2942 results about "Service provisioning" patented technology

The invention discloses a method for generating and constructing a database test knowledge base based on an open source large language model and retrieval enhancement, and relates to the technical field of database testing, and the method comprises the steps: building a local deployment system on a local computer system or server, and achieving the efficient local operation of the open source large language model and the stable output of language processing service; on a local computer system or a server, a retrieval enhancement generation framework is constructed, and accurate knowledge support and reliable content output are provided for local language processing service by integrating multi-modal knowledge, optimizing retrieval and generation processes and guaranteeing safety and compliance; on a local computer system or a server, a personalized database knowledge base is built, database related information is collected and processed from multiple channels and is output in an adaptive form, and the specified information requirement of local personalized language processing service is met. According to the method, efficient and stable operation of the open source large language model is realized, accurate and reliable language processing output is realized, and personalized services meet specific requirements.

An example operation may include at least one of retrieving vectors from a vector database, where the vectors include previous communication content between a source device and a service provider device, identifying an item of interest that has not been discussed in the previous communication content based on execution of a large language model (LLM) on the vectors, generating content about the item of interest, and outputting the content about the item of interest to at least one of the source device and the service provider device during an active communication session between the source device and the service provider device.

An example operation may include one or more of receiving interaction content from a communication session between a source device and a service provider device of a service provider, identifying a search criteria from the interaction content, retrieving a subset of vectors from a plurality of vectors stored in a vector database based on the search criteria of the interaction content, wherein the subset of vectors includes previous interaction content with the service provider, generating a response for the communication session based on execution of a large language model (LLM) on the subset of vectors, and outputting the response to at least one of the source device and the service provider device during the communication session.

An example operation may include at least one of storing first interaction content with a service provider; receiving second interaction content from a communication session between a source device and a service provider device of the service provider; identifying at least one contextual attribute associated with the source device; determining a response based on execution of at least one large language models (LLMs) on the second interaction content, the at least one contextual attribute associated with the source device, and the first interaction content with the service provider; and outputting the response to at least one of the source device and the service provider device during the communication session.

The invention provides a security verification method for a large model service operation environment, a medium, equipment and a product, and relates to the technical field of computers, large model services are deployed in a container group created in a virtual machine, and the virtual machine is deployed in a hardware-based trusted execution environment, so that the security verification of the large model service operation environment is realized. The method comprises the following steps: acquiring environment measurement corresponding to a running environment of a large model service through a remote attestation service deployed in a hardware-based trusted execution environment, the environment measurement at least comprising a first measurement corresponding to the trusted execution environment in which a virtual machine is located and a container measurement under a container stack dimension corresponding to a container group; the remote attestation service generates a remote attestation report according to the environmental metrics to enable a user to validate the security of the operating environment through the remote attestation report. According to the invention, not only can the attack from the IaaS layer be shielded, but also the credibility verification under the dimension of the virtual machine and the credibility verification under the dimension of the container stack can be provided, so that the credibility of the user to the service provided by the service provider is improved.

In one embodiment, a method of training one or more artificial intelligence (AI) models for language-based communication prompts with a service provider is disclosed. The training method includes generating industry specific labels used to fine tune a large language model; providing an industry specific database associated with the industry specific labels to fine tune the large language model; reading the industry specific database into the large language model; adjusting the parameters of the large language model to recognize industry specific terms associated with servicing equipment within the industry; adjusting the parameters of the large language model to discover the intent associated with the industry specific terms; and adjusting the parameters of the large language model for industry specific tasks including questions and answer tasks, named entity recognition, classification tasks, and machine translations tasks.

Techniques are disclosed for generating a ranked list of content for a user account of a service provider. A server device can determine that a first user account of a service provider is linked with a second user account of the service provider. The server device can then determine whether the first user account has been registered with the service provider a time period less than a threshold time. In response, the server device can determine interaction information associated with the second user account and generate, using a ranking model taking the interaction information as an input, a ranked list of content offered by the service provider. The server device can then cause the user device to present content at a graphical user interface of the user device according to the ranked list of content.

