Larry Page Quotes

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.

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.

The problem with Google is you have 360 degrees of omnidirectional information on a linear basis, but the algorithms for irony and ambiguity are not there. And those are the algorithms of wisdom.

Google will fulfill its mission only when its search engine is AI-complete. You guys know what that means? That's artificial intelligence.

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.

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.

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."

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

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.

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

AI2 was born from a desire to create a system that could truly reason about knowledge, rather than just offer up what had been written on a subject before.

I'd rather see artificial intelligence than no intelligence.

Everyone talks about how much data's in the world. Except, actually, 80% of it is pretty blind to computers. I mean, it can store it. But if it's a movie, a poem, a song, it doesn't know what it's actually saying or doing.

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.

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.

Google seems to be more intelligent than some people.

Without your data, Google couldn't pursue the dream of trying to figure out what you're really thinking when you're asking a question, of trying to discern, from the imprecision of your language, the exact answer you're looking for.

My own work falls into a subset of AI that is about building artificial emotional intelligence, or Emotion AI for short.

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.

There's a great phrase, written in the '70s: 'The definition of today's AI is a machine that can make a perfect chess move while the room is on fire.' It really speaks to the limitations of AI. In the next wave of AI research, if we want to make more helpful and useful machines, we've got to bring back the contextual understanding.

I am a brain, Watson. The rest of me is a mere appendix.

Although I'm not prepared to move up my prediction of a computer passing the Turing test by 2029, the progress that has been achieved in systems like Watson should give anyone substantial confidence that the advent of Turing-level AI is close at hand. If one were to create a version of Watson that was optimized for the Turing test, it would probably come pretty close.

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

Computers ought to help people find their own best path through lots of textual information.