In 2009, the team, led by Geoffrey Hinton, had implemented generalized backpropagation and other improvements which allowed generation of neural networks with substantially higher accuracy, for instance a 25% reduction in errors in speech recognition. Google assigned multiple computer scientists, including Jeff Dean, to simplify and refactor the codebase of DistBelief into a faster, more robust application-grade library, which became TensorFlow. Its use grew rapidly across diverse Alphabet companies in both research and commercial applications. Starting in 2011, Google Brain built DistBelief as a proprietary machine learning system based on deep learning neural networks.
