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Yann LeCun: Deep Learning, Convolutional Neural Networks, and Self-Supervised Learning
Lex Fridman Podcast
Value of Active Learning in Machine Learning
Active learning, a form of self-supervised learning, involves the system seeking human help for selecting parts that need further annotation. Although it enhances efficiency and learning in machines, it does not significantly increase machine intelligence. There is no conflict between self-supervised, reinforcement, supervised, imitation, or active learning, with self-supervised learning being a foundation for all. For instance, it takes 80 hours for machines to learn to play complex games using traditional reinforcement learning, while humans can reach the same level in 15 minutes.
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