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If we want to help Google become something meaningfully different in the future, then that's more likely to happen if we focus on the physical world instead.

I think what's really amazing is that given the scale of the web and getting the compute power we have today, we're starting to see things that appear intelligent but actually aren't semantically intelligent.

A lot of the Google inventions came from engineers just screwing around with ideas. And then management would see them, and we'd say, 'Boy, that's interesting. Let's add some more engineers.'

We want Google to be the third half of your brain.

Google is very much a not-invented-here, build-it-ourselves culture.

For the moment, machines able to 'think' in anything approaching a human sense remain science-fiction. How we should prepare for their potential emergence, however, is a deeply unsettling question - not least because intelligent machines seem considerably more achievable than any consensus around their programming or consequences.

Artificial intelligence is one of 50 things that Watson does. There is also machine learning, text-to-speech, speech-to-text, and different analytical engines - they're like little Lego bricks. You can put intelligence in any product or any process you have.

I look at Google and think they have a strong academic culture. Elegant solutions to complex problems.

Even though Google may do very well, there will always be an alternative to what Google is doing, and people will always have the free choice... because there's no way for us to prevent them from exercising that choice. That is one of the key aspects of why the Internet has been so successful. No technologies can dominate.

I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence.