2228 results about "Service provisioning" patented technology

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.

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.

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.

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.

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.

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.

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.

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.

A service provider may deploy a security threat detection and mitigation platform in a multi-tenant virtualization environment that includes pluggable data collection, data analysis, and response components. The data analysis components may apply machine learning techniques to generate (based on training data sets) and refine (based on subsequently received data sets and feedback about the resulting classifications) predictors configured to detect particular types of security threats, such as denial of service attacks, botnets, scans, or remote desktop attacks. A data collection layer may collect, filter, organize, and curate network packet traffic data, network packet header data, or other information emitted by computing instances or applications executing on them, and provide the curated data as streams to the analysis layer. A response layer may automatically take action in response to threat detections (which may be overridden by an administrator) and may store classification data for subsequent analysis, feedback, and predictor refinement.

Techniques for providing explicit proxy solutions for 5G Service Access Service Edge (SASE) with service provider network attach are disclosed. In some embodiments, a system, a process, and / or a computer program product for providing explicit proxy solutions for 5G SASE with service provider network attach includes receiving data plane traffic associated with a User Equipment (UE) from a mobile core network at a Secure Access Service Edge (SASE) cloud network via a service provider network attach using an interconnect between the mobile core network and the SASE cloud network; enforcing a security policy on data plane traffic associated with the UE based on contextual information associated with the UE to provide secured data plane traffic using the security policy configured per user group and / or per user; and forwarding the secured data plane traffic from the SASE cloud network to its original destination if allowed by the security policy, and blocking or dropping the data plane traffic from the SASE cloud network if not allowed by the security policy.

Errors in network service provisioning are upstream causes to service disruptions interruptions, and failures experienced by a telecommunications network’s subscribers. These challenges are overcome by the disclosed systems for diagnosing and auditing service provisioning errors in telecommunications networks. By addressing discrepancies between Customer Facing Services (CFS) as selected by network subscribers (e.g., voice calling, messaging, roaming, unlimited or limited broadband access) and the current states of network elements in the telecommunications network, the system ensures accurate service delivery. The system performs real-time diagnosis by comparing expected network service configurations, derived from queried subscriber CFS, with the actual network states or configurations through a reverse mapping process. The system's auditing process reduces operational costs and obviates existing techniques of manual inspection.

Techniques are described for providing a multi-cloud control plane (MCCP) in a first cloud infrastructure (included in a first cloud environment provided by a first cloud services provider) that enables services and / or resources provided in the first cloud infrastructure to be utilized by users of a second cloud environment, where the second cloud environment is different than the first cloud environment. The multi-cloud infrastructure enables a user associated with an account with a second cloud services provider to use, from the second cloud infrastructure, a first service from the set of one or more cloud services. The multi-cloud infrastructure creates a link between the account with the second cloud service provider and a tenancy created in the first cloud infrastructure for enabling using the first service by the user.

Example embodiments are directed towards an intelligent user interface for interrelated services. The data-rich ecosystem of a telecommunication service provider's wireless network is leveraged in creative and intuitive ways to bring data points to users' fingertips how they need it and when they need it. A single pane of glass is made up of selectable and controllable user interface elements that paint a larger picture together of the telecommunication service provider's network and individual components thereof. For example, the system may electronically provide a plurality of software services, each having a respective user interface (UI), and electronically orchestrate, at a service orchestration layer, the plurality of software services such that when any one service of the plurality of services is used, usage of the one service automatically affects what data is presented or how the data is presented in one or more respective user interfaces of other services of the plurality of services.

Techniques are provided for artificial intelligence (AI) based application error detection and resolution. Extensive amounts of time and resources are consumed by service providers when attempting to resolve application errors experienced by customers. Unfortunately, a service provider may spend tedious amounts of manual effort to evaluate and solve an error that is already known or already solved. The techniques provided herein reduce the amount of time and resources involved in detecting and resolving errors associated with applications. In particular, an error mapping is generated for a current troubleshooting case to resolve for an application. The error mapping is compared to error mappings of previously resolved troubleshooting cases. If a match is found, then a troubleshooting action associated with a previously resolved troubleshooting case is suggested or executed. Otherwise, a service ticket is created for solving the current troubleshooting cases.

Techniques for a service provider network to manage a meeting between individuals located in a conference room with one or more other individuals remote from the conference room are discussed herein. An Enterprise system can implement one or more machine learned models to generate tiles that represent different individuals associated with a meeting. A same or different machine learned model can automatically arrange a series of tiles for display that, when presented collectively, promotes inclusiveness and attention for both in-room and remote participants of the meeting. The meeting management techniques can include determining which content to include on a display device based on evaluating changes in behavior of the meeting participants over time.

In some implementations, the techniques described herein relate to a method including: receiving a data log entry associated with a driver that includes a service provider location and a timestamp; identifying a vehicle associated with the driver based on the data log entry by identifying the vehicle includes applying a machine learning model to the data log entry and a vehicle database; loading a vehicle location log associated with the identified vehicle, the vehicle location log including a plurality of location data points and associated timestamps; computing an alternate data log entry based on the data log entry and the vehicle location log, wherein computing the alternate data log entry includes applying a rule-based optimization algorithm to a historical service provider database; and transmitting a recommendation based on the alternate data log entry, wherein the recommendation includes a geospatial visualization of the alternate data log entry.

