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Turing Post · October 9 · 18 min

Peter Norvig Disagrees With Yann LeCun. Here’s Why

Peter Norvig on the future of AI: what experts get wrong, why language models are world models, and what we should learn when AI can write code. I sat down with the co-author of Artificial Intelligence: A Modern Approach, written with Stuart Russell, to talk about what more than 40 years in AI have taught him. Including why he once thought ordinary businesses couldn’t possibly get online. *We discuss:* - AI agents, from a textbook banner in 1995 to today’s multi-agent systems - Why he disagrees with Yann LeCun about the path to better world models - What Google learned from billions of clicks and a handful of detailed observations - What students should learn when AI can complete the assignment - Trust, concentrated power, and who benefits from AI - What should we still be learning? Share your thoughts in the comments. Read Turing Post: https://www.turingpost.com/ Thank you to The AI Conference https://aiconference.com/ for organizing this conversation. *About Peter Norvig* Peter Norvig is an AI researcher, educator, and co-author with Stuart Russell of Artificial Intelligence: A Modern Approach, adopted by more than 1,500 schools. His website brings together his books, essays, courses, and programming projects. Peter’s website: https://www.norvig.com/ Book and learning resources: https://aima.cs.berkeley.edu/ *Chapters* 00:00 Intro: Peter Norvig on 40+ Years of AI 00:58 Why Experts Get the Future Wrong 02:21 How AI Has Changed Since the 1980s 03:33 What AI Students Still Need to Learn 04:42 The Return of AI Agents 06:11 Do We Need Neuro-Symbolic AI? 07:12 Are Language Models World Models? 08:28 What Today’s AI Systems Are Still Missing 10:00 How AI Is Changing Computer Science Education 11:53 Rethinking Assignments and Exams in the AI Era 13:08 What Excites Peter Norvig Most About AI Today 13:27 Teaching Students to Build with AI 14:46 How AI Is Shifting the Balance of Power 16:31 Can We Trust the Leaders of AI Companies? 17:04 Will AI Power Stay Concentrated? 17:54 Final Thoughts *Did you like the episode? You know the drill:* 📌 Subscribe here and here (https://www.turingpost.com/subscribe) for more conversations with the builders shaping real-world AI. 💬 Leave a comment 👍 Like it 🫶 Thank you for watching and sharing! #PeterNorvig #ArtificialIntelligence #TuringPost

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Peter Norvig on the future of AI: what experts get wrong, why language models are world models, and what we should learn when AI can write code.


I sat down with the co-author of Artificial Intelligence: A Modern Approach, written with Stuart Russell, to talk about what more than 40 years in AI have taught him. Including why he once thought ordinary businesses couldn’t possibly get online.


*We discuss:*

- AI agents, from a textbook banner in 1995 to today’s multi-agent systems

- Why he disagrees with Yann LeCun about the path to better world models

- What Google learned from billions of clicks and a handful of detailed observations

- What students should learn when AI can complete the assignment

- Trust, concentrated power, and who benefits from AI

- What should we still be learning? Share your thoughts in the comments.


Read Turing Post: https://www.turingpost.com/


Thank you to The AI Conference https://aiconference.com/ for organizing this conversation.


*About Peter Norvig*

Peter Norvig is an AI researcher, educator, and co-author with Stuart Russell of Artificial Intelligence: A Modern Approach, adopted by more than 1,500 schools. His website brings together his books, essays, courses, and programming projects.

Peter’s website: https://www.norvig.com/

Book and learning resources: https://aima.cs.berkeley.edu/


*Chapters*

00:00 Intro: Peter Norvig on 40+ Years of AI

00:58 Why Experts Get the Future Wrong

02:21 How AI Has Changed Since the 1980s

03:33 What AI Students Still Need to Learn

04:42 The Return of AI Agents

06:11 Do We Need Neuro-Symbolic AI?

07:12 Are Language Models World Models?

08:28 What Today’s AI Systems Are Still Missing

10:00 How AI Is Changing Computer Science Education

11:53 Rethinking Assignments and Exams in the AI Era

13:08 What Excites Peter Norvig Most About AI Today

13:27 Teaching Students to Build with AI

14:46 How AI Is Shifting the Balance of Power

16:31 Can We Trust the Leaders of AI Companies?

17:04 Will AI Power Stay Concentrated?

17:54 Final Thoughts


*Did you like the episode? You know the drill:* 

📌 Subscribe here and here (https://www.turingpost.com/subscribe) for more conversations with the builders shaping real-world AI. 

💬 Leave a comment

👍 Like it 

🫶 Thank you for watching and sharing!


#PeterNorvig #ArtificialIntelligence #TuringPost

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