Abstract: There is provided a solution for rendering a transparent polyhedron. In a method, obtaining reflected light colors of respective positions on a back face of the transparent polyhedron; sampling on a background image or an ambient map according to the refracted light directions of respective positions on the back face to obtain refracted light colors; obtaining colors of respective positions on the back face according to the reflected light colors and the refracted light colors of respective positions on the back face; obtaining colors of respective positions on a front face of the transparent polyhedron; weighted-mixing the colors of respective positions on the back face and the colors of respective positions on the front face according to a first weighting coefficient to obtain rendering colors of respective positions of the transparent polyhedron; rendering the transparent polyhedron according to the rendering colors of respective positions of the transparent polyhedron.

Abstract: An effect processing method, an electronic device, and a storage medium are provided. The method includes: obtaining a first image in response to an effect processing request, where the first image includes a first foreground object; and performing effect processing on the first image to obtain a first video and displaying the first video, where the first video includes a first foreground image of the first image, the first foreground image includes the first foreground object, and at least a part of an object area of the first foreground object is presented in a preset style.

Abstract: Embodiments of the present application provide an electronic device for wireless communication. An example electronic device includes a low-frequency processing circuit, a high-frequency processing circuit, a coil, and at least one capacitor. The low-frequency processing circuit is electrically connected to two ends of the coil. The high-frequency processing circuit is electrically connected to the two ends of the coil. Each of the at least one capacitor is connected in parallel to the coil.

Abstract: Methods, systems and devices related to an electronic candle device having an adjustable height are disclosed. In one example aspect, an electronic candle device includes a flame sheet and a candle body. The candle body includes an upper housing that comprises an opening, a lower housing, an extendable and retractable apparatus coupled to the upper housing and the lower housing, and a motor coupled to the extendable and retractable apparatus. Upon driven by the motor, the extendable and retractable apparatus is configured to pull the upper housing and the lower housing together to at least partially overlap with each other or separate the upper housing and the lower housing such that a height of the electronic candle device is adjustable.

Abstract: Embodiments of the present disclosure provide a video generation method and apparatus, an electronic device, and a storage medium. The method includes: determining current scenario identifying information for a target object; and determining a target animation video for the target object according to the scenario identifying information and an animation image corresponding to the target object, where the animation image includes displaying position information of at least a portion of mesh models of a target model corresponding to the target object being displayed in preset video frames, and the target animation video includes the preset video frames.

Abstract: Agentic data is synchronized between a first device and a second device of a user when the first device detects a discrepancy between a cloud data chunk and an edge data chunk that are generated within a time interval. The edge data chunk is stored on the first device and contains user preferences obtained from the user interacting with first one or more artificial intelligence (AI) models. The cloud data chunk is uploaded from the second device to the cloud and contains user preferences obtained from the user interacting with second one or more AI models. The cloud data chunk is downloaded to the first device when a second timespan of the cloud data chunk is at least partially outside a first timespan of the edge data chunk. An updated data chunk is generated and uploaded to the cloud as an after-sync data chunk containing updated user preferences.

Abstract: Multiple predefined requests are sent to each of the artificial intelligence (AI) models deployed on a device. For each predefined request, a multi-dimensional complexity vector is obtained from inference operations of each AI model. The multi-dimensional complexity vector indicates, in each dimension, a complexity value of the inference operations. The agentic level provided by each AI model is evaluated by calculating a combination of complexity values obtained from each predefined request and averaging over the predefined requests. When receiving a user request, a required agentic level of the user request is estimated. The user request is directed to one of the AI models that provides the required agentic level.

Abstract: Electronic imitation candle devices are described that produce a scent while including a flame-like element that simulates a real fire flame. One example device includes a support assembly having a base, a top plate and a support rod that connects the base and the top plate, as well as a flame element and a light source to simulate a real candle flame. The device also includes a fragrance compartment above the top plate that includes a lid removably positioned on top of the fragrance container. The device is further provided with a heating element above the top plate and below the fragrance container to provide heat to the fragrance container, and a switch coupled to the lid of the fragrance container and operable to sense that the fragrance container is covered by the lid and to deactivate the heating element when the fragrance container is covered by the lid.

Abstract: A distributed agentic system includes multiple nodes that are communicatively connected. Each node is one of an edge device and a virtual machine (VM) operating on the edge device. Interaction peripherals are coupled to a subset of the nodes to receive user requests and output responses. In the distributed agentic system, an agentic manager receives a user request via one of the interaction peripherals. Based on the user request, the agentic manager sends a prompt to an artificial intelligence (AI) model managed by a model service. The agentic manager receives an action plan from the AI model, and calls at least one app according to the action plan to generate a response to the user request. The agentic manager, the AI model, the model service, and the at least one app are located on two or more of the nodes.

