4331 results about "Store instruction" patented technology

A computing system may include non-transitory computer-readable media storing instructions that when executed by the one or more computer processors, causes the computing system to perform operations comprising: causing presentation of a graphical user interface, the graphical user interface being associated with patient health data, wherein the graphical user interface is configured to: display one or more user interface elements, receive information identifying a logging action and at least one classification associated with the logging action, generate, by the processor, one or more models based on the received information, based on the generated one or more models, automatically associate the one or more user interface elements with one or more logging actions and update the graphical user interface with at least a portion of the one or more user interface elements.

Systems and methods for generating a workflow data structure are provided. The system includes one or more processors; and one or more transitory or non-transitory computer-readable media storing instructions that are executable to cause the one or more processors to perform operations, the operations comprising: receiving input data comprising a corpus of documents, a user query, and query context data; processing the corpus of documents to generate training data; training a large language model (LLM) using the training data; classifying, using the LLM, the user query to at least one content cluster of a plurality of content clusters based on the query context data; constructing, using the LLM, a workflow data structure as a function of the classifying; and generating, using the LLM, a query response as a function of the user query, the query context data, and the workflow data structure.

A non-transitory, processor-readable medium storing instructions that when executed by a processor, cause the processor to receive data artifacts, encode the artifacts to a standard data type, and compute, for each artifact, a hash function. The hash functions and encoded documents are stored in a first database. The processor is caused to tokenize the encoded artifacts, to produce tokens associated with natural-language identifiers extracted from the encoded artifacts. The processor is caused to transform, using an embedding model, the tokens to produce vectors that are stored in a second database and classified based on categories. The second database is configured to be queried to perform a semantic search in response to receiving a request from a user operating a user compute device. The processor is caused to retrieve, from the semantic search, a subset of vectors from the second database to be displayed on the user compute device.

An apparatus includes at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: determine information related to a usability of at least one image with an artificial intelligence model; and signal the information related to the usability of the at least one image with an artificial intelligence model.

A computer system may have one or computers and one or more data storage devices storing instructions, which when executed by the one or more computers implements a characterization manager, comprising: a test data database storing a plurality of test data sets; the characterization manager configured for selecting one or more test data sets from the test data database and apply the selected test data sets to a Generative AI system to derive from the Generative AI system an output; an output analyzer for processing the output to generate characterization data describing one or more facets of the output.

To simulate a 3D image of a subsurface below a surface, the system having a memory device for storing an instruction, a processor in communication with the memory device configured to execute the instruction, and a subsurface image capture module in communication with the processor, the subsurface image capture module having one or more wave generating device and one or more sensor affixed to a vehicle to capture a series of digital image datasets of the subsurface with a coordinate reference data, wherein the processor executes an instruction to generate a digital model of the series of digital image datasets of the subsurface while maintaining the coordinate reference data, wherein the processor executes an instruction to determine a depth map of the digital model, and wherein the processor executes an instruction to identify a key subject point in the digital model, where subsurface includes an internal biology, below ground, underwater.

A computing device is provided comprising a processor and a memory storing instructions executable by the processor. The instructions are executable by the processor to monitor location information for a plurality of aircraft in a geographic region. Geospatial data is received for the geographic region. The geospatial data comprises, for each of one or more physical objects in the geographic region, a virtual representation of the physical object. The instructions are further executable to determine that the location information meets a threshold difference compared to expected location information for a selected virtual representation of a physical object. An indication of an anomaly is output based at least on the determination that the location information meets the threshold difference.

Single-stage frameworks for open-vocabulary panoptic segmentation are provided. One aspect provides a computing system comprising a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive an image; extract a plurality of feature maps from the image using a convolutional neural network-based vision-language model; generate a plurality of pixel features from the plurality of feature maps; generate a plurality of mask predictions from the plurality of pixel features; generate a plurality of in-vocabulary class predictions corresponding to the plurality of mask predictions using the plurality of pixel features; generate a plurality of out-of-vocabulary class predictions using the plurality of feature maps; perform geometric ensembling on the plurality of in-vocabulary class predictions and the plurality of out-of-vocabulary class predictions to generate a plurality of final class predictions; and output the plurality of mask predictions and the plurality of final class predictions.

