satisfied, configurable threshold values for data accessible to the smart contract, and / or the like. To provide a specific example, configurable threshold values may be set, such as an expert votes threshold (e.g., at least three out of five reviewers must approve a comment before it is awarded), a score threshold (e.g., a comment must receive an impact score greater than 85% from the panel to trigger payout), an equity threshold (e.g., if a contribution qualifies as a “major” contribution, trigger equity distribution), and / or the like.

[0139] In some embodiments, system-defined occurrences act as triggers, such as an idea submission, an evaluation being uploaded, a milestone being reached (e.g., a startup business of the user logs progress such as MVP built to trigger equity to early contributors), and / or the like. In some embodiments, validation criteria may ensure legitimacy before triggering smart contract execution. For example, a submission time criteria may check if an idea or comment is submitted prior to a deadline, a confinnation of contribution criteria may check if the contribution is approved by others, an expert voting criteria may check if a threshold number of experts approved compensation for a comment, and / or the like.

[0140] In some embodiments, the smart contract 110 executes to perform a series of steps. First, the IPS 112 obtains the cryptographic hash of the comment evaluation data. Next, the IPS 112 obtains the comment evaluation data from the distributed file system 74. For example, the IPS 112 may identify the CID for the comment evaluation data which may be stored in association with the cryptographic hash of the comment evaluation data and may use the CID to obtain the comment evaluation stored in the distributed file system 74. Next, the IPS 12 may process the comment evaluation data to identify an evaluation score.

[0141] Now that the TPS 12 has determined the evaluation score, the IPS 12 may execute the smart contract 110 to record the result. For example, the IPS 12 may execute a function of the small contract 110 that defines the set of compensation rules and may pass the identified evaluation as a value in the function. The function may determine compensation based on the evaluation score. To provide a specific example where the compensation is in the form of a fixed fee, if the score is greater than or equal to 80, set the approved compensation value to $100, if the score is between 50 and 80, set the compensation value to $50, else, set the compensation value to $25. In this way, the smart contract provides automated reward determination based on an evaluation score provided in the comment evaluation data.

[0142] As shown by reference number 114, the smart contract 110 may provide a reward request to e-wallet 116 of the user. As shown by reference number 118, the e- wallet 116 may authenticate the reward request. As shown by reference number 120, the e-wallet 116 may provide a digital signature to the smart contract 110. As shown by reference number 122, the smart contract 110 may broadcast the signed request to a network of blockchain nodes 124. As shown by reference number 126, the network of blockchain nodes 124 may validate and approve the transaction.

[0143] As shown in Fig. 3F, and by reference number 128, at least one node, of the network of nodes (e.g., IPS 12 and / or another node) may generate a cryptographic hash of the approved transaction. As shown by reference number 130, at least one node (e.g., the IPS 12 and / or another node) may store approved transaction data using the distributed file system 74.

[0144] As shown by reference number 132, the at least one node may store the cryptographic hash of the approved transaction using the blockchain 78.

[0145] As shown in Fig. 3G, and by reference number 134, the smart contract 110 may provide an approved reward request to the e-wallet 116. As shown by reference number 136, the e-wallet 116 may provide a reward transaction to an e-wallet 138 of the second user. The reward transaction may include the compensation amount specified in the smart contract 110.

[0146] Figs. 4A-4F show an example process 140 for permitting or allowing access to a user interface of the innovation platform based on biometric authentication. As shown in Fig. 4A, and by reference number 142, the user may create an account with the innovation platform.

[0147] As shown by reference number 144, the user may configure a biometric profile to enable a screen-blurring feature. For example, the user device 16-1 may be communicativelycoupled to a camera 146 and may create a biometric profile that enables a screen-blurring feature to prevent unauthorized viewing of ideas and comments being shared over the innovation platform. To create the biometric profile, the user may use the camera 145 to capture image data depicting a face of the user.

[0148] A software application, which may be supported by the innovation platform or hosted locally on the user device 16-1, may be used to process the image data depicting the fact of the user to identify a set of baseline facial features. The set of baseline facial features may include a cheekbone prominence value, a jawline curvature value, a nose width / symmetry value, an interocular distance value, a facial symmetry value, and / or any other values capable of identifying distinguishing features of the user’s face.

[0149] In some embodiments, the user device 16-1 may encode the set of baseline facial features as a numerical feature vector. In the example shown in Fig. 4A, the numerical feature vector of the set of baseline facial features may include a cheekbone prominence value of 0.6569, a jawline curvature value of -0.3251, a nose width / symmetry value of -0.4703, an interocular distance value of -0.0730, and a facial symmetry value of -0.944.

[0150] Additionally, or alternatively, the biometric profile may contain baseline features for other parts of the user’s body (e.g., neck, torso, etc.). Additionally, or alternatively, the biometric profile may contain one or more other forms of biometric identification such as baseline features needed for a retina scan and / or a fingerprint login authentication.

[0151] As shown in Fig. 4B, and by reference number 148, the camera 146 may capture image data depicting an area around the user device 16-1. For example, to ensure that unauthorized users are not viewing ideas being posted by the user, the user may configure a setting in the account with the innovation platform to require biometric authentication. While the setting is enabled, camera 146 continuously captures image data and as will be described below, the user device 16-1 permits or allows access to a user interface of the innovation platform based on the result of a biometric authentication. In addition to capturing image data, the user device 16-1 may also generate image metadata, such as timestamp data identifying a time in which a given frame is captured, camera resolution for a given frame or set of frames, lighting conditions for a frame or set of frames, and / or the like.

[0152] In some embodiments, the camera 146 may begin to capture image data after the user has logged into the innovation platform. In some embodiments, the camera 146 may captureimage data based on another configurable trigger condition, such as a configured time period or another trigger condition known in the art.

[0153] As shown by reference number 150, the user device 16-1 may filter the image data. For example, the user device 16-1 may filter the image data using a first set of one or more computer vision techniques to improve image quality, thereby allowing more accurate facial recognition. The first set of one or more computer vision techniques may include an Open Computer Vision (OpenCV) technique, a technique using the Python Imaging Library (PIL), scikit-image technique, a NumPy-based custom filters technique, a TensorFlow technique, a technique using the MATLAB Image Processing Toolbox, and / or the like. The second set of one or more computer vision techniques may be supported by the innovation platform, a third party service provider, or hosted locally on the user device 16-1.

[0154] In some embodiments, the user device 16-1 may use a computer vision technique to convert the image data to grayscale. This allows for more efficient facial recognition by reducing the complexity of the image by eliminating color. Notably, facial recognition techniques perform best with grayscale images due to focusing on intensity variations rather than color.

[0155] Additionally, or alternatively, the user device 16-1 may use a computer vision technique to perform histogram equalization on the image data. Histogram equalization improves contract in an image, making it easier for facial recognition techniques to detect facial features under different lighting conditions. Histogram equalization works by spreading out intensity values in the image. For example, assume the image data depicts a dimly lit face where facial features are not clearly visible. By performing histogram equalization, the face may appear more distinct and may have more prominent edges.

[0156] Additionally, or alternatively, the user device 16-1 may use a computer vision technique to smooth the image data. For example, the user device 16-1 may use a Gaussian Blur to smooth the image data to reduce noise and to improve the robustness in edge and feature detection. This can be useful for eliminating sharper edges and random pixel variations before applying facial recognition techniques.

[0157] As shown by reference number 152, the user device 16-1 may identify one or more faces and corresponding facial features in the filtered image data. For example, the user device 16-1 may use a second set of one or more computer vision techniques to identify (e.g., locate)one or more faces and corresponding facial features in the filtered image data.

