193 results about "Multiple context" patented technology

An adaptive data system (ADS) for cognitive data processing is disclosed. The ADS includes an adaptive semantic preprocessor, a trigger detector, a temporal batching engine, a symbolic encoder, and a dynamic cognitive transformer engine. The adaptive semantic preprocessor is configured to receive input data from one or more databases and identify cognitive data attributes comprising one or more contextual, semantic, and temporal attributes from the received input data. The trigger detector is configured to identify semantic divergence of the identified cognitive data attributes and provide a standardized data. The temporal batching engine is configured to provide a high-dimensional cognitive data from the standardized data. The symbolic encoder compresses the high-dimensional cognitive data. The dynamic cognitive transformer engine is configured to determine decision making rules, analyze the compressed high-dimensional cognitive data based on the decision making rules and provide recommendations based on an outcome of the analysis to a user.

A method is described. The method comprises: extracting one or more contents related to an organization from one or more data sources based on one or more job role names and one or more contextual inputs; determining, using an artificial intelligence engine, at least one of an organizational structure, one or more roles, one or more responsibilities, one or more hierarchical relationships, one or more access levels, one or more service actions, and one or more departments of the organization from the one or more contents; and generating, using the artificial intelligence engine, one or more job descriptions based on at least one of the organizational structure, the one or more roles, the one or more responsibilities, the one or more hierarchical relationships, the one or more access levels, the one or more service actions, and the one or more departments.

An example operation may include one or more of receiving interaction content from a communication session between a source device and a service provider device of a service provider, identifying a plurality of contextual attributes of the communication session based on execution of at least one large language models (LLMs) on the interaction content, converting the interaction content and the plurality of contextual attributes of the communication session into vectorized data based on execution of an additional LLM, labelling the vectorized data with identifiers of the plurality of contextual attributes, and storing the vectorized data within a vector database.

Aspects of the disclosure are directed to automatic prompt generation based on a meeting discussion. A live transcript of a virtual meeting is obtained while a virtual meeting is being conducted. The live transcript includes current content discussed by participants of the virtual meeting. A determination is made based on the live transcript of whether the current content indicates a request of a participant for an operation to be performed with respect to the virtual meeting. Responsive to a determination that the current content indicates the request of the participant for the operation, one or more of a context or a sentiment associated with the request is identified. A prompt for an artificial intelligence (AI) model is generated based on the request and the one or more of the context or the sentiment. The AI model is trained to perform the operation with respect to the virtual meeting.

Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and / or the like for retrieving a subgraph that is used to generate one or more answer outputs responsive to an input query by: (i) generating one or more context embeddings that are associated with an input query, (ii) identifying one or more candidate node paths and one or more node relations based on a knowledge graph, (iii) identifying, using a predictive machine learning model, one or more context-relationship rankings based on the one or more candidate node paths, the one or more node relations, and the one or more context embeddings, and (iv) generating one or more subgraph data objects based on the one or more context-relationship rankings.

The invention discloses a power industry dynamic knowledge base construction method and system based on a large language model, and relates to the field of electric digital data processing, and the method comprises the steps: receiving a power field document imported by a user, and converting the power field document into an electronic document; calling a large language model to analyze the electronic document, extracting a terminology definition, chart position information and a document logic level in the electronic document, and generating a knowledge unit containing a plurality of contexts; connecting the knowledge units into directed knowledge links, calculating semantic similarity between adjacent knowledge units in the directed knowledge links, and segmenting the directed knowledge links to obtain a plurality of knowledge topics; receiving a knowledge retrieval instruction, and determining a target knowledge theme corresponding to the knowledge retrieval instruction; and extracting a corresponding target knowledge unit in the target knowledge theme, and generating a knowledge retrieval result based on a target context of the target knowledge unit. By implementing the method, knowledge base construction can be optimized, and the integrity of knowledge base data is ensured.

Techniques are described with respect to a system, method, and computer program product for dynamically creating virtual learning environments. An associated method includes analyzing plurality of users associated with a virtual environment; determining a plurality of contextual information based on respective geographic locations of the plurality of users; and adjusting the virtual environment based on the determination; wherein adjusting comprises monitoring a plurality of interactions of the plurality of users with the virtual environment based on the plurality of contextual information.

