Geoffrey Hinton Quotes

Computer vision and machine learning have really started to take off, but for most people, the whole idea of what is a computer seeing when it's looking at an image is relatively obscure.

When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face.

Understanding vision and building visual systems is really understanding intelligence.

As commentators like the American psychologist Gary Marcus have noted, it's extremely difficult to teach a computer to recognise cats. And that's not for want of trying.

One thing that humans still do better than computers is recognize images.

I want to build the next CNN with 'VICE' - it's within my grasp.

Yes, iD is a machine vision and sensor browser for the physical world. That's what we have been working on with Coca-Cola, Verizon, Bank of America and Disney to launch content when an image is recognised.

In the past, Google has used teams of humans to 'read' its street address images - in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically - and with a level of accuracy that meets or beats human operators.

By developing deep learning solutions that are faster, easier, and less expensive to use, Nervana is democratizing deep learning and fueling advances in medical diagnostics, image and speech recognition, genomics, agriculture, finance, and eventually across all industries.

Having been trained as a computer scientist in the '90s, everybody knew that AI didn't work. People tried it. They tried neural nets, and none of it worked.

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

My system uses the speed of components in cameras and cell phones to get four inches of depth through the brain.

Deep learning is already working in Google search and in image search; it allows you to image-search a term like 'hug.' It's used to getting you Smart Replies to your Gmail. It's in speech and vision. It will soon be used in machine translation, I believe.

I think the automation of vision is a much bigger deal than the invention of perspective.

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

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

I'm fascinated by artificial intelligence.

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.

There is huge demand for artificial intelligence technologies.

When you apply computer science and machine learning to areas that haven't had any innovation in 50 years, you can make rapid advances that seem really incredible.

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

When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.

Today, there are industries employing hundreds of thousands of engineers creating artificial intelligence.

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.

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.