[0158] The second set of one or more computer vision techniques may include a Haar Cascades technique, a technique using a histogram of oriented gradients (HOG) and a support vector machine (SVM), a technique using You Only Look Once version 5 (YOLOv5), a technique using RetinaFace, a technique using Open Computer Vision (OpenCV) Deep Neural Network (DNN), a technique using FaceNet, a technique using a DeepFace or a Dlib Residual Network (ResNet)-based model, and / or the like. The second set of one or more computer vision techniques may be supported by the innovation platform, a third party service provider, or hosted locally on the user device 16-1.

[0159] In some embodiments, to identify a face, the user device 16-1 may use a first computer vision technique to determine three-dimensional (3-D) coordinates of a bounding box that represents boundaries of the face found in the image data. In some embodiments, the user device 16-1 may use a second computer vision technique to identify key facial features such as eyes, nose, mouth, chin, and / or the like. Additionally, or alternatively, the second user device 16-1 may use a third computer vision technique to identify a more comprehensive list of facial features, such as a cheekbone prominence feature, a jawline curvature feature, a nose width / symmetry feature, an interocular distance feature, a facial symmetry, and / or the like.

[0160] In the example shown at the top of Fig. 4B, an unauthorized user is standing behind the user (shown as “authorized user”). In this example, the user device 16-1 may identify a first bounding box representing a face of the authorized user and a second bounding box representing a face of the unauthorized user. The user device 16-1 may further identify a first set of key facial features of the face of the authorized user and a second set of key facial features of the unauthorized user.

[0161] As shown in Fig. 4C, and by reference number 154, the user device 16-1 may encode the identified facial features. For example, the user device 16-1 may generate a numerical feature vector (sometimes referred to as an embedding) where each vector value represents a particular facial feature, such as cheekbone prominence, jawline curvature, nose width / symmetry, interocular distance, and / or facial symmetry.

[0162] In the example shown, the user device 16-1 encodes the identified feature features into a first set of encoded facial features and a second set of encoded facial features. The first set includes the following values: 0.6569, -0.3251, -0.4703, 0.0730, ..., and -0.9444. The second setincludes the following values: 0.9286, -0.1635, -0.6738, -0.3988, ..., and -0.8582.

[0163] As shown by reference number 156, the user device 16-1 may determine whether facial features match stored facial features of the authorized user. For example, the user device 16-1 may determine whether facial features match stored facial features of the authorized user by comparing encoded facial features with the set of encoded baseline facial features. If the facial features match the encoded baseline facial features, the user device 16-1 may permit access to the user interface of the innovation platform. If the facial features do not match the encoded baseline facial features, the user device 16-1 may deny access to the user interface, such as by blurring the user interface such that a detected unauthorized user is unable to view ideas and comments posted on the innovation platform.

[0164] As shown by reference number 158, the user device 16-1 may blur a user interface of the innovation platform. For example, the user device 16-1 may blur the user interface based on facial features for a second face not matching the stored facial features of the authorized user. In particular, the user interface may be blurred based on encoded facial features for a second face of an unauthorized user not matching the encoded facial features of the authorized user. This can be seen by comparing the encoded facial feature values for the second face shown in Fig. 4C with the baseline encoded facial feature values shown in Fig. 4A.

[0165] Notably, some embodiments described herein blur the user interface based on whether facial features (or encoded facial features) match stored baseline facial features (or encoded baseline facial features) of the authorized user. In other embodiments, the user device 16-1 may make this determination based on detecting multiple bounding boxes representing boundaries of multiple faces found in the image data. Due to detecting multiple bounding boxes, the user interface may be blurred without having to determine each individual facial feature found within the respective bounding boxes. This conserves computing resources of the user device 16-1 while still preventing unauthorized viewing of the innovation platform.

[0166] In some embodiments, once the user interface of the innovation platform is blurred, the user will have successfully complete biometric authentication to unblur the user interface. In some embodiments, the user may temporarily override a blurred user interface. This allows the user to intentionally share visibility of the user interface with an authorized collaborator. In some embodiments, the user may add recognized household members or specific faces as authorized collaborators.

[0167] In some embodiments, the biometric authentication may have user configurable sensitivity levels, thereby allowing users to adjust a sensitivity level of the facial recognition. Adjusting a sensitivity level may cause an increase or decrease in the one or more system performance thresholds. In some embodiments, a time-interval recheck may be configured to prompt a re-authentication of the user’s face if the face of the user is not detectable for a threshold time period.

[0168] In some embodiments, if x number of frames (or a user-configurable threshold) fails to produce a valid detection due to a CPU spike, network lag, or camera errors, the user device 16-1 defaults to blurring the user interface. If, for example, the CPU usage normalizes, the user device 16-1 resumes biometric authentication, rather than the default blurred user interface.

[0169] In some embodiments, if a default blurred user interface is implemented, each frame of the image data may be temporarily buffered in memory and encrypted (e.g., using AES-256 or another encryption technique) prior to transmission to the IPS 12. One or more embodiments described above default to having the user device 16-1 perform the data processing needed for biometric authentication and rely on the IPS 12 only if an event occurs. In other embodiments, the default may be to have the IPS 12 perform the data processing needed for biometric authentication. In this case, if an event occurs, such as the Internet of the user goes down (e.g., such that the user device 16-1 is offline and cannot stream frames to the IPS 12, then the user device 16-1 will perform local biometric authentication.

[0170] While Figs. 4A-4C show the process of performing a biometric authentication of the user while the user is logged into the innovation platform, Fig. 4D shows that security event data, such as user interface blurring, can be stored as part of the distributed file system 74 and / or blockchain 78. Figs. 4E and 4F show alternate embodiments of the process of performing a biometric authentication of the user.

[0171] As shown in Fig. 4D, and by reference number 160, the user device 16-1 may provide security event data to the IPS 12. A security event occurs when the user device 16-1 blurs the user interface of the innovation platform. In this situation, the user device 16-1 may provide screen-blurring security event data to the IPS 12 to create a record of the fact that an unauthorized user was in the vicinity of the first (authorized) user while the user was logged in to the innovation platform.

[0172] As shown by reference number 162, the IPS 12 may generate a cryptographic hash ofthe security event. For example, the IPS 12 may generate a cryptographic hash of the security event by executing the hash function to convert the security event data into a fixed-length hash value. In some embodiments, security event metadata may also be hashed, such as an account identifier of the user, a timestamp corresponding to the security event, and / or the like, vln the example shown, the IPS 12 may generate SHA-256 hash value F.

[0173] As shown by reference number 164, the IPS 12 may store security event data using the distributed file system 74. For example, the IPS 12 may store the security event data as a sixth record in the distributed file system 74.

[0174] As shown by reference number 166, the IPS 12 may store the cryptographic hash of the security event using the blockchain 78. For example, the IPS 12 may store the cryptographic hash (e.g., SHA-256 hash value F) as a sixth block in the blockchain 78.

[0175] In some embodiments, the IPS 12 may generate a content identifier (CID) for the sixth record (e.g., CID F). The CID for the sixth record may also be stored as part of the sixth block of the blockchain 78 and may serve as a pointer to the sixth record to allow authorized users to access the security event data from the distributed file system 74.

[0176] As shown in Fig. 4E, and by reference number 168, while the camera continuously captures image data, an event occurs that interferes with facial recognition capabilities of the user device 16-1. The users of the innovation platform may have different internet speeds (e.g., based on their internet service provider and data plan), computers with different computational power and data storage capabilities, cameras capable of capturing image data of different resolutions, different environments which contain different lighting and backgrounds, and / or the like. As such, in some situations, an event may occur that may interfere with the facial recognition capabilities of the user device 16-1. An event may include a central processing unit (CPU) overheating resulting in a frames per second (FPS) rate drop, poor light conditions resulting in FPS rate drop, low camera resolution making it more difficult to accurately perform facial recognition, slow CPU processing speeds, and / or insufficient random access memory (RAM) / virtual RAM (vRAM).

