Abstract: Aspects of the subject disclosure may include, for example, an apparatus, including: a processing system including a processor; and a memory configured to store executable instructions that, when executed by the processor, cause the apparatus to: receive, via one or more interfaces, network access parameters associated with a registration request from a user equipment; determine, based on the network access parameters and provisioning information for a data network name (DNN) of a data network, a mapping between the DNN and a plurality of available network functions deployed in a converged core network; select one or more network functions from the plurality of available network functions to provide service the user equipment; generate control signals to dynamically orchestrate provisioning and session establishment via the one or more network functions selected; and communicate the control signals to the one or more network functions selected. Other embodiments are disclosed.

Abstract: Aspects include obtaining first data indicative of a first location of a first user equipment, obtaining second data indicative of a second location of the first user equipment, obtaining third data indicative of a first transmit power level utilized by the first user equipment, obtaining fourth data indicative of a second transmit power level utilized by the first user equipment, determining, based on the first data and the second data, that the first user equipment has changed location in an amount less than a first threshold, resulting in a first determination, determining, based on the third data and the fourth data, that the first user equipment has changed a transmission power level that is utilized in an amount that is less than a second threshold, resulting in a second determination, and based on the first determination and the second determination, declaring that the first user equipment is stationary.

Abstract: Aspects of the subject disclosure may include, for example, determining, in relation to a communication node, a neighboring node of a wireless network, wherein the neighboring node comprises a baseband processor in communication with a radio frequency (RF) subsystem. A determination is made regarding one of a spatial configuration, a hosting infrastructure configuration, or both, of the neighboring node. The spatial configuration includes one of a divided configuration, including geographically separated centralized and a distributed baseband units, and an undivided configuration including an undivided baseband unit. The hosting infrastructure configuration distinguishes a physical configuration having the baseband processor includes dedicated compute resources allocated to the node, from a virtual configuration having a virtual baseband processor hosted on shared compute resources.

Abstract: Aspects of the subject disclosure may include, for example, a heat risk assessment system that integrates forward-looking climate data to evaluate and manage heat-related risks for outdoor workforces. The system utilizes wet-bulb globe temperature (WBGT) as a primary metric, combined with localized environmental factors such as solar irradiance, urban heat island effects, and technician density. By incorporating both historical and predictive climate data, the system provides dynamic heat risk scores that reflect both immediate and long-term heat stress factors. These scores are used to inform and implement heat risk mitigation strategies, enhancing safety and operational efficiency across various industries. The system leverages advanced data processing and data engineering techniques to deliver accurate and actionable insights, ensuring compliance with regulatory standards and improving workforce resilience to environmental heat stress. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a user equipment (UE) device operative for receiving, from a local network, a mobile country code identifying a jurisdiction in which the local network is located, identifying, in a memory of the UE device, a lawful intercept modify parameter associated with the jurisdiction, receiving, based on the lawful intercept modify parameter, regulatory requirements for implementing lawful intercept procedures by the UE device, and communicating with the local network according to the lawful intercept procedures. Other embodiments are disclosed.

Abstract: Techniques for mechanized modify/add/create/delete (MACD) for network configuration are provided. A method can include creating a data object from input data relating to a requested change to a target network configuration, the data object comprising a first parameter indicating a type of the requested change and a second parameter identifying the target network configuration; retrieving, from a repository according to a group of logical rules, executable instructions associated with the type of the requested change, as given by the first parameter of the data object, and the target network configuration, as given by the second parameter of the data object; and performing, further according to the group of logical rules, the requested change to the target network configuration, the performing of the requested change comprising executing the executable instructions retrieved from the repository.

