Abstract: Novel tools and techniques for providing an in-line AI virtual assistant are provided. A system includes a session border controller coupled to an end-user device, and a session initiation protocol stack. The session initiation protocol stack includes a processor, and non-transitory computer readable media comprising instructions executable by the processor to: receive, from the session border controller, a call invite request; provision, via the AI virtual assistant service, an AI virtual assistant instance in response to the call invite request; and join the AI virtual assistant instance to a call with the end-user device.

Abstract: The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherein the aggregated historical request data a time of the request, a location of a device from which the request originated, and/or a type of service being requested. The method also incudes training a machine learning model based on the aggregated historical request data; generating, from the trained machine learning model, a prediction for a type of service to be request; identifying an edge node, from a plurality of edge nodes, based on a physical location of the edge node; and based on predicted service, allocating computing resources for the computing service on the identified edge node.

Abstract: Tools are provided for distributing access-restricted content in an internet protocol television (“IPTV”) environment based on portable entitlement keys. Such tools can include a decoder, an encoder, and a network entitlement handler. The decoder may be configured to receive a key associated with entitlement information, and transmit the entitlement information over a network. The encoder may be configured to receive content from content providers, and to encode the content to create IP-compatible content, with access restrictions based on entitlement. The network entitlement handler may be configured to receive a request for requested content from the decoder; receive the access-restricted content (including the requested content) from the encoder; and transmit the requested content over the network to the decoder using IP, when the decoder is entitled to receive the requested content.

Abstract: Described herein are improved methods for fabricating devices that include a perovskite active layer as well as devices made by these methods.

Abstract: Novel tools and techniques for providing an in-line AI virtual assistant are provided. A system includes a session border controller coupled to an end-user device, and a session initiation protocol stack. The session initiation protocol stack includes a processor, and non-transitory computer readable media comprising instructions executable by the processor to: receive, from the session border controller, a call invite request; provision, via the AI virtual assistant service, an AI virtual assistant instance in response to the call invite request; and join the AI virtual assistant instance to a call with the end-user device.

Abstract: The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherein the aggregated historical request data a time of the request, a location of a device from which the request originated, and/or a type of service being requested. The method also incudes training a machine learning model based on the aggregated historical request data; generating, from the trained machine learning model, a prediction for a type of service to be request; identifying an edge node, from a plurality of edge nodes, based on a physical location of the edge node; and based on predicted service, allocating computing resources for the computing service on the identified edge node.

Abstract: Tools are provided for distributing access-restricted content in an internet protocol television (“IPTV”) environment based on portable entitlement keys. Such tools can include a decoder, an encoder, and a network entitlement handler. The decoder may be configured to receive a key associated with entitlement information, and transmit the entitlement information over a network. The encoder may be configured to receive content from content providers, and to encode the content to create IP-compatible content, with access restrictions based on entitlement. The network entitlement handler may be configured to receive a request for requested content from the decoder; receive the access-restricted content (including the requested content) from the encoder; and transmit the requested content over the network to the decoder using IP, when the decoder is entitled to receive the requested content.

Abstract: Novel tools and techniques for an IoT shell are provided. A system includes an internet of things (IoT) device, a database, and a license manager. The database may include one or more sets of authorized licenses, each set of authorized licenses associated with a respective vendor software. The license manager may be in communication with the IoT device and the database, and further include a processor and a non-transitory computer readable medium comprising instructions executable by the processor. The license manager may be configured to receive a request to reserve a license for a first vendor software, determine an availability of the license associated with the first vendor software, register a unique identifier of the IoT device in association with the license, and grant the license to the IoT device.

Abstract: The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a system that includes a plurality of edge nodes and a beacon. The system performs operations that may include collecting traffic data from the beacon over a period of time, wherein the traffic data includes at least an amount of devices sending probe requests to the beacon; comparing the amount of devices to a predetermined threshold for traffic data; and based on the comparison of the amount of devices to the predetermined threshold for traffic data, generating a recommendation for installation of a new edge node in addition to the plurality of edge nodes.

Abstract: Novel tools and techniques for an IoT shell are provided. A system includes an internet of things (IoT) device, a database, and a license manager. The database may include one or more sets of authorized licenses, each set of authorized licenses associated with a respective vendor software. The license manager may be in communication with the IoT device and the database, and further include a processor and a non-transitory computer readable medium comprising instructions executable by the processor. The license manager may be configured to receive a request to reserve a license for a first vendor software, determine an availability of the license associated with the first vendor software, register a unique identifier of the IoT device in association with the license, and grant the license to the IoT device.

