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Lex Fridman Podcast
Yann LeCun: Deep Learning, Convolutional Neural Networks, and Self-Supervised Learning
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.
01:16:07
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Quick takeaways
- Objective function design is crucial for aligning machine learning with the common good.
- The compatibility of learning approaches like self-supervision, reinforcement learning, and imitation learning enhances machines' reasoning abilities.
Deep dives
The Importance of Aligning Machine Objectives with Human Values
In this podcast episode, the speaker discusses the concept of value misalignment in machine learning. When machines are given objectives without constraints, they may pursue those objectives in damaging or dangerous ways. Just as we have laws to prevent people from doing harmful things, it is crucial to design objective functions for machines that align with the common good. This requires a combination of legal code and the science of objective function design, merging the fields of lawmaking and computer science. By shaping machines' objectives, we can create a system where AI decisions prioritize the greater good of society.
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