Abstract: The present application discloses a method, a device, equipment, and storage medium for determining a sensor solution, where the method includes: establishing a simulated unmanned vehicle and a simulation scene, where the simulation scene is used for the simulated unmanned vehicle to perform simulation driving; determining a first sensor solution according to a initialization parameter, and determining, according to the first sensor solution, simulation data generated by the simulated unmanned vehicle during the simulation driving in the simulation scene; and; and determining a first perception parameter of the first sensor solution according to the simulation data, and correcting the first sensor solution according to the first perception parameter to obtain a sensor solution applied to an unmanned vehicle.

Abstract: The disclosure discloses a method for generating a conversation, an electronic device, and a storage medium. The detailed implementation includes: obtaining a current conversation and historical conversations of the current conversation; selecting multiple reference historical conversations from the historical conversations and adding the multiple reference historical conversations to a temporary conversation set; and generating reply information of the current conversation based on the current conversation and the temporary conversation set.

Abstract: Embodiments of the present disclosure disclose a method for processing tasks in parallel, a device and a storage medium, and relate to a field of artificial intelligent technologies. The method includes: determining at least one parallel computing graph of a target task; determining a parallel computing graph and an operator scheduling scheme based on a hardware execution cost of each operator task of each of the at least one parallel computing graph in a cluster, in which the cluster includes a plurality of nodes for executing the plurality of operator tasks, and each parallel computing graph corresponds to at least one operator scheduling scheme; and scheduling and executing the plurality of operator tasks of the determined parallel computing graph in the cluster based on the determined parallel computing graph and the determined operator scheduling scheme.

Abstract: A method and apparatus for processing a table, a device, a storage medium and a product. An implementation of the method comprise: receiving a content query request for a target table; acquiring a target tree structure of the target table according to the content query request; where, the target tree structure is obtained by performing absorbing processing and merging processing on at least one target cell in the target table; acquiring to-be-queried content in the content query request; and querying target content matching the to-be-queried content from the target tree structure.

Abstract: An apparatus and a method for executing a customized production line using an artificial intelligence development platform, a computing device and a computer readable storage medium are provided. The apparatus includes: a production line executor configured to generate a native form of the artificial intelligence development platform based on a file set, the native form to be sent to a client accessing the artificial intelligence development platform so as to present a native interactive page of the artificial intelligence development platform; and a standardized platform interface configured to provide an interaction channel between the production line executor and the artificial intelligence development platform. The production line executor is further configured to generate an intermediate result by executing processing logic defined in the file set and to process the intermediate result by interacting with the artificial intelligence development platform via the standardized platform interface.

Abstract: A method for automated parking, a device, and a storage medium, which relate to a field of automated parking. The method for automated parking includes: determining, based on a historical location of a vehicle over a first time period, a frequented region associated with one or more candidate parking routes for the vehicle; acquiring the one or more candidate parking routes for the vehicle based on one or more historical parking routes of the vehicle in the frequented region, where the one or more historical parking routes include a driving-in route and/or a driving-out route; and providing the vehicle with the acquired one or more candidate parking routes in response to determining that the vehicle is in the frequented region, for the vehicle to drive in or drive out.

Abstract: The present disclosure discloses a method and apparatus for generating animation. An implementation of the method may include: processing a to-be-processed material to generate a normalized text; analyzing the normalized text to generate a Chinese pinyin sequence of the normalized text; generating a reference audio based on the to-be-processed material; and obtaining a animation of facial expressions corresponding to the timing sequence of the reference audio based on the Chinese pinyin sequence and the reference audio.

Abstract: A method for discovering causality from data includes acquiring to-be-processed data, and obtaining a covariance matrix of the to-be-processed data; determining a first target column in the covariance matrix, taking the number of columns of the first target column as a first place in a rearrangement sequence, and obtaining a first upper triangular matrix according to the first target column; determining a position of the number of columns of the covariance matrix other than the first target column except the first place in the rearrangement sequence according to the first target column and the first upper triangular matrix, and obtaining an upper triangular matrix in each position determination; obtaining an adjacency matrix according to an upper triangular matrix and a rearrangement sequence obtained in final position determination; and generating directed acyclic graph (DAG) by using the adjacency matrix, and taking the DAG as causality discovery result of the to-be-processed data.

Abstract: The present disclosure provides a method and apparatus for writing data in an append mode, a device and a storage medium. The present disclosure relates to the field of cloud storage technology, and can be applied to a cloud platform. The method includes: acquiring to-be-written data, and writing the to-be-written data into a magnetic disk; writing first index information of the to-be-written data in a memory; storing, in response to determining that the number of pieces of second index information is greater than a first preset threshold, the second index information into storage hardware, the second index information including the first index information; and writing first identifier information corresponding to the second index information in the memory.

Abstract: A method for recognizing product detection missed is performed by an electronic device. The method includes: obtaining a surveillance video collected by a surveillance device on a product production line; generating product detection results by inputting video frames of the surveillance video into a product detection model; generating detecting action recognition results by inputting the video frames of the surveillance video into an action recognition model; and determining whether product detection is missed based on the product detection results and the detecting action recognition results.

