Abstract: The present disclosure relates to synchronized sharing of playlists from a source client device to a listening client device. To facilitate synchronized sharing, a current playlist of one or more tracks of digital content is obtained from the source client device. A current playback location within the currently playing playlist is also obtained from the source client device. A shared queue accessible by the listener client device is generated. Further, a shared queue context for the listener client device is identified based in part upon the current playback location. This enables the listener client device to start playback synchronized with the source client device.

Abstract: Certain aspects of the disclosure are directed to context aggregation in a data communications network. According to a specific example, user-data communications between a client-specific endpoint device and the other participating endpoint device can be retrieved from a plurality of interconnected data communications systems. The client station can be configured to interface with a data communications server for providing such data communications services. Context information for each respective user-data communication between the client station and the participating station are aggregated, and operational statistics from network circuitry providing the user-data communications between the client station and the participating station are retrieved.

Abstract: A method and system for communicating artificial intelligence (AI) tasks between AI resources are provided. The method includes establishing a connection between a first AI resource and a second AI resource; encapsulating a request to process an AI task in at least one request data frame compliant with a communication protocol, wherein the at least one request data frame is encapsulated at the first AI resource; transporting the at least one request data frame over a network using a transport protocol to the second AI resource, wherein the transport protocol is different than the communication protocol; and using a credit-based flow control mechanism to transfer messages between the first AI resource and the second AI resource over the transport protocol, thereby avoiding congestion on compute resources.

Abstract: Multi-factor authentication techniques are used to verify an identity of an audio-only caller requesting to join a video-enabled virtual meeting. A request for an audio-only caller to join a video-enabled virtual meeting is received from a phone device of the audio-only caller, in which the audio-only caller is using the phone device to call into the video-enabled virtual meeting. An authentication request is transmitted to the phone device to verify an identity of the audio-only caller. A response to the authentication request is received from the phone device and includes an authentication code generated based on the request for the audio-only caller to join the video-enabled virtual meeting. The identity of the audio-only caller is then verified using the authentication code and information associated with the phone device, and the request for the audio-only caller to join the video-enabled virtual meeting is allowed or denied based on the verification.

Abstract: Systems and methods are provided for a computer-implemented method of implementing an on-demand computing network environment. A network specification is received from a user. Resources from one or more resource providers are provisioned. The on-demand computing network is configured, where configuring comprises assigning a first provisioned resource as a hub device and assigning one or more second provisioned resources as rim devices, where a particular rim device comprises a bridge device, where the bridge device repackages data received from the on-demand computing network prior to forwarding that data such that the data received from the on-demand computing network appears to terminate at the bridge device to an observer viewing the data between the hub device and the bridge device.

Abstract: Example embodiments are directed towards data delivery automation of a cloud-managed wireless telecommunication network. A disaggregated data construct is provided in a cloud-native, Open Radio Access Network (O-RAN), fifth-generation New Radio (5G NR) cellular telecommunication network. MNO cloud-native, O-RAN, 5G cellular telecommunication network engines are electronically mapped to components or services of a disaggregated network orchestrator. In an example embodiment, providing the disaggregated data construct may include electronically generating a mapping, via an open application programming interface (API), between a mobile network operator (MNO) cloud-native, O-RAN, 5G NR cellular telecommunication network service disaggregated slice design engine and a disaggregated intent engine of a disaggregated cellular telecommunication network orchestrator. The system operates the cloud-native, O-RAN, 5G NR cellular telecommunication network using the disaggregated data construct.

Abstract: A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: selectively aggregating in-session user activity of a user with historical activity data of the user into one or more respective groups based on interactions of the user with a GUI over a period of time; predicting, using a set of predictive algorithms, one or more intents of the user based on the one or more respective groups; and facilitating a display of an altered GUI on an electronic device of the user based on the one or more intents of the user, as predicted. Other embodiments are disclosed herein.

Abstract: There are provided systems and methods for scalable service discover and load balancing using direct client connections to servers. A service provider, such as an electronic transaction processor for digital transactions, may provide different computing services to users through client devices, which utilize server instances from server pools and the like to provide the computing services to users. This may include providing servers to handle client requests and process data with users. When client devices connect to the service provider's system, service discovery may be performed to find an available server instance to handle client requests. To provide scalable service discovery, load balancers may, instead of managing client requests through the load balancers, ping server instances from a server pool to identify a network address of an available server. This may be returned to the client device and a direction connection may be made between the device and server.

Abstract: A server (12) comprising means (123) for: generating at least one updated set of model parameters based on at least one current set of model parameters received from at least one apparatus (100-n), the at least one updated set of model parameters being parameters of a machine learning model and being an update of the at least one current set of model parameters; sending the at least one updated set of model parameters to at least one apparatus (100-n).

Abstract: Provided are a cell reselection method, apparatus, and system for sidelink communication. The cell reselection method for sidelink communication includes the following. A UE in an inactive state and participating in the sidelink communication receives cell reselection information, where the cell reselection information includes cell reselection information for implementing service continuity of the sidelink communication. The UE performs cell reselection according to the cell reselection information and capability information of the UE.

