377 results about "Client system" patented technology

In one embodiment, a method includes receiving, from a client system associated with a user, a first user request that includes a reference to a target object and one or more of an attribute or a relationship of the target object. Visual data including one or more images portraying the target object may then be accessed, and the reference may be resolved to the target object portrayed in the one or more images. Object information of the target object that corresponds to the referenced attribute or relationship of the first user request may be determined based on a visual analysis of the one or more images. Finally, responsive to receiving the first user request, the object information of the target object may be stored in a multimodal dialog state.

In one embodiment, a method includes receiving a voice input having acoustic features from a first client system associated with a first user, determining emotions associated with the voice input based on one or more of the acoustic features by machine-learning models, determining facial features for a first extended-reality (XR) avatar representing the first user based on the emotions, and sending instructions for rendering the first XR avatar representing the first user to a second client system associated with a second user, wherein the first XR avatar is rendered with the determined facial features.

Systems and methods are provided herein for providing a system to reconfigure a user's access network to provide varying quality of service (QOS) based on flow identification. For example, a policy server (PS) may transmit a plurality of addresses of virtual private network (VPN) servers associated with a priority status to a cable modem (CM) and / or cable modem termination system (CMTS) associated with a client device. The CMTS may notify the PS when the CM and / or CMTS detects VPN traffic between the client device and a VPN server associated with the priority status. In response to the notification, the PS may transmit an update message to the CMTS, wherein the update message comprises an updated configuration. The updated configuration may be used to update the CM and / or CMTS so that the updated CM and / or CMTS process future data packets according to an updated QoS policy.

Described is a system for cloud-based processing of backup data for storage onto various types of object storage systems. A specialized cloud-based component (e.g. proxy server) may act as an intermediary when backing up data from a client system to an object storage. For example, the cloud-based component may be provided as part of backup service that operates in conjunction with a client system. Accordingly, the system may allow different clients of a backup service to efficiently and seamlessly interact with the different third-party object storage providers via a single cloud-based component. To provide such object-storage-agnostic functionality, the cloud-based component may include a function library that includes object-storage-specific functions. For example, the cloud-based component may invoke a specific set of operations that interact with a storage API provided by a particular object storage provider.

Various techniques are disclosed for providing gateway services between a client system and downstream service systems for a service system. The disclosed gateway service system is capable of implementing a new service for a client system in response to a request from the client system. The gateway service system internally determines which downstream services are needed to implement the new service. In various instances, the gateway service system utilizes machine learning algorithms to determine the downstream services suitable for providing the output needed for the new service. The gateway service system is also capable of determining whether an existing application programming interface (API) is able to be used for the new service or whether a new API needs to be created for the new service. By internally determining the downstream services and APIs, the gateway service system has more efficient utilization of its computational resources.

Provided in the present application are a memory pre-loading processing method, and a device and a storage medium. The method comprises: a virtual machine manager collecting a plurality of pieces of historical page fault information that are generated by a target application program in a client; on the basis of a plurality of client virtual addresses that are included in the plurality of pieces of historical page fault information, determining a target client virtual address to be accessed when a page fault occurs in the target application program next time; on the basis of the target client virtual address and a storage address of a target client system page table corresponding to the target application program, determining a target host machine virtual address corresponding to the target client virtual address; and controlling a host machine operating system to allocate a target host machine physical address corresponding to the target host machine virtual address, and loading data, which corresponds to the target host machine virtual address, into the target host machine physical address. By means of loading, into a memory in advance, data corresponding to a target client virtual address in which a page fault may occur in the future, an access delay duration caused by the page fault is shortened.

The invention provides a memory preloading processing method and device and a storage medium, and the method comprises the steps that a virtual machine manager collects a plurality of pieces of historical missing page exception information generated by a target application program in a client, and stores the historical missing page exception information according to a plurality of client virtual addresses contained in the historical missing page exception information; determining a target client virtual address to be accessed when the target application program is subjected to page missing exception next time; determining a target host machine virtual address corresponding to the target client virtual address according to the target client virtual address and a storage address of a target client system page table corresponding to the target application program; and controlling the host machine operating system to distribute a target host machine physical address corresponding to the target host machine virtual address, and loading data corresponding to the target host machine virtual address into the target host machine physical address. And the data corresponding to the target client virtual address which may cause the page missing abnormity in the future is loaded into the memory in advance, so that the access delay duration caused by the page missing abnormity is reduced.