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

Provided is a process for mobile-initiated authentications to web services. Credential values of the user are established within a trusted execution environment of the mobile device and representations are transmitted to a server. The user of the mobile device may authenticate with the mobile device to the server, which may convey access to a web-based service from a relying device that executes a client authentication component to report user sessions to the server. The user may select the relying device from the mobile device to cause the relying device to present credentials to the web-service to login, authenticate, or otherwise obtain user-level permission for the user on the relying device. The user of the mobile device may authenticate with the mobile device to the server, and may initiate the authentication process from the mobile device, without inputting credentials corresponding to the web-service on the relying device.

Embodiments described herein relate to computer systems and methods for digital asset custodian that seamlessly integrates off-chain multi-party computation (MPC) signing with on-chain party identity authentication. The system comprises a service provider node, multiple computation nodes equipped with robust secure hardware, and a Blockchain accessible to all participating nodes. The nodes deliver a threshold signing service with utmost security—ensuring that no single node can recover the private key, while simultaneously recording and mutually authenticating each node's identity on-chain. The system boasts intrinsic support for hierarchical address creation and signing, facilitated by an enhanced protocol. Its scalability, particularly in the quantity of computation nodes, is complemented by efficient communication tailored to the demands of the MPC protocol.

Techniques described herein include providing personal data of users of a payment service to a data service when such users have granted sharing permissions. Then, a query may be configured to determine which of the users are eligible for a promotion from a third party service. The query may be sent to a data service and a query result may be received from the data service based on the third party service provisioning a temporary viewing permission to the payment service. Eligible promotions may be presented to individual users based on the query results.

There are provided systems and methods for a fine-tuning system for large language models trained for open-ended domain-specific tasks. An online transaction processor or other service provider may provide computing services and platforms to entities, which may include chatbots, information retrieval systems, question-and-answer systems, and the like. To provide better LLM training and fine-tuning, which may improve LLM performance in answering users' questions in an automated manner, the service provider may implement a fine-tuning system that may utilize automated annotations of training data, such as query and response pairs. An LLM may be prompted to determine an annotation to such pairs, and the annotations may be used to label the training data. A fine-tuning system and operations may then be implemented to fine-tune the LLMs using different processes including question-answering, retrieval augmented generation, or a continuous fine-tuning based on a size of the training data.

An example operation may include one or more of receiving interaction content from a communication session between a source device and a service provider device, executing a large language model (LLM) on the interaction content, wherein the LLM comprises a plurality of attention heads which are configured to simultaneously identify a mood and an item of interest from the interaction content, generating a response to the interaction content based on the mood and the item of interest, and outputting the response to at least one of the source device and the service provider device during the communication session.

Distributed media content history and preferences can be stored and maintained by media playback systems including one or more blockchain-capable playback devices. Content record sets, such as content experience record sets and content network record sets, can be stored via distributed ledgers and updated at least in part based on media consumption events performed or detected by playback devices, service providers, or other participants. Such distributed data can also be accessed to facilitate playback of media content for particular users, devices, households, or environments.

To provide a return device or the like that allows a person to receive service provision itself as a return from a local government by making a donation through hometown tax payment.SOLUTION: A return device 10 enables a doner to make a donation to a local government using a donor terminal 30, and in return for the donation, to receive service provision at a store of a service providing return service provider belonging to the local government. The return device includes: a memory processing unit that stores information about the local government and information about the service providing return service provider belonging to the local government; a communication processing unit that receives requests from the donor terminal 30, transmits screen configuration information to the donor terminal 30, and also transmits a payment execution request to an external server; and a control processing unit.SELECTED DRAWING: Figure 2

Some embodiments improve the security of service principals, service accounts, and other application identity accounts by detecting compromise of account credentials. Application identity accounts provide computational services with access to resources, as opposed to human identity accounts which operate on behalf of a particular person. Authentication attempt access data is submitted to a machine learning model which is trained specifically to detect application identity account anomalies. Heuristic rules are applied to the anomaly detection result to reduce false positives, yielding a compromise assessment suitable for access control mechanism usage. Embodiments reflect differences between application identity accounts and human identity accounts, in order to avoid inadvertent service interruptions, improve compromise detection for application identity accounts, and facilitate compromise containment and recovery efforts by focusing on credentials individually. Aspects of familiarity measurement, model feature selection, and a model feature engineering pipeline are also described.