[0177] To address these situations, the user device 16-1 may be configured with a set of system performance thresholds and may periodically monitor system parameters to determine if current performance data satisfies the set of system performance thresholds. For example, a system performance threshold for FPS rate may set a minimum permissible FPS rate. If the FPSrate drops below the minimally permissible FPS rate (i.e., drops below a configured FPS rate threshold), an event occurs. As would be understood by one skilled in the art, a minimum system performance threshold may be configured for any number of different system parameters such as those described above.

[0178] As shown by reference number 170, when an occurs, the user device 16-1 may provide the image data to the IPS 12. As shown by reference number 172, the IPS 12 may perform steps 150, 152, 154, and 156, to determine whether facial features included in the image data match stored facial features of the authorized user. As shown by reference number 174, the IPS 12 may provide, to the user device 16-1, instructions indicating whether to blur the user interface of the innovation platform. As shown by reference number 176, the user device 16-1 may implement the instructions. For example, the user device 16-1 may implement instructions to blur the user interface of the innovation platform or may continue to display the user interface if the biometric authentication is successful.

[0179] In this way, the user device 16-1 is able to offload some of the computationally heavy processing tasks to the IPS 12, thereby efficiently and effectively utilizing resources of all devices while still enabling biometric authentication of the authorized user.

[0180] As shown in Fig. 4F, and by reference number 178, the feed of the camera 146 may experience an interruption. As shown by reference number 180, the user device 16-1 may blur the user interface while the camera feed is interrupted. This provides a fail-safe mechanism that prevents accidental exposure in the event of an interruption.

[0181] Figs. 5A-5F show an example process 182 for receiving a request to post an idea on the innovation platform, determining that the idea is similar to one or more previously posted similar ideas, determining to post the idea as a comment to one of the one or more previously posted similar ideas, and orchestrating delivery of compensation for the comment in a manner that complies with one of the ISRPs for the previously posted similar idea. As shown in Fig. 5A, and by reference number 183, the fuser may input an idea. As shown by reference number 184, submitting the idea causes the user device 16-1 to provide a request to post the idea to the IPS 12.

[0182] As shown by reference number 186, the IPS 12 may perform one or more processing operations on text data and / or image data relating to the idea. For example, assume the idea data contains several paragraphs of text describing the idea and one image depicting the idea. In thiscase, the IPS 12 may perform a first set of one or more pre-processing operations on the text, such as by converting text to lowercase text, removing special characters, tokenizing words included in each respective paragraph, removing stop words, and / or the like.

[0183] Next, the IPS 12 may perform a second set of one or more pre-processing operations, such as by re-sizing the image to a size suitable for further processing by a convolutional neural network (CNN), applying a center-cropping technique, standardizing pixel values, and / or by performing any other pre-processing operations needed to standardize the image data into a format suitable for further processing by the CNN. To provide an example, an image may be received that is 300 x 400 pixels and the IPS 12 re- size the image to 224x224 pixels which is a size of historical images used to train the CNN. The IPS 12 may also apply a center cropping technique to ensure that the content depicted in the re-sized image is centered and may standardize pixel values to improve CNN performance while further processing the image data.

[0184] As will be described below, reference number 188 in Fig. 5B describes preprocessing operations that are additional to the pre-processing operations described in connection with Fig. 5A. These pre-processing operations are described separately for clarity purposes.

[0185] As shown in Fig. 5B, and by reference number 188, the IPS 12 may generate idea embeddings for the text data and / or the image data. This is yet another pre-processing operation performed by the IPS 12 but is described separately for clarity purposes.

[0186] In some embodiments, the IPS 12 may generate a first set of idea embeddings for the text data. For example, the IPS 12 may provide the text data as input to a transformer model 190 to cause the transformer model 190 to output the first set of idea embeddings. The transformer model 190 may be Bi-directional Encoder Representations from Transformers (BERT) or another type of transformer-based model. As described in connection with reference number 186, the IPS 12 may pre-process the text data by tokenizing the words included in the user’s description of the idea. Tokenization can be performed prior to providing the text data to the transformer model 190 or may be performed by the transformer model 190. The transformer model 190 may then convert each token and / or each string of text of a word into a word embedding vector of a fixed size. Each embedding captures semantic meaning.

[0187] Next, the transformer model 190 may identify relationships between words included in the text data. For example, in the phrase “a solar-powered retractable pool cover that adjusts based on weather conditions” the transformer model 190 may determine that the term “solar-powered” relates more to the term “cover” than to the term “pool”. The transformer model 190 may then generate a final idea embedding for the text. When the transformer model 190 is a BERT model, the model 190 may generate idea embeddings that include a 768-dimensional vector that represents the meaning of the text. Each idea embedding may be a numerical identifier representative of a given word, combination of words, relationships of words, positions of words, and / or may be representative of a way to differentiate between two words or combinations of words. The final idea embeddings generated is a vector containing a series of numerical identifiers.

[0188] In some embodiments, a sequence of token embeddings (corresponding to words, combinations of words, etc.) may be passed through transformer layers of transformer model 190. Each layer uses a multi-head self- attention function to relate each token to every other token in a bi-directional manner. In a practical sense, this means that words such as “cover” may be interpreted differently depending on the surrounding context (e.g., pool cover versus book cover). As will be described further herein, the vector output may be used for similarity classification.

[0189] In some embodiments, the transformer model 190 may be trained using historical idea data using unsupervised machine learning techniques. This means model 190 learns patterns from raw text without explicit labels. The first training objective involves masked language modeling (MLM), where the model 190 predicts missing (masked) words in a sentence using context on both sides. The second training objective involves next sentence prediction (NSP), where the model 190 predicts if sentence B logically follows sentence A. To provide an example, raw text is provided to a tokenizer. MLM is applied to mask random tokens. NSP is applied to randomly pair sentence A with B or a random sentence. Tokens and positional information is passed into the model 190. The model 190 computes loss from predicted tokens (MLM) and sentence prediction (NSP). The model 190 backpropagates gradients to update weights and repeats this process across tens of thousands, hundreds of thousands, or millions of text samples. The model 190 may be iteratively tuned in real-time based on expert feedback.

[0190] In some embodiments, the IPS 12 may generate a second set of idea embeddings for the image data. For example, the IPS 12 may provide the image data as input to CNN 192 to cause the CNN 192 to output the second set of idea embeddings. CNN 192 may be a contrastive language-image pretraining (CLIP) model, a residual network with 50 layers (ResNet-50), and / ora vision transformer. A first layer of the CNN 192 may be used to determine a set of low-level features (e.g., edges, corners, gradients, etc.) found in the image. The next set of one or more layers of the CNN 192 may be used to determine shapes, textures, and / or simple patterns found in the image. The next set of one or more layers of the CNN 192 may be used to determine objects included in the image (e.g., a pool cover, the sun, etc.). The next set of one or more layers of the CNN 192 may be used to generate a 512-dimensional vector representation of the image. Each vector value represents a particular feature. Positive values may represent a strong presence of a feature, whereas negative values may represent an absence of a feature. Spatial information is not preserved directly, while the feature relationships are preserved. Next, the CNN 192 weights different parts of the image based on a degree to which those parts of the image relate to a given feature.

[0191] To train the CNN 192, a labeled dataset may be provided as input. Historical image data is provided to layers of the CNN 192 to generate predictions. The CNN 192 computes a loss calculation. Backpropagation techniques use gradients to update the filters or kernels to reduce error. This process may be iteratively repeated over multiple images until the CNN 192 identifies useful features.

[0192] In some embodiments, a vector database may be used to store idea embeddings and / or comment embeddings for a collection of previously submitted ideas and comments. As shown by reference number 194, the IPS 12 may add the idea embeddings for the idea of the user to the vector database. The vector database may be a Facebook Al Similarity Search (FAISS) database, a Pinecone database, and / or the like. Each idea embedding may be stored with metadata, such as an account identifier of user, a timestamp, and / or any other stored reference data that may be needed (e.g., a cryptographic hash to a block in the blockchain, etc.).