Abstract: Aspects of the subject disclosure may include, for example, receiving artificial intelligence and machine learning (AI/ML) data from a network element in a radio access network (RAN) for communication to a core network (CN), determining a transport pathway for the AI/ML data based on one or more factors, wherein the determining a transport pathway comprises selecting a selected transport pathway from among a plurality of available pathways, the plurality of available pathways including a user plane path, a control plane path, and a management plane path, and transmitting the AI/ML data from the network element to the CN over the selected transport pathway. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, generating, on a physical device, a plurality of virtual device identities, each virtual device identity comprising a virtual international mobile equipment identity (vIMEI) that is matching a physical international mobile equipment identity (pIMEI) of the physical device, instantiating one or more virtual subscribers, each respective virtual subscriber associated with a respective virtual device identity of the plurality of virtual device identities, and associating each virtual device identity with a corresponding set of operational parameters, the set of operational parameters associated with a particular task of a virtual subscriber associated with the virtual device identity. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, determining, by an end user device, a destination location for the end user device; determining, by the end user device, frequency band data for the destination location according to connection data stored in a memory of the end user device; responsive to or after exiting an airplane mode of the end user device, scanning, by the end user device, bands of a cellular network providing coverage to the destination location, where the scanning is according to the frequency band data; and attaching, by the end user device, to a cell of the cellular network based on the scanning of the bands. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device of a first party, including: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of storing a first connection link for a call from the first party to a called party; receiving a request for contact information of the called party from a third-party device; and sending a copy of the first connection link to the third-party device, wherein a second device of the called party displays referring information indicating that the first connection link was shared by the first party when the third-party device uses the copy to call the second device. Other embodiments are disclosed.

Abstract: The disclosed technology is directed towards disabling mobile device communications when such communications can possibly interfere with aircraft equipment. Examples include disabling the C-Band communications of devices when proximate an aircraft and/or airport. A signal beacon can be sent to devices, and as one example, devices capable of C-Band communications can be configured to automatically disable this frequency band. Devices that cannot react to this signal can disable frequency band(s) / switch to airplane mode in other ways, including based on received notifications, or based on sensed condition data. For example, motion detection, possibly combined with location data and/or elevation data, can determine whether a device is aboard an aircraft that is taxiing, preparing for takeoff, taking off, preparing for landing or landing. Elevation data can detect when a device is below some defined ceiling elevation, to take action with respect to disabling one or more predetermined frequency bands.

Abstract: System information status is dynamically adjusted at a base station (e.g., a 5G gNB) from not broadcasting other system information block(s) to broadcasting, and vice versa, based on network condition data to improve network performance. When a sufficient number of user equipment devices are expected to transition from idle to connected mode, the base station broadcasts additional system information beyond minimum system information (e.g., SIB1) previously transmitted on-demand. A core network component can initiate the change, with the updated SIB1 data periodically broadcast to user equipment. A paging message is transmitted to instruct user equipment to process the updated SIB1 data. The system can revert to not broadcasting other system information when the network determines that broadcasting is unnecessary.

Abstract: Spatial-temporal informative patterns for users and devices associated with data networks can be predicted or determined. An information management component (IMC) can analyze respective groups of items of data stored in respective formats in respective databases. Some items of data can comprise respective signal measurement data representative of respective signal measurements associated with respective devices associated with a communication network. Based on the analysis results, IMC can determine a spatial-temporal pattern(s) associated with the respective groups of items of data, wherein the spatial-temporal pattern(s) can relate to a subject of interest. The IMC can utilize artificial intelligence and/or machine learning algorithms and models to facilitate determining the spatial-temporal pattern(s). In response to a query relating to the subject of interest, the IMC can provide information relating to the subject of interest and responsive to the query based on the spatial-temporal pattern(s).

Abstract: Aspects of the subject disclosure may include, for example, systems and methods for enabling traffic classification for extended reality (XR) applications over 5G NR networks. XR-specific traffic flow are adaptively classified with RAN-level characteristics including resource allocation, link adaptation, and radio resource management (RRM) metrics and configurations to optimize per-user and system performance and QoS parameters. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, systems, devices, and computer-readable media that improve automated troubleshooting of service degradations in cellular networks by leveraging information available after customer support interactions to enhance learning when reliable labeled examples are limited. In some implementations, network and user equipment measurements, including performance indicators and session behavior, are analyzed across time windows associated with prior service events to infer additional supervisory signals and reduce label noise. The enhanced learning can be used to support real-time classification of whether a current customer-reported problem is more likely attributable to the network or to the user equipment, and to provide actionable outputs that guide corrective operations in the network, on the user device, or both. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example: obtaining, repeatedly in a real-time manner, latency information for each of a plurality of candidate network paths between a source node and a destination node in a network, wherein the latency information for at least one candidate network path is based on queue depth information of an output queue of at least one router along the at least one candidate network path; selecting, based on the latency information, a selected network path from the plurality of candidate network paths; and facilitating forwarding of one or more packets from the source node toward the destination node via the selected network path. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device, having: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: receiving a prompt from a user; ingesting a document; separating the document into vectorized chunks; processing the vectorized chunks using a Retrieval-Augmented Generation (RAG) pipeline combined with Large Language Models (LLMs) to extract specific information using predefined prompts, wherein the predefined prompts incorporate information from the user prompt; assigning a plurality of AI assistants (AIAs) to independently extract information using different prompts, LLMs, or parameters, thereby generating diverse responses; aggregating the diverse responses from the plurality of AIAs to create aggregated responses; presenting the aggregated responses to the user in a multiple-choice format, including scores and relevant excerpts from the document; recei