The invention discloses a context poisoning attack defense method oriented to an RAG application, and relates to the technical field of RAG. the method comprises the following steps: inputting a target query statement, and retrieving the target query statement to obtain multiple pieces of context information; taking representative sentences in the retrieved context information, and identifying and filtering potential malicious template clusters; the big language model gives all candidate answers according to existing context information, the logarithmic probability of all contexts to different candidate answers is calculated, and after the influence of parameter knowledge of the big language model is removed from the logarithmic probability, the support degree of all contexts to different candidate answers is obtained; the whole logarithmic probability vector is used as a support degree distribution condition of the context to the candidate answers; identifying a single piece of harmful information from the support degree distribution condition of the context to the candidate answers through a logistic regression model so as to filter wrong answers; according to the attack defense method provided by the invention, centralized injection of multiple malicious texts and sparse injection of a small number of malicious texts can be defended.

An example method performed by a Wireless Transmit / Receive Unit (WTRU) is described. The method comprises determining context information for execution of an edge-assisted task associated with a machine-type-communications (MTC) application, sending the context information, receiving one or more context-aware parameters and information related to usage of the one or more context-aware parameters, determining a configuration for at least one of an application layer or an upper network (NW) layer based on the received information, and sending a first uplink (UL) transmission using the one or more context-aware parameters for the application layer or the upper NW layer based on the determined configuration. The context information may indicate one or more of performance of the MTC application or performance of the edge-assisted task.

The invention discloses a visual Token compression method and device based on double-path fusion, and the method comprises the steps: obtaining an initial visual Token through employing a visual encoder; obtaining a learnable query vector, and adopting an attention mechanism to enable the learnable query vector to interact with the initial visual Token to obtain a plurality of context Token; analyzing a self-attention map of the initial visual Token in the visual encoder, so as to screen out a plurality of detail Token according to the self-attention map; obtaining a text prompt Token, and calculating a task correlation score of each detail Token by taking the text prompt Token and the plurality of context Token as a query; dynamically filtering or weighting the plurality of details Token according to the task correlation score to obtain a plurality of filtered details Token; the plurality of filtered detail Tokens are spliced with the plurality of context Tokens, so that a compressed visual Token can be obtained; therefore, the key global and local visual information can be intelligently reserved while the high compression ratio is realized and the calculation cost is reduced.

A computer implemented method for managing and remediating security drift in a public cloud network is disclosed. A security drift event may be received at a contextual impact classification engine of a server. An impact tier for the received security drift event may be assigned at the contextual impact classification engine. A queue shaping orchestrator at the server may reorder a queue with entries that include the received security drift event based on the assigned impact tier. A remediation engine of the server may determine a remediation for the received security drift event based on the assigned impact tier, and / or one or more contextual inputs received by the server.

A system and method for managing queries pertaining to a product are provided. The method includes receiving, by a processing unit, a user query from a user device. Further, one or more contexts are identified from a plurality of contexts by comparing the user query with each context among the plurality of contexts. Each of the contexts includes values of one or more attributes characteristic to at least a part of the product. Further, a prompt is generated by updating the user query based on the one or more contexts identified. The prompt is provided as input to a Large Language Model to generate a natural language output, on an output device.

The invention relates to the technical field of industrial document management, in particular to a document management method and system and a computer readable storage medium. The method comprises the following steps: constructing a structure tree according to a plurality of documents and a plurality of entries; according to a preset standard relationship type, establishing an association relationship between the entries; according to user requirements, target operation is executed on the items in the structure tree, and the target operation comprises any one of item reference, item copying and item distribution. The method not only solves the problems of cross-document multiplexing of contents, consistency keeping and circulation and use of entries in a plurality of contexts, but also realizes fine management control of the entry level.

Techniques for generating recommendations using a recommendation model include receiving one or more user inputs, determining one or more context features based on one or more context inputs, determining one or more user features based on the one or more user inputs, determining one or more user embeddings based on the one or more user features, determining one or more context embeddings based on the one or more context features, merging the one or more user embeddings and the one or more context embeddings to generate one or more merged embeddings; and generating recommendations based on the one or more merged embeddings.

The invention discloses a training data quality inspection method and a related device, and relates to the technical field of data processing, and the method comprises the steps: marking instruction data to obtain a label set of the instruction data, the label set comprising labels of multiple granularities, labels of multiple visual angles and labels of at least two marking dimensions in labels associated with multiple contexts; clustering the labels in each label set to obtain a plurality of label clusters, and performing quality evaluation from at least two evaluation dimensions of semantic accuracy, logic consistency, field correlation and user demand matching degree corresponding to each label cluster to obtain a comprehensive quality score based on the at least two evaluation dimensions corresponding to each label cluster; determining a diversity score of the instruction data set according to the distribution uniformity of the plurality of instruction data clusters, the distribution condition of the instruction length and the label distribution condition; the complexity score of the instruction data set is determined at least according to the density of the instruction data cluster and the density of the semantic association matrix, and the accuracy of training data quality inspection is improved.

