5963 results about "Data storing" patented technology

A system is disclosed for continuous and intermittent monitoring of physiological parameters. The system comprises at least one sensor coupled to a wearable device configured to measure physiological parameters of a user; a non-transitory data store storing data collected from the at least one sensor and computer-executable instructions; and a processor in communication with the at least one sensor and the non-transitory data store, wherein the computer-executable instructions, when executed by the processor, configure the processor to: continuously measure the physiological parameters by sampling the at least one sensor at a sampling rate to obtain repeated measurements at series of intervals configured to capture important physiological events; compare measurements of the physiological parameters to a threshold to determine a likelihood of a physiological event; and alert the user when an occurrence of the physiological event is likely.

A nonvolatile memory device includes a plurality of latch groups, an address controller, an encoder, and a buffer. The address controller controls an input address and an output address to indicate one of the plurality of latch groups. The encoder receives sector data from a latch group corresponding to the output address among the plurality of latch groups and also compresses the received sector data. The buffer stores the compressed sector data. Among the plurality of latch groups, the compressed sector data stored in the buffer is overwritten in a latch group corresponding to the input address.

A federated distributed computational system enables secure, privacy-preserving biological data analysis and engineering through interconnected nodes coordinated in a distributed graph architecture. A federation manager allocates resources, manages data flow and lineage, establishes privacy boundaries, and maintains cross-institutional knowledge relationships. Each node contains a processing unit for biological data analysis, privacy preservation protocols for secure multi-party computation, a knowledge graph structure with supporting data stores, and encrypted network connections. The federation manager enforces all computation and data exchange through secure channels while maintaining privacy, security, and contractual boundaries. This architecture enables research institutions to collaborate on complex biological analyses without compromising sensitive data, facilitating breakthrough discoveries through shared computational resources while maintaining strict data privacy and security controls.

The disclosed technology is generally directed to a method for controlling a satellite system comprising at least one satellite. The method may include receiving and processing a set of control parameters associated with an orientation of the at least one satellite via a classic control model to generate a set of actions to control the orientation of the at least one satellite and storing the set of actions as data in a buffer. The processing and storing are iteratively repeated until the data stored in the buffer exceeds a threshold. When the data stored in the buffer exceeds the threshold, the method may further include iteratively implementing, based on each of the set of control parameters and the data stored in the buffer, the machine learning model to control the orientation of the at least one satellite to stabilize the at least one satellite.

Systems and methods include discovering and classifying any of data discovered by inline cloud inspection, data stored across one or more cloud services, and data stored across one or more endpoints; continuously monitoring access to and usage of classified data, wherein the monitoring is performed in real-time and includes analyzing data access patterns, user behaviors, and application interactions; evaluating a security posture of the classified data by identifying misconfigurations, compliance violations, excessive permissions, and vulnerabilities; and enforcing one or more security policies based on the evaluated security posture.

Methods, systems, and devices for programmable metadata and related operations are described. A method may include receiving signaling that indicates a set of rules for transitions of states of metadata at a memory device storing the metadata. The memory device may receive a command from a host device associated with a set of data after receiving the set of rules. The memory device may transition metadata associated with the set of data stored at the memory device from a first state to a second state based in part on the set of rules and the command. The memory device may execute the command received from the host device.

Methods, systems, and devices for programmable metadata and related operations are described. A method may include receiving signaling that indicates a set of rules for transitions of states of metadata at a memory device storing the metadata. The memory device may receive a command from a host device associated with a set of data after receiving the set of rules. The memory device may transition metadata associated with the set of data stored at the memory device from a first state to a second state based in part on the set of rules and the command. The memory device may execute the command received from the host device.

The present disclosure pertains to natural language techniques for querying data stored in feature stores using zero shot learning. In a particular aspect, a computer-implemented method includes receiving a natural language query for retrieving features from a feature store, generating an input prompt by appending a script to the natural language query, and then using a large language model to determine tables or databases from the feature store that are relevant to the natural language query, retrieve metadata for the tables or databases from the feature store, determine feature groups comprising features relevant to the natural language query, and generate a programming language query based on the input prompt, the metadata, and the groups. A list of features within the feature groups that are accessible within the feature store may then be retrieved by executing the programming language query on the feature store.

