Top 25 Geoffrey Hinton Quotes

The role of radiologists will evolve from doing perceptual things that could probably be done by a highly trained pigeon to doing far more cognitive things.

I think it’s very clear now that we will have self-driving cars.

We want to take AI and CIFAR to wonderful new places, where no person, no student, no program has gone before.

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.

Machines can do things cheaper and better. We’re very used to that in banking, for example. ATM machines are better than tellers if you want a simple transaction. They’re faster, they’re less trouble, they’re more reliable, so they put tellers out of work.

Everybody right now, they look at the current technology, and they think, ‘OK, that’s what artificial neural nets are.’ And they don’t realize how arbitrary it is. We just made it up! And there’s no reason why we shouldn’t make up something else.

The brain sure as hell doesn’t work by somebody programming in rules.

I had a stormy graduate career, where every week we would have a shouting match. I kept doing deals where I would say, ‘Okay, let me do neural nets for another six months, and I will prove to you they work.’ At the end of the six months, I would say, ‘Yeah, but I am almost there. Give me another six months.’

All you need is lots and lots of data and lots of information about what the right answer is, and you’ll be able to train a big neural net to do what you want.

Irony is going to be hard to get. You have to be master of the literal first. But then, Americans don’t get irony either. Computers are going to reach the level of Americans before Brits.

I am betting on Google’s team to be the epicenter of future breakthroughs.

In the brain, you have connections between the neurons called synapses, and they can change. All your knowledge is stored in those synapses.

In science, you can say things that seem crazy, but in the long run, they can turn out to be right. We can get really good evidence, and in the end, the community will come around.

My father was an entomologist who believed in continental drift. In the early ’50s, that was regarded as nonsense. It was in the mid-’50s that it came back. Someone had thought of it 30 or 40 years earlier named Alfred Wegener, and he never got to see it come back.

I have a Reagan-like ability to believe in my own data.

Humans are still much better than computers at recognizing speech.

The pooling operation used in convolutional neural networks is a big mistake, and the fact that it works so well is a disaster.

We now think of internal representation as great big vectors, and we do not think of logic as the paradigm for how to get things to work. We just think you can have these great big neural nets that learn, and so, instead of programming, you are just going to get them to learn everything.

I am scared that if you make the technology work better, you help the NSA misuse it more. I’d be more worried about that than about autonomous killer robots.

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

The brain has about ten thousand parameters for every second of experience. We do not really have much experience about how systems like that work or how to make them be so good at finding structure in data.

Any new technology, if it’s used by evil people, bad things can happen. But that’s more a question of the politics of the technology.

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.

A deep-learning system doesn’t have any explanatory power.

I got fed up with academia and decided I would rather be a carpenter.