Methods, systems, and apparatus for generating trajectory predictions for one or more target agents. In one aspect, a system comprises one or more computers configured to obtain scene context data characterizing a scene in an environment at a current time point, where the scene includes multiple agents that include a target agent and one or more context agents, and the scene context data includes respective context data for each of multiple different modalities of context data. The one or more computers then generate an encoded representation of the scene in the environment that includes one or more embeddings and process the encoded representation of the scene context data using a decoder neural network to generate a trajectory prediction output for the target agent that predicts a future trajectory of the target after the current time point.

The embodiment of the invention provides a question and answer query method and device based on a large model. The method comprises the following steps: in response to a question query instruction, determining a to-be-queried question; identifying target multi-tuple information included in the to-be-queried question according to the large language model and the first cue word; wherein the target multi-tuple information indicates information under a plurality of context dimensions; determining to-be-queried multi-tuple information meeting a similarity requirement with the target multi-tuple information from preset multi-tuple information of each data field in a newly-built data layer of the database; generating a problem query statement according to the large language model, the second cue word and the to-be-queried multi-tuple information, and obtaining a statement query result after executing the problem query statement; and according to the large language model and the third cue word, performing readable processing on the statement query result to obtain a problem query result, and outputting the problem query result. The method can enhance the understanding ability of the large model to the database, thereby improving the efficiency and accuracy of intelligent question answering.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing a task. In one aspect, a method comprises: receiving a query for a task to be performed; receiving a plurality of context content items for the task; for each content item of the plurality of content items, processing an input comprising a representation of the content item using a trained compression model to generate a compressed representation of the content item comprising one or more vectors of a fixed size; generating, using the compressed representations, an aggregated compressed representation comprising one or more vectors that represents the plurality of content items; and processing an input comprising (i) the query and (ii) the aggregated compressed representation using a generative neural network to generate a response to the query.

In one example, a method for context-tagging access credentials for physical access control includes receiving, by an access control device associated with a locking device for a controlled area and from a computing device, an access request including one or more access credentials and contextual information indicating one or more activities being performed by a user of the computing device, and determining, by the access control device, whether the contextual information satisfies one or more contextual conditions. The method may further include determining, by the access control device, whether the one or more access credentials are valid, and, responsive to determining that the one or more access credentials are valid and responsive to determining that the contextual information satisfies the one or more contextual conditions, changing, by the access control device, a state of the locking device.

A method comprises determining, based on signals from sensors of hearing instruments, current values of context parameters; determining, based on the current values of the context parameters, that a current context of the hearing instruments has changed or is likely to change from a first to a second context of a plurality of contexts, wherein each of the contexts corresponds to a different unique combination of potential values of the context parameters; updating statistics of the contexts, wherein for each of the contexts, the statistics of the context include statistics with respect to time the hearing instruments spent in the context; and based on the determination that the current context of the hearing instruments has changed or is likely to change from the first context to the second context, initiating, based on the statistics of at least one of the first or second contexts, one or more actions.

A computer system includes circuitry for executing operations, including receiving an input text file comprising metadata, receiving risk enrichment data, and generating an affinitized data set based on the input text file and the risk enrichment data. Generating the affinitized data set includes the operations of determining a context-indicative keyword, determining a synonym of the context-indicative keyword, searching the input text file for the context-indicative keyword or the synonym, identifying the context-indicative keyword or the synonym in the input text file, and generating the affinitized data set, the affinitized data set comprising a risk descriptor determined based on the at least one of the plurality of context-indicative keywords and the metadata.

A system includes an image signal processor (ISP). The ISP is a discrete hardware unit and includes a line buffer, a memory controller, and one or more image processors. The memory controller is configured to assign blocks within the line buffer to a plurality of contexts, and for each of the contexts: receive one or more lines of image data associated with the respective context, and storing the one or more lines of the image data associated with the context in a respective block assigned to the respective context. The one or more image processors of the ISP are configured to process, for each respective context of the plurality of contexts, the one or more lines of the image data stored in the line buffer associated with the respective context.

An encoding device (100) is provided with: a memory (152); and a circuit (151) capable of accessing the memory (152), the circuit (151), during operation, encodes a connection type pertaining to a connection relationship between a surface to be processed and an unprocessed surface by context-based arithmetic encoding for each of a plurality of surfaces constituting a three-dimensional grid, and, during encoding of a current connection type, which is the connection type to be encoded, encodes the current connection type to be encoded by context-based arithmetic encoding for each of the plurality of surfaces constituting the three-dimensional grid. The context to be applied to the arithmetic encoding is selected from a plurality of contexts using a previous connection type that is the connection type encoded prior to the current connection type.