Abstract: Aspects of the subject disclosure may include, for example, determining whether a bandwidth deficit exists in association with communications of a device, resulting in a first determination; responsive to the first determination being that the bandwidth deficit exists, communicating with a server to determine whether the device can participate in a link aggregation group (LAG), resulting in a second determination, wherein the communicating with the server comprises sending to the server a unique identifier, and wherein the second determination is based at least in part upon the unique identifier; responsive to the second determination being that the device can participate in the LAG, identifying a source of available bandwidth; and using the unique identifier to track bandwidth provided to the device via the source of available bandwidth. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving content related to a communication between a first user and at least one other user, analyzing the content to derive at least one communication behavioral trait of the first user, and presenting to the first user at a user device of the first user, information about the at least one communication behavioral trait, the presenting to provide insight to the first user about how the first user communicates. Other embodiments are disclosed.

Abstract: Transfer knowledge from auxiliary data for more inclusive machine learning models is provided. A method can include generating a common feature space comprising first data features, wherein the first data features are present in training data used to train a first machine learning model, and wherein the first data features are present in auxiliary data that are independent of the training data; generating a combined learned feature representation, the combined learned feature representation being representative of the first data features of the common feature space and second data features that are unique to the training data; and training a second machine learning model based on the combined learned feature representation.

Abstract: Aspects of the subject disclosure may include, for example, receiving application traffic from a plurality of Internet of Things (IoT) devices processing an application, including receiving the application traffic over a mobile communication network, clustering the application traffic to identify clusters of similar IoT devices based on common characteristics of the application traffic, receiving unknown traffic over the mobile communication network, determining a closest cluster based on similarities between the unknown traffic and respective clusters of the clusters of IoT devices, decomposing traffic signals of the closest cluster into trend, period, and noise information, forming decomposed traffic, reconstructing the decomposed traffic into reconstructed traffic based on the trend information and the period information to remove noise information from the traffic signals of the closest cluster, forming a baseline for the closest cluster, detecting an anomaly in the reconstructed traffic based on a variat

Abstract: Aspects of the subject disclosure may include, for example, identifying a first value corresponding to a constraint pertaining to a number of beams, conveying the first value to at least one communication device, and obtaining, based on the conveying, at least one report from the at least one communication device, wherein an at least a second value corresponding to a number of the beams referenced in the at least one report is less than or equal to the first value. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, detecting initiation of a service associated with a UE, where the service comprises an OTT voice/video call, facilitating, for the service, activation of an end-to-end network slice between a core network and the UE, detecting a RAT switch determination for the UE, where the RAT switch determination relates to communicative coupling of the UE with a second network node, and where the second network node is associated with a second RAT different from the first RAT, responsive to the detecting the RAT switch determination, determining whether the service is ongoing over the end-to-end network slice, and, based on a determination that the service is ongoing over the end-to-end network slice, preventing the UE from communicatively coupling with the second network node until the service is determined to be completed or until the end-to-end network slice is released. Other embodiments are disclosed.

Abstract: The technologies described herein are generally directed to detecting reflective surfaces for use reflecting a signal from access point equipment to destination equipment in advanced networks, e.g., at least a fifth generation (5G) network. For example, a method described herein can include receiving a request to establish a reflective path usable to facilitate a connection between user equipment and access point equipment, resulting in reflected path information corresponding to the reflective path. The method can further include, based on the reflected path information, selecting a location for a reflective surface to facilitate the connection by the access point equipment. The method can further include, facilitating communicating the reflected path information to the access point equipment.

