Abstract: A computer-implemented method for classifying video data with improved accuracy includes obtaining, by a computing system comprising one or more computing devices, video data comprising a plurality of video frames; extracting, by the computing system, a plurality of video tokens from the video data, the plurality of video tokens comprising a representation of spatiotemporal information in the video data; providing, by the computing system, the plurality of video tokens as input to a video understanding model, the video understanding model comprising a video transformer encoder model; and receiving, by the computing system, a classification output from the video understanding model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images using mixer neural networks. One of the methods includes obtaining one or more images comprising a plurality of pixels; determining, for each image of the one or more images, a plurality of image patches of the image, wherein each image patch comprises a different subset of the pixels of the image; processing, for each image of the one or more images, the corresponding plurality of image patches to generate an input sequence comprising a respective input element at each of a plurality of input positions, wherein a plurality of the input elements correspond to respective different image patches; and processing the input sequences using a neural network to generate a network output that characterizes the one or more images, wherein the neural network comprises one or more mixer neural network layers.

Abstract: In one embodiment, a computer-implemented method includes obtaining incident data related to a plurality of servers, including a first server. Configuration data is obtained for each of the plurality of servers. The configuration data includes information about a set of one or more configuration items of the first server. A predictive modeler is trained to predict incident characteristics, based at least in part on the incident data and the configuration data. A modification is selected to the set of configuration items of the first server. Predicted incident characteristics of the first server are simulated, by a computer processor, based on the selected modifications. It is recommended that the selected modifications be made to the first server if predetermined criteria are met by the simulation.

Abstract: In one embodiment, a computer-implemented method includes obtaining incident data related to a plurality of servers, including a first server. Configuration data is obtained for each of the plurality of servers. The configuration data includes information about a set of one or more configuration items of the first server. A predictive modeler is trained to predict incident characteristics, based at least in part on the incident data and the configuration data. A modification is selected to the set of configuration items of the first server. Predicted incident characteristics of the first server are simulated, by a computer processor, based on the selected modifications. It is recommended that the selected modifications be made to the first server if predetermined criteria are met by the simulation.