Larry Page Quotes

Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the Web. It would understand exactly what you wanted, and it would give you the right thing. We're nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.

I think people need to understand that deep learning is making a lot of things, behind-the-scenes, much better. Deep learning is already working in Google search, and in image search; it allows you to image search a term like "hug."

AI does not keep me up at night. Almost no one is working on conscious machines. Deep learning algorithms, or Google search, or Facebook personalization, or Siri or self driving cars or Watson, those have the same relationship to conscious machines as a toaster does to a chess-playing computer.

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

When people speak of creating superhumanly intelligent beings, they are usually imagining an AI project.

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

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.

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.

You could claim that moving from pixelated perception, where the robot looks at sensor data, to understanding and predicting the environment is a Holy Grail of artificial intelligence.

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.

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.

If you step back a little and say we want to do A.I., then you will realize that A.I. needs knowledge, reasoning, and explanation.

One of our big goals in search is to make search that really understands exactly what you want, understands everything in the world. As computer scientists, we call that artificial intelligence.

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.

From one perspective, we're in the early stage in artificial intelligence, but exponentials start out slowly, and then they take off.

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.

I'm fascinated by artificial intelligence.

There is huge demand for artificial intelligence technologies.

When you use Google, do you get more than one answer? Of course you do. Well, that's a bug. We have more bugs per second in the world. We should be able to give you the right answer just once. We should know what you meant.

The ultimate search engine would basically understand everything in the world, and it would always give you the right thing. And we're a long, long ways from that.

If you want to solve very complex problems, you will have to end up letting machines work out a lot of the details for themselves, and in ways that we don't understand what they are doing.

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

I'm working on artificial intelligence. Actually, natural language understanding, which is to get computers to understand the meaning of documents.