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[Large language models] require enormous amounts of data to reach a level of intelligence that is not that great in the end. And they can't really re… - Yann LeCun
" "[Large language models] require enormous amounts of data to reach a level of intelligence that is not that great in the end. And they can't really reason. They can't plan anything other than things they’ve been trained on. So they're not a road towards what people call “AGI.”
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About Yann LeCun
Yann André LeCun (born 8 July 1960) is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice-President, Chief AI Scientist at Meta. LeCun received the 2018 Turing Award, together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. The three are sometimes referred to as the "Godfathers of AI" and "Godfathers of Deep Learning.
Also Known As
Alternative Names:
LeCun
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YL Cun
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Yann L. Cun
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Y. LeCun
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Y LeCun
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Yann André LeCun
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Yann André Le Cun
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Y. Le Cun
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Yann A. LeCun
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Yann Andre LeCun
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Yann Andre Le Cun
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Additional quotes by Yann LeCun
My problem with sticking too close to nature is that it's like "cargo-cult" science... I don't use neural nets because they look like the brain. I use them because they are a convenient way to construct parameterized non-linear functions with good properties. But I did get inspiration from the architecture of the visual cortex to build convolutional nets.
Don't get fooled by people who claim to have a solution to Artificial General Intelligence, who claim to have AI systems that work "just like the human brain", or who claim to have figured out how the brain works (well, except if it's Geoff Hinton making the claim). Ask them what error rate they get on MNIST or ImageNet.
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