7625 results about "Identicon" patented technology

Disclosed herein are methods and systems for providing individualized responses and recommendations based on a shared knowledge language. A method of receiving a user query for a personalized response associated with a profile; interpreting the query by executing a machine-learning model; generating a data query corresponding to the user query by executing the machine-learning model, the data query configured for execution in a computer model comprising one or more nodes having an identifier corresponding to a series of nouns and verbs generated in accordance with a schema associated with a shared knowledge language; receiving a first node of the computer model, wherein the first node is associated with the profile and generated based at least in part on an application accessed by the profile; presenting the personalized response, wherein the personalized response comprises an indication of the first node of the computer model.

A method of electronic communication assistance involves receiving a partial electronic communication at an AI assistant computing facility from a first electronic identifier linked to a first user. This communication includes content associated with both the first user and a second user. The method extracts the communication context and encodes the partial communication for processing, creating an encoded version. It retrieves the first user's communication profile from a database using their identifier, containing user attributes, and retrieves the second user's profile similarly. The encoded communication is then processed by a processor to generate a compositional change using at least one of the communication context, the first user communication attribute, or the second user communication attribute. Finally, a revised electronic communication is generated from the partial communication and the compositional change.

Systems and methods for determining attributes in media content. A computing device may be configured to obtain the media content based on a received media content identifier and segment the media content into scenes. The computing device may analyze viewer engagement metrics to identify a scene associated with a viewer engagement score that exceeds a threshold, select video frames from the identified scene, and identify primary objects in the series of images in the scene. The computing device may add a bounding box around the identified primary objects in one or more selected frames and perform text extraction within the bounding box. The computing device may determine object attributes of the identified primary objects, querying a database to identify topics of interest (ToIs) based on the extracted text and the determined object attributes, and performing a responsive action in response to identifying the one or more ToIs.

In an aspect, a computer-implemented method may include: performing word tokenization on identifiers in a first identifier set to obtain a first set of tokens; performing word tokenization on identifiers in a second identifier set to obtain a second set of tokens; obtaining a weighting value for each of a plurality of tokens in the first set of tokens and the second set of tokens based on a frequency of occurrence; for each identifier of a plurality of identifiers in the first identifier set and of a plurality of identifiers in the second identifier set, obtaining embeddings for the identifier based on the embeddings of tokens obtained by performing word tokenization on that identifier and based on the weighting value for such tokens; obtaining similarity metrics. The similarity metrics may be used for rapid query handling to generate user interface screens in real time.

An example operation may include one or more of storing a generative artificial intelligence (GenAI) model configured to create images, displaying a plurality of prompts on a user interface of a software application, receiving an identifier of a goal of the user and attributes of the goal via the plurality of prompts on the user interface, executing the GenAI model on the identifier of the goal of the user and the attributes of the goal to generate a custom image of the goal for the user, and displaying the custom image of the goal via the user interface of the software application.

An example operation may include one or more of receiving a first code base and a second code base from a software repository, wherein each of the first and second code bases comprise source code of a plurality of different software programs, identifying a source code within the first code base that is interdependent with a source code within the second code base based on execution of a generative artificial intelligence (GenAI) model on the first and second code bases, determining a software component to connect the source code within the first code base to the source code within the second code base, and displaying an identifier of the software component via a user interface.

An example operation may include one or more of ingesting profile data from one or more websites via one or more application programming interfaces (APIs) and storing the profile data within a data store, displaying one or more prompts on a user interface of a user profile page within a software application hosted by a host platform, receiving one or more responses to the one or more prompts, determining a goal for a user of the user profile page based on execution of an artificial intelligence (AI) model on the profile data, the one or more prompts, and the one or more responses to the one or more prompts, and displaying an identifier of the goal via the user interface of the user profile page of the software application.

Systems and methods for data streaming with attribute-based access control. A client apparatus in a data streaming system receives a message via a data stream, form a data stream provider. The message has a schema version of the schema associated therewith. The client apparatus processes the message to retrieve a record, the record including a data item and a data tag corresponding to the data item. The client apparatus, with reference to the schema version, determine whether an identifier (e.g., client ID) of with the client apparatus has permission to access the data item associated with the data tag. After detecting that the identifier does not have permission to access data associated with the data tag, the client apparatus masks the data item to produce a masked data record. The client apparatus releases the masked data record for further processing by the client apparatus.

