Voices in AI – Episode 1: A Conversation with Yoshua Bengio

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In this episode Byron and Yoshua talk about knowledge, unsupervised learning, how the brain learns, creativity, and machine translation.

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Guest

Yoshua Bengio received a PhD in Computer Science from McGill University in Canada in 1991. After two post-doctoral years, one at MITand one at AT&T Bell Labs, he became professor at the Department of Computer Science and Operations Research at the University of Montreal. He is the author of two books and more than 200 publications. The most cited being in the areas of deep learning, recurrent neural networks, probabilistic learning algorithms, natural language processing and manifold learning. He is among the most cited Canadian computer scientists and is or has been Associate Editor of the top journals in machine learning and neural networks.

Transcript

Byron Reese: This is Voice in AI, brought to you by Gigaom. I’m Byron Reese. Today our guest is Yoshua Bengio. Yoshua Bengio received a PhD in Computer Science from McGill University in Canada in 1991. After two post-doctoral years, one at MIT and one at AT&T Bell Labs, he became professor at the Department of Computer Science and Operations Research at the University of Montreal. He is the author of two books and more than two hundred publications. The most cited being in the areas of deep learning, recurrent neural networks, probabilistic learning algorithms, natural language processing and manifold learning. He is among the most cited Canadian computer scientists and is or has been Associate Editor of the top journals in machine learning and neural networks. Welcome to the show, Yoshua.

Yoshua Bengio: Thank you.

So, let’s begin. When people ask you, “What is artificial intelligence,” how do you answer that?

Artificial intelligence is looking for building machines that are intelligent, that can do things that humans can do, and for doing that it needs to have knowledge about the world and then be able to use that knowledge to do useful things.

And it’s kind of kicking the can down the street just a little bit, because there’s unfortunately no consensus definition of what intelligence is either, but it sounds like the way you describe it, it’s just kind of like doing complicated things. So, it doesn’t have an aspect of, you know, it has to respond to its environment or anything like that?

1 Comment

Jasmine Demeester

In unsupervised learning, an AI program is presented with unlabeled, uncategorised information and the system’s methods act on the information without prior training. The outcome relies upon the written methods. Submitting a process to without supervision studying is one way of examining AI.

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