Abstract: A convolution operation device includes a multiply-accumulate (MAC) circuit and a post-processing circuit. The MAC circuit performs a convolution operation according to first feature data and a weight coefficient to generate initial operation data and generates a completion signal. The post-processing circuit obtains a first shift value from a memory according to the completion signal, performs a bit shift on the initial operation data according to the first shift value to generate shifted operation data, and performs a first clipping operation on the shifted operation data according to a predetermined value range to generate first operation data, wherein the number of bits of the first operation data is less than the number of bits of the initial operation data.

Abstract: A first agentic manager and a second agentic manager collaborate to respond to user requests. The first agentic manager on an originating device receives a user request and processes the user request using a first artificial intelligence (AI) model to generate a sequence of sub-requests. The first agentic manager sends one or more of the sub-requests to a second agentic manager on a target device. The second agentic manager processes the one or more of the sub-requests using a second AI model on the target device, and sends an output of an app on the target device to the first agentic manager. Based on the output of the app, the first agentic manager generates a response to the user request on the originating device.

Abstract: A computer system includes a first computing node and a second computing node. The first computing node includes a first device and a first memory. The second computing node includes a second device and a second memory. The first memory includes a first memory space. The second memory includes a second memory space. The first device obtains a cross-node read instruction. The cross-node read instruction includes a virtual address of the second memory space and a size of first data. The first device determines an identifier (ID) of the second computing node based on the virtual address of the second memory space and a first correspondence, to obtain a first network transmission packet, and sends the packet to the second device. The second device receives the packet, reads the first data from the second memory space, and sends the first data to the first device.

Abstract: An edge device provides an agentic framework to manage apps and artificial intelligence (AI) models used by the apps. An app and app metadata are downloaded from a cloud of servers to the device. The app metadata describes requirements of the app for AI models to be used by the app. The agentic framework performs a search in an on-device database that stores the app metadata and model metadata of edge models installed on the device. The search is performed to determine whether one of the edge models satisfies the requirements of the app. Following the search, the agentic framework sets a given edge model already installed on the device as a target model of the app, where the target model satisfies the requirements of the app. The agentic framework then directs the app to use the target model in response to a request for service.

Abstract: A device provides an agentic experience for a user. An agentic manager, which is a management app on the device for providing the agentic experience, receives a request from the user via a user interface. The agentic manager sends a prompt incorporating contextual information of the request to an agentic artificial intelligence (AI) model. The contextual information is retrieved from an on-device database and identifies one or more apps on the device. The agentic manager receives from the agentic AI model an action plan for calling a target app among the one or more of apps. The agentic manager sends action requests according to the action plan to the target app to invoke functionalities of the target app, and sends to the user via the user interface an output that incorporates a response generated by the target app.

Abstract: A device is in collaboration with a cloud. In response to a request for service, the device identifies one or more apps to serve the request by searching an on-device database that stores vector embeddings of features of on-device apps. The device ranks the features of the one or more apps based on similarities to requested features indicated in the request, and identifies an app having a highest-ranking feature as a target app. The device further identifies a target model for the target app. The target model is an edge artificial intelligence (AI) model when the highest-ranking feature is a local feature, or the target model is a cloud AI model when the highest-ranking feature is a non-local feature. The device then requests the target app to use the target model to serve the request.

Abstract: Flameless candles are described that improve the mounts used to support the flame sheet. The improved mounts can include a support base or a hook for movably supporting a flame sheet. The enhanced mounts improve the manufacturing of the assembly of the flameless candle and also enable the flame element to have a more natural flame-like flicker of light.

Abstract: Methods, systems and devices associated with an electronic candle are described. In one example, an electronic candle comprises a housing having a through-hole at its top and a component shell. The component shell encloses a transfer mechanism including a driver motor and one or more gears positioned inside the component shell, a light emitting component coupled to the transfer mechanism such that the transfer mechanism causes the light emitting component to move vertically up or down to protrude from the housing or to retract into the housing, a lid positioned inside the component shell and movable to remain in at least one of an open configuration or a closed configuration, and a controller configured to turn on or off the light emitting component. The candle also includes a controller configured to turn on or off the light emitting component.

Abstract: The present invention relates to the technical field of metal lamp shades, and more particularly, relates to a detachable and foldable assembled metal lamp shade, which comprises a shade body, an end cover, and a handle. The shade body is a tubular structure provided with a top opening or openings at both ends, and includes at least one flexible metal plate. First and second side edges are vertically disposed on both sides of the flexible metal plate, and the first and second side edges are detachably connected to enclose the flexible metal plate to form the shade body. The flexible metal plates can be assembled into the shade body through a detachable connection of the first and second side edges, providing a convenient assembly method and ease of disassembly into flexible metal plates for portability.

Abstract: A virtual model processing method and apparatus, an electronic device and a storage medium are provided. Said method comprises: acquiring audio information; according to attribute information of the audio information, adjusting parameters of a virtual model; and according to the adjusted parameters of the virtual model, displaying the virtual model in a target image. The parameters of the virtual model are adjusted according to the attribute information of the audio information. The attribute information of the audio information can change with time. Accordingly, the parameters of the virtual model can also change with time.