4247 results about "Identicon" patented technology

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.

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.

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 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.

The invention relates to the technical field of UI design, can be applied to business scenes such as financial science and technology and medical health, and discloses a page layout method based on display material driving, which comprises the following steps: obtaining page display materials and storing the materials in a material resource library, selecting target display materials and generating a page frame, inserting display blocks of preset elements in the page frame, and displaying the preset elements in the display blocks. Generating visual preview data based on layout parameters of the page frame, outputting the visual preview data to an interface rendering processing module, performing association coding on coordinate mapping data of the page frame and a content identifier of the display block to generate a structured storage file, analyzing terminal feature parameters in the access request, generating an access identifier, and displaying the access identifier to the interface rendering processing module. And generating a target display interface according to the access identifier. According to the method and the device, the association relationship between the display material and the coordinate mapping data and the content identifier is established, and the layout metadata and the rendering parameters are extracted in combination with the terminal features to complete interface generation, so that the adaptation accuracy of structured expression of page configuration and interface output is realized.

The invention discloses a lightweight incremental question answering system based on graph structure index and double-layer retrieval. Comprises: a graph-based incremental index module for segmenting an input document into text blocks, extracting entities and relationships through a large language model (LLM), and constructing a dynamic knowledge graph; the double-level retrieval module is used for mapping user query into a graph structure, adopting a double-strategy retrieval mechanism associated with local keyword matching and global theme and combining graph vectors for collaborative query; and the path constraint sub-graph generation module is used for generating an identifier sub-graph based on an n-hop reasoning path on the basis of the retrieved content, and performing deep semantic extension and answer generation. During work, through the modular and progressive collaborative design, the system realizes full-process optimization from data acquisition to knowledge representation and from query response to deep reasoning.

The invention provides a communication method and device, and the method can be suitable for IOT or A-IOT scenes exemplarily. In the method, a tag device receives a first paging message sent by a reader-writer, the first paging message comprising first indication information indicating a first access opportunity; based on the first access opportunity, sending a first D2R message including a first identifier to the reader-writer, the first identifier being an identifier randomly generated by the first Internet of Things device; a first R2D message sent by the reader-writer is received, the first R2D message comprises a temporary identifier allocated to the first Internet of Things device, the temporary identifier comprises a second identifier and further comprises an identifier of the first paging message and / or an identifier of the first access opportunity, and the second identifier comprises all or part of identifiers in the first identifier. According to the method, the probability of conflict of the temporary identifiers allocated to the tag equipment by the reader-writer can be reduced, so that the network access success rate and the communication reliability of the equipment are improved.

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for decentralized data control and access management. For example, a data owner may perform a subscription procedure to obtain verification credentials and an index (e.g., address, identifier) to public data control and access information. The data owner may perform a registration procedure to register ownership of data using the public data control and access information. The public data control and access information may include a public key. The public key is paired with a private trapdoor key to form a key pair. The data owner and a data consumer may perform an access procedure to grant access to registered data. For example, the registration procedure may verify collisions between a token hash, a data hash, and a data owner hash based on use of the key pair.

A system for extracting a number of data elements from one or more unstructured data sources. The system may separate the text from the tables in a document, such that only the table data may be sent to the large language model (LLM), when the LLM only needs to review the table data. The system generates chunks from the document. The system associates unique identifiers with each chunk to provide traceability. The system identifies relevant chunks from the documents and includes the relevant chunks with a request to extract the data elements in a prompt to the LLM. The system also includes a request for the LLM to report the chunks used during extraction of the data elements. The reported chunks are stored with the extracted data for verification, auditing, and error control.

An embodiment includes receiving, from a device, at an authentication service, a dynamic user identifier having a one-time password in an authentication message constructed to carry the dynamic user identifier in place of a pre-determined user identifier of a user. The embodiment locates in a profiles database, using a customized search query with a code based on the dynamic user identifier, a user profile. The embodiment receives at the authentication service, a secondary identification data of the user including a biometric information of the user. The embodiment validates the biometric information using the user profile and enables, when the validating is successful, the device to perform an operation. The enabling is not based on the authentication service validating an entirely static user identifier and is not based on the authentication service validating a manually typed password.