Systems, methods, and computer-readable storage mediums are disclosed that prevent users from exchanging unauthorized content with a remote server via a client application. A system receives media instructions from a client application for rendering a user interface for the remote server on a user's device. Using the media instructions, the system determines permissions for accessing content to be presented in the user interface. Based on the permissions, the system generates modified media instructions and transmits the modified media instructions to a browser of the user device.

A chat robot system for filtering dialogue content. The chat robot system receives a prompt of the user from the client system during the interactive session. The chat robot system filters the user's cues based on a set of platform policies and generates a response based on the filtering of the user's cues and transmits the response to the client system.

A lightweight machine learning model (MLM) microservice is hosted in a cloud computing environment suitable for large-scale data processing. A client system can utilize the MLM service to run a MLM on a dataset in the cloud computing environment. The MLM can be already developed, trained, and tested using any appropriate ML libraries on the client side or the server side. However, no data schema is required to be provided from the client side. Further, neither the MLM nor the dataset needs to be persisted on the server side. When a request to run a MLM is received by the MLM service from a client system, a data schema is inferred from a dataset provided with the MLM. The MLM is run on the dataset utilizing the inferred data schema to generate a prediction which is then returned by the MLM service to the client system.

Methods, apparatuses, systems, computing entities, and / or the like are provided. An example method may include retrieving a base image associated with at least one software application; generating a customized base image based at least in part on conducting at least one operational verification operation on the base image; generating a validated base image based at least in part on conducting at least one operational testing operation on the customized base image; generating a release note data object associated with the validated base image; and performing one or more image release operations by releasing the validated base image and the release note data object to at least one client system.

The present application discloses a method, system, and computer system for processing queries to sparsely populated datasets. The method includes (i) receiving a query from a client system, (ii) determining, based at least in part on the query, a plurality of partitions of a hypercube that are expected to comprise information used in generating a response for the query, (iii) communicating a set of requests to a data source storing the hypercube, the set of requests comprising one or more requests corresponding to the plurality of partitions of the hypercube, (iv) obtaining, from the data source, a set of results to the set of requests, the set of results comprising data stored in the plurality of partitions of the hypercube, (v) determining a plurality of virtual objects for the set of results, (vi) combining the plurality of virtual objects into a response to the query, and (vii) providing, to the client system, the response to the query.

A system, method, and device for domain-level sinkholing of network traffic. The method includes (i) obtaining network traffic, (ii) determining a client system or user associated with the network traffic, (iii) determining a domain for which the client system is attempting to access in connection with the network traffic, (iv) performing a sinkholing of the network traffic and / or traffic handling for automated analysis of vulnerable and / or malicious network traffic using one or more of a name-based virtual hosting or an IP-based virtual hosting.

Systems and methods are disclosed for implementing sensitive data proxy. In certain embodiments, a method may comprise implementing a sensitive data proxy configured to prevent unintended traffic from a client system to a target domain, including receiving a message from the client system intended for the target domain, determining a security rule to apply to the message, evaluating the message for compliance with the security rule, applying a corrective action to the message to bring the message into compliance with the security rule, and forwarding the message to the target domain based on the message being in compliance with the security rule.

A method includes receiving, from a client system, one or more utterances comprising one or more first words in a first language and one or more second words in a second language. The method further includes generating, based on a single bilingual automatic-speech-recognition (ASR) model, a transcription of the one or more utterances, such that the transcription comprises one or more first text strings in the first language and one or more second text strings in the second language. The method further includes executing one or more tasks based on the one or more first text strings in the first language and the one or more second text strings in the second language, and sending, to the client system, instructions for presenting a response responsive to the one or more utterances, such that the response is based on both the first and second languages.

