Abstract: A server for artificial intelligence (AI) service-based handling of exceptions in consumer electronic (CE) devices is provided. The server stores a neural network model that provides an AI service to handle exceptions in a plurality of CE devices. The server detects a new exception in an in-device system function of an in-device system of a first CE device and determines a cause of trigger of the new exception in the in-device system function of the in-device system based on the AI service and a plurality of different parameters of the first CE device. The server generates a first instruction to configure the in-device system specific to the new exception based on the AI service and the cause of trigger of the new exception. The server controls the in-device system in accordance with the first instruction based on the AI service such that the in-device system function is restored.

Abstract: Embodiments generally relate to managing user profiles on electronic devices. In some embodiments, a method includes detecting a voice of a first user. The method further includes identifying the first user from among a plurality of users based on the voice. The method further includes accessing a first user profile based on the identifying of the first user, where the first user profile is associated with the first user. The method further includes configuring a client device based on the first user profile. The method further includes presenting at least one media content item on the client device based on the configuring of the client device.

Abstract: Embodiments generally relate to providing a personalized program and channel guide database. In some embodiments, a method includes receiving a personalized database request from a user. The method further includes obtaining one or more playlists from one or more corresponding content providers. The method further includes generating a personalized database for the user, where the personalized database includes the one or more playlists.

Abstract: A server that includes circuitry and memory is provided. The memory stores a trained neural network model to provide a first application associated with a first service. The first application is executable on a first electronic device associated with first capability information. The circuitry receives, from a second electronic device, second capability information associated with the second electronic device. The circuitry further generates a second program code based on the received second capability information of the second electronic device and a first program code associated with first application. The circuitry further generates a second application associated with the first service based on the generated second program code. The circuitry further transmits the generated second application to the second electronic device. The generated second application may be executed on the second electronic device to provide the first service on the second electronic device.

Abstract: A server that includes circuitry and memory is provided. The memory stores a neural network model trained based on first device-usage information and a first set of configuration values for a first plurality of settings, associated with at least one first electronic device. The circuitry receives second capability information of a second electronic device from the second electronic device and compares the second capability information with first capability information of the at least one first electronic device. The circuitry further determines a second set of configuration values for a second plurality of settings of the first plurality of settings based on the comparison of the second capability information with the first capability information. Further, the circuitry transmits the second set of configuration values for the second plurality of settings and the corresponding first device-usage information to the second electronic device for configuration of the second electronic device.

Abstract: Embodiments generally relate to a virtual gateway for multiple network connection routes. In some embodiments, a method includes identifying at least one server for sourcing data. The method further includes establishing a first network connection to a first network associated with the at least one server. The method further includes fetching data from the at least one server via the first network based on a first network protocol. The method further includes establishing a second network connection to a second network associated with the at least one server. The method further includes switching from the first network to the second network based on one or more selection policies. The method further includes fetching data from the at least one server via the second network based on a second network protocol.

Abstract: Embodiments generally relate to managing user profiles on electronic devices. In some embodiments, a method includes detecting a voice of a first user. The method further includes identifying the first user from among a plurality of users based on the voice. The method further includes accessing a first user profile based on the identifying of the first user, where the first user profile is associated with the first user. The method further includes configuring a client device based on the first user profile. The method further includes presenting at least one media content item on the client device based on the configuring of the client device.

Abstract: An artificial intelligence-enabled device that handles delivery of user consumable information independent of network connectivity of the AI-enabled device, includes a memory and neural circuitry. The neural circuitry allocates a dedicated cache storage and determines a type of intelligent service on the AI-enabled device, for which first information is to be cached at the dedicated cache storage. The neural circuitry caches first information from a cloud server to a local sub-cache in the dedicated cache storage. The first information of the determined type of service is adaptively cached during at least one of a background activity or a foreground activity of the AI-enabled device, in accordance with an offline state or an online state of the AI-enabled device. The neural circuitry further controls delivery of user consumable information, based on a user input, on the AI-enabled device, based on the local sub-cache and supplemental information retrievable from the cloud server.

Abstract: A server that includes circuitry and memory is provided. The memory stores a trained neural network model to provide a first application associated with a first service. The first application is executable on a first electronic device associated with first capability information. The circuitry receives, from a second electronic device, second capability information associated with the second electronic device. The circuitry further generates a second program code based on the received second capability information of the second electronic device and a first program code associated with first application. The circuitry further generates a second application associated with the first service based on the generated second program code. The circuitry further transmits the generated second application to the second electronic device. The generated second application may be executed on the second electronic device to provide the first service on the second electronic device.

Abstract: A server that includes circuitry and memory is provided. The memory stores a neural network model trained based on first device-usage information and a first set of configuration values for a first plurality of settings, associated with at least one first electronic device. The circuitry receives second capability information of a second electronic device from the second electronic device and compares the second capability information with first capability information of the at least one first electronic device. The circuitry further determines a second set of configuration values for a second plurality of settings of the first plurality of settings based on the comparison of the second capability information with the first capability information. Further, the circuitry transmits the second set of configuration values for the second plurality of settings and the corresponding first device-usage information to the second electronic device for configuration of the second electronic device.

