Google aspires to create technologies that solve important problems — and we are relying on machine learning to help us reach our goal.
We believe these technologies can promote innovation and further our mission to organize the world’s information and make it universally accessible and useful.
To implement these algorithms and these advanced technologies, for many years we have been relying on Moore’s law to give us the computing power that we need. But as you know, Moore’s Law is in decline and we cannot hope to get larger speedups in terms of the board anymore.
That’s why, at Google, several years ago we started to work on a project. We made custom hardware for machine learning called Tensor Processing Unit or TPUs.
We have been using TPUs in our data center for several years and found them to give us an order of magnitude better optimized performance per watt for machine learning.
This is roughly equivalent to fast-forwarding technology about 7 years into the future — or 3 generations of Moore’s Law.