Tim Berners-Lee Quotes

The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.

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

The deep learning techniques, while relatively easy to learn, are quite foreign to traditional engineering modalities. It takes a different mindset and a relaxation of the presumption of control. The practitioners are like magi, sequestered from the rest of a typical engineering process.

A new, a vast, and a powerful language is developed for the future use of analysis, in which to wield its truths so that these may become of more speedy and accurate practical application for the purposes of mankind than the means hitherto in our possession have rendered possible.

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.

To make real progress in A.I., we have to overcome the big challenges in the area of common sense.

There's a long history of artificial intelligence programs that try to mimic what the brain is doing, but they've all fallen short.

The whole concept of data science is that the software becomes the expert, and you, as the average user, are able to understand what's going on.

We want to build intelligence that augments human abilities and experiences.

Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here's one example of something it cannot do: have a meaningful conversation.

Watson augments human decision-making because it isn't governed by human boundaries. It draws together all this information and forms hypotheses, millions of them, and then tests them with all the data it can find. It learns over time what data is reliable, and that's part of its learning process.

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.

The future of Windows is to let the computer see, listen and even learn.

Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we'll augment our intelligence.

Think about when a digital business marries up with what I'll call 'digital intelligence.' It is the dawn of a new era about being a 'cognitive' business. When every product, every service, how you run your company can actually have a piece that learns and thinks as part of it, you will be a cognitive business.

If it's digital, it will be cognitive. If you think that, you're going to change the way you run a business.

I believe this artificial intelligence is going to be our partner. If we misuse it, it will be a risk. If we use it right, it can be our partner.

I've always believed that human learning is the result of relatively simple rules combined with massive amounts of hardware and massive amounts of data.

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.

One of the interesting applications of symbolic systems is artificial intelligence, and I spent some time thinking about how to create a brain that operates the way ours does.

Artificial intelligence... I've been following that since I was in high school.

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.

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.

Google seems to be more intelligent than some people.