Abstract: Aspects of the subject disclosure may include, for example, obtaining data indicative of a location of a satellite; obtaining data indicative of locations of each of a plurality of mobile devices, battery states of each of the mobile devices, and transmit powers that are required for the mobile devices to upload traffic to a wireless terrestrial network; generating, based upon the location of the satellite and upon the locations of the mobile devices, data indicative of predicted transmit powers that would be required for each of the mobile devices to upload traffic to the satellite; selecting, based upon the battery states of each of the mobile devices, upon the transmit powers that are required for each of the mobile devices to upload traffic to the wireless terrestrial network, and upon the predicted transmit powers that would be required for the mobile devices to upload traffic to the satellite, at least one mobile device of the plurality of mobile devices to be instructed to upload traffic to the satelli

Abstract: A method includes determining, by a vehicle, a failure with a computer or telecommunications system operating in the vehicle and when a failure is detected, activating an acoustic system on the vehicle, detecting a vibration by the vehicle; and transmitting an audible signal responsive to the detecting step. The audible signal may include words in a human vocabulary.

Abstract: Dynamic, continuous quality of service adjustment (e.g., using a computerized tool) is enabled. For example, a system can comprise: a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: determining a condition associated with a user profile, wherein the user profile is associated with a mobile device, determining a quality of service metric representative of a quality of service of a data transmission, via a radio access network, between the mobile device and network equipment, and based on the condition, modifying a quality of service parameter, wherein modifying the quality of service parameter comprises modifying the quality of service.

Abstract: Aspects of the subject disclosure may include, for example, a passive fiberoptic signal sensing device configured for visually detecting physical properties of fiberoptic transmission signals without external diagnostic equipment. The device includes a housing and an integrated optical sensing assembly including a photosensitive screen and a beam spreading element. The screen, coated with photosensitive material, undergoes visible changes—such as varying shades or colors—based on signal intensity or wavelength. A beam spreading element disperses the signal over the screen, enabling visual indication of signal presence and quality. The device can be installed in a wall jack for customer self-installation of broadband services, facilitating troubleshooting and reducing technician visits. The method involves positioning the screen along an optical axis, selectively occluding signal propagation, and spreading the signal to provide visual feedback.

Abstract: Aspects of the subject disclosure may include, for example, configuring network nodes in a wireless mobility network based on a service trigger, facilitating communications among agentic artificial intelligence (AI) agents running in the network nodes, and dynamically assembling a necessary network node in the wireless mobility network to provide a service. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving a request relating to a call from a caller directed to a callee, determining, based on call preferences, call policies, or user intent associated with the callee, whether to forward the call for AI-based handling or processing, and based on a determination to forward the call for AI-based handling or processing, causing an AI agent to facilitate the handling or processing of the call, wherein the handling or processing involves obtaining first media packets from the caller, converting the first media packets into LLM inputs, providing the LLM inputs to an LLM for processing and output generation, converting LLM-generated outputs into second media packets, and causing the second media packets to be provided to the caller. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving, from a first user device, a first command to register a first AI identity for a user and, from a second user device, a second command to register a second AI identity for the user, wherein the first command includes first profile data that identifies a first type for the first AI identity, and wherein the second command includes second profile data that identifies a second type for the second AI identity, causing the first and second profile data to be included in a mapping for the user, obtaining, from an AI system, a request to access the first AI identity, and providing information for accessing the second AI identity to the AI system based on a determination that the second AI identity is to be accessed according to criteria being satisfied, thereby enabling dynamic AI identity selection/access.

Abstract: Aspects of the subject disclosure may include, for example, a device having: a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: analyzing a subscription request to identify a type of a machine learning (ML) model; retrieving, from an evaluation metric repository stored in the memory, a plurality of preconfigured evaluation metrics associated with different types of ML models; selecting an evaluation metric from the plurality of preconfigured evaluation metrics; applying the evaluation metric selected to an output of the ML model to generate a performance score; comparing the performance score to a predetermined accuracy threshold; and initiating a corrective operation responsive to the performance score not meeting the predetermined accuracy threshold. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, dynamically managing quality of service in a communication network based on situational context and network conditions, including using analytics and machine learning to generate quality-of-service information that drives policy decisions for traffic associated with applications executing on user devices. Policy control functionality can select, generate, and distribute routing and service policies to user devices, including policies that modify how traffic is mapped to connectivity parameters, network slices, or data networks, and such policies can be applied during ongoing communication services. A user device can be presented with an option to accept a service change, which may be associated with account treatment such as charges, rewards, or other incentives, and notifications can indicate durations or termination times for a service change.

