There’s still a lot of potential to build more efficient and larger scale computing systems, particularly ones tailored for machine learning. And I think the basic research that has been done in the last 5 or 6 years still has a lot of room to be applied in all the ways that it should be. We’ll collaborate with our Google product colleagues to get a lot of these things out into real-world uses.

But we also are looking at what are the next major problems on the horizon, given what we can do today and what we can’t do. We want to build systems that can generalize to a new task. Being able to do things with much less data and with much less computation is going to be interesting and important.

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