Sebastian Thrun Quotes

This is a magical time for computer programming. We are moving towards the artifical intelligence holy grail of programming the computer to simulate the human brain.

The thing that's going to make artificial intelligence so powerful is its ability to learn, and the way AI learns is to look at human culture.

Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.

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

Note that I am not proposing that AI research be ignored or less funded.

Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.

As the founding lead of the Google Brain team, former director of the Stanford Artificial Intelligence Laboratory, and now overall lead of Baidu's AI team of some 1,200 people, I've been privileged to nurture many of the world's leading AI groups and have built many AI products that are used by hundreds of millions of people.

I'd rather see artificial intelligence than no intelligence.

A lot was happening in A.I. But I also realized it wasn't clear what Salesforce's role in A.I. was. That's when we started acquiring quite a few artificial intelligence companies, maybe a dozen.

Even companies like Baidu and Google, which have amazing AI teams, cannot do all the work needed to get us to an AI-powered society. I thought the best way to get us there would be creating courses to welcome more people to deep learning.

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.

We really believe that long-term, the way AI will drive is similar to the way humans drive - we don't break the problem down into objects and vision and localization and planning. But how long it will take us to get there is questionable.

A lot of what people are calling 'artificial intelligence' is really data analytics - in other words, business as usual. If the hype leaves you asking 'What is A.I., really?,' don't worry, you're not alone.

The popular dystopian vision of AI is wrong for one simple reason: it equates intelligence with autonomy. That is, it assumes a smart computer will create its own goals and have its own will and will use its faster processing abilities and deep databases to beat humans at their own game.

Early AI was mainly based on logic. You're trying to make computers that reason like people. The second route is from biology: You're trying to make computers that can perceive and act and adapt like animals.

The only path to build intelligent machines is to enable it with powerful visual intelligence, just like what animals did in evolution.

I have always been convinced that the only way to get artificial intelligence to work is to do the computation in a way similar to the human brain. That is the goal I have been pursuing. We are making progress, though we still have lots to learn about how the brain actually works.

Artificial intelligence is the science of making machines do things that would require intelligence if done by men.

Artificial Intelligence (AI) is the science of how to get machines to do the things they do in the movies.

I think that the artificial-intelligence people are making a lot of noise recently, claiming that artificial intelligence is making huge progress and we're going to be outstripped by the machines.

You may not realize it, but artificial intelligence is all around us.

The field of artificial intelligence is pushing new boundaries.

IA is something that is proceeding very naturally, in most cases not even recognized by its developers for what it is.

We often attribute 'understanding' and other cognitive predicates by metaphor and analogy to cars, adding machines, and other artifacts, but nothing is proved by such attributions.

The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence.