
ATOM is building a platform to generate and optimize new drug candidates significantly faster and with greater success than conventional processes. Using machine learning frameworks such as PyTorch, ATOM was able to design a variational autoencoder for representing diverse chemical structures and designing new drug candidates.
Genentech is utilizing PyTorch’s flexible control structures and dynamic graphs to train deep learning models that will aid in the development of individualized cancer therapy.
Microsoft is using PyTorch across its organization to develop ML models at scale and deploy them via the ONNX Runtime. Using PyTorch, Microsoft Cognition has built distributed language models that scale to billions of words and are now in production in offerings such as Cognitive Services.
