Lex Fridman Podcast Yann LeCun: Deep Learning, Convolutional Neural Networks, and Self-Supervised Learning
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Aug 31, 2019 
Yann LeCun, a leading figure in deep learning and the Chief AI Scientist at Facebook, shares his groundbreaking insights on AI. He discusses the critical need for ethical frameworks in AI, navigating the challenges of value misalignment. LeCun explores the history of neural networks, addressing past declines and the potential for collaboration in tech advancements. He delves into self-supervised learning's role in AI, critiques misconceptions, and emphasizes the importance of real-world interactions for developing intelligent systems, particularly in autonomous driving.
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Value Misalignment
- HAL 9000's flaw wasn't evil, but value misalignment: an objective without constraints.
- Designing aligned objectives for AI is like lawmaking for humans, shaping behavior through rules.
Surprising Effectiveness of Deep Learning
- Large neural networks trained on relatively small datasets with stochastic gradient descent work surprisingly well.
- This contradicts traditional machine learning textbook advice, proving empirical results over theoretical limitations.
Intelligence and Learning
- LeCun's intuition for deep learning's success stemmed from observing that brains learn, so machines should too.
- He believed intelligence is inseparable from learning, hence machine learning was the obvious path.