[0193] As shown in Fig. 5C, and by reference number 196, the IPS 12 may identify one or more previously posted ideas that are similar to the idea provided by the user. To identify the one or more previously posted similar ideas, the IPS 12 may perform a similarity analysis that compares the idea embeddings for the idea provided by the user with a stored collection of idea embeddings.

[0194] In some embodiments, to identify the one or more previously posted similar ideas, the IPS 12 may search the vector database using a k-nearest neighbor (k-NN) search to obtain a list of idea embeddings for previously posted similar ideas. The k-NN search may be performedusing distance measures, such as by using cosine similarity for text-based idea embeddings and Euclidean distance for image-based idea embeddings. The k-NN search may involve computing similarity scores between the idea embeddings for the idea submitted by the user and stored idea embeddings. A previously posted idea may be selected for the list based on whether a computed similarity score satisfies a threshold similarity level. The output of the k-NN search is the list of idea embeddings corresponding to the previously posted similar ideas which have similarity scores that satisfy the threshold similarity level.

[0195] In some embodiments, such as when a previously posted similar idea includes both text data and image data, the IPS 12 may determine a weighted similarity score. To provide a specific example, assume previously posted similar ideas is identified for the idea that uses a retractable pool cover and solar energy. In this example, assume the text of the previously posted idea has been assigned a similarity score of 0.85 as it includes text describing another solar powered pool cover. Further assume the image of the previously posted idea has been assigned a similar score of 0.72 as it depicts a foldable solar panel. In this example the IPS 12 may assign a weight of x percent (e.g., 0.70) to the text and may assign a weight of y percent (e.g., 0.3) to the image and may compute a weighted similarity score. The previously posted idea may be added to the list of previously posted similar ideas if the weighted similarity score satisfies the threshold similarity level.

[0196] As shown by reference number 198, the IPS 12 may provide data identifying the previously posted similar ideas to the user device 16-1. This may cause the user interface of the innovation platform to display the list of previously posted similar ideas.

[0197] As shown by reference number 200, the user may input instructions to post the idea as a comment to one of the previously posted similar ideas. In addition to displaying the list of previously posted similar ideas, the user interface may display one or more selection choices for the user. For example, the user may accept that the idea is in fact similar to one of the previously posted similar ideas. In this case, the user may select the previously posted similar idea and may select to post the user’s idea as a comment to the selected previously posted idea.

[0198] Additionally, or alternatively, the user may take one or more other courses of action. For example, the user may mark one or more of the previously posted ideas in the list as being unrelated ideas. As another example, the user may mark one or more of the previously posted ideas as being “inspired by”, but distinct from, the idea submitted by the user. As anotherexample, the user may choose to refine the idea (e.g., before the idea is posted) so as to further distinguish the idea from the list of previously posted ideas. In the example shown in Fig. 5C, the choice made by the user is underlined: to post the idea as a comment to a previously posted similar idea.

[0199] As shown in Fig. 5D, and by reference number 202, when the user submits the selection to post the idea as a comment to the previously posted similar idea, the user device 16-1 provides data indicative of that selection to the IPS 12. As shown by reference number 204, the IPS 12 may provide, to the user device 16-1, reward offer data for the previously submitted similar idea. As shown by reference number 206, the user may accept reward offer data via a user interface of the innovation platform. As shown by reference number 208, when the user submits acceptance of the reward offer data, the user device 16-1 provides data identifying that acceptance to the IPS 12. As shown by reference number 210, the IPS 12 may post the idea as a comment to the previously submitted similar idea.

[0200] As shown in Fig. 5E, and by reference number 212, the evaluation devices 42 may provide, to the IPS 12, comment evaluation data identifying the ISRP that has been approved based on an evaluation performed by the panel of experts.

[0201] As shown in Fig. 5F, and by reference number 214, the IPS 12 may provide a payment interface link to a user device 16-3 that is associated with a third user who submitted the previously posted similar idea. As shown by reference number 216, the third user may interact with the user device 16-3 to cause transaction information to be provided to a transaction server 50-3. Transaction server 50-3 may, for example, be associated with a bank of the third user. As shown by reference number 218, transaction server 50-3 may provide the transaction information to transaction server 50-1, which may, for example, be associated with a bank of the user.

[0202] As shown by reference numbers 220, 222, 224, and 226, a confirmation message indicating that the transaction was successfully processed may be provided from transaction server 50-1 to transaction server 50-3, to user device 16-3, to IPS 12, and / or to user device 16-1. As shown by reference number 227, the user device 16-1 the confirmation message may be provided for display on a user interface of the innovation platform and / or a separate user interface outside of the innovation platform which is operated by a third party.

[0203] In some embodiments, the distributed file system 74 and blockchain 78 discussed inconnection with Figs. 3A-3G and Figs. 4A-4F may be implemented in connection with the embodiments of Figs. 5A-5F. For example, one or more records of one or more corresponding transactions described in Figs. 5A-5F may be stored using the distributed file system 74 and one or more blocks each containing a cryptographic hash of a respective transaction and / or a CID serving as a pointer to a memory location in the distributed file system 74 may be stored as part of the blockchain 78.

[0204] Figs. 6A-6F show an example process 228 for posting a modified version of an original idea on the innovation platform (referred to herein as a modified idea), creating versioned records of the idea and the modified idea, and for making version management decisions such as merging the idea and the modified into a merged idea.

[0205] As shown in Fig. 6A, and by reference number 230, the user may input modified idea. For example, assume the original idea included three paragraphs of text describing a solar- powered retractable pool cover that adjusts based on weather conditions. In this example, assume the user inputs a modified idea which includes three paragraphs of text, where the first paragraph is the same but where the second and third paragraphs includes one or more changes relative to the corresponding second and third paragraphs of the original idea. When the user submits the modified idea, the user device 16-1 provides, to the IPS 12, a request to post the modified idea.

[0206] As shown by reference number 234, the IPS 12 may determine a degree of similarity between the original idea and the modified idea. The IPS 12 may first split the idea and the structured idea into structured components, such as title, description, paragraph-by-paragraph text, particular uploaded images, and so forth. Each paragraph of text may be tokenized into words or sub- words.

[0207] Next, the IPS 12 may determine a degree to which each paragraph in the idea data is similar to a corresponding paragraph in the modified idea. First, the IPS 12 may first generate a cryptographic hash of each paragraph included in the idea and in the modified idea and may compare cryptographic hashes of the idea to corresponding cryptographic hashes of the modified idea. This allows the IPS 12 to detect exact matches such as when a paragraph is completed unchanged (e.g., because changing even one character will change the hash). The cryptographic hashes also provide a secure way to implement a version control mechanism as cryptographic hashes may be stored over the blockchain 78 (see, e.g., the description of Fig. 6C). In theexample above, the IPS 12 may determine that paragraph one in the original idea is identical to paragraph one in the modified idea, but that paragraphs two and three in the modified idea include one or more changes relative to paragraphs two and three in the original idea.

[0208] To determine a degree to which the second and third paragraphs in the original idea are similar to paragraphs two and three of the modified idea, the IPS 12 may perform a similarity analysis such as that described in connection with Figs. 5B and 5C. For example, the IPS 12 may generate idea embeddings for paragraph two and three of the original idea and paragraphs two and three of the modified idea and may use cosine similarity to determine a degree of semantic similarity between the respective corresponding paragraphs. The output from using cosine similarity may be a similarity value for each of the second and third paragraphs of the modified idea, where each similarity value represents a degree of semantic similarity between the respective paragraph of the modified idea and the corresponding paragraph of the original idea.

