1050 results about "Data system" patented technology

In embodiments, systems and methods for configuring and deploying artificial intelligence driven transacting agents that are permitted to autonomously execute transactions on behalf of the individual or organization and configuring the transacting agent based on the agent configuration instructions and a set of predefined system prompts. The method further includes granting the transacting agent access to a digital wallet associated with the individual or organization and deploying the transacting agent to a public network, such that the transacting agent executes transactions on behalf of the individual or organization via one or more digital marketplaces using the digital wallet to which the transacting agent was granted access. In some embodiments, the transacting agent is granted access to the digital wallet using a consent token. In some embodiments, the method also includes hyper-personalizing and / or fine-tuning the agent.

A computerized system receives an original prompt that a querying user sends to a Large Language Model (LLM) that is operably connected to organizational data sources of an organization. Instead of executing the original prompt by the LLM, the system obtains user-related organizational context that pertains to characteristics of the querying user, obtains data-related organizational context that pertains to data from which the LLM is expected to obtain information for responding to the original query, and obtains pre-defined organizational policy rules, that indicate which type of users are authorized to access which type of organizational data. Based on the obtained data, the system modifies the original prompt into an adapted prompt. The system sends the adapted prompt, and not the original prompt, to the LLM for processing. The system obtains LLM-generated output from the LLM in response to the adapted prompt, and provides that LLM-generated output to the querying user.

Systems, methods, and computer-readable media provide a context-specific prompt to answer a user query. The systems, methods, and computer-readable media determine a context based on content of a natural language request and / or determine a role of a user who submitted the natural language request. Additionally or alternatively, templates or RAG sources that will be used for prompt generation may include financials domain-specific knowledge or other domain-specific knowledge or insights. Inclusion of this additional information in the prompt enhances the context to promote more accurate results from a large language model. In one embodiment, the prompt templates are created from various RAG sources, such as payables, general ledger, receivables, and asset management, containing structured data and information specific to the financial domain, enterprise, or other domain, which helps craft accurate prompts. A prompt is generated that identifies a subset of available fields and other selected information based on the role or other context. The prompt template may contain domain-specific knowledge uses a relevant domain or enterprise information to drive relevant results, and an executable query is generated by a large language model based on the prompt. The executable query causes data to be retrieved from a database to generate a result, and information is displayed based at least in part on the result.

The invention discloses a financial abnormal event analysis method, electronic equipment, a medium and a product. The method comprises the steps of obtaining at least one financial clue event, and performing structured element extraction and standardization processing on each financial clue event to obtain a standardized event behavior sequence; performing semantic feature and behavior pattern analysis based on the normalized event behavior sequence, performing event reasoning rule recall in combination with a pre-constructed event reasoning library, and determining a recalled rule set; generating an abnormal event analysis execution plan based on at least one inference rule in the rule set; querying original data in the data system according to an inference rule included in the abnormal event analysis execution plan, generating a data view, executing the abnormal event analysis execution plan based on the data view, and generating an inference execution result set and execution path information; and an event reasoning analysis result is generated according to the reasoning execution result set and the execution path information, and the problems of complex abnormal event analysis modeling, low interpretability and the like are solved.

A system and method for querying, processing, and ranking governmental data across heterogeneous databases may include integrating large language models (LLMs) and multi-agent orchestration to enhance accuracy and mitigate bias. The system receives a natural language query, processes the query using an agent orchestration LLM to generate search query instructions, and executes specialized data record processing agents to retrieve data from diverse sources, including relational, vector, and graph databases. A plurality of candidate natural language responses is generated and validated by data verification LLMs based on relevance and accuracy metrics to reduce hallucinations. The system further employs cross-source validation, statistical and linguistic consistency analyses, and weighted scoring to refine responses, which may include textual summaries, tables, or downloadable files presented via a graphical user interface. Accordingly, the approach ensures precise and contextually relevant results, particularly for applications involving sensitive or regulated data such as legislative and governmental records.