There are provided systems and methods for a domain-knowledge guided agent framework for automated system analysis. An online transaction processor or other service provider may provide computing services and platforms to entities, which may require compliance enforcement for different policies, regulations, and the like. To provide compliance review, investigations, and enforcement in a computing system of a service provider, the service provider may implement an intelligent and automated agent and framework that may utilize different large language models for processing compliance investigation requests and queries. The agent may utilize the models to plan and execute tasks using an available toolkit of computing operations and capabilities for compliance investigation. A data guard module may also be used to ensure data privacy and security is maintained. Within a main task, sub-tasks may be executed by models with specific domain knowledge.

Various aspects of the present disclosure relate to methods, apparatuses, and systems that support service monitoring in wireless networks. For instance, when a service request from a UE to a visited serving network is rejected, rejection reports can be generated and validated using secure techniques, such as via a blockchain and / or a permissioned distributed ledger (PDL). The information can then be maintained and communicated in a trusted and secure manner, such as to a home serving network and / or service providers that provide network services.

A method performed by a computer-implemented controller is provided. The method includes receiving a request for managing one or more user equipments (UEs); obtaining a user-specific security profile from a first service provider; obtaining a subscriber identity module (SIM) profile from a network node or a second service provider; obtaining a set of secure access service edge (SASE) instances from the network node; building one or more UE-specific bootstrap configurations based on the user-specific security profile, the SIM profile, and the set of SASE instances; and sending the one or more UE-specific bootstrap configurations to a third service provider. The one or more UE-specific bootstrap configurations are obtainable by the one or more UEs to establish a secured wireless communication channel through a zero-trusted network.

Systems and methods are disclosed for autonomous security enhancement of a tenant network via a managed security service provider (MSSP) server comprising a processor and a memory, with information from a plurality of data sources, the method comprising querying a database or server, upon an encounter with an indicator of compromise (IoC), by a security system, to identify data sources of a plurality of data sources, wherein the data sources include information on the IoC; generating, via the processor, an IoC threat score for the IoC; generating, at least one actionable security enhancement notification based on the IoC threat score; and deploying an automated security response that can comprise displaying the IoC threat score and an actionable security enhancement notification to a user, allowing triggering or disabling of at least one action based on the single IoC threat score.

The invention belongs to the technical field of cloud computing, and discloses a method for integrating and sharing internal resources of digital media in a cloud environment. The method comprises the following specific steps: S1, multi-modal resource discovery and metadata standardization; s2, distributed resource pool construction and intelligent indexing; s3, a dynamic scheduling algorithm driven by AI; s4, a permission and traceability mechanism endowed by the block chain; s5, opening a containerized micro-service interface; s6, resource optimization driven by user behaviors; and S7, edge-cloud collaborative dynamic caching is carried out. The method has the advantages that on one hand, through multi-objective optimization, delay load regulation and control and reinforcement learning, cost is reduced, response is improved, high-quality tasks are guaranteed, and resource scheduling is optimized; on one hand, a trust foundation is built for resource management and copyright is protected from behavior recording and permission grading to tracking protection by utilizing the characteristics of the block chain; in addition, micro-services are packaged, APIs and SDKs are provided, third-party access and integration are promoted, the development efficiency is improved, and all-around enabling is achieved.

The invention discloses an intelligent call capability monitoring method and system based on a cloud mobile phone and a storage medium, and the method comprises the steps: collecting and preprocessing audio, video and other heterogeneous data through a QUIC protocol, dynamically evaluating the weight through a Transform architecture model to generate an abnormal confidence coefficient, triggering multi-modal data backtracking during abnormality, and carrying out the correlation analysis of a high-frequency sampling bottom hardware index. And constructing a three-level time sequence evidence chain and a root cause knowledge graph to position a fault root, and performing joint training and reinforcement learning parameter adjustment in combination with user feedback to realize online iteration of the model. The system comprises a heterogeneous data fusion acquisition unit, a dynamic weight evaluation unit and the like, and the steps of the method are correspondingly executed. According to the invention, through multiple dimensions, full-process accurate monitoring of the call data, rapid abnormal positioning and efficient solution are realized, a closed-loop optimization system is constructed, continuous evolution of a monitoring model is promoted, the cloud mobile phone call quality and the user experience are remarkably improved, and a solid technical guarantee is provided for the cloud mobile phone call service.

