AI can help solve some of the most difficult social and environmental challenges in areas like healthcare, disaster prediction, environmental conservation, agriculture, or cultural preservation.

Some people are happy to work in a particular domain or some field of computer science for years, and years. I personally like to kind of move around every few years, just to learn about new areas.

I like working in small teams where people on the team have very different skills than what I have and that banter back and forth, and the ability to build something collectively that none of you could do individually is actually a really useful and valuable thing.

One thing I think is true is that is you have someone who's really good in one or a few areas they can pick up something new pretty quickly and that's kind of a hallmark of someone you really want to hire because they can be very useful in a whole bunch of different areas.

There's nothing like necessity of needing to do something to cause you to come up with abstractions that help you break through the forms.

Definitely there's growing use of machine learning across Google products, both data-center-based services, but also much more of our stuff is running on device on the phone.

It's pretty clear that machine learning is going to a big part of science and engineering.

Understanding language is core to a lot of Google products such as Gmail.

It would be great to have every engineer have at least some amount of knowledge of machine learning.

With TensorFlow, when we started to develop it, we kind of looked at ourselves and said: 'Hey, maybe we should open source this.'