114 results about "Multiple context" patented technology

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 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.

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.

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 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.

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.

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.

Implementations of the disclosure provide a video decoding apparatus and method for transform coefficient sign prediction on a video decoder side. The method may include receiving a bitstream including a sequence of sign signaling bits for a set of candidate transform coefficients. The method may further include generating a set of predicted signs for the set of candidate transform coefficients associated with a transform block of a video frame from a video. The method may also include decoding the sequence of sign signaling bits based on one or more contexts used to entropy-encode the sequence of sign signaling bits to obtain an indication of correctness of the predicted signs of the respective candidate transform coefficients. The method may additionally include estimating original signs for the set of candidate transform coefficients based on the set of predicted signs and the decoded sequence of sign signaling bits.

Conventional Question and Answer (QA) datasets are created for generating factoid questions only and the present disclosure generates longform technical QA dataset from textbooks. Initially, the system receives a technical textbook document and extracts a plurality of contexts. Further, a first plurality of questions are generated based on the plurality of contexts. A plurality of answerable questions are generated further based on the plurality of contexts using an unsupervised template-based matching technique. Further, a combined plurality of questions are generated by combining the first plurality of questions and the plurality of answerable questions. Further, an answer for the combined plurality of questions are generated using an autoregressive language model and a mapping score is computed. Further, a plurality of optimal answers are selected based on the corresponding mapping score. Finally, a longform technical question and answer dataset is generated based on the combined plurality of questions and optimal answers.

The image decoding method includes determining a context for use in a current block to be processed, from among a plurality of contexts, wherein in the determining: the context is determined under a condition that control parameters of a left block and an upper block are used, when the signal type is a first type; and the context is determined under a third condition that the control parameter of the upper block is not used and a hierarchical depth of a data unit to which the control parameter of the current block belongs is used, when the signal type is a third type, and the third type is one or more of (i) “merge_flag”, (ii) “ref_idx_l0” or “ref_idx_l1”, (iii) “inter_pred_flag”, (iv) “mvd_l0” or “mvd_l1”, (v) “intra_chroma_pred_mode”, (vi) “cbf_luma”, and (vii) “cbf_cb” or “cbf_cr”.

A method that includes at least one 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.

A station (STA) may transmit an intent to roam to one or more neighboring APs to a current AP associated with the STA. In an embodiment, a context transfer may be performed to transfer contexts from a current AP to a target AP, where the context transfer may reduce a time that may be needed for a link to reach an optimal performance level upon the STA roaming to a target AP. A context transfer may include an exchange of relevant information between APs, including between a current AP and a target AP, such that the target AP is aware of one or more parameters of one or more contexts when the STA roams to the target AP.

The present disclosure is directed to systems and methods that include and / or leverage one or more machine-learned language models that generate intermediate textual analysis (e.g., including usage of structural tools such as APIs) in service of contextual text generation. For example, a computing system can obtain a contextual text string that includes one or more contextual text tokens. The computing system can process the contextual text string with the machine-learned language model to generate one or more intermediate text strings that include one or more intermediate text tokens. The computing system can process the one or more intermediate text strings with the machine-learned language model to generate an output text string comprising one or more output text tokens. The one or more intermediate text strings can include textual analysis of the contextual text string that supports the output text string.

In an example, a method includes storing a plurality of access control rules in different rows of a static random-access memory (SRAM); storing a plurality of context entries in different rows of the SRAM; receiving a request for an access control rule, of the plurality of access control rules, for a memory location from a first context; searching one or more access control rules, of the plurality of access control rules, for the first context; responsive to finding the access control rule for the memory location, returning the access control rule to the first context; and responsive to not finding the access control rule for the memory location, returning a null notification to the first context.

A display apparatus includes a display; a memory containing data associated with the display and computer instructions; and one or more processors configured to execute the computer instructions to cause the display apparatus to: receive a command for setting a sound mode that is currently used as a target sound mode; display a sound setting menu on the display, and display a name of the target sound mode, one or more context menus corresponding to the target sound mode; and in response to at least one context menu of the one or more context menus being a non-default context menu: display a prompt identifier for the non-default context menu that refers to a context menu with a current sound effect parameter that is a non-default value; and display a reset option that is configured to set a current sound effect parameter in the non-default context menu to a default value.

This invention discloses a context-aware adaptive tourism audio narrative method and system, relating to the field of interactive entertainment technology, including the following steps: collecting multi-dimensional context data through a multi-dimensional perception module; calculating team aggregation degree, average team movement speed, and environmental status based on the multi-dimensional context data; constructing a preset script through a dynamic plot engine module, processing multi-dimensional context data, and making dynamic plot decisions; generating and broadcasting adaptive audio through an adaptive mixing module; and achieving real-time adaptive linkage between plot content and real-world scenes through deep integration of multi-dimensional environmental perception, dynamic plot decisions, and intelligent mixing technology. It can automatically select and broadcast matching narrative branches based on multiple context data such as weather, crowd flow, and team status. Simultaneously, through spatial audio rendering and intelligent fusion of ambient sound, it breaks down the auditory boundaries between the plot and reality, significantly enhancing tourists' immersion and emotional resonance.

