Quotes from Jeff Dean

Computers don't usually have a sense of if you have a picture of something what is in that image. And if we can do a good job of understanding what is in an image, that can bring along a lot of new things you can do in applications.

A lot of human learning comes from unsupervised learning where you're just sort of observing the world around you and understanding how things behave.

I think robotics is a really hard problem - to make robots that operate in sort of arbitrary environments, like a big conference room with chairs and stuff.

In Google data centers, our energy usage throughout the year for all our computing needs is 100 percent renewable.

We have a lot of work to do to get really important useful capabilities into people's hands - self-driving cars are going to save an enormous number of lives.

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.

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.

The healthcare space is a very complicated one for a variety of reasons: It's much more regulated than some other kinds of industries, for good reason.

Transportation, with self-driving vehicles, is going to be a big use of machine learning.

I think there are sometimes issues with - no matter where you put a conference, there's always going to be constraints on that. For example, sometimes students studying in the U.S. have trouble leaving the U.S. to go to a conference. So if you hold it outside the U.S. in a particular place, that sometimes creates complications.

There's a lot of potential for machine learning all around the world. We're seeing it in academia, at other companies, in government.

Computers can see, and understand what people say via speech recognition.

I think multimodal kinds of models are pretty interesting - like can you combine text with imagery or audio or video in interesting ways?

Vision I think is going to be an important input. Like, if you're using Google Glass, it's going to be able to look around and read all the text on signs and do background lookups on additional information and serve that. That will be pretty exciting.