The Impact of Open Source Technology and Model Size in AI Development

Yann LeCun is VP & Chief AI Scientist at Meta and Silver Professor at NYU affiliated with the Courant Institute of Mathematical Sciences & the Center for Data Science. He was the founding Director of FAIR and of the NYU Center for Data Science. After a postdoc in Toronto he joined AT&T Bell Labs in 1988, and AT&T Labs in 1996 as Head of Image Processing Research. He joined NYU as a professor in 2003 and Meta/Facebook in 2013. He is the recipient of the 2018 ACM Turing Award for "conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing". Huge thanks to David Marcus for helping to make this happen.

1.) The Road to AI OG:

• How did Yann first hear about machine learning and make his foray into the world of AI?
• For 10 years plus, machine learning was in the shadows, how did Yan not get discouraged when the world did not appreciate the power of AI and ML?
• What does Yann know now that he wishes he had known when he started his career in machine learning?

2.) The Next Five Years of AI: Hope or Horror:

• Why does Yann believe it is nonsense that AI is dangerous?
• Why does Yann think it is crazy to assume that AI will even want to dominate humans?
• Why does Yann believe digital assistants will rule the world?
• If digital assistants do rule the world, what interface wins? Search? Chat? What happens to Google when digital assistants rule the world?

3.) Will Anyone Have Jobs in a World of AI:

• From speaking to many economists, why does Yann state "no economist thinks AI will replace jobs"?
• What jobs does Yann expect to be created in the next generation of the AI economy?
• What jobs does Yann believe are under more immediate threat/impact?
• Why does Yann expect the speed of transition to be much slower than people anticipate?
• Why does Yann believe Elon Musk is wrong to ask for the pausing of AI developments?

4.) Open or Closed: Who Wins:

• Why does Yann know that the open model will beat the closed model?
• Why is it superior for knowledge gathering and idea generation?
• What are some core historical precedents that have proved this to be true?
• What did Yann make of the leaked Google Memo last week?

5.) Startup vs Incumbent: Who Wins:

• Who does Yann believe will win the next 5 years of AI; startups or incumbents?
• How important are large models to winning in the next 12 months?
• In what ways does regulation and legal stop incumbents? How has he seen this at Meta?
• Has his role at Meta ever stopped him from being impartial? How does Yan deal with that?