A computer platform for generating a video includes one or more memories to store instructions and one or more processors to execute the instructions to perform operations, the operations including: receiving a query from a user relating to a location; in response to receiving the query, generating conditioning parameters based at least in part on the query, wherein the conditioning parameters provide values for one or more conditions associated with a scene to be rendered at the location; generating, using a generative machine-learned model, the video, wherein the video depicts the scene at the location and with the values for the one or more conditions; and providing the video for presentation to the user.

According to an embodiment, it is a system comprising, a communication module, and a processor; wherein the processor storing instructions in a non-transitory memory that, when executed, cause the processor to receive, a first message by a host vehicle via the communication module from a source, wherein the first message comprises information on an erratic vehicle, wherein the information comprises one or more of a license plate number, a make and model, a color, a first contact zone, a location of the erratic vehicle, and a direction of travel of the erratic vehicle; and transmit a second message, via the communication module, to alert a second vehicle, wherein the second message comprises a part of the first message, a second contact zone, and an evasive action for the second vehicle.

A system and method for optimizing automated textual prompts in artificial intelligence (AI) conversational systems is disclosed. The system comprises a network interface, processors, and memory-storing instructions for performing operations to optimize prompts. These operations include receiving and preprocessing input data, tokenizing the data, verifying data authenticity, performing temporal analysis, calculating prompt complexity scores, and selectively expanding or refining prompts based on complexity thresholds. The system further incorporates context-aware optimization, multi-faceted prompt refinement, variation generation, and evaluation using machine learning models. Additional features include a technological hub with advanced processing capabilities, sensor-augmented input apparatus, device-specific prompt optimization, AI model selection, multimodal context integration, and an AI-driven creativity booster. The system provides interactive prompt visualization, certification, and uniqueness verification modules. This comprehensive approach ensures the generation of optimized, contextually relevant, and creative prompts for various AI applications while maintaining data integrity and user engagement.

A model predictive maintenance (MPM) system for building equipment includes one or more processing circuits including one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining one or more performance indicators for the building equipment and determining whether a trigger condition has been satisfied based on the one or more performance indicators. The operations include triggering a model predictive maintenance process to generate a maintenance schedule for the building equipment in response to determining that the trigger condition has been satisfied. The operations include initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

A computer-readable storage medium stores instructions for execution by one or more processors of a UE to configure the UE for simultaneous connection with a 5G NR network and at least a second network, and to cause the UE to perform operations. The operations include encoding UE capability information for transmission to a base station. The UE capability information indicates the UE supports MUSIM operations. First RRC signaling received from the base station includes a plurality of MUSIM configurations to configure the UE for the MUSIM operations. Interference between at least one of the plurality of MUSIM configurations and operation of the UE on the at least second network is detected. Second RRC signaling is transmitted, which indicates a temporary UE capability restriction based on the interference.

A system for predicting system component failures within a computer system that comprises a plurality of hardware components and a plurality of software components. The system may comprise memory storing instructions that, when executed, cause a processor to: obtain performance metrics by monitoring a network interface of the computer system; generate component failure probabilities by processing the performance metrics; determine that a first component failure probability among the component failure probabilities exceeds a risk threshold; determine remedial actions that mitigate a first component failure probability; and mitigate the first component failure probability by initiating an execution of the remedial actions.

Systems and methods for determining neural network brittleness are disclosed. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving a modeling request comprising a preliminary model and a dataset. The operations may include determining a preliminary brittleness score of the preliminary model. The operations may include identifying a reference model and determining a reference brittleness score of the reference model. The operations may include comparing the preliminary brittleness score to the reference brittleness score and generating a preferred model based on the comparison. The operations may include providing the preferred model.

A building system of a building, the building system including one or more memory devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to update a building condition of an HVAC system of a space in a building at a time t1, wherein the building condition is updated from a default building condition. The instructions when executed by the one or more processors, cause the one or more processors to update the building condition of the space at a time t2 and receive an occupant response of an occupant from the space. The instructions when executed by the one or more processors, cause the one or more processors to update an artificial intelligence (AI) model based on the occupant response and generate, using the AI model, one or more actions for the HVAC system of a plurality of spaces.