The invention discloses a high-precision instrument assembly fault backtracking method and system, belongs to the field of precision manufacturing, and aims to solve the problems that in a traditional backtracking method, assembly data are scattered and unreliable, fault root positioning is fuzzy, and new scene adaptation depends on a large amount of data. The method comprises the following steps: collecting assembly structured data, video images and environment data in a multi-source manner, filtering out low-quality images, and distributing unique identifiers for products; fusing the multi-modal data to generate a depth feature matrix; constructing an anomaly detection model to output a risk score and a label; hashing the data and then storing the data into a product exclusive private block chain; when a fault occurs, extracting data on the chain through a unique identifier, reconstructing an assembly process by using a graph neural network, and comparing a standard positioning root; and based on the fault report incremental training model, parameters are optimized in combination with meta-reinforcement learning. According to the method, the data authenticity is guaranteed, the fault backtracking precision and efficiency are improved, a new scene is quickly adapted, the production rework rate is reduced, and the stable assembly quality is maintained.

HyperText Markup Language (HTML) content analysis (HCA) using machine learning is described. A feature vector schema may be generated based on domain names corresponding to HTML webpages and corresponding indications of a status of the HTML webpage. The schema may map each position in a feature vector of a given HTML webpage to a resource identifier. Information may be processed using the schema to generate respective feature vectors. The feature vectors may be used to train a model to generate risk indicators for HTML webpages. A potentially parked domain webpage or a potentially malicious domain webpage may be received. A feature vector for the webpage may be generated and inputted to the model. The model may generate a risk indicator for the webpage. The risk indicator may be output and may cause responsive actions. The model may be updated based on a determination indicating whether the webpage was a parked domain webpage or a malicious domain webpage.

Data platforms described herein are configured to monitor a compute environment and facilitate interactive analysis of multifaceted security threats within the compute environment. Such a data platform may determine that one or more assets within the compute environment are possibly being targeted by a multifaceted security threat and present an interactive user interface. The user interface may be configured to display an identifier indicative of the multifaceted security threat, a set of selectable evidence items each associated with a different facet of the multifaceted security threat and assessed based on the monitoring of the compute environment, and a presentation pane for displaying information. As such, the data platform may detect a selection of a particular evidence item from the set of selectable evidence items and, in response to the selection, populate the presentation pane with information related to the particular evidence item. Corresponding methods, systems, and products are also disclosed.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intelligent document processing method, device, equipment and medium, comprising: receiving a document processing request and generating a task identifier, creating and sending a document processing task, constructing an intermediate document structure and generating a plurality of subtasks, and processing the sub-tasks, writing states and page contents into a cache, regularly querying task states, updating accessible identifiers, responding to an access request, loading the page contents, and integrating pages to generate a complete document after all the sub-tasks are completed. According to the method, the document generation task is divided into a plurality of sub-tasks which can be independently processed, and page-level asynchronous loading is realized in combination with a state cache and a regular query mechanism, so that the response speed and the system processing efficiency are remarkably improved while the generation accuracy is ensured; the problems that in the prior art, document generation delay is high, loading is slow, and user waiting time is long are effectively solved.

A user of an identity management system may configure a software agent with a set of parameters within one or more user interfaces of an agent management service. The set of parameters may include an identifier of an application programming interface (API) endpoint of a first service that the software agent is authorized to query and one or more permissions associated with queries to the API endpoint by the software agent. Further, the user may receive an authentication token for the software agent from the agent management service. The software agent may use the authentication token for accessing resources of the service via the API endpoint in accordance with the one or more permissions. Thus, the user may configure the first software agent with the authentication token to enable the software agent to perform the queries to the API endpoint of the first service.

An example method includes receiving an identifier associated with a security deficiency, wherein the security deficiency is associated with a computer system; determining, based on the identifier, text data associated with the identifier; determining a text prompt, wherein the text prompt comprises an instruction segment and the text data, and wherein the instruction segment identifies a remediation strategy detection task and an output constraint; providing the text prompt to a generative machine learning model; receiving, from the generative machine learning model, a set of outputs including a first output identifying a first remediation strategy and a second output identifying a second remediation strategy; determining that the first output satisfies the output constraint; determining that the second output fails to satisfy the output constraint; determining, based on the first output, a final output; and providing the final output using an output interface.

