Jeremy Howard: fast.ai Deep Learning Courses and Research | Lex Fridman Podcast #35

ℹ️ EPISODE INFO

Released

August 27, 2019

Duration

1h 44m

Channel

Lex Fridman Podcast

Watch on YouTube

▶ Open ↗

🎤 SPEAKERS

• Lex Fridman

  host

• Jeremy Howard

  guest

• Narrator

  other

🧾 EPISODE SUMMARY

In this episode of Lex Fridman Podcast, featuring Lex Fridman and Jeremy Howard, Jeremy Howard: fast.ai Deep Learning Courses and Research | Lex Fridman Podcast #35 explores jeremy Howard on democratizing deep learning, tools, and real impact Jeremy Howard discusses his path from early programming and music to founding fast.ai, emphasizing a lifelong focus on practical data work and useful tools. He contrasts different programming languages and paradigms, arguing current Python-based deep learning stacks are powerful but fundamentally constrained for real innovation, and outlines why he’s betting on Swift and MLIR-style compilers. A large portion of the conversation centers on making deep learning accessible—through fast.ai courses, better tooling, and cloud setups—so domain experts (especially in areas like medicine) can solve real problems with limited data and compute. He also critiques academic incentives, over-reliance on big data and big compute, and stresses the ethical responsibilities and labor implications of AI.

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