A Quote by Geoffrey Hinton

Now that neural nets work, industry and government have started calling neural nets AI. And the people in AI who spent all their life mocking neural nets and saying they'd never do anything are now happy to call them AI and try and get some of the money.
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.
New methods always look better than old ones. Neural nets are better than logistic regression, support vector machines are better than neural nets, etc.
The first attempts to consider the behavior of so-called "random neural nets" in a systematic way have led to a series of problems concerned with relations between the "structure" and the "function" of such nets. The "structure" of a random net is not a clearly defined topological manifold such as could be used to describe a circuit with explicitly given connections. In a random neural net, one does not speak of "this" neuron synapsing on "that" one, but rather in terms of tendencies and probabilities associated with points or regions in the net.
My main interest is in trying to find radically different kinds of neural nets.
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.
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.
The paradigm for intelligence was logical reasoning, and the idea of what an internal representation would look like was it would be some kind of symbolic structure. That has completely changed with these big neural nets.
Besides publishing its own work, the Google AI China Center will also support the AI research community by funding and sponsoring AI conferences and workshops and working closely with the vibrant Chinese AI research community.
Google or other search engines are examples of AI, and relatively simple AI, but they're still AI. That plus an awful lot of hardware to make it work fast enough.
There are two companies that the AI Fund has invested in - Woebot and Landing AI - and the AI Fund has a number of internal teams working on new projects. We usually bring in people as employees, work with them to turn ideas into startups, then have the entrepreneurs go into the startup as founders.
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 metaphor I've used is... somebody's going to push my family off a cliff pretty soon, and I won't be there to catch them. And that breaks my heart. But I have some time to sew some nets to cushion the fall. So, I can curl up in a ball and cry, or I can get to work on the nets.
I'm a geek through and through. My last job at Microsoft was leading much of the search engine relevance work on Bing. There we got to play with huge amounts of data, with neural networks and other AI techniques, with massive server farms.
Beyond helping other people build AI systems with Deeplearning.ai, I also hope to build some AI systems myself!
Baidu's AI is incredibly strong, and the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone.
I will continue my work to shepherd in this important societal change... In addition to working on AI myself, I will also explore new ways to support all of you in the global AI community so that we can all work together to bring this AI-powered society to fruition.
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