The embodiment of the invention provides a parallel simulation method, system and device of a multi-core processor and a storage medium, the parallel simulation method of the multi-core processor comprises the following steps: creating a context for each of a plurality of cores of the multi-core processor, the plurality of contexts corresponding to the plurality of cores being mutually independent; a system thread is created for each context of the plurality of contexts such that the plurality of cores are allocated in different contexts into different system threads that are automatically scheduled to different processor cores for execution. According to the parallel simulation method of the multi-core processor provided by the embodiment of the invention, the parallel simulation is realized based on a plurality of independent contexts, the problem of low simulation efficiency in a traditional simulation framework is effectively solved, and the execution speed of the simulation is remarkably improved through a multi-thread simulation technology.

Methods and apparatus are provided for unified significance map coding. An apparatus includes a video encoder (400) for encoding transform coefficients for at least a portion of a picture. The transform coefficients are obtained using a plurality of transforms. One or more context sharing maps are generated for the transform coefficients based on a unified rule. The one or more context sharing maps are for providing at least one context that is shared among at least some of the transform coefficients obtained from at least two different ones of the plurality of transforms.

In one aspect, a user's intent can be inferred based on voice analysis during a communications session, and prompts can be presented, or other actions taken, at least partly in response to the inferred intent. For example, a network microphone device (NMD) having one or more microphones can capture voice input and transmit the voice input to remote computing device(s) for a communication session (e.g., a videoconference). The NMD can analyze the voice input to detect one or more utterances. Based on the utterance(s), the NMD can cause a user prompt to be displayed via a display device communicatively coupled to the NMD. The particular prompt can depend at least in part on one or more context parameters associated with the communication session (e.g., a microphone state of one or more users, a screen share state of one or more users, or a recording status of the session, etc.).

A hardware acceleration circuit, comprising a communication interface for connecting to one or more event-driven circuits, a memory, an event handling circuit, and a hardware acceleration engine. The event handling circuit is adapted to detect one or more events triggered by one or more of the event-driven circuits, update one or more pointers pointing to one or more event handling routines stored in the memory and to a context memory segment in the memory storing a plurality of context parameters relating to the one or more events, and transmit the pointer(s) to the hardware acceleration engine. The hardware acceleration engine is adapted to receive the pointer(s) from the event handling circuit, and execute the event handling routine(s) pointed by the pointer(s) to process data relating to the event(s) according to at least some of the context parameters retrieved from the context memory segment using the pointer(s).

System and methods for generating a context-selection interface and executing one or more context-limited operations within a user-defined, context-limited action space are disclosed. A first set of context elements is received and a graphical interface including graphical elements representative of each the first set of context elements is generated. A selection of a first context set including context elements selected from the first set of context elements is received and a first user-defined, context-limited action space defined by the context elements of the first context set is generated. A contextually appropriate artificial intelligence operation is executed based on the first user-defined, context-limited action space and a first hierarchical graphical element representative of the contextually appropriate artificial intelligence operation is generated via the graphical interface. The first hierarchical graphical element is illustrated in a hierarchical arrangement with the graphical elements representative of the first context set.

The present disclosure provides a method and system for dynamically transmitting notification messages to users of a client device. The method comprises, receiving one or more messages to be transmitted to one or more client applications on the client device. The method further comprises monitoring the one or more messages based on one or more user profiles and one or more contextual real-time metrics and determining if the one or more contextual real-time metrics exceeds a pre-defined threshold. In response to determining that the one or more contextual real-time metrics does not exceed the pre-defined threshold, the method comprises, transmitting the one or more messages to the one or more client applications on the client device based on one or more static rules embedded within the one or more messages. In response to determining that the one or more contextual real-time metrics exceeds the pre-defined threshold, the method comprises disabling the one or more static rules to temporality pause transmission of the one or more messages. The method further comprises, updating the one or more static rules for subsequent transmission of the one or messages to the one or more client applications on the client device. A system for dynamically transmitting notification messages to users of a client device is also disclosed.

An example method includes generating, using an interface token encoder, a plurality of interface token encodings respectively for a plurality of interface tokens of an input data sequence corresponding to a query. The example method includes generating, using a contextual tokenizer that processes the plurality of interface token encodings, one or more contextual tokens representing the plurality of interface tokens. The example method includes generating, using a machine-learned sequence processing model that processes the one or more contextual tokens, one or more predicted contextual tokens. The example method includes generating, using a contextual detokenizer that processes the one or more predicted contextual tokens, an output sequence including one or more predicted interface tokens that represent the one or more predicted contextual tokens. The example method includes generating, using an interface detokenizer that processes the output sequence, a response to the query.