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 scene rendering, in particular to a building information model scene rendering method and system based on parallel computing, and the method comprises the following steps: based on scene data stored in a building information model, analyzing space coordinates of geometric structure nodes of a building, and associating the geometric structure nodes with material attributes; and analyzing a data partition relationship according to the illumination distribution, and generating a geometric material illumination analysis result. According to the method, deep integration of geometry, materials and illumination is realized by analyzing spatial coordinates of geometric nodes and material attributes and combining illumination partition analysis, the data organization efficiency of a complex scene and the analysis precision of an illumination path are improved, light energy in a noise area is optimized by analyzing light propagation and energy distribution in a segmented manner, refraction and reflection paths are corrected, and the accuracy of the light path analysis is improved. And through texture boundary and scene geometry conjoint analysis, texture fracture is repaired, detail expression is enhanced, efficient analysis and optimization of complex building scene data are realized, and the high-precision rendering requirement is met.

An exemplary machine-learning-based method for generating a response to a natural-language query from an entity associated with an organization comprises: obtaining a sub-query from the natural-language query; determining if a cache associated with the organization stores a matching historical sub-query: if the cache stores the matching historical sub-query, retrieving a historical sub-response associated with the historical sub-query from the cache as a sub-query response; if the cache does not store any matching historical sub-query: inputting the sub-query into a cache-based enhancement machine-learning model to enhance the sub-query, wherein the cache-based enhancement machine-learning model is trained based on historical query data stored in the cache associated with the organization; and inputting the enhanced sub-query into a language model to generate the sub-query response; and generating the response to the natural-language query based on the sub-query response.

The invention discloses a BMC intrusion protection method and device, a BMC and computer equipment. The method is applied to the BMC in the computer equipment. The BMC comprises a service module and a security detection module which are in communication isolation, and storage media accessed by the service module and the security detection module are isolated. The business module is used for providing a management function for parts in the computer equipment, and the security detection module is used for implementing security detection on the BMC. The method comprises the steps that the security detection module obtains data stored in the storage medium associated with the service module, analyzes the security situation of the data sensing service module, and obtains a security detection result. And when the security detection result indicates that the BMC suffers from the APT attack, restarting the BMC in a degraded starting mode. Through a deep defense scheme, namely on the basis of defense, intrusion detection capability is added to the BMC, a dynamic defense chain of defense, detection, degradation and recovery is formed, the APT attack resisting capability of the BMC is improved, and the BMC is ensured to be safe and credible.

The present invention relates to a system (100) and method (300) for automated product validation, identification, and transaction management in shopping environments. The system (100) integrates a smart shopping cart (102) equipped with at least one camera (106), a load cell (108), and a user interface (110). An AI model trained on a dataset of high-resolution, 360° product images generate unique image embeddings for each product. The system performs multimodal validation by comparing the extracted image embeddings, measured weight data, and scanned barcode information with reference data stored in a vector database. Further, discrepancies, such as unscanned products or mismatches, are flagged, and payment is blocked until resolved.

The disclosure relates to systems, methods, and computer-readable media for an artificial intelligence (AI) conversational agent configured for enhanced user interaction in multi-channel contact centers. An example method includes receiving a query regarding a particular property of an asset during a real-time conversation, classifying an intent of the query into a predefined category, triggering, based on the classifying of the intent, a finetuned large language model for the predefined category to answer the query, generating, by the finetuned large language model, a response to the query based on at least one of an information data model and a knowledge graph data store, and outputting the response to the query.

An electronic hardware wallet for conducting cryptocurrency transactions, blockchain transactions, or other secure communications is embodied on a monolithic integrated circuit (IC) die supported on a single substrate. The monolithic semiconductor device can include a non-volatile data store for storing application software executable by the multi-core processor, and the secure element can include a secure data store for storing secret data (e.g., a private key) for use in a secure electronic transaction. In some embodiments, the secure element can include hardware logic embodying a cryptocurrency algorithm associated with executing the secure electronic transaction and can have a limited and selective communication bus between the secure element and the multi-core processor. The electronic hardware wallet can communicatively couple with one or more other devices to facilitate a multi-party computation (MPC) algorithm for authenticating the cryptocurrency algorithm and validating the secure electronic transaction.

Secure access to a database is facilitated by an LLM. A natural language (NL) query is received and passed to an LLM in a prompt along with all or part of a commands for accessing a database without passing the data stored in the database. The prompt may further include instructions to generate one or more commands to access the database to retrieve data responsive to the query. The instructions may instruct the generation of a URL to access relevant data. Data responsive to the command may be embedded in a document presented to a user. The document may be selected by the LLM in response to a second prompt. The command is executed with respect to the database only upon validating access of a user to the data referenced by the command.

