Abstract: A system is provided that detects a start of a camera session, captures initial raw data frames and stores them in memory. Upon determining that the camera session corresponds to a video recording session, the system activates a video recording pipeline and upon determining that the video recording pipeline is active, the system retrieves the initial raw data frames, encodes the initial raw data frames using the video recording pipeline, accesses additional captured raw data frames, and encodes the additional captured raw data frames using the video recording pipeline until detection of an end of the camera session. Upon detecting an end of the camera session, the system deactivates the video recording pipeline.

Abstract: A system, automobile, and method for implementing an electronic control function of an automobile. The system includes a first vehicle integration unit (VIU), an automobile control unit, and a plurality of automobile parts. The automobile control unit includes a first domain controller (DC) or a central computing platform (CCP). The automobile control unit is configured to send first control information to the first VIU. The first VIU is configured to control the plurality of automobile parts based on the first control information. In embodiments of this application, the first VIU controls the plurality of automobile parts.

Abstract: The present application provides a method of training a natural language processing model, which relates to a field of artificial intelligence, and in particular to a field of natural language processing. A specific implementation scheme includes: performing a semantic learning for multi-tasks on an input text, so as to obtain a semantic feature for the multi-tasks, wherein the multi-tasks include a plurality of branch tasks; performing a feature learning for each branch task based on the semantic feature, so as to obtain a first output result for each branch task; calculating a loss for each branch task according to the first output result for the branch task; and adjusting a parameter of the natural language processing model according to the loss for each branch task. The present application further provides a method of processing a natural language, an electronic device, and a storage medium.

Abstract: Provided are a photosensitive assembly, a camera module, and an electronic device. The electronic device includes an electronic device body and a camera module mounted on the electronic device body. The camera module includes a lens and a photosensitive assembly. The photosensitive assembly includes a circuit board, a photosensitive element, a base, and an adhesive. The circuit board is provided with an accommodation cavity that extends through the circuit board. The photosensitive element is accommodated in the accommodation cavity and electrically connected to the circuit board. The base is disposed on the circuit board. The lens is located in the photosensitive path of the photosensitive element. The adhesive includes a first adhesive portion and a second adhesive portion. The first adhesive portion is located in the accommodation cavity. The second adhesive portion is located outside the accommodation cavity.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by automating the client-side transcoding of video data based on content. For example, an appropriate transcoding configuration can be selected for video data having complex motion or textures. Accordingly, video quality can be improve when complex motions or textures are present.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by automating the client-side transcoding of video data based on content. For example, an appropriate transcoding configuration can be selected for video data having complex motion or textures. Accordingly, video quality can be improve when complex motions or textures are present.

Abstract: The present disclosure provides a multi-lingual model training method, apparatus, electronic device and readable storage medium and relates to the technical field of deep learning and natural language processing. A technical solution of the present disclosure when training the multi-lingual model is: obtaining training corpuses comprising a plurality of bilingual corpuses and a plurality of monolingual corpuses; training a multi-lingual model with a first training task by using the plurality of bilingual corpuses; training the multi-lingual model with a second training task by using the plurality of monolingual corpuses; and completing the training of the multi-lingual model in a case of determining that loss functions of the first training task and second training task converge.

Abstract: A method for fault isolation includes: acquiring a thermal imaging picture of a surface of a to-be-tested chip, the thermal imaging picture being obtained by scanning the to-be-tested chip to which a test signal is applied through an infrared thermal imaging device, and analyzing the thermal imaging picture to obtain a phase angle of each point on the surface of the to-be-tested chip; acquiring a three-dimensional image of the surface of the to-be-tested chip, the three-dimensional image being obtained by scanning the to-be-tested chip to which the test signal is applied through an image scanning device, and analyzing the three-dimensional image to obtain a three-dimensional coordinate of each point on the surface of the to-be-tested chip; calculating a three-dimensional coordinate of the fault in the to-be-tested chip according to the phase angle and the three-dimensional coordinate of each point on the surface of the to-be-tested chip.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by automating the client-side transcoding of video data based on content. For example, an appropriate transcoding configuration can be selected for video data having complex motion or textures. Accordingly, video quality can be improve when complex motions or textures are present.

Abstract: A display module and manufacturing method thereof. The display module comprises a display screen, a first absorption polarizer, a first quarter wave plate, an optical lens component, and a convex lens component in sequence from a display side to a viewing side. The optical lens component and the convex lens component are optically coaxial. The convex lens component comprises a convex lens, a second absorption polarizer, and an optical integrated element, which are laminated in sequence from the viewing side to the display side. The optical integrated element comprises a second quarter wave plate and, on one side surface of the optical integrated element, a coated reflective polarizing film or a nano-imprinted metal grating. The reflective polarizing film or the metal grating is attached to the second absorption polarizer.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by automating the client-side transcoding of video data based on content. For example, an appropriate transcoding configuration can be selected for video data having complex motion or textures. Accordingly, video quality can be improve when complex motions or textures are present.