Abstract: A method for training a click rate prediction model includes: obtaining sample feature information and a label value, in which the sample feature information includes feature information of a sample user and feature information of a target object, and the label value is configured to indicate whether the sample user interacts with the target object; obtaining a plurality of adjacent matrixes for feature interaction by processing the feature information of the target object based on the hypernetwork module; obtaining a click rate prediction value of the sample user on the target object using the prediction module, according to the sample feature information and the plurality of adjacent matrixes; and training the click rate prediction model according to the label value and the click rate prediction value.

Abstract: The present application discloses a test method and apparatus for an application, an electronic device, and a storage medium, relates to the field of test technologies, and may be applied to the fields of artificial intelligence and big data technologies. A specific solution includes: obtaining, from a target APP, a first recommended item for being selected, where the target APP is an APP of interest to a target user; triggering the target APP to open a first sub-page corresponding to the first recommended item for being selected when the first recommended item for being selected matches target information of interest, where the target information of interest is information of interest to the target user; and determining a test result for the target APP based on a matching degree between a first target recommended item and the target information of interest, where the first target recommended item includes a recommended item generated by the target APP after the first sub-page is opened on the target APP.

Abstract: The present disclosure provides a method for graph computing, an electronic device and a non-transitory computer-readable storage medium. An execution engine for managing execution of the graph computing is configured in a CPU. One or more interface functions running in a GPU for processing parameters of the graph computing are configured. During the execution of the graph computing, the one or more interface functions are called by the execution engine through a graph computing interface. The interface functions are executed in the GPU in parallel through multiple parallel threads. The interface functions are configured to process a plurality of graph vertexes in parallel. The multiple parallel threads are configured to feedback respective execution results of the interface functions to the execution engine. The graph computing is completed by the execution engine according to the execution results.

Abstract: A method for training a trajectory planning model, an apparatus, and computer storage medium are provided. The method may include: obtaining an image of a physical environment in which a vehicle is located via at least one sensor of the vehicle, the image including multiple objects surrounding the vehicle; obtaining a feature chart indicating multiple initial trajectory points of the vehicle in the image from a trajectory planning model based on the image; identifying the image to determine in the image a first area associated with a road object in multiple objects and a second area associated with a non-road object in the multiple objects; determining a planning trajectory point based on positional relationship of the multiple initial trajectory points with respect to the first area and the second area; and training a trajectory planning model based on the planning track point and the actual trajectory point of the vehicle.

Abstract: A method for acquiring point of interest (POI) representation information, includes: acquiring a POI relationship graph, and acquiring a node relationship set of each node on the POI relationship graph based on the POI relationship graph, in which the POI relationship graph includes edges representing relationships between nodes of POIs, and the node relationship set includes relationship paths where the node reaches all second-order neighbor nodes via any one first-order neighbor node; acquiring a spatial distance matrix between the node and corresponding second-order neighbor nodes; and determining first POI representation information of the node based on the node relationship set of the node and the spatial distance matrix.

Abstract: An information acquisition method and apparatus, an electronic device, and a storage medium are suggested, which relates to the field of artificial intelligence (AI) such as machine learning and distributed storage. The method may include: determining hardware devices located on a to-be-processed node in response to determining that a trigger condition is met; selecting an x processing unit (XPU) from the hardware devices; and acquiring predetermined information of the XPU by using a system management interface (SMI) management tool corresponding to the XPU, the predetermined information including model information of the XPU.

Abstract: Provided are a method and apparatus for processing map information, a device, and a storage medium which relate to the field of computer technology and, in particular, to the fields of intelligent transportation and computer vision technology. The specific implementation includes that an object in an image for query is recognized to obtain an object recognition result and that a target point of interest matching the image for query is selected from at least one candidate point of interest of an electronic map according to the object recognition result.

Abstract: The present disclosure provides an ultrasonic radar array, an obstacle detection method and system. The method includes: obtaining obstacle information collected by ultrasonic radars in an ultrasonic radar array in an obstacle scenario; judging false detection and missed detection for the obstacle information collected by ultrasonic radars according a preset rule; processing the obstacle information collected by the ultrasonic radars according to the judgement result; determining a position of the obstacle according to the processed obstacle information collected by the ultrasonic radars.

Abstract: The present disclosure provides a method and system for processing an obstacle detection result of an ultrasonic sensor array. The method comprises: obtaining obstacle coordinates collected by ultrasonic sensors in an ultrasonic sensor array; inputting the obstacle coordinates collected by ultrasonic sensors in the ultrasonic sensor array into a pre-trained neural network model, to obtain true or false labels for the obstacle coordinates collected by the ultrasonic sensors output by the pre-trained neural network model; process the obstacle coordinates collected by the ultrasonic sensors in the ultrasonic sensor array according to the true or false labels. The present disclosure improves the accuracy in the obstacle detection of the ultrasonic sensor array, avoids detection error and omission and improves the driving safety.

Abstract: A multi-modal pre-training model acquisition method, an electronic device and a storage medium, which relate to the fields of deep learning and natural language processing, are disclosed. The method may include: determining, for each image-text pair as training data, to-be-processed fine-grained semantic word in the text; masking the to-be-processed fine-grained semantic words; and training the multi-modal pre-training model using the training data with the fine-grained semantic words masked.