The author seems to be completely clueless. 1. "This is the first time any major cloud service provider has publicly offered customers the opportunity to run t

The author seems to be completely clueless. 1. "This is the first time any major cloud service provider has publicly offered customers the opportunity to run their data on an accelerator from any of the dozens of AI chip startups" No. Google purchased an AI chip startup around 2015 and since February 2018 you could use TPUs on their cloud. The TPU is a hardware accelerator for AI and matrix multiplication. 2. The TensorFlow values in their diagram are "* estimated" which I guess makes sense because TensorFlow & TPU is the biggest competitor to Graphcore. Thanks to XLA, TF2 tends to be a few percent faster on GPU than PyTorch. For example, see here: https://wrosinski.github.io/deep-learning-frameworks/ https://wrosinski.github.io/deep-learning-frameworks/ 3. They compare Graphcore against GPU, but the real comparison target here would be other accelerators, e.g. TPU. Graphcore comes out similarly fast as a V100, meaning it would be roughly 50% slower than a TPU.