Google uses its own deep learning chip for artificial intelligence (AI)
▻https://cloudplatform.googleblog.com/2016/05/Google-supercharges-machine-learning-tasks-with-custom-chi
Tensor Processing Unit (TPU), a custom ASIC we built specifically for machine learning — and tailored for #TensorFlow.
We’ve been running TPUs inside our data centers for more than a year, and have found them to deliver an order of magnitude better-optimized performance per watt for machine learning.
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TPU is tailored to machine learning applications, allowing the chip to be more tolerant of reduced computational precision, which means it requires fewer transistors per operation. Because of this, we can squeeze more operations per second into the silicon, use more sophisticated and powerful machine learning models and apply these models more quickly, so users get more intelligent results more rapidly. A board with a TPU fits into a hard disk drive slot in our data center racks.
TPUs already power many applications at Google, including RankBrain, used to improve the relevancy of search results and Street View, to improve the accuracy and quality of our maps and navigation. AlphaGo was powered by TPUs in the matches against Go world champion, Lee Sedol, enabling it to “think” much faster and look farther ahead between moves.