[0209] As shown in Fig. 6B, and by reference number 236, the IPS 12 may classify the one or more changes made to the modified idea relative to the original idea. Some embodiments described herein involve classifying total changes made to the modified idea relative to the original idea. In other embodiments described herein, classifications can be made on a paragraph-by-paragraph basis and / or an image -by-image basis. For example, each paragraph of text describing the original idea may be compared to each paragraph of text describing the modified idea, or, alternatively, the entire original idea may be compared to the entire modified idea.

[0210] In some embodiments, the IPS 12 may classify the one or more changes using four classification categories. A similarity score of 1.0 may be classified as having no change (i.e., identical paragraphs). A similarity score between 0.85 and 1.0 may be classified as a minor change. A similarity score between 0.50 and 0.85 may be classified as a moderate change. A similarity score that is less than 0.50 may be classified as being a major change. In the example shown, 0.5 <- SIM < 0.85 is underlined because the changes incorporated in the modified idea constitute a moderate change relative to the original idea.

[0211] As will be shown further herein, classifying the one or more changes permits the IPS 12 to perform dynamic, accurate, version control tasks as ideas and modifications to the ideas are periodically posted on innovation platform. It is to be understood that this classification scheme is provided by way of example, and that in practice, any number of different classificationcategories may be configured to distinguish between types of changes made to ideas posted on the innovation platform.

[0212] As shown by reference number 238, the IPS 12 may update the graph data structure using the classification. One or more embodiments described herein refer to the graph data structure as being a directed acyclic graph (DAG). This is provided by way of example, and in practice, a different type of graph data structure may be used and / or a data structure that is different from a graph may be used.

[0213] The manner in which the IPS 12 updates the DAG may be based on the particular classification. For example, when the classification is a major change, the IPS 12 may create a new branch in the DAG to track the modified idea as a new version. When the classification is a moderate change, the IPS 12 may create a new branch in the DAG but the new branch may require review from a user, such as a review from the user posting the modified idea or from a subject matter expert on the topic being discussed by the idea and modified idea. When the classification is a minor change, the IPS 12 may not create a new branch, but instead, may simply add the change as a new node in the main trunk of the DAG. In each of these scenarios, the change constitutes a new version. However, a new branch is only created when the change is a moderate change or a major change.

[0214] In the DAG shown in Fig. 6B, the IPS 12 may update the DAG to include a new branch based on the change being classified as a moderate change. The new branch is shown as a path a root node to the modified idea node to hashes Pl, P4, and P5. Comparatively, the main trunk in the DAG is shown as a path from the root node to the original idea node to hashes Pl, P2, and P3.

[0215] In some embodiments, such as when the version classification involves a moderate change, the user and / or one or more other users may be required to approve the version classification. As shown in Fig. 6C, and by reference number 240, the user may review and accept the version classification. In some embodiments, the original idea (version 1) and the modified idea (version 2) may be displayed in sequence on a user interface of the innovation platform. The user interface may also display the DAG and / or any other information related to version control. As shown by reference number 242, when the user submits the accepted version classification, the user device 16-1 provides acceptance data to the IPS 12.

[0216] As shown by reference number 244, the IPS 12 may generate a cryptographic hash ofthe modified idea. The cryptographic hash is shown as SHA-256 hash value G. As shown by reference number 246, the IPS 12 may store modified idea data using the distributed file system 74. As shown by reference number 248, the IPS 12 may store the cryptographic hash of the modified idea using the blockchain 78.

[0217] In some embodiments, the IPS 12 may generate a cryptographic hash of each respective paragraph in the original idea and in the modified idea. In this case, the blockchain 78 may have separate blocks storing cryptographic hashes of each respective paragraph, along with a corresponding CID which serves as a pointer to a memory location in which the respective paragraph can be found within the distributed file system 74.

[0218] As shown by reference number 250, the IPS 12 may post the modified idea on the forum of the innovation platform.

[0219] As shown in Fig. 6D, and by reference number 252, the user may submit a request to merge the modified idea and the original idea. The user may want to merge the modified idea and the original for a number of reasons, including resolving conflicting changes that require resolution, improving an overall business model process flow, correcting an issue in the main trunk, restoring lost features from a prior version, and / or the like.

[0220] As shown by reference number 254, to merge the modified idea and the original idea, the IPS 12 may first compare the modified idea and the original data. In this case, the IPS 12 may determine similarity scores between the main trunk (e.g., representing the original idea) and the new branch (e.g., representing the modified idea). As is shown by reference number 256, the IPS 12 may identify or flag one or more conflicts based on comparing the modified idea and the original idea. For example, the IPS 12 may identify a conflict based on partially conflicting content between two corresponding paragraphs in separate versions and / or may identify a conflict based on substantially conflicting content between two corresponding paragraphs in separate versions. Example conflicts include a direct textual conflict, an overlapping feature expansion conflict, a structural change conflict, a conflict involving a terminology and / or definition discrepancy, a user experience change conflict, a workflow logic conflict, a merge conflict between two or more users, and / or the like. In some embodiments, the IPS 12 may be configured to automatically merge paragraphs with no conflicts. In some embodiments, the IPS 12 may be configured to generate a merge conflict record when a conflict is identified.

[0221] As shown in Fig. 6E, and by reference number 256, the IPS 12 may resolve one ormore conflicts. For example, the IPS 12 may be configured to resolve a conflict automatically. In some embodiments, the IPS 12 may be configured to report a conflict to a user for manual resolution. In some embodiments, the IPS 12 may be configured to implement a partially automated resolution of a conflict.

[0222] As shown by reference number 260, the IPS 12 may create a new branch for merged idea data (version 3). As can be seen, the new branch for the merged idea includes a path from the root node to a merged idea node to a paragraph one hash to a paragraph four hash to a paragraph three hash. In this case, the first two versions (e.g., the idea and the modified idea) are combined such that a third version (e.g., the merged idea data) is created which includes the overlapping first paragraph, the fourth paragraph from the modified idea data, and the third paragraph from the original idea data. Notably, the DAG still creates a new branch such that a complete history of each version of the idea is maintained.

[0223] As shown in Fig. 6F, and by reference number 262, the IPS 12 may generate a cryptographic hash of the merged idea. The cryptographic hash may include SHA-256 hash value H. As shown by reference number 264, the IPS 12 may store the merged idea data using the distributed file system 74. As shown by reference number 266, the IPS 12 may store the cryptographic hash of the merged idea using the blockchain 78. A CID may be created (e.g., CID H) which serves as a pointer to a memory location in which the merged idea data is stored in the distributed file system 74.

[0224] In some embodiments, assume two separate versions lead to productization, where commenting contributors to each version each claim an ISRP in the form of equity in a startup business. In this case, each idea node or branch in the DAG has metadata that includes a parent node to which the idea derives, equity lineage data, a smart contract link, and a fork status indicating whether the fork is collaborative or contested. When a new branch (version 2) is created, this branch inherits metadata from the parent idea node. That is to say, unless specified otherwise, version 2 contributors earn equity within the context of version 1’s equity pool. Each version 1 smart contract defines the contributors and their equity percentages, whether forks inherit equity, and rules for sub-branch allocation (if permitted). For example, a smart contract may have a clause indicating that equity allocations apply only to merged branches and that parallel forks not merged back into the trunk of the DAG by milestone X will not share in equity unless a new proposal is approved. This ensures forks must be merged to receive compensationand contributors to unmerged forks may earn a new equity pool only with board approval or user vote. Next, mcrgc-rcquircd equity activation is described. A new branch (version 2) must be merged back into the main trunk (version 1) to trigger equity payment from the version 1 contract. This may be enforced as a merge event in the DAG (e.g., a MergeCommit function), where a new “merged” smart contract inherits allocations and only contributors to the merged branch are awarded. This creates a “no merge = no shared equity” policy. In other embodiments, a merge governance board may assist in equity resolution conflicts by reviewing branching history, auditing user contributions, and by approving or denying equity extension to forked branches.