An illustrative storage management system is configured to provide persistent data storage to workloads managed by a container orchestration platform deployed in a cluster of nodes. The storage management system is configured to receive a request comprising identifiers indicative of a plurality of layers associated with a virtual machine to be run in the cluster, generate, based on the request, a virtual machine disk image comprising the plurality of layers, the virtual machine disk image configured to be used to run the virtual machine in the cluster, and provide the virtual machine disk image in response to the request. In some implementations, the virtual machine disk image is used by a virtual machine handler associated with the container orchestration platform to run the virtual machine in a virtual machine type pod that is managed by the container orchestration platform.

A method of automatic pre-prompt generation includes receiving at least one user preference from a user device, modifying a system prompt for a machine-learning language model based on the received at least one user preference to generate a modified system prompt, providing the modified system prompt as an initial input to the machine-learning language model, receiving a natural-language text prompt provided by the user to a chat application on the user device, receiving a user identifier from the user device, querying a first database with the user identifier to retrieve first information, generating a representation of the first information and the natural-language prompt, querying a second database using the representation to retrieve second information, and generating a modified text prompt based on the natural-language prompt, the first information, and the second information.

The embodiment of the invention provides a bill collaborative management method and system based on multi-source heterogeneous data fusion, and belongs to the technical field of data processing. The method comprises the following steps: performing hash calculation according to standardized bill data to obtain a unique identifier; and obtaining a map node corresponding to the standardized bill data to obtain a target map node. The path from the map root node to the target map node is a target structure path. And obtaining a complete behavior sequence of the standardized bill data according to the unique identifier and the behavior log. And constructing a behavior structure joint sequence according to the target structure path and the complete behavior sequence. And inputting the behavior structure joint sequence into the structure perception embedding model to obtain a sequence embedding vector. And obtaining a structure behavior inconsistency score and an abnormal type label according to the structure behavior consistency evaluation function, the behavior structure joint sequence and the sequence embedding vector. And generating a suggestion text according to the structure behavior inconsistency score and the abnormal type label, and displaying the suggestion text. Accurate identification of abnormal bills is realized.

Various embodiments described herein relate to systems, methods, and non-transitory computer-readable media structured to perform server-to-device secure data exchange using a device access token. In an embodiment, a smart device receives, from a requestor entity provided to the smart device, an account data provisioning request for an account. Based on the account data provisioning request, an account identifier for the account is determined. In some arrangements, the account identifier comprises or is associated with a device access token. Based on the device access token, a data element associated with the account is determined. In some embodiments, the data element is accessible to the requestor entity only if it is not access-restricted based on the device access token. Based on the data element, an executable graphic rendering instruction is generated. The executable graphic rendering instruction is executed, which includes generating and displaying, on a user interface of the smart device, a dynamic account status indicator relating to the account.

Systems and processes are disclosed for a multidimensional, cross-node, hashchain, network-based Meta-Content Enabler (MCE) providing real time anomaly detection and impact analysis. Unique hexadecimal sequence identifiers are generated based on real time indexing and categorization to create a golden virtual metadata copy used by AI engine to determine content score to identify the degree of deviation therefrom, and to identify the hexadecimal nodes in the hashchain. The identified discrepancy is verified across cross-node hashchains to give end to end parallel impact analysis on the anomaly. By leveraging real-time monitoring, multidimensional verification, and blockchain-based storage, the system provides a robust and efficient solution for ensuring the accuracy and integrity of user activities. The system integrates privacy-preserving techniques, such as differential privacy or secure multi-party computation, to protect sensitive metadata. These techniques enable the system to analyze and process the metadata while preserving the privacy of individual users.

An end-to-end rendering system enforces policy-constrained, symbolic presentation of artificial-intelligence (AI) outputs prior to any pixel emission. An AI accelerator emits inference tokens as (token identifier, confidence, domain tag) tuples into an output FIFO. A graphics processor with a command processor and SIMD co-processor executes a policy engine that runs a deterministic finite automaton (DFA) stored in non-transitory memory. The DFA consumes the tuples and produces, before any frame-buffer writes, a permit / deny decision and a visibility mask that constrain presentation attributes. A glyph selector maps permitted tuples to entries in a constrained glyph dictionary specifying a glyph identifier, semantic class, and allowed substitutions. A provenance tagger computes a cryptographic hash over at least the glyph identifier, a DFA-state policy identifier, a session nonce, and a checksum of the tuples to create an evidence capsule bound to the glyph. A device-aware renderer, consulting a device profile registry and a rendering grammar, emits a renderable asset for the glyph only when permitted by the visibility mask and grammar. A justification ledger records, for each displayed glyph, the evidence capsule and a monotonic timestamp. Executed entirely within the graphics processor, the pipeline prevents unauthorized tokens from entering the display path, enables cryptographically verifiable traceability of visible content, and reduces bandwidth by representing outputs as glyph identifiers rather than text or raster imagery, while allowing runtime policy updates without modifying the underlying inference model.