The invention relates to a matrix storage operator optimization method and device, computer equipment and a readable storage medium. The method comprises the following steps: allocating memory resources for target data; determining a logic structure corresponding to the source data, establishing a first mapping relation between each logic index in the logic structure and a register address of the source data, and establishing a second mapping relation between each logic index in the logic structure and a memory address of the target data; and determining a corresponding relationship between a memory address of the target data and a register address of the source data based on the first mapping relationship and the second mapping relationship, and storing the source data stored in a register into a memory resource corresponding to the target data based on the corresponding relationship. By adopting the method, the generalization ability of the matrix storage operator can be improved.

An illustrative method for querying multiple datasets may include generating, based on models each associated with and defining attributes of a different datasets stored in a plurality of data stores, a semantic layer defining relationships between the models and that provides a centralized application programming interface (API) for exposing the datasets by way of a common query language, receiving, by way of the centralized API, a query request for information that depends on data included in multiple datasets included in the plurality of datasets, querying, based on the query request and the relationships between the models defined by the semantic layer, the multiple datasets, and presenting, based on the querying, a query result representative of the information that depends on the data included in the multiple datasets.

The invention discloses an SSD (Solid State Disk) cache management method, which relates to the technical field of SSDs, and comprises the following steps: step 1, cache space division: the cache space of the SSD is divided into a plurality of different types of sub-cache regions, and each sub-cache region at least comprises a hot data cache region, a cold data cache region and an intermediate data cache region; 2, data popularity monitoring: monitoring the access frequency of the data stored in the SSD in real time, judging the popularity level of the data according to the access frequency, judging the data with the access frequency higher than a set threshold as hot data, judging the data with the access frequency lower than another set threshold as cold data, and judging the data between the hot data and the cold data as intermediate data; 3, data cache allocation: according to the heat level of the data, storing hot data into a hot data cache region, storing cold data into a cold data cache region, and storing intermediate data into an intermediate data cache region; the cache utilization rate and the read-write performance are comprehensively improved, and the delay is reduced.

A computer-based system and corresponding computer-implemented method process input data queries in a manner enabling advanced functionality for data analytics. The method transforms a query plan tree into a query strategy tree. The query plan tree is constructed from an input data query associated with a computation workload. The method compiles the query strategy tree into dataflow graph(s) (DFG(s)). The method transmits the DFG(s) for execution via a virtual platform. The method monitors execution of the DFG(s). The method outputs, based on a result of the execution monitored, a response to the input data query. The result is received from the virtual platform and represents at least one computational result of processing the computation workload by the virtual platform. The system and method enable rapid and efficient retrieval and analysis of data stored in data lakes and other data storage systems, in response to user queries.

In a method for controlling access to customer data of a multi-tenant software as a service (SaaS) system, a SaaS agent at a user endpoint sends a request for storage credentials to a SaaS agent facing application interface (API) of a SaaS system cloud. The storage credentials provide access to a SaaS encrypted data store of the multi-tenant SaaS system. The SaaS agent receives the storage credentials from the SaaS agent facing API, and the SaaS agent uses the storage credentials to store customer data in the SaaS encrypted data store. A customer-controlled encryption key is maintained on a customer-controlled cloud hosting a key management system (KMS). The customer-controlled cloud is in communication with the SaaS agent facing API.

A Retrieval-Augmented Generation (“RAG”) framework may include an RAG vector data store with information about vector embeddings. An RAG pre-processing platform may access unstructured data and perform vector embedding to generate a vector embedding for unstructured data to be stored in the RAG vector data store. The RAG pre-processing platform may also access structured data from the knowledge base and create a summary and metadata about the structured data to be stored in the RAG vector data store. An RAG retriever platform may receive a user prompt from a user, perform vector embedding, and retrieve context-relevant information for unstructured and structured data by searching for similar embeddings in the RAG vector data store. An RAG reader platform may combine the context-relevant information with the user prompt and an RAG prompt to create a LLM prompt. A context-aware response is then output to the user.