The embodiment of the invention provides an automatic driving method, device and system, a model fine adjustment method, device and system and a vehicle, and relates to the field of automatic driving, the method comprises the steps that system prompt information and multi-modal data of an automatic driving task are acquired, and the system prompt information indicates that a reasoning mode is selected according to scene information; processing the multi-modal data and the system prompt information by using a VLA model to obtain current scene information of the automatic driving task and a current reasoning mode corresponding to the current scene information; in a current reasoning mode of the VLA model, processing the multi-modal data to obtain a current processing result; and executing an automatic driving task according to the current processing result. According to the scheme, the problems of insufficient cross-scene reasoning flexibility and low reasoning efficiency of the VLA model can be solved.

Systems and methods are disclosed for real-time anomaly prediction using near real-time data. The invention addresses delays in telemetry data collection from infrastructure components, by collecting metrics and logging this data in real-time. Extracted logged data undergoes initial analysis to identify patterns and anomalies, followed by cleaning to remove noise and errors. Feature engineering enhances the data, creating or modifying features to improve machine learning model performance. The system calculates weighted means of previous data values and computes first and second-order differences to capture immediate changes and trends. These calculations adjust the extrapolated value to accurately reflect current conditions. The adjusted data is integrated into the dataset and validated. The validated data trains and tests a machine learning model, which is then finalized and deployed for real-time anomaly detection. This system ensures accurate and timely anomaly prediction, enabling automated incident response to maintain the reliability and performance of infrastructure components.

An extended Reality (XR) system is provided that enhances user interaction within XR environments. The XR system captures tracking data using one or more sensors, including hand tracking data of a user's hand and pose data of the XR system itself. By continuously capturing this data, the XR system dynamically generates a hand-located user interface that includes interactive virtual objects associated with specific locations on the surface of the user's hand. Additionally, the XR system generates labels for the interactive virtual objects that are dynamically oriented toward the user as the user moves their hands and head when interacting with an XR environment.

The invention discloses a tunnel or mine water gushing space-time prediction method and system coupled with a hydrodynamic numerical model, and the method comprises the steps: outputting multi-source data based on an identified and verified underground water numerical model, complementing the missing of measured data, quantifying the difference between the permeability characteristics of a fault and a normal stratum, and coupling the difference to a data system, and tunnel or mine excavation space data are merged. And constructing an LSTM-isolated forest-K neighbor regression coupling model, and configuring a multifunctional module to realize multi-scene data co-training. The preprocessed multivariate time series data is divided into a training set and a test set, hidden features are extracted through a coupling model, anomaly detection results are fused, a residual error correction model is synchronously trained, and hyper-parameters and weights are adaptively optimized according to multi-engineering prediction error feedback. And based on the trained coupling model, carrying out synchronous water gushing space-time prediction by adopting a window rolling strategy, and outputting prediction data meeting engineering precision in combination with residual correction. And reliable technical support is provided for safety prevention and control of engineering construction.

The invention relates to the technical field of big data systems, and particularly discloses an AI big data driven hierarchical learning condition diagnosis and intervention system, which comprises a data acquisition module, a multi-dimensional learning condition fusion analysis module, an AI hierarchical diagnosis module, a dynamic intervention strategy generation module, an effect tracking module and a system linkage interface, through technical innovation, complete data, accurate diagnosis, precise intervention and smooth cooperation are realized in a K12 learning condition diagnosis and intervention scene, the problem that teachers are difficult to consider individual differences in large-scale teaching can be solved, the defect that high-quality teachers are insufficient in rural schools can be overcome, and a landing technical scheme is provided for K12 personalized teaching.

The invention relates to the technical field of cloud computing, and particularly provides a data cache prefetching method and device, a storage medium and a program product. According to the method, file access characteristics representing file access preferences of a user are obtained based on historical access data of the user, a target file meeting a cache prefetching strategy is determined based on the file access characteristics, and the target file is cached and prefetched. By dynamically analyzing the historical access data of the user, the system can adjust the cache content in real time, actively load the data possibly required by the user and ensure that the high-frequency access data is always available, and the mechanism not only improves the data access speed, but also remarkably reduces the influence caused by network delay.