[0225] By implementing the IPS 12 in the manner described in this application, the IPS 12 adequately incentivizes meaningful contributions from users and adequately compensates contributors for their valuable input. Further, by providing secure, time-stamped, verifiable records of ideas shared over the platform, the IPS 12 can prove exactly when each user created an idea and / or a comment to idea. Furthermore, by implementing version control techniques, the IPS 12 links each posted comment to a particular version of an idea posting, eliminating any ambiguity in when an idea posting, updated idea posting, and / or comment is made, thereby allowing fair compensation to be awarded for each posting. Still further, by providing an efficient and effective way to authenticate access to and viewership of the platform, the IPS 12 can verify that the individual submitting an idea posting or comment posting is in fact the authorized user who registered with the platform.

[0226] Fig. 7 is a diagram of an example environment 268 in which systems and / or methods described herein may be implemented. As shown in Fig. 7, environment 268 may user devices 16, evaluation devices 42, transaction servers 50, an IPS 12 supported within a cloud computing environment 270, a network of nodes 124, and / or a network 274. Devices of environment 268 may interconnect via wired connections, wireless connections, or a combination of wired and wireless connections.

[0227] User device 16 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information associated with the exchange of ideas. For example, user device 16 may include a device, such as a tablet computer (e.g., an iPad, etc.), a mobile phone (e.g., a small phone, a radiotelephone, etc.), a laptop computer, a handheld computer, a server computer, a gaming device, a wearable communication device (e.g., a smartwristwatch, a pair of smart eyeglasses, etc.), or a similar type of device. In some embodiments, the user device 16 may be communicatively coupled to a sensor, such as a camera, which captures image data depicting an environment around a user.

[0228] Evaluation device 42 includes one or mor devices capable of receiving, generating, storing, processing, and / or providing information associated with the evaluation of ideas and / or comments pertaining to those ideas. For example, evaluation device 42 may include a device, such as a tablet computer (e.g., an iPad, etc.), a mobile phone (e.g., a smart phone, a radiotelephone, etc.), a laptop computer, a handheld computer, a server computer, a gaming device, a wearable communication device (e.g., a smart wristwatch, a pair of smart eyeglasses, etc.), or a similar type of device. In some embodiments, the evaluation device 42 may be communicatively coupled to a sensor, such as a camera, which captures image data depicting an environment around a evaluating user.

[0229] Transaction server 50 includes one or mor devices capable of receiving, generating, storing, processing, and / or providing information associated with a transaction involving compensation for a comment relating to an idea shared via the IPS 12. For example, transaction server 50 may include a server device (e.g., a host server, a web server, an application server, etc.), a data center device, or a similar device.

[0230] A node 124, that is part of a network of nodes 124, may include one or more devices capable of receiving, storing, processing, and / or providing information associated with the exchange of ideas. The node 124 may include any combination of devices described in connection with the user device 16, the evaluation device 42, the transaction server 50, and / or the IPS 12. In some embodiments, one or more of the user device 16, the evaluation device 42, the transaction server 50, and / or the IPS 12 may be nodes on the network of nodes 124. In some embodiments, each node 124, in the network of nodes 124, may have access to the distributed file system 74 and / or to the blockchain 78.

[0231] IPS 12 includes one or more devices capable of receiving, storing, processing, and / or providing information associated with the exchange of ideas. For example, IPS 12 may include a server device (e.g., a host server, a web server, an application server, etc.), a data center device, or a similar device. In some embodiments, the IPS 12 may have access to a database and / or data structure used to sort, organize, and filter one or more types of data described herein. In some embodiments, the database and / or data structure may be local to the IPS 12. In someembodiments, the database and / or data structure may be a third-party storage provider.

[0232] In some embodiments, the IPS 12 may train a data model using machine learning. The data model may be used to make classifications, predictions, and / or recommendations in accordance with the principles of the present disclosure. In some embodiments, the data model may be trained by an external device or server and the trained data model may be provided to or made accessible to the IPS 12.

[0233] In some embodiments, as shown, the IPS 12 may be hosted in the cloud computing environment 270. Notably, while embodiments described herein describe the IPS 12 as being hosted in the cloud computing environment 270, in some embodiments, the IPS 12 may not be cloud-based (i.e., may be implemented outside of a cloud computing environment) or may be partially cloud-based.

[0234] Cloud computing environment 270 includes an environment that hosts IPS 12. Cloud computing environment 270 may provide computation, software, data access, storage, etc. services that do not require end-user knowledge of a physical location and configuration of system(s) and / or device(s) that hosts the IPS 12. As shown, the cloud computing environment 270 may include a group of computing resources 272 (referred to collectively as “computing resources 272” and individually as “computing resource 272”).

[0235] Computing resource 272 includes one or more personal computers, workstation computers, server devices, or another type of computation and / or communication device. In some embodiments, the computing resource 272 may host the IPS 12. The cloud resources may include compute instances executing in the computing resource 272, storage devices provided in the computing resource 272, data transfer devices provided by the computing resource 272, and / or the like. In some embodiments, the computing resource 272 may communicate with other computing resources 272 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0236] As further shown in Fig. 7, computing resource 272 may include a group of cloud resources, such as one or more applications (“APPs”) 272-1, one or more virtual machines (“VMs”) 272-2, virtualized storage (“VSs”) 272-3, one or more hypervisors (“HYPs”) 272-4, and / or the like.

[0237] Application 272-1 may include one or more software applications that may be provided to or accessed by user device 16. Application 272-1 may eliminate a need to install andexecute the software applications on these devices. Tn some embodiments, one application 272-1 may scnd / rcccivc information to / from one or more other applications 272-1, via virtual machine 272-2. In some embodiments, application 272-1 may be an application used to facilitate the exchange of ideas. In some embodiments, application 272-1 may include one or more user interfaces that are accessible by users who have registered accounts with the IPS 12.

[0238] Virtual machine 272-2 may include a software implementation of a machine (e.g., a computer) that executes programs like a physical machine. Virtual machine 272-2 may be either a system virtual machine or a process virtual machine, depending upon use and degree of correspondence to any real machine by virtual machine 272-2. A system virtual machine may provide a complete system platform that supports execution of a complete operating system (“OS”). A process virtual machine may execute a single program and may support a single process. In some embodiments, virtual machine 272-2 may execute on behalf of another device (e.g., user device 16), and may manage infrastructure of the cloud computing environment 270, such as data management, synchronization, or long-duration data transfers.

[0239] Virtualized storage 272-3 may include one or more storage systems and / or one or more devices that use virtualization techniques within the storage systems or devices of the computing resource 272. In some embodiments, within the context of a storage system, types of virtualizations may include block virtualization and file virtualization. Block virtualization may refer to abstraction (or separation) of logical storage from physical storage so that the storage system may be accessed without regard to physical storage or heterogeneous structure. The separation may permit administrators of the storage system flexibility in how the administrators manage storage for end users. File virtualization may eliminate dependencies between data accessed at a file level and a location where files are physically stored. This may enable optimization of storage use, server consolidation, and / or performance of non-disruptive file migrations.

[0240] Hypervisor 272-4 may provide hardware virtualization techniques that allow multiple operating systems (e.g., “guest operating systems”) to execute concurrently on a host computer, such as computing resource 272. Hypervisor 272-4 may present a virtual operating platform to the guest operating systems and may manage the execution of the guest operating systems.

[0241] Network 274 includes one or more wired and / or wireless networks. For example, network 274 may include a cellular network (e.g., a fifth generation (5G) network, a fourthgeneration (4G) network, such as a long-term evolution (LTE) network, a third generation (3G) network, a code division multiple access (CDMA) network, a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber optic-based network, a cloud computing network, or the like, and / or a combination of these or other types of networks.

