Intel adds its new Data Center GPU Flex Series to Pluggable Devices, something Intel is calling Intel Extension for TensorFlow, available right now.

Ideally, you’d use a computer with a GPU but that’s optional, the difference being between three or twenty-four hours of training.

There is no real middle ground when it comes to TensorFlow use cases. Most implementations take place either in a single node or at the drastic Google-scale, with few scalability stories in between.

If you are looking to get started with TensorFlow yourself, we’ve covered quite a few tutorials. On the other hand, we talk quite a bit about Fourier transforms, too.

Every major deep-learning framework, such as TensorFlow, PyTorch, and others, is already GPU-accelerated, so data scientists and researchers can get up to speed without GPU programming.