An example network system includes processing circuitry and one or more memories coupled to the processing circuitry. The one or more memories are configured to store instructions which, when executed by the processing circuitry, cause the network system to receive connection data related to an egress connection of an application service of an application. The instructions cause the network system to analyze the connection data to determine that the egress connection is an anomalous connection. The instructions cause the network system to generate a notification indicative of the egress connection being an anomalous connection and send the notification to a computing device.

An intelligent legal document generation and review system and associated methods are disclosed. The system comprises one or more processors coupled to memory storing instructions to provide a user interface for receiving user input, execute a natural language processing subsystem to extract relevant information, access a legal rules database, store document templates, and execute an AI algorithm. The AI algorithm retrieves a relevant template based on user input and extracted information, populates the template to generate a customized legal document, and stores the document. An attorney feedback loop allows attorneys to provide feedback that the AI algorithm learns from to improve document generation. The AI algorithm collaborates with attorneys to revise and finalize documents based on the feedback. The system streamlines document preparation, automates complex tasks, and provides expert guidance to help users adhere to legal requirements across jurisdictions.

The invention relates to a non-transitory computer-readable storage medium storing instructions, that when executed by one or more computers configures the one or more computers to perform the steps of: (a) receive at an input of the one or more computers, unstructured data; (b) output at an interface of the one or more computers, a request to a Generative Al system to associate the unstructured data to a workflow selected among a set of workflows, wherein each workflow in the set of workflows is characterized by a series of stages; (c) receive from the interface as a result of processing by the Generative Al system an identification of the selected workflow.

An electronic gaming system includes a processor and a memory storing instructions, which when executed by the processor, cause the processor to generate an output in response to a player input at a gaming device; evaluate the output to determine an award value; select, based on the award value, a presentation record of an electronic game that includes a base game mode and a feature game mode from a plurality of presentation records stored in the memory, wherein the plurality of presentation records includes: a first presentation record set including presentation records each including a base game mode outcome without a feature; a second presentation record set including presentation records each including a feature of the base game mode; and a third presentation record set including presentation records each including a feature of the feature game mode; and cause display of the selected presentation record on the display device.

A system for assessing the ecological sensitivity and development potential of areas within ecologically sensitive mountain towns, consisting of: a data acquisition module configured to extract various data types, including multi-source geospatial data, environmental data, built environment data, socio-economic data and community participation data, with the extracted data being validated and stored in a database; a central processing unit comprising one or more processors connected to a memory, the processor communicatively connected to the database in which the extracted data is stored, the memory storing instructions that, when executed, configure the processor to implement the following: a data input module configured to receive data corresponding to multiple indicators from different assessment dimensions, including ecology and environment, built environment, economy, heritage and culture, mobility, location, community participation, visual aspects and safety from hazards; an indicator evaluation module configured to evaluate each indicator according to predefined sensitivity categories and assign corresponding sensitivity index values in the range of 0.1 to 1; a dimension weighting module configured to apply dimension-specific weights to calculate weighted scores for each indicator; a development potential calculation module that aggregates the weighted assessments to determine an overall sensitivity assessment and assigns this overall sensitivity assessment to a development potential rating scale; and a visualization module configured to generate visual representations and reports of the assessment results; and an output module having a user interface operatively connected to the visualization module of the central processing unit, the output module configuring the user interface to display the visualized results and the final index value obtained from the central processing unit.

A computing device for generating a customized digital map includes one or more memories to store instructions and one or more processors to execute the instructions to perform operations, the operations including: receiving an input from a user relating to customizing features associated with a location viewable on a digital map; in response to receiving the input, implementing a generative machine-learned model to generate the customized digital map which depicts the location with one or more customized features which are generated via the generative machine-learned model based on the input; and providing the customized digital map for presentation via a display device.

A volumetric content presentation system includes a head-worn display device, which includes one or more processors, and a memory storing instructions that, when executed by the one or more processors, configure the display device to access AR content items that correspond to either real-world objects or virtual objects, mix and match these AR content items, and present volumetric content that includes these mixed and matched AR content items overlaid on a real-world environment to create a new AR scene that a user can experience.

An agricultural system can include an implement including a frame assembly. A basket assembly can be operably coupled with the frame assembly. A basket assembly actuator can be operably coupled with the basket assembly and the frame assembly. The basket assembly actuator can be configured to alter a position of the basket assembly relative to the frame assembly. A computing system can be communicatively coupled to the basket assembly actuator. The computing system can include a processor and associated memory, the memory storing instructions that, when implemented by the processor, configure the computing system to receive a defined soil finish, receive data indicative of a soil profile, determine a soil compaction limit based on the soil profile, and determine a defined basket assembly actuator position based at least partially on the soil compaction limit and the defined soil finish.