[0242] The number and arrangement of devices and networks shown in Fig. 7 are provided as an example. In practice, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or differently arranged devices and / or networks than those shown in Fig. 7. Furthermore, two or more devices shown in Fig. 7 may be implemented within a single device, or a single device shown in Fig. 7 may be implemented as multiple, distributed devices. Additionally, or alternatively, a set of devices (e.g., one or more devices) of environment 270 may perform one or more functions described as being performed by another set of devices of environment 270.

[0243] Fig. 8 is a diagram of example components of a device 276. Device 276 may correspond to the user device 16, the evaluation device 42, the transaction server 50, the node 124, and / or the IPS 12. In some embodiments, the user device 16, the evaluation device 42, the transaction server 50, the node 124, and / or the IPS 12 may include one or more devices 268 and / or one or more components of device 276. As shown in Fig. 8, device 276 may include a bus 278, a processor 280, a memory 282, a storage component 284, an input component 286, an output component 288, and / or a communication interface 290.

[0244] Bus 278 includes a component that permits communication among multiple components of device 276. Processor 280 is implemented in hardware, firmware, and / or a combination of hardware and software. Processor 280 includes a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), and / or another type of processing component. In some embodiments, processor 280 includes one or more processors capable of being programmed to perform a function. Memory 282 includes a random-access memory (RAM), a read only memory (ROM), and / or another type of dynamic or static storage device (e.g., a flash memory, a magnetic memory, and / or an optical memory) that stores information and / orinstructions for use by processor 280.

[0245] Storage component 284 stores information and / or software related to the operation and use of device 276. For example, storage component 284 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optic disk, and / or a solid-state disk), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium, along with a corresponding drive.

[0246] Input component 286 includes a component that permits device 276 to receive information, such as via user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and / or a microphone). Additionally, or alternatively, input component 286 may include a sensor for sensing information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and / or an actuator). Output component 288 includes a component that provides output information from device 276 (e.g., a display, a speaker, and / or one or more light-emitting diodes (LEDs)).

[0247] Communication interface 290 includes a transceiver- like component (e.g., a transceiver and / or a separate receiver and transmitter) that enables device 276 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. Communication interface 290 may permit device 276 to receive information from another device and / or provide information to another device. For example, communication interface 290 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, an application programming interface (API), and / or the like.

[0248] Device 276 may perform one or more processes described herein. Device 276 may perform these processes based on processor 280 executing software instructions stored by a non- transitory computer-readable medium, such as memory 282 and / or storage component 284. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0249] Software instructions may be read into memory 282 and / or storage component 284 from another computer-readable medium or from another device via communication interface 290. When executed, software instructions stored in memory 282 and / or storage component 284may cause processor 280 to perform one or more processes described herein. Additionally, or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, embodiments described herein are not limited to any specific combination of hardware circuitry and software.

[0250] The number and arrangement of components shown in Fig. 8 are provided as an example. In practice, device 276 may include additional components, fewer components, different components, or differently arranged components than those shown in Fig. 8. Additionally, or alternatively, a set of components (e.g., one or more components) of device 276 may perform one or more functions described as being performed by another set of components of device 276.

[0251] The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the embodiments to the precise form disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the embodiments.

[0252] Certain user interfaces have been described herein and / or shown in the figures. A user interface may include a graphical user interface, a non-graphical user interface, a text-based user interface, etc. A user interface may provide information for display. In some embodiments, a user may interact with the information, such as by providing input via an input component of a device that provides the user interface for display. In some embodiments, a user interface may be configurable by a device and / or a user (e.g., a user may change the size of the user interface, information provided via the user interface, a position of information provided via the user interface, etc.). Additionally, or alternatively, a user interface may be pre-configured to a standard configuration, a specific configuration based on a type of device on which the user interface is displayed, and / or a set of configurations based on capabilities and / or specifications associated with a device on which the user interface is displayed.

[0253] It will be apparent that systems and / or methods, described herein, may be implemented in different forms of hardware, firmware, and / or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not limiting of the embodiments. Thus, the operation and behavior of the systems and / or methods were described herein without reference to specific software code - it being understood that software and hardware can be used to implement the systems and / ormethods based on the description herein.

[0254] No clement, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more.” Furthermore, as used herein, the term “set” is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, etc.), and may be used interchangeably with “one or more.” Where only one item is intended, the phrase “only one” or similar’ language is used. Also, as used herein, the terms “has,” “have,” “having,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise.

[0255] Appendix I provides a description of one or more embodiments that are described according to the principles of the present disclosure.

Claims

WHAT IS CLAIMED IS:

1. A method, comprising: receiving, by a server device, a request from a first registered account of a user to post an idea on a platform designed to manage an exchange of ideas and idea compensation packages, the platform supported by the server device, the request including idea data describing the idea and reward offer data describing one or more idea sharing rewards packages (TSRPs) being offered in exchange for comments determined to add value to the idea; causing, by the server device, the idea data and the reward offer data to be posted in a manner that is accessible to a group of registered accounts via the platform; receiving, by the server device, a request to post a comment that relates to the idea, the request being made by a second user associated with a second registered account, the request including comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted; causing, by the server device, the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform; receiving, by the server device, comment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP, of the ISRPs; generating, by the server device, cryptographic hashes of the idea data, the comment data, and the comment evaluation data; storing, by the server device, the cryptographic hashes as blocks in a blockchain such that blockchain provides a time-stamped, immutable record of the idea and time- stamped, immutable records of interactions that users have with the platform that involve the idea; orchestrating, by the server device, delivery of compensation for the second user in the manner that complies with the terms of the ISRP; and notifying, by the server device, the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

2. The method of claim 1, further comprising: generating a smart contract that defines compensation rules for the ISRP; and wherein orchestrating the delivery of the compensation for the second user comprises:executing the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP arc satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user.

3. The method of claim 2, further comprising: generating a cryptographic hash of the smart contract; storing the cryptographic hash as a block on the blockchain; generating a cryptographic hash of a transaction which approves the compensation of the second user; and storing the cryptographic hash of the transaction as another block on the blockchain.

4. The method of claim 1, wherein the user is an authorized user that has a biometric identification profile that includes data identifying a set of baseline facial features; and wherein the method further comprises: processing image data depicting an area around a user device of the authorized user to identify facial features for one or more faces found in the image data; determining whether the facial features for the one or more faces include a set of facial features that match the baseline facial features of the authorized user; determining whether the facial features for the one or more faces include a set of additional facial features of one or more unauthorized users; and in response to the set of facial features matching the set of baseline facial features and excluding the set of additional facial features of the one or more unauthorized users, permitting access to a user interface of the platform, or in response to the set of facial features not matching the set of baseline facial features or including the additional facial features of the one or more unauthorized users, blurring the user interface of the platform as it is shown on the user device to prevent unauthorized access.

5. The method of claim 1, wherein the user is an authorized user that has a biometric identification profile that includes data identifying a set of baseline facial features; and wherein the method further comprises:receiving image data depicting an area around a user device associated with the authorized user, where the user device provides the image data to the server device based on determining that one or more system parameters fail to satisfy one or more corresponding system performance thresholds; processing the image data to identify facial features for one or more faces found in the image data; determining whether the facial features include a set of facial features that match the baseline facial features of the authorized user; determining whether the facial features for the one or more faces include a set of additional facial features of one or more unauthorized users; and in response to the set of facial features matching the set of baseline facial features and excluding the additional facial features of one or more unauthorized users, permitting access to the user device for a user interface of the platform, or in response to the set of facial features not matching the set of baseline facial features or including the additional facial features of the one or more unauthorized users, blurring the user interface of the platform as it is shown on the user device to prevent unauthorized access.