Abstract: A display module and manufacturing method thereof. The display module comprises a display screen, a first absorption polarizer, a first quarter wave plate, an optical lens component, and a convex lens component in sequence from a display side to a viewing side. The optical lens component and the convex lens component are optically coaxial. The convex lens component comprises a convex lens, a second absorption polarizer, and an optical integrated element, which are laminated in sequence from the viewing side to the display side. The optical integrated element comprises a second quarter wave plate and, on one side surface of the optical integrated element, a coated reflective polarizing film or a nano-imprinted metal grating. The reflective polarizing film or the metal grating is attached to the second absorption polarizer.

Abstract: Provided are a photosensitive assembly, a camera module, and an electronic device. The electronic device includes an electronic device body and a camera module mounted on the electronic device body. The camera module includes a lens and a photosensitive assembly. The photosensitive assembly includes a circuit board, a photosensitive element, a base, and an adhesive. The circuit board is provided with an accommodation cavity that extends through the circuit board. The photosensitive element is accommodated in the accommodation cavity and electrically connected to the circuit board. The base is disposed on the circuit board. The lens is located in the photosensitive path of the photosensitive element. The adhesive includes a first adhesive portion and a second adhesive portion. The first adhesive portion is located in the accommodation cavity. The second adhesive portion is located outside the accommodation cavity.

Abstract: A method for pre-training a language model includes: constructing a pre-training language data set, in which the pre-training language data set comprises unsupervised language data and supervised language data; generating a hierarchical multi-template and multi-task language data set based on the pre-training language data set; and pre-training the language model based on the hierarchical multi-template and multi-task language data set.

Abstract: A method, an apparatus, a device and a storage medium for learning a knowledge representation are provided. The method can include: sampling a sub-graph of a knowledge graph from a knowledge base; serializing the sub-graph of the knowledge graph to obtain a serialized text; and reading using a pre-trained language model the serialized text in an order in the sub-graph of the knowledge graph, to perform learning to obtain a knowledge representation of each word in the serialized text. The knowledge representation learning in this embodiment is performed for entity and relationship representation learning in the knowledge base.

Abstract: The present invention discloses a livestock tracing system and method. The system includes: a feeding module, an adopting and purchasing module, a weighing module, a server, a first commutation module and a second communication module; the feeding module is configured to provide food intake information of livestock and transmit the food intake information to the server via the first communication module; the weighing module is configured to provide weight information of the livestock and transmit the weight information to the server via the second communication module; the adopting and purchasing module is configured to provide vaccine information of the livestock and transmit the vaccine information to the server; and the server is configured to store the food intake information, the weight information and the vaccine information, and obtain corresponding tracing information according to a tracing look-up instruction.

Abstract: A universal wireless charging receiver for an electronic device is provided. The universal wireless charging receiver includes a base casing, a first magnetic shielding element, a power supply module and an induction coil. The first magnetic shielding element, the power supply module and the induction coil are installed in the base casing. The power supply module is located over the first magnetic shielding element. A magnetic field is shielded by the first magnetic shielding element. Consequently, an eddy current is not generated by the power supply module through the magnetic field.

Abstract: A method and apparatus for pre-training a model, a device, a storage medium, and a program product. An embodiment of the method includes: acquiring a sample natural language text; generating N types of prompt words based on the sample natural language text, where N is a positive integer; generating sample input data based on the sample natural language text and the N types of prompt words; and training an initial language model based on the sample input data, to obtain a pre-trained language model.

Abstract: A system, automobile, and method for implementing an electronic control function of an automobile. The system includes a first vehicle integration unit (VIU), an automobile control unit, and a plurality of automobile parts. The automobile control unit includes a first domain controller (DC) or a central computing platform (CCP). The automobile control unit is configured to send first control information to the first VIU. The first VIU is configured to control the plurality of automobile parts based on the first control information. In embodiments of this application, the first VIU controls the plurality of automobile parts.

Abstract: The subject technology determines, by at least one processor, that a value of a capability parameter is not available for a first recipient device, the first recipient device being one of a plurality of recipient devices. The subject technology receives, from the first recipient device, a value of the capability parameter. The subject technology clusters, by at least one processor, the plurality of recipient devices into a plurality of groups of recipient devices based on device capabilities including an available storage space. The subject technology determines, for each group of recipient devices, a set of content parameters compatible with device capabilities of the plurality of recipient devices of a group of client devices. The subject technology generates, for each group of recipient devices, a version of content according to an associated set of content parameters.