Example methods and systems for blockchain-based licensing as a service are described. In one example, a computer system may receive a first request to obtain a first license associated with a first product from a first client system. In response, the computer system may (a) select a first blockchain from multiple blockchains, and (b) generate and store a first non-fungible token (NFT) on the first blockchain to issue the first license. Further, the computer system may receive a second request to obtain a second license associated with the first product or a second product from a second client system. In response, the computer system may (a) select a second blockchain from multiple blockchains, and (b) generate and store a second NFT on the second blockchain to issue the second license.

Embodiments of systems and methods are provided to trigger migration of a workload from cloud-based resources to local resources, or vice versa. In the disclosed embodiments, an orchestration service receives telemetry data from a client system associated with a user and cloud resource usage data corresponding to the user from a plurality of cloud service providers. Before the end of each cloud computing service billing cycle, the orchestration service: uses the cloud resource usage data and / or the telemetry data to determine a cloud resource usage, which is expected for the user at the end of the cloud computing service billing cycle; generates a trigger to migrate the user's workload from cloud-based resources to local resources, or vice versa, based on the expected cloud resource usage; and initiates migration of the user's workload if a trigger is generated. As such, the orchestration service can be used to effectively manage per-user cloud resource costs.

The present application discloses a method, system, and computer system for providing a dataframe as a service. The method includes (a) receiving, from a client system, one or more hints identifying parameters for source data; (b) executing a plan for a source dataframe including determining whether accessing the source data for the source dataframe is permitted based at least in part on one or more security policies, wherein the plan is based at least in part on the one or more hints; (c) receiving from the client system a business logic pertaining to a transformation to be applied to the source dataframe; and (d) providing to the client system information pertaining to an execution result obtained based at least in part on the business logic.

The invention relates to the technical field of role recognition, and discloses a large model dialogue control method based on role enhancement, which comprises the following steps: step 1, user role information is defined and configured, the user role information comprises internal roles and external roles, the internal roles comprise at least one type of enterprise internal users, and the external roles comprise at least one type of enterprise internal users; the external role comprises at least one type of enterprise external users; step 2, configuring corresponding task background and authority information for each user role, and determining accessible resources and data types according to the user roles; by accurately identifying the role identity of the user, customized dialogue and information services can be provided according to requirements and task backgrounds of different roles. For internal employees and external clients of an enterprise, the system can respectively provide in-depth technical support and basic product information query, and information overload or permission leakage possibly caused by a unified response is avoided.

In one embodiment, a method includes accessing visual signals comprising images portraying textual content in a real-world environment associated with a first user from a client system associated with the first user, recognizing the textual content based on machine-learning models and the visual signals, determining a context associated with the first user with respect to the real-world environment based on the visual signals, executing tasks determined based on the textual content and the determined context for the first user, and sending instructions for presenting execution results of the tasks to the first user to the client system.

Various embodiments of the present invention comprise a supply chain platform configured in connection with an inventory hub, a supplier system, an enterprise data platform, and a customer system to respond to disturbance events within a supply chain. Such a supply chain platform may collect a variety of supply chain data to determine a risk score relating to such disturbance event(s) and one or more mitigation opportunities in response thereto via a mitigation module configured to generate one or more scenarios and assess the same for efficacy and readiness. Such mitigation opportunities may include the use of one or more supplier sites within the supply chain. Such a supply chain platform may be configured to generate a plurality of reports having interactive data visualizations configurable according to key element data and / or parameter input(s) supplied by a user through a user device and may differentiate between important and inconsequential disturbance events.

In one embodiment, a method includes accessing sensory data captured by cameras, identifying people in a field of view of the cameras based on facial recognition of the sensory data, detecting actions of one or more of the people based on the sensory data, generating media files with each being associated with one or more of a recording of at least one of the people or at least one of the determined actions, and sending instructions for presenting one or more of the media files to a client system.

A parallel file system (PFS) comprising a plurality of storage nodes. The PFS receives a request to write data in a file from an application running on a client system. The file is stored in a set of storage nodes. The PFS identifies a target storage node to which data needs to be written in response to the request to write data. The PFS detects that the target storage node is inaccessible. The PFS completes the request to write by writing parity data corresponding to the data being written to one or more other storage nodes. The PFS reconstructs the data of the target storage node when the target storage node is accessible.