Systems and methods iteratively train, using training data, a natural language processing (NLP) model to interpret conversational input during a conversation between an agent and a user by predicting key statements to be used in the prediction of a user intent, the training comparing outputs to a target variable during each iteration and adjusting parameters of the NLP model during each iteration to improve predictability of the user intent from the conversational input. Real-time conversational data is transmitted to the NLP model and the trained NLP algorithm derives key statements predicted to indicate intents and predicts one or more user intents based on the data from the conversation. One or more pre-filled forms predicted to effectuate the one or more user intents is generated, the pre-filled forms including generated text derived from information from the data of the conversation, and the form is transmitted to an agent device.

The invention relates to the technical field of low-altitude aircraft chip safety monitoring, and discloses a low-altitude aircraft chip safety monitoring system which comprises a state acquisition module, a risk assessment module, an anomaly detection module, a strategy generation module, an instruction execution module, an effect verification module, a threshold setting module, a data output module, a feedback optimization module and a system regulation module. The state acquisition module analyzes the operation parameters and the environment interference to obtain a state value; the risk assessment module extracts and screens abnormal protection feature combinations; the anomaly detection module combines a sample variation matching feature with an evaluation combination; the strategy generation module maps a feature strategy based on real-time data and sets a rule; the instruction execution module captures feature data and analyzes a trend; the effect verification module adjusts rules according to errors; the threshold setting module determines a monitoring threshold interval; the data output module generates standardized data; the system realizes comprehensive monitoring of the chip state through cooperation of multiple modules, and the operation safety and stability are improved.

A device to process data associated with a surgical event of a surgery may include a processor. The processor may be configured to receive multiple data streams during the surgical event. The processor may be configured to select a primary data stream based on a surgical data interface via which the primary data stream is received. The processor may be configured to select a secondary data stream based on a surgical data interface via which the second data stream is received. The processor may be configured to identify the surgical data interfaces. The processor may be configured to generate situational data associated with the primary data stream based on the secondary data stream. The situational data may indicate a medical decision-making factor of the surgical event. The primary data stream and the situational data may be sent during the surgical event.

The invention relates to the technical field of community management, in particular to a dynamic monitoring analysis method and system for vehicles in an intelligent community, and the method comprises the steps: collecting multi-source data through a sensor, and generating structured sensing data through a lightweight OCR algorithm; calculating the real-time weight of each sensor by using a self-adaptive dynamic weight algorithm according to the structured sensing data in combination with environmental parameters and equipment states, calculating fusion confidence through a feature confidence fusion formula, rejecting unqualified data, and generating high-precision sensing data; constructing a community digital twinning scene, performing anomaly judgment through a dynamic threshold algorithm, positioning a fault through a three-level mechanism, generating a configuration updating instruction, and generating system state data; and inputting the high-precision sensing data, the system state data and the historical vehicle violation records into the game theory model to calculate the vehicle violation probability, and generating a differentiated management strategy according to the vehicle violation probability. According to the scheme, precise management of community vehicles is realized through multi-source fusion and hierarchical association.

Disclosed herein are system, method, and computer program product aspects for semantic search in a model-based prompt builder system. A system generates a search retriever object based on a search index comprising unstructured data. The search retriever object includes metadata specifying one or more details of a vector search operation to be performed on the search index. The system obtains search results by performing the vector search on the search index based on the one or more details of the vector search operation provided by the search retriever object and a search query. The system provides the search results to a prompt generator configured to use a model to generate a reply to a prompt request requiring the search results.

Systems and methods for generating predicted end-to-end cyber-security attack characteristics via bifurcated machine learning-based processing of multi-modal data are disclosed. The system accesses multi-modal data indicating a set of security information related to a computing system. The system then generates a set of extracted characteristics indicating a cyber-security attack on the computing system, via a supervised machine learning model, using the multi-modal data. Using this information, the system generates a revised set of extracted characteristics indicating the cyber-security attack, via an unsupervised machine learning model, using the extracted set of characteristics indicating the cyber-security attack, where the revised set of characteristics includes at least one new characteristic that was not included in the extracted set of characteristics indicating the cyber-security attack on the computing system. The system then generates for display a graphical representation of the revised set of extracted characteristics.