Abstract: A device may receive network data identifying at least one of a signal-to-interference-plus-noise ratio (SINR), a bit error rate (BER), a packet loss, or a frame loss associated with a radio access network (RAN), and may receive model data associated with a plurality of machine learning models. The device may receive inference confidence scores associated with the plurality of machine learning models, and may process the network data, the model data, and the inference confidence scores, with a model, to select a machine learning model from the plurality of machine learning models. The device may cause the selected machine learning model to be implemented in connection with processing images.

Abstract: Novel tools and techniques for providing an in-line AI virtual assistant are provided. A system includes a session border controller coupled to an end-user device, and a session initiation protocol stack. The session initiation protocol stack includes a processor, and non-transitory computer readable media comprising instructions executable by the processor to: receive, from the session border controller, a call invite request; provision, via the AI virtual assistant service, an AI virtual assistant instance in response to the call invite request; and join the AI virtual assistant instance to a call with the end-user device.

Abstract: The present disclosure provides for a composition comprising a compound configured to form internal ? bonds, and an inorganic material, wherein the composition is defined by a first surface opposing a second surface and a first thickness measured from the first surface to the second surface of the composition, and a method of making thereof. Further provided herein is a device comprising at least one of the compositions disclosed herein. Also disclosed herein is a photovoltaic device.

Abstract: The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherein the aggregated historical request data a time of the request, a location of a device from which the request originated, and/or a type of service being requested. The method also incudes training a machine learning model based on the aggregated historical request data; generating, from the trained machine learning model, a prediction for a type of service to be request; identifying an edge node, from a plurality of edge nodes, based on a physical location of the edge node; and based on predicted service, allocating computing resources for the computing service on the identified edge node.

Abstract: Novel tools and techniques for providing an in-line AI virtual assistant are provided. A system includes a session border controller coupled to an end-user device, and a session initiation protocol stack. The session initiation protocol stack includes a processor, and non-transitory computer readable media comprising instructions executable by the processor to: receive, from the session border controller, a call invite request; provision, via the AI virtual assistant service, an AI virtual assistant instance in response to the call invite request; and join the AI virtual assistant instance to a call with the end-user device.

Abstract: A device may receive network data identifying at least one of a signal-to-interference-plus-noise ratio (SINR), a bit error rate (BER), a packet loss, or a frame loss associated with a radio access network (RAN), and may receive model data associated with a plurality of machine learning models. The device may receive inference confidence scores associated with the plurality of machine learning models, and may process the network data, the model data, and the inference confidence scores, with a model, to select a machine learning model from the plurality of machine learning models. The device may cause the selected machine learning model to be implemented in connection with processing images.

Abstract: Tools are provided for distributing access-restricted content in an internet protocol television (“IPTV”) environment based on portable entitlement keys. Such tools can include a decoder, an encoder, and a network entitlement handler. The decoder may be configured to receive a key associated with entitlement information, and transmit the entitlement information over a network. The encoder may be configured to receive content from content providers, and to encode the content to create IP-compatible content, with access restrictions based on entitlement. The network entitlement handler may be configured to receive a request for requested content from the decoder; receive the access-restricted content (including the requested content) from the encoder; and transmit the requested content over the network to the decoder using IP, when the decoder is entitled to receive the requested content.

Abstract: Novel tools and techniques are provided for remotely configuring and orchestrating multifunctional cloud devices located on customer premises, in some cases, using a smart cloud adaptive device. In some embodiments, the smart cloud adaptive device, which might have one or more wireless programmable radios configured to communicate with a network termination device, might communicate with a cloud configuration server over a network via the one or more wireless programmable radios (and, in some embodiments, through the network termination device). The smart cloud adaptive device might transmit device identification information associated with a customer and/or service codes indicative of services to be provided to the customer. The smart cloud adaptive device might receive one or more configuration files from the cloud configuration server based on the service codes, and enable functionality among a plurality of functionalities to provision the services, based on the one or more configuration files.

Abstract: The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a method that includes aggregating historical request data for a plurality of requests, wherein the aggregated historical request data a time of the request, a location of a device from which the request originated, and/or a type of service being requested. The method also incudes training a machine learning model based on the aggregated historical request data; generating, from the trained machine learning model, a prediction for a type of service to be request; identifying an edge node, from a plurality of edge nodes, based on a physical location of the edge node; and based on predicted service, allocating computing resources for the computing service on the identified edge node.

Abstract: Novel tools and techniques for an IoT shell are provided. A system includes an internet of things (IoT) device, a database, and a license manager. The database may include one or more sets of authorized licenses, each set of authorized licenses associated with a respective vendor software. The license manager may be in communication with the IoT device and the database, and further include a processor and a non-transitory computer readable medium comprising instructions executable by the processor. The license manager may be configured to receive a request to reserve a license for a first vendor software, determine an availability of the license associated with the first vendor software, register a unique identifier of the IoT device in association with the license, and grant the license to the IoT device.