In one embodiment, a method includes receiving, from a client system associated with a user, a first user request that includes a reference to a target object and one or more of an attribute or a relationship of the target object. Visual data including one or more images portraying the target object may then be accessed, and the reference may be resolved to the target object portrayed in the one or more images. Object information of the target object that corresponds to the referenced attribute or relationship of the first user request may be determined based on a visual analysis of the one or more images. Finally, responsive to receiving the first user request, the object information of the target object may be stored in a multimodal dialog state.

In one embodiment, a method includes receiving, from a client system, a user query inputted on the client system, wherein the user query corresponds to a plurality of dialog-intents, executing a plurality of tasks corresponding to the plurality of dialog-intents, generating a multi-perspective response based, at least in part, on a plurality of execution results corresponding to the plurality of tasks, respectively, wherein the multi-perspective response comprises a natural-language response that combines the plurality of execution results based, at least in part, on natural-language processing, and sending, to the client system, the multi-perspective response for presentation.

The invention discloses a federated learning privacy protection method and system based on selective homomorphic encryption, and the method comprises the steps: a client defines a sensitivity vector according to the sensitivity of a model parameter, and an aggregation server carries out the clustering of the client according to the similarity, and obtains a client cluster. Within each cluster, the server evaluates client system capabilities and derives an encryption budget. And the client constructs an encryption mask through a multi-objective optimization problem, iteratively updates the model parameter, the sensitivity vector and the encryption mask, partially encrypts the model parameter, and sends the encrypted model parameter and the encryption mask to the server. And the server completes model parameter aggregation, generates a union set of encrypted masks, and sends the union set back to the client. And the client decrypts the model parameters according to the union set, and performs training by taking the cluster as a unit until the model converges. According to the method, the problems of high homomorphic encryption communication and calculation cost and unbalanced security and encryption overhead under cross-device data isomerism and system isomerism in the prior art are solved.

Systems and methods for federated model validation and data verification are disclosed. A method may include: (1) receiving, by a local computer program executed by client system, a federated machine learning model from a federated model server; (2) testing, by the local computer program and using a policy service, the federated machine learning model for vulnerabilities to attacks; (3) accepting, by the local computer program, the federated machine learning model in response to the federated machine learning model passing the testing; (4) training, by the local computer program, the federated machine learning model using input data comprising local data and outputting training parameters; (5) identifying, by the local computer program using the policy service, accidental leakage and / or contamination by comparing the training parameters to the input data; and (6) providing, by the local computer program, the training parameters to the federated model server.

To provide system and methods for dynamically consolidating interaction points in a distribution ecosystem.SOLUTION: An operating environment 200 includes a system 110 as a distribution platform that serves as a central hub for managing and facilitating a distribution process. The system 110 can be configured to perform functions and operations as a bridge between customer systems 220, vendor systems 240, reseller systems 260, and other entities within an ecosystem. It can integrate communication, data exchange, and transactional processes, providing stakeholders with a unified and streamlined experience. Moreover, the operating environment 200 can include one or more integration points 210 to ensure smooth data flow and connectivity. The integration point can enable the system connect with customer systems, vendor systems, or reseller systems, enabling efficient data exchange, synchronization, and integration or connection.SELECTED DRAWING: Figure 2

Systems and methods for identifying and tracking users include receiving eavesdropped data from monitoring a base station in a wireless network; decoding the eavesdropped data to detect data therein to identify user equipment (UE) of a plurality of UEs associated with the base station; and tracking the plurality of UEs of the base station in the wireless network based on the detected data in the eavesdropped data.

Various techniques are disclosed for providing gateway services between a client system and downstream service systems for a service system. The disclosed gateway service system is capable of providing a final decision response to a service request from the client system based on responses received from the downstream service systems. The gateway service system internally determines the final decision response through implementation of a decision determination processor in combination with a configuration file and a response mapping table. The configuration file provides information that allows the decision determination processor to determine the final decision response based on decision mapping in the response mapping table. In some instances, the decision determination processor may access a dynamic decision mapping model when the response mapping table does not provide a final decision response determination.