Abstract: A server for artificial intelligence (AI) service-based handling of exceptions in consumer electronic (CE) devices is provided. The server stores a neural network model that provides an AI service to handle exceptions in a plurality of CE devices. The server detects a new exception in an in-device system function of an in-device system of a first CE device and determines a cause of trigger of the new exception in the in-device system function of the in-device system based on the AI service and a plurality of different parameters of the first CE device. The server generates a first instruction to configure the in-device system specific to the new exception based on the AI service and the cause of trigger of the new exception. The server controls the in-device system in accordance with the first instruction based on the AI service such that the in-device system function is restored.

Abstract: A system and method for reconfiguration of embedded services on devices using device functionality information, is provided. The system includes an AI-enabled device and a server. The server receives first usage information associated with the AI-enabled device and second usage information associated with a plurality of embedded AI services on the AI-enabled device. Further, the server generates an AI model based on the received first usage information and the received second usage information and discovers, from the plurality of embedded AI services, a first embedded AI service that requires a model response. The server outputs the model response using the generated AI model and reconfigures the discovered first embedded AI service based on the model response. The model response includes first functionality information and second functionality information associated with the AI-enabled device.

Abstract: An artificial intelligence-enabled device that handles delivery of user consumable information independent of network connectivity of the AI-enabled device, includes a memory and neural circuitry. The neural circuitry allocates a dedicated cache storage and determines a type of intelligent service on the AI-enabled device, for which first information is to be cached at the dedicated cache storage. The neural circuitry caches first information from a cloud server to a local sub-cache in the dedicated cache storage. The first information of the determined type of service is adaptively cached during at least one of a background activity or a foreground activity of the AI-enabled device, in accordance with an offline state or an online state of the AI-enabled device. The neural circuitry further controls delivery of user consumable information, based on a user input, on the AI-enabled device, based on the local sub-cache and supplemental information retrievable from the cloud server.

Abstract: A system and method for designing integrated circuits is disclosed. An embodiment comprises placing a standard cell with a first cell height into a cell row with a different height. The standard cell may have a height smaller than the cell row or else may have a height that is larger than the cell row. Vertical fillers and horizontal fillers are utilized to extend and connect the standard cell to adjacent cells without having to redesign the entire cell row.

Abstract: Various aspects of an electronic device and method for distribution and access management of individual media content are disclosed herein. The electronic device includes a memory configured to store a first media content and a plurality of eraser codes. The electronic device further includes a central processing unit (CPU) configured to detect a content-type of the first media content. The CPU selects a first eraser code from the plurality of eraser codes based on the detected content-type. The selected first eraser code is embedded within the first media content based on the detected content-type. The first media content with the embedded first eraser code is then communicated to a second electronic device. The first electronic device controls deletion of at least a portion of the first media content at the second electronic device based on a communicated control instruction and the embedded first eraser code.

Abstract: A custom browser can be setup or configured by end user to scan, monitor, filter out or eliminate any element of HTTP or HTTPS or Java script code or cookie downloading from the Internet in real time. The browser with custom security protects and eliminates unnecessary data or hacker attempts from the Internet by transcoding the downloading HTML/HTML5 code without requiring any plug-in, security app or changed system security level of devices. The application is particularly useful in IPTV and Remote UI HTML5 implementations.

Abstract: A portable device is provided. A first processor performs an initial procedure according to an operation clock with a first frequency value and an operation voltage with a first voltage value, and performs a calibration procedure according to the operation clock with a second frequency value and the operation voltage with a second voltage value when the initial procedure has been performed and a self-calibration event is present. A second processor detects whether a specific function of the calibration procedure is being performed by the first processor. The second processor stores the second frequency value and the second voltage value into a storage unit after the calibration procedure is performed. The second voltage value is lower than the first voltage value, and the second frequency value is lower than the first frequency value.

Abstract: A custom browser can be setup or configured by end user to scan, monitor, filter out or eliminate any element of HTTP or HTTPS or Java script code or cookie downloading from the Internet in real time. The browser with custom security protects and eliminates unnecessary data or hacker attempts from the Internet by transcoding the downloading HTML/HTML5 code without requiring any plug-in, security app or changed system security level of devices. The application is particularly useful in IPTV and Remote UI HTML5 implementations.

Abstract: A system and method for designing integrated circuits is disclosed. An embodiment comprises placing a standard cell with a first cell height into a cell row with a different height. The standard cell may have a height smaller than the cell row or else may have a height that is larger than the cell row. Vertical fillers and horizontal fillers are utilized to extend and connect the standard cell to adjacent cells without having to redesign the entire cell row.

Abstract: A system and method for designing integrated circuits is disclosed. An embodiment comprises placing a standard cell with a first cell height into a cell row with a different height. The standard cell may have a height smaller than the cell row or else may have a height that is larger than the cell row. Vertical fillers and horizontal fillers are utilized to extend and connect the standard cell to adjacent cells without having to redesign the entire cell row.