In an aspect, a computer-implemented method may include: performing word tokenization on identifiers in a first identifier set to obtain a first set of tokens; performing word tokenization on identifiers in a second identifier set to obtain a second set of tokens; obtaining a weighting value for each of a plurality of tokens in the first set of tokens and the second set of tokens based on a frequency of occurrence; for each identifier of a plurality of identifiers in the first identifier set and of a plurality of identifiers in the second identifier set, obtaining embeddings for the identifier based on the embeddings of tokens obtained by performing word tokenization on that identifier and based on the weighting value for such tokens; obtaining similarity metrics. The similarity metrics may be used for rapid query handling to generate user interface screens in real time.

An example operation may include one or more of storing user data in a storage device, receiving inputs via prompts displayed on a user interface of a software application, identifying a plurality of goals within the received inputs and generating a plurality of data structures corresponding to the plurality of goals, respectively, executing a generative artificial intelligence (GenAI) model on the plurality of goals and the stored user data to generate a plurality of custom images of the plurality of goals, and displaying a plurality of identifiers of the plurality of data structures corresponding to the plurality of goals on a user interface, and simultaneously display the plurality of custom images next to the plurality goals, respectively.

Systems, methods, and computer-readable media for modeling cyber resilience data using cyber resilience identities and associated metadata are disclosed. A system can include one or more processing circuits configured to receive or identify cyber resilience data, encrypt a portion of the cyber resilience data, and generate a metadata object including metadata of cyber resilience data. The processing circuits can generate a cyber resilience identity including at least a link with the metadata object, a unique identifier (UID), and a performance event dataset. The processing circuits can encapsulate the cyber resilience identity within a control structure restricting one or more updates and redemptions of the metadata object, determine at least one access data structure being compatible with the control structure, and broadcast, using the control structure, the cyber resilience identity to a ledger or distributed ledger.

In one implementation, a computer-implemented method involves receiving a user message corresponding to a query or a statement to AI chatbot, performing preprocessing operations resulting in generation of initial context of the user message by extracting text of the user message, metadata of the user message, and a conversation identifier, obtaining historical context pertaining to the user message from a plurality of storage mechanisms provided in differing formats including a knowledge graph, a vector database comprised of vector embeddings, and a database comprising text summaries of prior conversations between the user and the AI chatbot, generating a prompt for a LLM that instructs the LLM to generate a response to the user message that is based on and consistent with the user message, the initial content, and the historical context, and providing a final response to the user that is corresponds to an LLM-generated response.

A method of automated technical support includes receiving a natural-language prompt from a user and a user identifier corresponding to the user, the natural-language prompt including at least one technical support query, querying a first database with the user identifier to retrieve first information, generating a vector embedding representative of the first information and the natural-language prompt, querying a second database using the vector embedding to retrieve second information, and generating a natural-language response text based on the natural-language prompt, the first information, and the second information. The second database is a vector database comprising a plurality of vectors, each vector of the plurality of vectors representative of a text segment of a plurality of text segments, the second information comprises at least one text segment of the plurality of text segments, and the natural-language response text responsive to the at least one technical support query.

In some aspects, a server determines an input provided to a generative artificial intelligence, parses the input to determine: a type of content to generate, a content description, and creator identifiers. The server embeds the input into a shared language-image space to create an input embedding. The server determines a creator description comprising a creator-based embedding associated with individual creators. The server performs a comparison of the input embedding to the creator-based embedding associated with individual creators to determine a distance measurement of an embedding of individual creators in the input embedding. The server determines creator attributions based on the distance measurement and creates a creator attribution vector to provide compensation to the creators.

Systems, methods, and computer-readable for endpoint integration and mapping are disclosed. A system can include one or more processing circuits configured to identify endpoints and access information. The processing circuits can generate an object package corresponding to the endpoint by initiating the object package based on an identifier corresponding to an endpoint type of which the object package is structured and mapping the access information to an access scheme corresponding to formatted requests to access the endpoints for protection data. The processing circuits can perform an endpoint request by invoking the object package using at least one formatted request and receiving output data with a response to the endpoint request by a DCDSI system. The processing circuits can further update a distributed ledger or data source based on the output data.

Various embodiments of the present disclosure provide access control for data provided by a federated query system based on attributes of a federated query. The techniques include determining a user identifier associated with a federated query, determining a set of access controls for a plurality of third-party data sources based on the user identifier, and generating an execution plan for resolving the federated query via one or more executable tasks with respect to the plurality of third-party data sources. The techniques also include generating, using a first portion of the execution plan, a result set that comprises information aggregated from the plurality of third-party data sources in accordance with the federated query. The techniques also include generating, using a second portion of the execution plan, a user result set that masks a portion of the information for the result set in accordance with the set of access controls.

