3169 results about "Service provider" patented technology

Systems, devices, apparatuses, and methods for more effectively protecting a user's private data and information regarding their browsing and other on-line activities. Embodiments remove constraints on an application developer by not requiring them to specify an authentication service provider as part of their application, and instead permit a user to make that choice in a protected and anonymous manner.

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.

Systems and techniques for location management are described herein. In an example, a system may include at least one processor and at least one memory with instructions stored thereon that when executed by the processor, cause the processor to obtain data originating from one or more sensors proximate to the location. A trained activity-based detection model may identify an activity at the location and perform a determination of a service to be offered at the location based on the detected activity. The system may then send a message to a user offering the service to the user, and in response to receiving an authorization accepting the service from the user, cause the service to be implemented at the location, which may include classifying the service as a service type, matching the service type to a service provider, and sending a notification to the service provider.

This invention relates to methods and systems of procuring services in the cloud and specifically procurement where the requirements are defined by the consumer in a machine understandable knowledge representation language such as RDF and OWL using semantic web technology to establish a cloud agent for discovery of a service provider and effectuate the automatic generation of a contract, or service-level agreement, that can be monitored due to the coupling between the machine understandable knowledge representation language and the contract.

There are provided systems and methods for automated chatbots that detect privacy data sharing and leakage by other automated chatbot systems. A service provider and other chatbot services, including an electronic transaction processor, may provide self-service channels for assistance through chatbot and other automated computing processes. However, these chatbots may be regulated by compliance with privacy protection requirements, and therefore use of the chatbots and / or user data when responding to users via chatbots in chat sessions may be noncompliant and / or attacked by malicious users to compromise privacy protected data. In order to facilitate detection of leaks and shares by chatbots, an AI for a privacy protection chatbot may be trained on regulations for chatbot use and / or data security and privacy protection. The chatbot may then interact with other chatbots and question the other chatbots using the trained AI model to detect whether privacy protected data is exposed.

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.

The invention discloses a system (100) for generating conversational content using a generative artificial intelligence (AI), said system (100) comprising: a user (101), an administrator (102), an application programming interface (API) server (103), a generative artificial intelligence (AI) server (104), a plurality of databases (105), a generative artificial intelligence (AI) processor (106), an audio generate processor (107), a text-to-speech processor / service provider (108), a video generation service (109), a video generation processor (110), and a memory communicatively coupled to the processor, wherein the memory stores processors instructions, which, on execution, causes the processor to generate at least one of conversational script, audio, video, or combination thereof. The system (100) allows users to create and customize various aspects of conversational content, including characters / personas / speakers, groups (of personas / characters / speakers), tones, content types, topics, conversation formats, and tone.

The invention belongs to the technical field of cloud security services, and provides a trusted cloud security confidential privacy three-dimensional level product service method, which comprises the following steps that: a cloud service provider matches products and services with different security levels by separating differentiated demands of an application development service provider and a final user in confidential, privacy and security dimensions; configuring different security modules for the product, performing hardware and software type selection matching, and determining a product type in combination with an end-to-end scene; then deploying a dynamic strategy adjustment mechanism, monitoring abnormal access in real time and adaptively adjusting a protection strategy; and continuously optimizing the security configuration. The invention discloses a trusted cloud security confidential privacy three-dimensional grade product service system, which is used for realizing a trusted cloud security confidential privacy three-dimensional grade product service method. The method is beneficial for transparently solving the security demand and conflict problem of the cloud service provider, the application development service provider and the final user, and promoting the healthy development of the cloud computing market.

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.

The embodiment of the invention provides a local life service integration method and device and terminal equipment. The method comprises the following steps: integrating a plurality of heterogeneous local life service providers into a gas station service platform to obtain a local life service platform, and collecting real-time service data in real time; non-oil sales fluctuation of the gas station is predicted based on the real-time service data, and the order quantity and the delivery cycle of upstream and downstream suppliers are dynamically adjusted according to a prediction result; constructing a multi-dimensional data analysis model, predicting user traffic and various service demands in different time periods every day, and configuring a corresponding local life service time window based on a prediction result; dynamically updating callable local life service resources and dynamically deploying gas station human resources based on the order quantity, the delivery cycle and the local life service resource configuration; and generating a personalized service list of the user by using a collaborative filtering algorithm and a reinforcement learning algorithm, interacting with the user in an interaction interface, and providing corresponding local life service resources for the user.

A text interaction record is received at a database system. The text interaction record may include interaction text from one or more messages between a client machine and a service provider. An input database record creation prompt that includes natural language instructions to generate database record field text based on the text interaction record may be determined. The input database record creation prompt may include some or all of the interaction text. The input database record creation prompt may be transmitted to a large language model for completion. A completed database record creation prompt may be received from the large language model. The completed database record creation prompt may include a text element created by the large language model based on the input database record creation prompt. A database record including a database field storing the text element may be generated in the database system.