The invention provides a write-after-read conflict prediction method, device and equipment, which are applied to the technical field of data processing, and the method comprises the following steps: reading a to-be-transmitted loading instruction; the loading instruction is located in a loading queue of the out-of-order execution processor. Determining an index value of the loading instruction; the index value is used for quickly positioning a conflict record matched with the loading instruction in a historical conflict table of the out-of-order execution processor. The conflict record comprises a first storage instruction corresponding to the loading instruction. And when it is determined that the conflict record corresponding to the index value exists in the historical conflict table, setting the loading instruction to be in a suspended state. And after the execution of the first storage instruction is finished, executing the loading instruction. The problem that the execution efficiency of a processor is affected due to pipeline emptying and pause caused by write conflicts after reading can be solved.

An example system includes: a first large language model; a memory storing instructions and one or more processors operable to execute the instruction to: receive a natural language text string from a client device, where the natural language text string comprises a formal rule expressed in natural language; input the natural language text string and a control string into a large language model (LLM), where the control string is configured to cause the LLM to generate a formal expression representing the formal rule of the natural language text string; output, by the large language model, the formal expression to an output device; and evaluate a consistency of the formal expression using a test input.

The invention provides a processor memory access optimization implementation method and system with multi-channel concurrent instructions, and relates to the technical field of processor integrated circuits, and the method comprises the steps: obtaining a Load instruction and a Store instruction to be executed; distributing a plurality of memory access instructions to each memory access channel which is independently processed in parallel, wherein each memory access channel comprises a Load memory access channel and a Store memory access channel; an independent Load queue and an independent RAW check queue are arranged in the Load memory access channel, and an independent Store queue, an independent STD queue and an independent Store Buffer queue are arranged in the Store memory access channel; the Load instruction is sequentially subjected to an address generation stage, a TLB parallel query stage, an L1Cache access stage, a RAW check and data forward push stage and a data write-back stage in the Load memory access channel; according to the method, address and data separation processing is carried out on a Store instruction, an address part enters a Store queue, a data part enters an STD queue, then merging is carried out, multiple Store operations on the same Cache Line are merged into one-time writing, the merged data are written into a Store Buffer queue, and then the Store Buffer queue submits and caches in a unified mode.

A wearable device, a method, and a non-transitory computer-readable recording medium for displaying content are provided. The wearable device includes: a display, at least one processor, comprising processing circuitry, and a memory storing instructions that, when executed by the at least one processor individually or collectively cause the wearable device to: determine a usage environment of the wearable device displaying content; generate a boundary, based on at least one of a number of contents and the usage environment; and display, through the display, the content placed based on a shape of the boundary; wherein the boundary comprises a virtual space including a specified area surrounding at least a part of a user or the wearable device based on the user wearing the wearable device or the wearable device, in which the content is displayed on a surface of the boundary, and the content including a lock attribute is moved on the surface according to the user's posture.

A computer system and method for answering a natural language question is provided. The system comprises at least one processor and a memory storing instructions which when executed by the processor configure the processor to perform the method. The method comprises receiving a natural language question, generating a SQL query based on the natural language question, generating an explanation regarding a solution to the natural language question as answered by the SQL query, and presenting the solution and the explanation.

Provided are a wearable device, a method, and a storage medium for displaying content. The wearable device comprises: a display; at least one processor including a processing circuit; and a memory storing instructions that are individually or collectively executed by the at least one processor. The at least one processor may be configured to individually or collectively execute the stored instructions and cause the wearable device to determine the usage environment of the wearable device displaying content. The at least one processor is configured to cause the wearable device to generate a boundary on the basis of at least one of the number of pieces of content or the usage environment. The at least one processor is configured to cause the wearable device to display, through the display, content arranged on the basis of the shape of the boundary. The boundary includes an area set in advance on the basis of the user wearing the wearable device or the wearable device, displays the content on the surface of the boundary, and includes a virtual space in which content including a lock attribute is moved on the surface according to the posture of the user.