Lex Fridman Podcast Jeremy Howard: fast.ai Deep Learning Courses and Research
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Aug 27, 2019 
Jeremy Howard, founder of fast.ai and a distinguished AI researcher, discusses making deep learning accessible to all. He explores the advantages of self-funding startups, shares innovative learning strategies, and reveals his journey in programming. The conversation touches on using AI to revolutionize healthcare and the balance between privacy and data use. Howard also highlights hands-on learning in AI, success stories from his courses, and the societal implications of artificial intelligence, advocating for ethical considerations in its development.
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Array-Oriented Programming
- Jeremy Howard champions J, an array-oriented language derived from APL, for its expressiveness and composability.
- He highlights the power of array-oriented programming, contrasting it with imperative and object-oriented paradigms.
Hackable Languages
- Jeremy Howard emphasizes the importance of "hackable" languages like Swift for deep learning innovation.
- Python's slow speed limits hackability, hindering research in areas like RNNs and sparse CNNs.
Enlitic and AI in Medicine
- Jeremy Howard founded Enlitic, the first company applying deep learning to medicine, addressing the global doctor shortage.
- He aimed to empower healthcare workers with AI-driven diagnostics and treatment planning, especially in developing countries.