6. The method of claim 1, wherein a vector database stores idea embeddings for a collection of ideas shared over the platform; and wherein the method further comprises: generating idea embeddings for the idea by using a data model trained using machine learning to process the idea data; identifying one or more previously posted ideas that are similar to the idea provided by the user by performing a similarity analysis that compares the idea embeddings for the idea and the idea embeddings for the collection of ideas shared over the platform; providing idea data for the one or more previously posted ideas to a user device associated with the user; receiving, from the user device, an instruction to post the idea as a comment to a previously posted idea of the one or more previously posted ideas; providing the user device with reward offer data for the previously posted idea; receiving, from the user device, reward acceptance data for the previously posted idea; andwherein causing the idea data to be posted comprises: causing the idea data to be posted as comment data relating to the previously posted idea.

7. The method of claim 1, wherein a graph data structure stores the idea as a first version of the idea using a first set of nodes and edges; and wherein the method further comprises: receiving another request from the first registered account of the user to post a modified idea that includes at least one change relative to the idea; determining a degree of semantic similarity between the idea data and modified idea data for the modified idea; and updating the graph data structure to store the modified idea data as a second version of the idea using a second set of nodes and edges, wherein a position in which the second set of nodes and edges are placed in the graph data structure is based on the degree of semantic similarity between the idea data and the modified idea data.

8. The method of claim 7, further comprising: receiving a request to merge the modified idea and the original idea into a merged idea that represents a third version of the idea; identifying one or more conflicts by analyzing the idea data and the modified idea data using machine learning; resolving the one or more conflicts using an automated or semi- automated conflict resolution technique; and updating the graph data structure to include a third set of nodes and edges for the merged idea.

9. A device, comprising: one or more memories; and one or more processors, operatively coupled to the one or more memories, to: receive a request from a first registered account of a user to post an idea on a platform designed to manage an exchange of ideas and idea compensation packages, the platform supported by the server device, the request including idea data describing theidea and reward offer data describing one or more idea sharing rewards packages (ISRPs) being offered in exchange for comments determined to add value to the idea; cause the idea data and the reward offer data to be posted in a manner that is accessible to a group of registered accounts via the platform; receive a second request from the first registered account to post a modified idea that includes at least one change relative to the idea; receive a request to post a comment that relates to the idea, the request being made by a second user associated with a second registered account, the request including comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted; cause the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform; receive comment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP, of the ISRPs; associate different versions of the idea by using a graph data structure that includes a set of nodes and edges for each respective version of the idea, wherein the comment data and the comment evaluation data is linked to a particular version of the different versions; orchestrate delivery of compensation for the second user in the manner that complies with the terms of the ISRP; and notify the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

10. The device of claim 9, wherein the one or more processors are further to: generate cryptographic hashes of the idea data, modified idea data for the modified idea, the comment data, and the comment evaluation data; and store the cryptographic hashes as blocks in a blockchain such that blockchain provides time-stamped, immutable, versioned records of the idea and time-stamped, immutable records of interactions that users have with the platform that involve the idea.11 . The device of claim 9, wherein the one or more processors are further to: generate a smart contract that defines compensation rules for the ISRP; and wherein the one or more processors, when orchestrating the delivery of the compensation for the second user, are to: execute the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP are satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user.

12. The device of claim 9, wherein the one or more processors, when associating the different versions of the idea, are to: generate a first set of nodes and edges for the idea, wherein one or more nodes, of the first set of nodes, represent paragraphs of content describing the idea; and generate a second set of nodes and edges for the modified idea, wherein one or more nodes, of the second set of nodes, represent paragraphs of content describing the modified idea, wherein a position of the second set of nodes and edges in the graph data structure is selected based on classifying one or more changes between the idea data and the modified idea data.

13. The device of claim 12, wherein the one or more processors are further to: generate a cryptographic hash of each paragraph of content describing the idea and each paragraph of content describing the modified idea; and store each respective cryptographic hash as a block in a blockchain to establish an immutable record of versioned pieces of paragraph-specific content.

14. The device of claim 9, wherein a vector database stores idea embeddings for a collection of ideas shared over the platform; and wherein the one or more processors are further to: generate idea embeddings for the idea by using a data model trained using machine learning to process the idea data; identify one or more previously posted ideas that are similar to the idea provided by the user by performing a similarity analysis that compares the idea embeddings for the idea and the idea embeddings for the collection of ideas shared over the platform;provide idea data for the one or more previously posted ideas to a user device associated with the user; receive, from the user device, an instruction to post the idea as a comment to a previously posted idea of the one or more previously posted ideas; provide the user device with reward offer data for the previously posted idea; receive, from the user device, reward acceptance data for the previously posted idea; and wherein the one or more processors, when causing the idea data to be posted, are to: cause the idea data to be posted as comment data relating to the previously posted idea.

15. A non-transitory, computer-readable medium storing instructions, the instructions comprising; one or more instructions that, when executed by one or more processors, cause the one or more processors to receive image data depicting an area around a user device of a user who has a first registered account with a platform designed to manage an exchange of ideas and idea compensation packages; process the image data to identify facial features for one or more faces found in the image data; determine whether the facial features for the one or more faces match baseline facial features of the user; permit or deny access to a user interface of the platform based on whether the facial features for the one or more faces match the baseline facial features of the user; in response to permitting access to the user interface, receive a request from a first registered account of the user to post an idea on the platform, the request including idea data describing the idea and reward offer data describing one or more idea sharing rewards packages (ISRPs) being offered in exchange for comments determined to add value to the idea; cause the idea data and the reward offer data to be posted in a manner that is accessible to a group of registered accounts via the platform;receive a request to post a comment that relates to the idea, the request being made by a second user associated with a second registered account, the request including comment data describing the comment and reward acceptance data indicating that terms of the one or more ISRPs have been accepted; cause the comment data to be posted such that the comment data is accessible to the group of registered accounts via the platform; receive comment evaluation data indicating that the second registered account that posted the comment is to be compensated in a manner compliant with the terms of an ISRP, of the ISRPs; orchestrate delivery of compensation for the second user in the manner that complies with the terms of the ISRP; and notify the second registered account that compensation for the comment has been made in the manner that complies with the ISRP.

16. The non-transitory, computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: associate different versions of the idea by using a graph data structure that includes a set of nodes and edges for each respective version of the idea, wherein the comment data and the comment evaluation data is linked to a particular’ version of the different versions.

17. The non-transitory, computer-readable medium of claim 16, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: generate a cryptographic hash of each paragraph of content included in each respective version of the idea; and store each respective cryptographic hash as a block in a blockchain to establish an immutable record of versioned pieces of paragraph-specific content included in each respective version of the idea.

18. The non-transitory, computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: generate a smart contract that defines compensation rules for the ISRP; and wherein the one or more instructions, that cause the one or more processors to orchestrate the delivery of the compensation for the second user, cause the one or more processors to: execute the smart contract in response to an event trigger to cause the smart contract to determine that the compensation rules for the ISRP are satisfied and to cause the compensation for the comment to be delivered to an electronic wallet of the second user.

19. The non-transitory, computer-readable medium of claim 15, wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: generate a graph data structure that includes a set of nodes to associate the idea data, the comment data, and the comment evaluation data, wherein respective nodes, in the set of nodes, represent versioned pieces of content described in in the idea data, the comment data, or the comment evaluation data.

20. The non-transitory, computer-readable medium of claim 15, wherein a graph data structure stores the idea as a first version of the idea using a first set of nodes and edges; and wherein the one or more instructions, when executed by the one or more processors, further cause the one or more processors to: receive another request from the first registered account of the user to post a modified idea that includes at least one change relative to the idea; determine a degree of semantic similarity between the idea data and modified idea data for the modified idea; and update the graph data structure to store the modified idea data as a second version of the idea using a second set of nodes and edges, wherein a position in which the second set of nodes and edges are placed in the graph data structure is based on the degree of semantic similarity between the idea data and the modified idea data.

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