The disclosure is directed to various ways of improving the functioning of computer systems, information networks, data stores, search engine systems and methods, and other advantages. Among other things, provided herein are methods, systems, components, processes, modules, blocks, circuits, sub-systems, articles, and other elements (collectively referred to in some cases as the “platform” or the “system”) that collectively enable, in one or more datastores (e.g., where each datastore may include one or more databases) and systems. A system and method for providing conversation intelligence services may include pre-processing, transcribing, and post-processing. A conversation recording may be pre-processed generating a conversation record (e.g., conversation object). The pre-processed conversation recording may be transcribed into a transcript. The transcript may be post-processed which may include keyword extraction, topic extraction, feature extraction, event generation, trigger action, and / or search indexing. Conversation information may be presented based on the pre-processing, the transcribing, and the post-processing.

A store employee assistance platform is provided that is enabled with generative artificial intelligence to deliver role-specific, context-aware responses to natural language questions submitted by users, including store employees. The platform includes a store employee assistance application with a chat interface through which a user may submit a question. The platform identifies the user's role, store location, and access level, and retrieves relevant enterprise content from a vector database and historical data store. A prompt engine constructs a contextualized prompt incorporating the user's identity and the retrieved information, and submits the prompt to one or more generative AI models. The resulting response is tailored to the user's responsibilities and delivered through the chat interface, providing real-time operational guidance specific to the user's role within the retail environment.

Embodiments are described herein for document authentication certification using information stored on a distributed ledger such as a blockchain. A distributed ledger may securely store document data describing the document. Use of a distributed ledger may provide an immutable, readily auditable record of the history of the document. Each user participating in the system may be assigned a unique identifier to be used for conducting transactions on the distributed ledger network. A user may also be provided with a digital security token such as a cryptographic key that is useable to authenticate the user and enable access to the document data stored on the distributed ledger(s).

Methods and corresponding systems and apparatuses for configuring user access to data stored in and / or accessed through an external computer system are described. Access permissions can be configured through defining a permission set relative to a proxy entity and assigning the permission set to one or more users. A proxy entity is a local representation of an external data entity. A proxy entity can be a virtual entity in that the proxy entity does not contain underlying data. A proxy entity can, however, include metadata describing its corresponding external data entity. A computer system maintaining a proxy entity can store mapping information linking the proxy entity to an external data entity. The mapping information and the permission set can be used to determine an access permission relative to the external data entity and to communicate this access permission to the external computer system so that access can be provided accordingly.

Methods and systems are presented for providing a framework for facilitating electronic transactions by dynamically managing and sharing user data with multiple online platforms. As a user accesses one or more online platforms, a connect system that is integrated with the online platforms interacts with the user and obtain, from the user, user data that is usable for completing transactions between the user and the online platforms. The user data is stored in a user profile associated with the user and linked to an identifier of the user. When the user subsequently accesses an online platform, the connect system authenticates the user based on an identifier associated with the user, and share at least a portion of the user data stored in the user profile with the online platform to facilitate a transaction between the user and the online platform.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

The invention discloses a data reading method and device, computer equipment and a storage medium, and relates to the technical field of flash memories, and the data reading method comprises the following steps: before reading data, firstly obtaining a performance index value of a current flash memory page at a current moment, and firstly carrying out detection operation on the current flash memory page to obtain an error code index value of the current flash memory page; and determining a target risk level according to the performance index value and the error code index value, then obtaining a target pre-charging duration corresponding to the target risk level, and performing a reading operation on the current flash memory page based on the target pre-charging duration to read data stored in the current flash memory page. As the pre-charging duration can influence the accuracy of data reading, the accuracy of reading the data for the first time can be improved by reading the data by adopting the target pre-charging duration corresponding to the target risk level before data reading, so that the number of times of re-reading is reduced, and the waste of resources is reduced.

A robotic fleet resource provisioning system includes a computer-readable storage system storing a fleet resources data store and resource provisioning rules. The fleet resources data store maintains a fleet resource inventory indicating fleet resources, each with features, configuration requirements, and a status. The resource provisioning rules are accessible to an intelligence layer to ensure that provisioned resources comply with the resource provisioning rules. The system receives a request for a robotic fleet to perform a job and determine a job definition data structure. The definition data structure defines a set of tasks that are to be performed in performance of the job. The system determines a robotic fleet configuration data structure corresponding to the job based on the set of tasks and the fleet resource inventory. The system determines a respective provisioning configuration for each respective fleet resource. The system deploys the robotic fleet to perform the job.