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.

A system for classifying customer communications based on customer intent receives a communication from a customer during a communication session. The communication can include natural language. The system can create an embedding vector based on the natural language of the communication. The first embedding vector can include a numerical representation of natural language extracted from the communication. The system can compare the embedding vector to multiple embedding vectors associated with intent classifications corresponding to a prediction of a type of assistance available for customers. The multiple embedding vectors can be created based on a model that is configured to identify customer intent. The system can identify which intent classification of the multiple intent classifications is associated with the embedding vector based on the comparison. The system can redirect the communication session to a sub-unit of the telecommunications network service provider based on the identified intent classification.

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.

Latency, response times, and efficiency improvements for data querying are provided herein, particularly in the context of querying large database systems and data tables from disparate data sources. There are provided systems and methods for automatic query and data retrieval optimization through procedural generation of data tables from query patterns. A service provider may utilize different computing services for query processing and data retrieval for different applications and services used by internal and / or external users. Instead of querying large database systems and numerous data tables, pre-aggregated data tables may instead be used and searched by procedurally generating such tables based on precomputation rules and query patterns. Once patterns have been identified in queries, corresponding data may be aggregated from data sources in a pre-aggregated data table. Query optimization rules may then be used to have these data tables queried in place of their original sources.

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.

The invention relates to the technical field of communication, and provides a short message content compliance generation method and system fusing a semantic large model. The method comprises the following steps: carrying out coarse identification on short message content to be processed by a service provider to obtain a short message type and a user demand; inputting the short message content into a semantic large model for deep semantic analysis, and outputting short message semantic analysis information; performing multi-dimensional compliance comparison on the semantic analysis information of the short message according to the type of the short message and a user demand, and identifying risk description content; and optimizing and adjusting the risk description content according to the short message type and the user demand and the semantic analysis information of the risk content, and generating target short message content. The technical problem that short message content generation in communication service depends on a template, and compliance risks cannot be dynamically identified and avoided according to user requirements is solved, and deep semantic analysis and multi-dimensional risk comparison through a semantic large model are realized; and the intelligent level and compliance guarantee capability of short message content generation in the communication service are improved.

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.

There are provided systems and methods for configuration-driven efficient transformation of formats and object structures for data specifications in computing services. A service provider, such as an electronic transaction processor for digital transactions, may utilize different computing services that implement rules and artificial intelligence models for decision-making of data including data in production computing environment. Different services may process data in different data formats and structures. However, transformation of data between different services, such as a gateway service that may receive data processing requests and / or data objects and downstream services that may process such requests and objects, may take significant time and resources. A configuration-driven data transformation platform may intelligently create code for and select from transformers that may be used for data transformations. When selected, the transformers may transform data between services faster and more efficiently by being specifically selected based on past performances and code configurations.

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.

The invention relates to the technical field, in particular to a credit-based IT equipment lease management system, which comprises a credit state recognition module, an equipment matching and screening module, a lease term behavior monitoring module, an equipment state rechecking module and a lease permission backtracking module. According to the method, the dynamic credit label is formed by extracting the credit score change trend of the service party and combining the task emergency degree, intelligent judgment on resource priority configuration is achieved, and in the equipment screening link, a scheduling combination is accurately constructed through purpose consistency comparison and historical adaptation data screening, the matching efficiency is improved, and the matching efficiency is improved. In the operation process, multi-dimensional behavior data is collected and equipment self-inspection information is combined to realize joint identification of abnormal use, interface response analysis is used to guide servicing task assignment, and a closed-loop treatment system of pre-rental evaluation, in-rental monitoring and post-rental management and control is constructed by combining service party score fluctuation and equipment credit bearing limit.

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.

Techniques are described for predicting a wide area network (WAN) issue based on detection of service provider connection swapping. A cloud-based network management system (NMS) obtains connection event data for one or more network access server (NAS) devices at a site, where each event included in the connection event data comprises a connection or disconnection event of a connection session provided by a service provider. The NMS detects a number of connection swaps in the connection event data over a time window, where a connection swap includes a change from a first connection session provided by a first service provider to a second connection session provided by a second service provider. Based on the detected number of connection swaps satisfying a threshold, the NMS predicts a root cause of the connection swaps as a WAN issue and generates a notification of the predicted root cause of the connection swaps.

Systems and methods for machine learning of medical records are provided. The system can execute multiple machine learning models on the medical records in parallel using multi-threaded approach wherein each machine learning model executes using its own, dedicated computational thread in order to significantly speed up the time with which relevant information can be identified from documents by the system. The multi-threaded machine learning models can include, but are not limited to, sentence classification models, comorbidity models, ICD models, body parts models, prescription models, and provider name models. The system can also utilize combined convolutional neural networks and long short-term models (CNN+LSTMs) as well as ensemble machine learning models to categorize sentences in medical records. The system can also extract service provider, medical specializations, and dates of service information from medical records.