Abstract: Aspects of the subject disclosure may include, for example, obtaining network-related data or device-related data associated with a UE, wherein the UE is associated with a network-hosted AI assistant that provides AI services for a user of the UE, detecting an attempt from an endpoint to access the network-hosted AI assistant, and validating the attempt based on the network-related data or the device-related data. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, techniques for improving cybersecurity for connected device deployments by using threat intelligence and automated analysis of threat information to identify, characterize, and prioritize potential threats in view of context associated with Internet of Things environments. In some embodiments, threat information can be derived from external feeds and research content and can be analyzed with machine learning or generative artificial intelligence to infer properties of malware, campaigns, tools, or threat actors, and to tailor mitigation guidance for specific operating environments. Recommendations can be presented via a security dashboard and can support actions such as alert prioritization, suppression of non-actionable alerts, and configurable enforcement responses. The disclosed techniques can be implemented in devices, network elements, cloud or virtualized platforms, and non-transitory computer-readable media. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, techniques for managing and enhancing communication services using profiles and adaptive coordination among distributed computing and network resources, including edge and cloud resources. Service delivery can be tailored based on application context and performance objectives such as latency, reliability, throughput, and device constraints, with resources selectively engaged, reconfigured, or supplemented to meet target experience levels. In some implementations, processing tasks may be partitioned between a communication device and one or more external processing systems to reduce device load, improve responsiveness, or conserve power. The subject disclosure also contemplates user- or operator-driven selection, modification, and storage of templates or profiles, as well as on-demand enablement of additional resources and associated charging or accounting. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including: receiving sounding reference signal (SRS) data for an uplink transmission of a user equipment (UE) from a remote unit (RU); generating SRS-based beam weights; transmitting the SRS-based beam weights to the RU; instructing the RU to generate DMRS-based beam weights and send demodulation reference signal (DMRS) channel estimates from subsequent uplink transmissions of the UE; and receiving the DMRS channel estimates from the RU. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining data that corresponds to one or more interactions of a user with an AI agent, causing the data to be converted into one or more AI memories of the user, after the causing, receiving a request for AI memories of the user, and responding to the request by retrieving the one or more AI memories, wherein the one or more AI memories are stored in a predefined format that enables access thereto by an external system or portability thereof to the external system. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving an input image relating to one or more network elements of a telecommunications network, deriving an embedding based on the input image, resulting in an input image embedding, conducting a search for the input image embedding in a vector database that stores embeddings associated with images relating to telecommunications network elements, determining whether a particular embedding in the vector database corresponds to the input image embedding, and based on a determination that there is a lack of a particular embedding in the vector database that corresponds to the input image embedding, causing a corrective action to be taken with respect to the one or more network elements of the telecommunications network. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a device utilizing a distilled artificial intelligence (AI) model to dynamically allocate resources in user equipment (UE). The AI model, received from a server, analyzes application requests to determine resource allocations. The device adjusts resource allocation based on real-time metrics, battery status, and network loading, enhancing multitasking and execution of complex applications like AI and extended reality (XR). Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving remote cell antenna information from each of a group of communication devices resulting in a group of remote cell antenna information, determining a group of cell key performance indicators (KPIs) and a group of cell location information based on the group of remote cell antenna information, and generating a coverage heat map based on the group of cell (KPIs) and the group of cell location information. Further embodiments can include analyzing the coverage heat map to determine interference caused by a remote cell antenna resulting in an analysis, identifying the remote cell antenna based on the analysis, and providing first instructions to a remote base station associated with the remote cell antenna, the instructions indicate to adjust configuration(s) of the remote cell antenna to mitigate the interference. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, based on an attachment of a UE to a telecommunications network, causing the telecommunications network to bind phone number-related information to an AI identity corresponding to the UE, resulting in a binding that enables the UE to request for an allocation of a phone number for the UE, and based on the allocation of the phone number for the UE, associating the AI identity with data relating to the phone number, thereby facilitating on demand telecommunications services for the UE via the AI identity. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, receiving a first command to associate an AI service identity with a first mobile number relating to a user, wherein the AI service identity is associated with user settings or preferences for AI-based services, based on the first command, causing the AI service identity to be bound to the first mobile number, resulting in a first binding, receiving a second command to associate the AI service identity with a second mobile number relating to the user, and based on the second command, causing the AI service identity to be bound to the second mobile number, resulting in a second binding, wherein the first binding and the second binding enable converged AI-based services for both the first mobile number and the second mobile number. Other embodiments are disclosed.

