Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4

ℹ️ EPISODE INFO

Released

October 20, 2018

Duration

42m

Channel

Lex Fridman Podcast

Watch on YouTube

▶ Open ↗

🎤 SPEAKERS

• Lex Fridman

  host

• Yoshua Bengio

  guest

🧾 EPISODE SUMMARY

In this episode of Lex Fridman Podcast, featuring Lex Fridman and Yoshua Bengio, Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4 explores yoshua Bengio on credit assignment, world models, and AI’s future Yoshua Bengio discusses the gaps between biological and artificial neural networks, focusing on long-term credit assignment, memory, and the need for richer world models. He argues that current deep learning is too shallow in abstraction and overly dependent on passive supervised learning, and that progress requires new training frameworks emphasizing causality, active agents, and disentangled high-level representations. Bengio connects these technical issues to broader themes like symbolic vs. neural approaches, generalization to new distributions, and the importance of machine teaching. He also touches on AI safety, societal impacts, bias and ethics, how science actually progresses, and his own motivations and persistence through the AI winter.

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