Tim Berners-Lee Quotes

The Semantic Web isn't inherently complex. The Semantic Web language, at its heart, is very, very simple. It's just about the relationships between things.

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

I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.

Interactive computers and software will, I think, provide a less costly method of doing some kinds of inquiry, in knowledge acquisition and even reasoning and interaction.

I will argue that in the literal sense the programmed computer understands what the car and the adding machine understand, namely, exactly nothing.

By 2020, most home computers will have the computing power of a human brain. That doesn't mean that they are brains, but it means that in terms of raw processing, they can process bits as fast as a brain can. So the question is, how far behind that is the development of a machine that's as smart as we are?

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

We have to make machines understand what they're doing, or they won't be able to come back and say, 'Why did you do that?'

We've seen computers play chess and beat grand masters. We've seen computers drive a car across a desert. But interestingly, playing chess is easy, but having a conversation about nothing is really difficult for a computer.

Web pages are designed for people. For the Semantic Web, we need to look at existing databases.

If you write a blog post, you've got something to say; you're not just creating words and synonyms. We'd like the computers to actually pick up on that semantic meaning.

The big question society will have to answer is whether it wants computers thinking like humans.

Artificial intelligence is always 20 years away.

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.

In order to be truly intelligent, computers must understand - that is probably the critical word.

None of us today know how to get computers to learn with the speed and flexibility of a child.

If we can make computers more intelligent - and I want to be careful of AI hype - and understand the world and the environment better, it can make life so much better for many of us. Just as the Industrial Revolution freed up a lot of humanity from physical drudgery I think AI has the potential to free up humanity from a lot of the mental drudgery.

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.

Understanding of natural language is what sometimes is called 'AI complete,' meaning if you can really do that, you can probably solve artificial intelligence.

I'm trying to use AI to make the world a better place. To help scientists. To help us communicate more effectively with machines and collaborate with them.

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.

Think of ChatGPT as a blurry JPEG of all the text on the Web. It retains much of the information on the Web, in the same way that a JPEG retains much of the information of a higher-resolution image, but, if you’re looking for an exact sequence of bits, you won’t find it; all you will ever get is an approximation. But, because the approximation is presented in the form of grammatical text, which ChatGPT excels at creating, it’s usually acceptable. You’re still looking at a blurry JPEG, but the blurriness occurs in a way that doesn’t make the picture as a whole look less sharp.

In A.I., the holy grail was how do you generate internal representations.

I think a lot of jobs, with that additional artificial intelligence, we can augment human capabilities and impact.

Human players have their strengths and weaknesses and Watson is the same way. He just has different strengths and weaknesses than most people.