Google reveals the mysterious custom hardware that powers AlphaGo

Tweet Share The machine learning community has coalesced around Google’s TensorFlow library. Interestingly, one major holdout was DeepMind, which did most of its research on the Torch7 library. Then, late last month, DeepMind announced it was moving to TensorFlow as well — it was already using it for portions of AlphaGo. Why does any of this matter? Well, with standardization comes the opportunity for optimization, and Google has gone wild with optimization in this case. On its blog, Google just announced it has built a custom “TPU” (Tensor Processing Unit) ASIC chip for machine learning and it’s specifically optimized for TensorFlow. How optimized? About an order of magnitude better performance per watt than the alternatives (Nvidia GPUs, presumably), which Google equates to leaping forward three generations of Moore’s Law. Almost any…


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