Abstract: In one example, a method includes receiving a report indicating that a mobile device has been lost or stolen, sending, in response to the report, an instruction to the mobile device that causes the mobile device to connect to a network slice that is dedicated for protecting and tracking lost and stolen mobile devices, sending, in response to determining that the mobile device has connected to the network slice, a second instruction to the mobile device that causes the mobile device to modify a setting of the mobile device to limit a functionality of the mobile device and to permit tracking of the mobile device, receiving, via the network slice, a message from the mobile device indicating a current physical location of the mobile device, and reporting the current physical location of the mobile device.

Abstract: A processing system including at least one processor of a network access device may detect an installation of the network access device in a wireless communication system of a vehicle. The processing system may next interrogate at least one antenna unit of the wireless communication system of the vehicle and obtain, from the at least one antenna unit in response to the interrogating, a set of antenna capability information. The processing system may then configure the wireless communication system of the vehicle in accordance with at least a portion of the set of the antenna capability information.

Abstract: In one example, a method includes receiving a message from a mobile device of a user that initiates a virtual handshake, wherein the user is not a first responder, sending, in response to a completion of the virtual handshake, a first instruction that causes the mobile device to modify a setting of the mobile device to facilitate access to a slice of a communications network that is dedicated for use by emergency services, detecting, via the slice, a current physical location of the mobile device; and reporting, via the slice, the current physical location of the mobile device to a provider of an emergency service.

Abstract: A processing system may obtain a request from a user device to activate an access credential locker for use in accessing at least one enterprise system of an enterprise via the processing system, the request comprising a token that identifies the access credential locker, obtain a first key from the user device, transmit, to the enterprise, a request for a second key, obtain the second key from the enterprise in response to the request, apply the first key and the second key to the access credential locker, the access credential locker being encrypted in accordance with the first and second keys and being decrypted via the applying of the first and second keys, and establish a communication session between the user device and the at least one enterprise system via the processing system using at least one access credential that is stored in the decrypted access credential locker.

Abstract: Aspects of the subject disclosure may include, for example, training a large language model (LLM) on data related to malware that may infect internet of things (IoT) devices communicating on a mobility network, receiving, from the LLM, information about malware affecting the IoT devices, conducting a dialog with the LLM to develop additional information about the malware affecting the IoT devices, wherein the conducting the dialog with the LLM comprises providing textual questions to the LLM and receiving textual answers to the textual questions from the LLM, and providing, to a device operator associated with the IoT devices, diagnostic information about a malware threat to IoT devices in the network and prescriptive information that may be used to avoid the malware threat, wherein the diagnostic information and the prescriptive information are based on the dialog with the LLM. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, obtaining training from wireless devices, where the wireless devices collect the training data that indicates first operational parameters and operational errors at the wireless devices; analyzing the training data to generate pre-failure thresholds according to the first operational parameters and the operational errors; receiving operational data from a particular wireless device, where the particular wireless device collects the operational data that indicates second operational parameters at the particular wireless device; analyzing the operational data according to the pre-failure thresholds resulting in a pre-failure analysis; and providing an alarm when the pre-failure analysis indicates that one or more of the second operational parameters violates one or more of the pre-failure thresholds, where the alarm is generated prior to a failure of the particular wireless devices that is predictable based on the second operational parameters.

Abstract: An automated information retrieval system includes a processor coupled to a communications interface and a non-transitory memory. The processor is configured to read instructions from the non-transitory memory to cause the system to perform operations comprising receiving a term including a plurality of words and generating a plurality of word vectors corresponding to the plurality of words respectively. A plurality of term vectors associated with the term is generated using the plurality of word vectors based on a plurality of term vector rules respectively. A combination term vector associated with the term is generated by combining the plurality of term vectors. One or more search results from a database for the term are provided using the combination term vector.