A virtual gateway for transmission of packets from a service provider virtual network to a service consumer virtual network of a user is established at a cloud computing environment. A limited-access endpoint is created in the service consumer virtual network, with security settings provided by the user which enable transmission of packets from a service implemented at the service provider virtual network to resources within the service consumer virtual network. A packet directed to a resource in the service consumer virtual network is received at the gateway from the service. If the security settings permit delivery of packets via the endpoint to the resource, the packet is transmitted to the resource.

The invention discloses an electric vehicle cluster peak clipping service control method based on charge state fuzzy control. The method comprises the following steps of S1, performing fuzzy theory and peak clipping service demand evaluation; s2, carrying out modeling on charging and discharging behaviors of the electric vehicle; s3, analyzing the charge and discharge degradation cost of the electric vehicle; s4, optimizing a model objective function; according to the control method, an EVs cluster charging and discharging strategy optimization model for maximizing the benefits of EVs users and load aggregators is constructed based on SOC fuzzy control under the condition that the peak clipping demand degree of each time period is considered, the charging and discharging willingness of the EVs users is considered, an adjustable space is reserved for the EVs, the peak clipping service is supported, and the peak clipping demand degree is optimized. And meanwhile, the total expected revenue of the load aggregator and the EVs user is maximized, the optimization model is solved by combining the genetic algorithm and the CPLEX, and a better scheme is provided for the EVs cluster peak clipping service in the source network load storage system.

Aspects of the subject disclosure may include, for example, transmitting a request to generate an authorization object; receiving a first confirmation that authenticates a primary user device from a service provider system; generating the authorization object that meets a predetermined standard and contains audio visual representation of a primary user associated with the primary user device; receiving a second confirmation that authenticates a matching between the authorization object and the primary user; uploading the authorization object to a storage of a trusted server; and executing an access mechanism to access the stored authorization object on the trusted server. Other embodiments are disclosed.

The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. According to the present disclosure, MBS services for flexible and dynamic MBS service scenarios become possible in the next-generation wireless communication systems.

Techniques for providing security for providing a Secure Access Service Edge (SASE) solution for enhanced security for unmanaged devices for mobile networks (e.g., service provider networks for mobile subscribers) are disclosed. In some embodiments, various techniques to apply per network slice security for unmanaged devices in mobile networks with SASE are disclosed. In some embodiments, various techniques to apply per subscriber identity and / or equipment identity and / or subscriber number security for unmanaged devices in mobile networks with SASE are disclosed. In some embodiments, various techniques to apply per access point name / data network name (APN / DNN) security for unmanaged devices in mobile networks with SASE are disclosed. In some embodiments, various techniques to apply per location security for unmanaged devices in mobile networks with SASE are disclosed. In some embodiments, various techniques to apply per Radio Access Technology (RAT) security for unmanaged devices in mobile networks with SASE are disclosed.

The invention discloses an open source system framework layer custom interface authentication method comprising the following steps: creating a custom service in an open source system framework layer, the custom service providing at least one custom interface; establishing an encrypted and stored authentication white list file, wherein the encrypted and stored authentication white list file comprises a package name and signature fingerprint information of an application needing to be authorized; integrating an authentication trigger mechanism in the custom interface, and executing a hierarchical authentication process when an external application calls the custom interface; the hierarchical authentication process comprises the following steps: acquiring a package name of a calling party application and checking whether the package name exists in an authentication white list file or not; if yes, signature fingerprint information of the calling party application is further obtained and compared with fingerprints recorded in the authentication white list file; and if the fingerprints are consistent, the authentication is successful, and the function logic of the user-defined interface is executed. According to the method provided by the invention, the custom interface is ensured to be only open to the authorized application through a dual verification mechanism of the package name and the signature fingerprint information, and the full choice and stability of the system are ensured.

There are provided systems and methods for identifying relevance of documents for automated retrieval models using large language models. 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 retrieval model training and refinement, the service provider may generate training data from user interaction logs, which may include user feedback that may be used to determine if documents are relevant to queries, and therefore should be retrieved for answering those queries by automated retrieval models. An LLM may be used as a judge to determine whether chatbot responses reference certain document. If not references, the query may be analyzed to determine whether certain retrieved documents are relevant. Data pairs may be generated for the training data from these processes and used for model refinement.

The present invention relates to methods and apparatus for testing and mitigating problems with Spectrum Access System (SAS) service provider systems. An exemplary method includes performing, by an SAS switch and availability function (SSAF), one or more tests on a first SAS service provider system, the first SAS service provider system providing SAS services to one or more wireless base stations (e.g., CBSDs) of a first wireless network (e.g., a first CBRS network); and determining whether or not the first SAS service provider system is experiencing problems providing SAS services to the first wireless network based on results of the one or more tests performed on the first SAS service provider system. In response to determining that there are problems with the first SAS service provider system switching the one or more wireless base stations to a second SAS service provider system.