Geoffrey Hinton Quotes

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.

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."

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.

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.

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

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

There's a very long tail of all sorts of creative products - beyond our core web search, image search and advertising businesses - that are powered by deep learning.

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.

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

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.

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

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

Understanding vision and building visual systems is really understanding intelligence.

I think the way we're doing computer vision is just wrong.

Deep learning is a subfield of machine learning, which is a vibrant research area in artificial intelligence, or AI.

Artificial intelligence is the science of making machines do things that would require intelligence if done by men.

Pretend I asked, now answer the question.

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

We may hope that machines will eventually compete with men in all purely intellectual fields. But which are the best ones to start with? Many people think that a very abstract activity, like the playing of chess, would be best. It can also be maintained that it is best to provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English.

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.

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.

When I was building robots in the early 1990s, the problems of voice recognition, image understanding, VOIP, even touchscreen technologies - these were robotics problems.

There is huge demand for artificial intelligence technologies.

The real goal of AI is to understand and build devices that can perceive, reason, act, and learn at least as well as we can.