The invention provides a visual form construction method, which comprises the following steps: receiving user form operation data, carrying out business logic calculation, state change control and inter-service coordination operation on the user form operation data based on domain-driven design, and generating domain events, state data and service governance data. Domain events and state data are recorded to an event storage system, a query optimization view is constructed, event logs and query view data are generated, and dual optimization of data persistence and query efficiency is ensured. According to a preset security policy rule, real-time security monitoring is performed on the service governance data, a system health state index and security audit data are generated, and a system-level observability and security protection mechanism is established. And performing interface rendering and synthesis based on the event log, the query view data, the system health state index and the security audit data to generate a user interactive form interface. Through fusion processing of multi-source data, deep integration of interface rendering and security policies is realized.

Systems and methods that enable, in association with a client device, a first wager to be placed on a play of a game displayed by a streaming device in which the first wager to be placed includes an amount of fiat currency and a second wager placed via the streaming device includes an amount of virtual currency. Following a placement of the first wager and responsive to a receipt, from a remote game server associated with a remote gaming platform, of first data associated with the play of the game displayed by the streaming device, the systems and methods determine, based on the received first data associated with the play of the game displayed by the streaming device, second data associated with a result of the first wager, and communicate the second data to the client device.

Systems and techniques for environment mapping are described. In some examples, a system receives image data and depth data captured using at least one sensor. The image data and the depth data both include respective representations of an environment. The system processes the image data using semantic segmentation to identify segments of the environment that represent different types of objects in the environment in the image data. The system combines the depth data with the semantic segmentation to generate a voxel-based three-dimensional map of the environment.

The invention provides a power battery passport management method and device, electronic equipment and a storage medium. A data system covering the whole life cycle of a battery is constructed; obtaining power battery multi-source data reported by suppliers at all levels, binding the power battery multi-source data with a unique identifier of the power battery, and realizing evidence storage and verification through a block chain consensus mechanism; constructing a digital twin engine based on a preset battery electrochemical model and a thermal runaway model, performing working condition prediction on the battery operation state, and generating working condition early warning threshold data; and filling a preset passport template with the multi-source data and the working condition early warning threshold data, generating a power battery electronic passport, and performing versioning maintenance and uplink release. Unified management, credible evidence storage and traceability of power battery full life cycle data are realized, normalization and dynamism of passport generation are improved, prospective early warning of battery operation risks is realized in combination with digital twinborn prediction, and integrity, safety and compliance of the electronic passport are guaranteed.

The invention provides an MES-based defect detection and quality control optimization method and system. Defect prevention and process dynamic adjustment are realized through a full-process data closed loop. The method comprises the following steps: collecting multi-process data, extracting features such as material batches, process parameters and equipment numbers to construct defect tags, cleaning historical data, constructing time window features, performing multi-class defect classification prediction by adopting an LSTM + attention mechanism model, and analyzing feature contribution degrees in combination with an SHAP value. And setting a multi-stage early warning mechanism, triggering equipment pause and maintenance notification based on a yield threshold, performing graded response according to defect severity, dynamically adjusting equipment parameters, and linking process optimization suggestions. And iterating the model and the rule, returning rework data to generate an optimized sample, mining a defect-parameter association rule in combination with an Apriori algorithm, and updating the equipment health degree evaluation model. The problems of hysteresis quality and staticization of traditional quality control are solved, and an intelligent closed-loop system from defect prediction to process optimization is constructed.

Computer implemented methods and systems for testing one or more operational changes in a drill rig includes initiating the one or more operational changes and using, in part, image data of a mechanical mud separation machines (“MMSM”) to detect the impact of the one or more changes. The image data may be processed by a Deep Neural Network to identify objects in the object flow, operational parameters of the MMSM, and wellbore environmental conditions. Additional image data may be selected for additional processing based on the results of the analysis. The results of the test may be used to update the drilling operation or a drilling model.