Context rules, machine learning, and user interface in context-based search techniques are described. In an implementation, inputs are received via a user interface describing a plurality of contexts associated with user consumption of digital content. A plurality of context rules are generated based on the inputs and a plurality of rule search results are generated based on context data. The context data details the plurality of contexts associated with user consumption of the digital content. One or more machine learning models are trained based on the context data. A determination is made that a transition point has been reached, and in response, a transition is performed between use of the plurality of context rules and use of the one or more machine-learning models in generating a plurality of subsequent search results.

The invention provides a video page rendering method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a viewport position and a current action of a user in a process that the user browses a page, and dynamically requesting image resources according to an acquisition result; according to the action of the user on the video content, three-level cache processing is carried out, and the cache used by the browser is reasonably distributed; furthermore, the hardware and software configuration of the equipment is detected, for the equipment with lower configuration, the image to be rendered is split into a plurality of smaller image blocks and then is distributed to a plurality of WebGL contexts for asynchronous rendering in the background, and the main thread is not blocked while the rendering performance is greatly optimized. In addition, the WebGL textures are managed by adopting a strong reference mechanism and a weak reference mechanism, so that a large number of unused WebGL textures can be effectively prevented from being accumulated in the background, thereby avoiding memory leakage and excessive memory occupation, and ensuring stability and high efficiency when the user browses the video page for a long time.

The present disclosure is directed to systems and methods that include and / or leverage one or more machine-learned language models that generate intermediate textual analysis (e.g., including usage of structural tools such as APIs) in service of contextual text generation. For example, a computing system can obtain a contextual text string that includes one or more contextual text tokens. The computing system can process the contextual text string with the machine-learned language model to generate one or more intermediate text strings that include one or more intermediate text tokens. The computing system can process the one or more intermediate text strings with the machine-learned language model to generate an output text string comprising one or more output text tokens. The one or more intermediate text strings can include textual analysis of the contextual text string that supports the output text string.

This specification discloses a fragmented intelligent agent system and its processing method based on multi-model tentacle-like collaboration. The intelligent agent system, by setting a control central module, decomposes the original task context into multiple context fragments, and distributes these fragments to multiple isolated real-time model modules for processing, ensuring that no single real-time model module can obtain the complete task context during processing. The system further uses a fragment reconstruction module to verify and reconstruct the consistency of the processing results from multiple real-time model modules, thereby generating the final decision result. This specification also provides a detailed description of the intelligent agent system's structural composition, context fragmentation method, multi-model collaboration mechanism, processing result reconstruction process, and compatible operating modes, aiming to improve security, reliability, and scalability while ensuring processing power.

This invention discloses a method and system for optimizing draft model inference for long-context speculative decoding, belonging to the field of electronic information technology. The method includes: dividing the historical context into multiple context units according to a predetermined strategy; evaluating the relevance of the context units to select the most relevant subset of contexts for the current generation step; adapting rotational position encoding to the tree-like draft tokens generated by the draft model, and simultaneously maintaining the position encoding state during sliding window pruning and rollback; jointly constraining attention reachability relationships, outputting results and scores, and generating a candidate token sequence; submitting the candidate token sequence to the target model for verification, and performing a consistent rollback of the generation state, context cache state, and position encoding state of the failed verification token sequences. This invention optimizes the inference process of the draft model by introducing a rollbackable sliding window mechanism and a relevance-based context retrieval mechanism.

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.

A context navigation and action user experience framework that facilitates workflows across multiple contexts and object hierarchy levels is disclosed. Exemplary features include a switcher interface, an action toolbar with context buttons and context tabs, and a toolkit that provides an overview portal to view alerts, cross-reference information, and perform actions on objects and insights important to the user across an entire product suite.

A computer implemented method of using a large language model (LLM) in a Source-to-Pay platform. The method comprises receiving a user query associated with context data; estimating a number of tokens associated with the context data and dividing the context data into a plurality of context data parts each having an estimated number of tokens below a maximum number of tokens per transaction associated with the LLM; determining a user intent from the user query and selecting one or more of a plurality of predetermined processing workflows based on the user intent; processing the context data parts according to said workflow to generate one or more LLM prompts each comprising a respective context data part; forwarding the one or more LLM prompts to the LLM and receiving a respective response; and using at least some content from the one or more responses to generate an answer to the user query.