Various embodiments relate to normalizing raw data by mapping the raw data to a computer-readable tag. A computer-readable tag may be an identifier that at least partially represents a category (e.g., a department) and / or the raw data itself. In response to receiving the raw data, some embodiments perform the mapping by, for example, performing natural language processing (NLP) on each particular department's raw data to associate natural language words in the raw data to its corresponding computer-readable tag and then populating, at a data structure that includes the computer-readable tag, an entry with data (representing the raw data) in a standardized format. In this way, regardless of whether different sets of raw data come from disparate sources that have diverse formats, protocols, or structures relative to each other, the normalized data and standardized form makes the data compatible.

Systems or techniques are provided for facilitating retrieval augmented generative question and answer boosting. In various embodiments, a system can access a plain text question regarding a scientific instrument. In various aspects, the system can generate, via a large language model that references a document-graph repository, a structured or unstructured answer for the plain text question. In various instances, the document-graph repository can comprise a plurality of document-graphs that respectively correspond to a plurality of technical documents. In various cases, for a first document-graph that corresponds to a first technical document, leaf nodes of the first document-graph can represent respective text blocks written in the first technical document, and non-leaf nodes of the first document-graph can respectively represent a document title, one or more section headings, and one or more scientific instrument identifiers written in the first technical document and beneath which the respective text blocks are nested.

A database of text associated with different domains is maintained. Large language models (LLMs) are prepared for use in the different domains by providing the associated text to an instance of an LLM. Thus, using multiple instances of the same pre-trained LLM, domain-specific LLMs are generated. The text provided to the LLM instance may be selected based on an account identifier of the user accessing the LLM, the tenant accessing the LLM, a user selection of a domain, or any suitable combination thereof. A pool of prepared LLM instances may be generated before the access request is received. If a response provided by an LLM instance in a domain to a prompt was rejected by a user and additional information was received during the session to improve the response of the LLM instance, the additional information may be to the text used to prepare future LLM instances for the domain.

Systems and methods for implementing sticky tokens are illustrated. One embodiment includes a machine-readable medium containing bytecode stored within an immutable ledger. The bytecode encodes a review token, comprising a token identifier. The review token comprises a content element, wherein: the content element comprises a text document; and the text document corresponds to a written review. The review token comprises a recipient identifier, wherein the recipient identifier identifies a blockchain address of an intended recipient. The review token comprises access control information, comprising a right to transfer the review token. Execution of the bytecode occurs automatically when the recipient identifier matches a current owner of the review token. Execution of the bytecode renders of the content element. Execution of the bytecode blocks the blockchain address of the intended recipient from possessing the right to transfer.

The invention relates to a network attack tracing method, system and device based on a user portrait, and a medium. The attack tracing method comprises the following steps: collecting interactive behavior data of a user in a Web page; performing compression and serialization processing on the interaction behavior data to generate a structured interaction log file; collecting fingerprint data of the user terminal and performing standardization processing to generate a fingerprint feature vector; based on the structured interaction log file and the fingerprint feature vector, generating a user unique identifier containing a risk level tag; performing clustering analysis on the interaction behavior data according to the unique identifier of the user, identifying an abnormal behavior mode of the abnormal user and marking an attack type; acquiring a public network IP address of an abnormal user, and positioning a geographic position in combination with an IP database; and constructing an attack traceability report based on the user unique identifier of the abnormal user, the abnormal behavior mode, the public network IP address and the geographic position. According to the invention, the user portrait can be accurately constructed, and the network attack behavior can be effectively identified and traced.

The invention relates to the technical field of agent construction, and discloses an agent construction method and system based on agentive workflow, and the method comprises the following steps: defining an agent core function module and distributing a unique identifier, building an inter-module communication protocol standard, and determining a message format and a priority rule; the method comprises the following steps: distributing computing resources for each module, setting an elastic capacity expansion and contraction strategy, generating a module dependency graph and an architecture metadata file, detecting the loss and delay of multi-modal input data, generating compensation characteristics based on historical context, calculating the quality confidence of each modal, and carrying out dynamic weighted fusion. According to the invention, a three-level alignment architecture is provided to realize cross-modal semantic consistency, and the generated content is ensured to accord with real scene logic; a double-layer decision-making mechanism is designed to drive workflow dynamic optimization, and the system agility under a complex task is remarkably enhanced; a privacy-efficiency balanced federated architecture is constructed, and differential content generation is supported while enterprise data sovereignty is protected.

