It looks like small team of ML coders defeated Google in their own game. Jeremy Howard and team have managed to train Imagenet to 93% accuracy in just 18 minutes, using 16 public AWS cloud instances, each with 8 NVIDIA V100 GPUs, running the fastai and PyTorch libraries. This is a new speed record for training Imagenet to this accuracy on publicly available infrastructure, and is 40% faster than Google’s DAWNBench record on their proprietary TPU Pod cluster and lot more cost effective!
https://www.theverge.com/2018/5/7/17316010/fast-ai-speed-test-stanford-dawnbench-google-intel
https://www.theverge.com/2018/5/7/17316010/fast-ai-speed-test-stanford-dawnbench-google-intel
