Abstract: A method to predict that a text file contains source code written in one or more of a plurality of source code programming languages involves creating a feature vector comprising a plurality of values, wherein each value represents a corresponding piece of text found in the text file. Then, during an inference workflow with a neural network model, embedding representation values identified for each value in the feature vector. An overall embedding representation value is calculated for the feature vector based on the obtained embedding representation values. A plurality of class label prediction values is then created, based on the overall embedding representation value and a plurality of class labels corresponding to the plurality of source code programming languages. Finally, a prediction is made as to the source code programming language in which the source code is written in the text file based on the plurality of class label prediction values.

Abstract: A method for autonomous vehicle test data distribution and analysis is described. The method includes uploading driving session data from a computer of a drive site to a network attached storage of the drive site. The method also includes uploading the driving session data from the network attached storage of the drive site to a cloud-based storage location. The method further includes distributing the driving session data from the cloud-based storage location and a work unit to at least one research site separate from the drive site. The method also includes processing, by the at least one research site, the driving session data according to an analysis/processing task associated with the work unit.

Abstract: A method for autonomous vehicle test data distribution and analysis is described. The method includes uploading driving session data from a computer of a drive site to a network attached storage of the drive site. The method also includes uploading the driving session data from the network attached storage of the drive site to a cloud-based storage location. The method further includes distributing the driving session data from the cloud-based storage location and a work unit to at least one research site separate from the drive site. The method also includes processing, by the at least one research site, the driving session data according to an analysis/processing task associated with the work unit.