The invention provides a vehicle-mounted music recommendation method and device based on a large language model and a storage medium, and the method comprises the steps: obtaining a plurality of recommendation factors which comprise driver music preference information, and vehicle travel information, vehicle exterior environment information and driver state information which are collected in real time; filling each recommendation factor into a preset music recommendation prompt template to construct a music recommendation prompt word; inputting the music recommendation cue words into a large language model to determine a corresponding music recommendation suggestion text; and generating a recommended music list according to the music recommendation suggestion text, and sending the recommended music list to the vehicle-mounted terminal, so that the vehicle-mounted terminal can request music resources in the recommended music list from a music service provider. Therefore, music recommendation based on context awareness is realized, and the comfort and pleasure of driving can be improved.

A quantum computing service provides a quantum algorithm development kit that enables a customer to define a quantum task, a quantum algorithm, or a quantum circuit using an intermediate representation. The quantum computing service is then configured to automatically translate the quantum task, quantum algorithm, or quantum circuit into a specific representation specific to a particular quantum computing technology selected by the customer to be used to execute the customer's quantum task, quantum algorithm, or quantum circuit.

The invention relates to the field of communication service support systems, and particularly provides a service provisioning process oriented anomaly identification and automatic compensation method and device, service provisioning process modeling is an ordered process chain composed of a plurality of processing nodes, and each node corresponds to a specific service system operation; a unique flow identifier Flow ID is generated for each service instance and used for whole flow state tracking, execution results, state codes and response time information of all flow nodes are recorded in a flow tracking database in real time, and after execution of each node is completed, events are published for other modules to subscribe to, so that an asynchronous observable link is formed. Compared with the prior art, the method can achieve the closed-loop processing of the abnormal process, remarkably reduces the manual intervention rate, improves the business activation success rate and customer service experience, and improves the stability and reliability of a service opening link.

Aspects of the subject disclosure may include, for example, obtaining first positional information comprising a location of a non-stationary entity mobile within an environment, the first positional information obtained from a service provider monitoring a positional status of the non-stationary entity within the environment. A path of the non-stationary entity is predicted according to the first positional information. A delivery device mobile within the environment is directed according to the predicted path to deliver an item to the non-stationary entity. Second positional information is obtained, identifying a location of the delivery device within the environment. A separation distance is calculated between the location of the non-stationary entity and the location of the delivery device within the environment and a delivery opportunity is detected based upon the separation distance not exceeding a threshold distance. Other embodiments are disclosed.

Methods and apparatuses for facilitating network slice selection are disclosed. According to an embodiment, a service consumer sends, to a service provider, a request for subscribing to a notification of a change in network slice selection assistance information (NSSAI) availability information. The request indicates that the notification is to be subscribed to for all tracking area identifiers (TAIs) supported by an access and mobility management function (AMF) set. The service consumer receives, from the service provider, a response to the request.

A text mining engine running on an artificial platform is trained to perform conversation role identification, semantic analysis, summarization, language detection, etc. The text mining engine analyzes words in a transcript that represent unique characteristics of a conversation and, based on the unique characteristics and utilizing classification predictive modeling, determines a conversation role for each participant of the conversation and metadata describing the conversation such as tonality of words spoken by a participant in a particular conversation role. Outputs from the text mining engine are indexed and useful for various purposes. For instance, because the system can identify which speaker in a customer service call is likely an agent and which speaker is likely a customer, words spoken by the agent can be analyzed for compliance reasons, training agents, providing quality assurance for improving customer service, providing feedback to improve the performance of the text mining engine, etc.

Methods, systems, and devices for wireless communications are described. A first network entity of a first service provider may obtain, from a first user equipment (UE), an invite message for initiating a call between with a second UE that includes an identity associated with the first UE and an authorization server. Based on whether the first UE is subscribed to a third-party information service, the first network entity may obtain third-party information from the authorization server. The first network entity may output the invite message to a second network entity of a second service provider, where the invite message output by the first network entity includes the third-party information in accordance with whether the third-party information is obtained. Based on whether the second UE is subscribed to a third-party information verification service, the second network entity may verify the third-party information and output the invite message to the second UE.