Systems and methods disclosed herein are enabled to dynamically generate structured documents using one or more artificial intelligence models. A computing device receives an output generation request and uses a first AI model to retrieve data chunks from source documents and applicable templates. A second AI model ranks the retrieved chunks based on one or more metrics, such as vector similarity, keyword density, and temporal relevance. A third AI model subsequently generates a response using the ranked chunks, templates, and predefined operational boundaries for each chunk. The generated response is tagged with source identifiers to enable the traceability of the response back to corresponding chunks. The system transmits, via the computing device, the response, the retrieved chunks, and / or the source identifiers.

The present disclosure provides techniques and solutions for automatically correcting software tests. When a test failure is detected, it is determined whether a screenshot or code associated with a second version of a software artifact includes a user interface element that has a semantically equivalent identifier to a user interface element in a screenshot or code associated with a first version of the software artifact. Identifying a semantically equivalent identifier can include determining a section of the user interface, in the screenshot of the code, of the first version of the software artifact where the user interface is located and searching the corresponding section of the user interface of the second version of the software artifact. A definition of the software test can be updated to reference the semantically equivalent user interface element.

The invention discloses a vehicle knowledge question-answering method based on a GraphRAG method and computer equipment, and the method comprises the steps: building a document tree structure based on the title hierarchy of a vehicle knowledge document, distributing a text identifier, and adding metadata information; converting the stored text units into text unit vectors by adopting a vector embedding model, and establishing a text vector index; calculating a similarity score between the query vector and the text unit vector, and determining a traditional RAG path text unit based on the similarity score; identifying entities and entity relationships of the text units according to the entity types and the relationship types by adopting a large language model so as to generate a vehicle knowledge graph; performing multi-level community division on the vehicle knowledge graph by adopting a Leiton community detection algorithm, and generating a structured community abstract according to each level of community; determining a GraphRAG path community abstract by adopting a large language model; and fusing the community abstract of the GraphRAG path with the text unit of the traditional RAG path and generating an answer.

Systems and methods are provided for managing AI (Artificial Intelligence) agents interactions with electronic communications that are displayed at an electronic communications interface, such as an email interface. The systems parse electronic communications to determine whether they correspond to new or existing requests and actions to be performed when responding to the request(s). The systems also generate notifications identifying the set of actions with visual identifiers that visually distinguish the set of actions based on whether they have been completed or not and whether they need authorization to be completed. The systems also display selectable controls for controlling how the AI agent performs the actions.

An apparatus and system for privacy protection for Ambient Internet-of-Things (A-IoT) devices are disclosed. A-IoT devices transmit obfuscated identifiers (OIDs) instead of actual identifiers, which are de-obfuscated by the network to retrieve the original identifiers. The device identifiers are obfuscated using shared secret parameters and periodically updated configurations. Hash-based lightweight privacy mechanisms, temporary identifiers (TempIDs), and pseudonym generation may be used to ensure secure communication and prevent replay attacks.

The invention relates to the technical field of artificial intelligence, in particular to an AI digital human-based customer service method and system, and the method comprises the steps: receiving a voice stream, a visual stream and auxiliary sensor data inputted by a user, achieving the time-space alignment of multi-modal data through a cross-modal feature synchronization engine, and fusing the multi-modal data into a unified fusion data packet; based on the fused data packet, extracting an emotion intensity value and an emotion type code in real time, generating a dynamic emotion label, and extracting service demand characteristics to generate a demand vector; inputting the dynamic emotion label and the demand vector into a strategy decision tree, and generating a strategy identifier containing an emotion pacifying coefficient and a response emergency degree; the AI digital human is driven to generate the multi-modal response based on the strategy identifier, deep perception and flexible response to the user state can be achieved, the interaction naturalness and the user satisfaction of a digital human service system are effectively improved, and the method is suitable for multiple intelligent service scenes such as online customer service and intelligent terminal assistants.