Reflections on AI

Reading List

I will keep track of books, articles, interviews, courses, and other content I want to consume to learn about AI here.

12 tentative ideas for US AI policy Luke Muehlhauser
Learning to summarize with human feedback OpenAI
On Emergence and Explanation Santa Fe Institute
Learning from human preferences OpenAI
Discovering Latent Knowledge in Language Models Without Supervision Collin Burns
Self-supervised learning: The dark matter of intelligence Yann LeCun
What developers need to know about generative AI GitHub
The Vulnerable World Hypothesis Nick Bostrom
Inside View interview with Simeon Campos
Liv Boeree on Moloch, Beauty Filters, Game Theory, Institutions, and AI
Lennart Heim on the AI Triad: Compute, Data, and Algorithms
Nathan Labenz on the Cognitive Revolution, Red Teaming GPT-4, and Potential Dangers of AI
Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting Miles Turpin
Attention is All You Need Summary Google
Moore's Law for Everything Summary Sam Altman
AGI Ruin: A List of Lethalities Summary Eliezer Yudkowsky
FLI interview with Connor Leahy Summary
Bankless interview with Paul Christiano Summary
AI Alignment Is Turning from Alchemy Into Chemistry Summary Alexey Guzey
Lex Fridman interview with Yann LeCun Summary
The Superintelligent Will Summary Nick Bostrom
The Basic AI Drives Summary Steve Omohundro
Lex Fridman interview with Max Tegmark Summary
On AutoGPT Summary Zvi Mowshowitz
Ezra Klein interview with Sam Altman Summary
Eight Things to Know about Large Language Models Summary Sam Bowman
Our approach to AI safety Summary OpenAI
Lex Fridman interview with Eliezer Yudkowsky Summary
Lex Fridman interview with Sam Altman Summary
Kara Swisher interview with Sam Altman Summary