“I brought this up because we began thinking about using this for place-and-route in ASIC design,” Dean said. “The game of place-and-route is far bigger than the game of go. The problem size is larger, though there isn’t as clear goal as there is with go.”
Google created a learning model for place-and-route, and then set out to find if the tool could generalize. Could it take what it learned on one design and apply it to a new design it had never seen before? The answer was an unambiguous “yes.”
Furthermore, Dean said, “We’ve gotten super-human results on all the blocks we’ve tried so far. It does a little bit better, and sometimes significantly better than humans.”