Performing charge / showback operations in a large-scale data system by scanning multiple data sources to identify data objects for processing as a unitary group with respect to common characteristics that have an impact on finances within the system. Metadata of the identified data objects are stored in a dynamic dataset that defines a single data access unit for the referenced data objects. The system processes a user query regarding cost allocations, cost forecasts, and resource usage of respective groups within an organization. The query initiates a charge-back or show-back operation that allocates costs associated with each respective usage of resources by a department or cost center, and accesses the referenced data objects through the dataset as a single unit based on data content rather than data location in a file directory of the system.

The invention provides a 2.4 GHz wireless remote control method and device based on hardware code matching, and relates to the technical field of wireless remote control. The present invention is applied to control communication between at least one transmitting end and at least one receiving end. The group identifier and the role information are analyzed by reading the hardware address setter to realize rapid networking; generating a session key and establishing a secure session according to the pre-shared root key in a handshake stage; a sending end collects man-machine input data to form a control frame, and the control frame is sent according to a token rotation or time slice distribution mechanism after encryption and message authentication; and the receiving end drives the controlled object and returns feedback data after completing verification and decryption. The system adaptively adjusts communication parameters according to feedback information and a channel state, so that secure, stable and intelligent control of multi-terminal wireless remote control is realized.

Systems and methods for forecasting recurring anomalies in time series data include determining forecast data from historical data of time series data where the forecast data is for a desired future time span; combining the forecast data with the historical data to form a combined time series; determining a normal operating range using the combined time series; detecting anomalies in the forecast data based on the normal operating range; and providing an output including the detected anomalies in the forecast data.

Systems and methods for dynamic error resolution in hybrid quantum-classical computing environments are disclosed. A system can obtain telemetry data corresponding to a processing job. The system can determine that an error resolution technique is to be applied to the quantum portion of the processing job. The system can select, for a quantum portion of the processing job, the error resolution technique from a plurality of error correction techniques and a plurality of error mitigation techniques. The system can update a hierarchical data structure representing the processing job as at least a set of nodes. The hierarchical data structure can be updated to include the error resolution technique in association with a respective node of the hierarchical data structure representing the quantum portion of the processing job.

An XR system using interactive virtual objects having gelatinous attributes is provided. The XR system captures tracking data of a first hand and a second hand of a user. The XR system generates an interactive XR user interface with an interactive virtual object associated with a location on the first hand. The system renders the interactive virtual object using specific attributes and displays it as a component of the interactive XR user interface. The XR system detects a hover event of the user holding a digit of the second hand in proximity to the location on the first hand without touching the location, and in response, renders the interactive virtual object using a second set of attributes and re-displays the interactive virtual object. The XR system applies gelatinous attributes to the interactive virtual object to convey a state of an interactive XR user interface.

One or more systems, devices, computer program products and / or computer-implemented methods of use provided herein relate to identifying training data for quantum machine learning models. A system can comprise a processor that can execute computer executable components stored in memory, wherein the computer executable components can comprise a training component that can employ a training dataset to train a hybrid machine learning model to generate predictions, wherein training the hybrid machine learning model can comprise assigning, via a combination model, respective first weights to a first subset of training data comprised in the training dataset, assigning, via the combination model, respective second weights to a second subset of the training data, training the at least one classical machine learning model based on the first subset of the training data, and training the at least one quantum machine learning model based on the second subset of the training data.

Systems and methods for detecting anomalies in generative outputs are disclosed herein. The system receives a user prompt indicating a request for data over a time period. The system inputs, into a model, the user prompt to cause the model to generate an output based on the user prompt. The system then generates the first tokens based on the output. To generate the second tokens, the system retrieves, based on the user prompt, sources relating to the data requested by the user prompt. The system then generates queries to request, from the sources, the data over the time period and generates the second tokens based on the retrieved data. The system then performs a comparison of the first tokens and the second tokens and accepts or rejects the output of the model based on the comparison.