Abstract: A system can include a backend system and a sensor kit configured to monitor an industrial setting. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to the backend system via a public network. The backend system can include a processing system and a storage system, where the processing system performs backend operations on the sensor data and the storage systems stores the sensor data.

Abstract: An electronic eyewear device communicates with a backend service system via a device hub that provides an edge proxy server for a service request from the electronic eyewear device to the backend service system. The device hub provides a standardized request/response optimized schema for providing a standardized communication between the electronic eyewear device and the backend service system in response to the service request in a standardized format adapted to minimize network requests. A standardized communication is provided to at least one backend service of the backend service system, and a standardized response to the standardized service request is received from the backend service(s) and provided to the electronic eyewear device. In one configuration, the device hub may issue asynchronous requests to backend services in response to a service request from the electronic eyewear device and merge responses into a standardized response for the electronic eyewear device.

Abstract: A method enables testing and evaluation of an expert human reviewer or an artificial intelligence (AI) error detection engine associated with a radiotherapy treatment planning process. Intentional errors are introduced into the output of a software module or AI engine that performs a certain step in the radiotherapy treatment planning process. The efficacy of the human or AI reviewer in detecting errors can then be evaluated or tested by determining whether the human or AI reviewer has detected the introduced error.

Abstract: Example techniques describe may facilitate a playback device applying a determined audio setting. An example implementation involves a first playback device receiving, over an unsecure network, a message indicating that a second playback device is available to join a playback network, wherein the first playback device is connected to the playback network. Based on a pre-existing configuration table, the first playback device determines an audio setting corresponding to a playback configuration for the second playback device, the playback configuration including the second playback device playing back audio synchronously with the first playback device in the playback network. The first playback device transmits, to the second playback device, one or more messages instructing the second playback device to apply the determined audio setting upon joining the playback network.

Abstract: Systems, methods, and apparatus to identify media devices are disclosed. An example network communications monitor includes network interface circuitry, computer readable instructions, and processor circuitry. The processor circuitry is to execute the computer readable instructions to detect, via the network interface circuitry, multiple network communications transmitted on a home network within the household, access panelist data that associates a panelist of the household with a panelist device of the panelist, determine, based on the panelist data, that one or more of the multiple network communications are associated with the panelist device, and cause storage of data identifying the one or more network communications in association with the panelist.

Abstract: Disclosed are a method and apparatus for determining an occasion of an HARQ-ACK feedback. The method includes: in response to one DCI scheduling PDSCHs of more than one cell, taking a timeslot in which an end occasion of a PDSCH of one of the scheduled cells is located as a reference timeslot, calculating a timeslot in which an occasion of an HARQ-ACK feedback is located according to the following equation: the timeslot in which the occasion of the HARQ-ACK feedback is located=n+k, where n represents the reference timeslot, and k represents a timeslot offset, indicated in the DCI, between the timeslot in which the occasion of the HARQ-ACK feedback is located and the reference timeslot.

Abstract: A communication method for communicating with a telecommunication system is provided, with a network node, a base station and a UE coordinately implementing the method. The telecommunication system transmits a control message comprising a channel occupancy duration COD field configured to indicate a duration candidate, such that the UE is configured with control message and enabled to perform transmission and/or reception over the unlicensed spectrum within a remaining channel occupancy duration RCOD determined from the control message.

Abstract: Techniques for neutralizing malicious malware embedded in a media item being sent to a user equipment (UE) are discussed herein. A network device may receive (e.g., intercept) a medial file in transit via a wireless communication network being sent to a UE. The media file may include some type of perceptible content (e.g., audio, video, image data, etc.) as well as malware embedded in the media file. The network device may generate a transcoded media file based on the received media file that includes the perceptible content while neutralizing the malware.

Abstract: An AI-based platform for enabling intelligent orchestration and management of power and energy is provided herein. The AI-based platform includes a set of adaptive, autonomous data handling systems, wherein each of the adaptive, autonomous data handling systems is configured to collect data relating to energy generation, energy storage, energy delivery, and/or energy consumption, wherein the data is collected from a set of edge devices that are in operational control of a set of distributed energy resources; and a set of intelligent agents configured to, by robotic process automation, autonomously adjust, based on the collected data, a set of operational parameters for such operational control.

Abstract: A network node receives a data packet. In response to receiving the data packet, the network node performs a lookup on a label stack of the data packet to determine a next hop for the data packet. The network node scans the label stack to identify a Structured Entropy Label (SEL). The SEL includes a Path Tracing Indicator (PTI). The network node computes Midpoint Compressed Data (MCD) as a result of the PTI being set to a pre-defined value. The network node records the MCD in a MCD stack of the data packet by shifting the MCD stack and stamping the MCD on top of the MCD stack. The network node transmits the data packet to the next hop with the recorded MCD stack. The network sink node encapsulates the received data packet to generate an encapsulated data packet and transmits the data packet.