Meet Geoffrey Hinton, U of T's Godfather of Deep Learning

Meet Geoffrey Hinton: U of T Professor Emeritus of computer science, an Engineering Fellow at Google, and Chief Scientific Adviser at the Vector Institute for Artificial Intelligence.
In this interview with U of T News, Prof. Hinton discusses his career, the field of artificial intelligence and the importance of funding curiosity-driven scientific research.

[@dexmoe]

"If you know nothing about a topic, get yourself made a professor of it, and nobody will ever ask you again if you actually know anything about it." SOOO DOPE

[@sajanrai9047]

Dex Hunter 😂😂😂

[@thegeneralist7527]

I love how his eyes dart about after he says that, and then he awkwardly smiles like an eccentric mad professor.

[@5Gazto]

Brilliant!

[@Burn1nSun]

Very well made video, it seems like a part of some bigger documentary. If that's the case, I'd sure love to see it!

[@thegeneralist7527]

I just love the way his brain works. "I've never taken a computer science course."

[@pezib8587]

Its so bad that great work isn't directly profitable and alot needs to be done for leaders to absorb that fact

[@thegeneralist7527]

For once Canada is leading the US. Many Canadian AI graduates are joining Fortune 500 companies as fast as they can be produced by Canadian universities. Our prime minister has invested heavily in AI in recognition that this is the next technological revolution. The US president just followed suit this week. My fear is that without extreme effort and prioritization Canada will quickly relinquish its leadership to the US like it so often does. The Canadian brain drain to the US has been going on for decades because the money and opportunities exist in the US, not in Canada.

[@sajanrai9047]

Legend

[@caonima323]

neural network gangster！AI is dead，long live nn！

[@zhongzhongclock]

Reasoning AI is dead, long live NN AI.
Reasoning is highest level of NN, maybe the deepest layer's content in our human brain neural network, we couldn't make fully use of it if we haven't setup its foundation: those shallower layer's content.
Maybe someday, our artificial NN could generate its logic by itself in its deepest layer after our training process.