The invention discloses an AI interactive data protection method and system based on a security context protocol. According to the method, a client application sends a user request carrying a session identifier to an application gateway; the gateway queries a required context range and a security processing strategy according to the request type, and transmits a strategy instruction; after the SCS verifies the gateway permission, the context data is retrieved and processed according to the strategy instruction, and a security context data block is generated; the gateway assembles the user input and the security context data block into a final request according to an SCP protocol, and sends the final request to an AI model; the AI model processes the request and returns a response; after receiving the response, the gateway updates the session context and updates the stored context data; and finally, the gateway returns the response of the AI model to the client application to complete interaction. According to the method, the exposure of the sensitive context data in the system can be reduced to the greatest extent while the AI interaction effect is ensured, so that the data security and compliance of the AI application are improved.

Aspects of the present disclosure are directed to group travel between artificial reality (XR) destinations. Currently, users in an artificial reality (XR) experience cannot travel with a group to a specific destination or between destinations (e.g., to and from virtual worlds, levels, applications, etc.). Thus, some implementations assign users within a group in a multiplayer XR experience (e.g., a virtual lobby) a same session identifier. When the users select a destination, some implementations can provide a computing system hosting the destination with the session identifier associated with the users, such that the hosting computing system can ensure that the users travel to the same instance of the destination together. If a user does not already have the destination installed, some implementations can allow the user to acquire access rights to the destination, then travel to the same instance of the destination as the other users.

A system for integrating real-world items into video games is disclosed. The system is configured to generate a digital token that is cryptographically linked to an item identifier of a real-world item and to write the token to a cryptographic ledger, wherein the token corresponds to an in-game benefit in a video game that is unlocked for an owner of the token. The system includes a video game integration system that receives a request from an instance of the video game, wherein the request is indicative of the user and requests eligible digital tokens owned by the user; accesses the account of the user on the blockchain using a public address of the user to verify that the user is the owner of the digital token; and serves the digital token to the instance of a video game that unlocks the in-game benefit in response to receiving the token.

The present disclosure provides a method of managing an interaction with a large language model (LLM). Further, the method may include receiving a prompt data from a user device associated with an organization. Further, the method may include receiving a policy data from an organization device associated with the organization. Further, the policy data may be associated with the organization. Further, the method may include analyzing the prompt data based on the policy data. Further, the method may include generating an output data based on the analyzing. Further, the generating may be based on the LLM. Further, the method may include storing each of the prompt data, the output data, and an identifier associated with one or more of the user device, the organization device, and the organization. Further, the method may include transmitting the output data to the user device.

A data processing system implements and iterative process for dynamically creating a template including receiving a request for a template suggestion for an electronic content item for an application on a client device. The request includes an identifier of the application and textual content from the first electronic content item. The system further implements providing the identifier of the first application and the textual content to a language model to obtain a template suggestion, the language model being trained to analyze the identifier of the application and the textual content and to output the template suggestion, the template suggestion comprising a template identifier and a first subsection identifier identifying a first subsection of the first template predicted to be relevant to the user for creating the electronic content item, sending the template suggestion to the client device, and causing the client device to present the template suggestion in the application.

The invention discloses an embedded system construction method and device, and the method comprises the steps: loading a configuration file which is a. Config file generated based on configuration parameters selected by a user through a visual configuration interface; when the CONFIGCONANAUTOUPDATE flag bit is detected to be in an activated state, the Conan warehouse data center is accessed, the latest compatible version of each Conan software package dependency item is inquired, and a semantic version constraint analysis algorithm is adopted to update a version identifier in the configuration file into the latest compatible version; generating a description file containing a dependency item list based on the updated configuration file, and generating a dependency lock file through a Hash locking mechanism; and importing the pre-compiled binary package into the construction environment, calling the corresponding pre-compiled binary package according to the version information and the Hash check value in the dependency lock file in the firmware compiling process, and executing hierarchical compiling operation.

A large language model (LLM) message generation system and method tor generating a response to a user message. The method includes: obtaining a text document specified by a user; chunking the text document into a plurality of chunks; generating text gloss data for each of the plurality of chunks based on the chunk and a predetermined prompt; storing the text gloss data for each chunk into a vector data store along with an identifier for the chunk and / or tine chunk itself; receiving a user message; querying the vector data store with a vector data store query, wherein the vector data store query is generated based on the user message; obtaining chunk(s) based on querying the vector data store with the vector data store query; generating a language model input based on the one or more identified chunks; and generating a response message based on inputting the language model input.