Beyond: suggested readings and resources to learn more
Learning more
Beyond: Suggested readings and resources to learn more
Gábor’s collection of recommended readings, listening. Wide variety from practical to business and nerdy stuff.
Basics
Core readings
- Ethan Mollick “Co-Intelligence: Living and Working with AI” Penguin Random House 2024
- Anton Korinek “Generative AI for Economic Research: Use Cases and Implications for Economists,” Journal of Economic Literature 61(4) December 2024 Update 1–74
Important reviews
- Review of LLMs by Simon Willison
- Machines of Loving Grace Dario Amodei
Prompting
- AI Frontiers in Plain English: Prompt Engineering guide from Google with LM Notebook Part 1. LLM output configurations + others
Understanding LLMs
- Glossary of LLM terms Glossary of LLM Terms
- Financial Times: How AI Large Language Models Work
- The Economist: How Large Language Models Work
- Thinking like AI
- What’s an LLM context window and why is it getting larger? IBM research on context window
AI and business / management
- Strategy in business Build a winning AI strategy, HBR 2023
- Interview with Rafella Sadun on Reskilling workforce with AI from MIT Sloan Review
New methods and tools
- Best video series on introduction to neural networks and LLMs. [3blue1brown youtube playlist] (https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi) 7 times 20-30mins videos, from zero to conversational understanding
- Very usefil video on skills and Claude’s skill creator.
Additional content
Consequence of AI
How NLP was killed by Transformers/ LLMs in Quant magazine 2025 April
Amazing compilation of videos by leading AI Lab founders and leaders on the future of AI by Nature, published on 14 November 2025. Mustafa Suleyman on fears is one of my favourite short vids here.
Video Resources on AI
- Andrej Karpathy Introduction to Large Language Models – 1hs overview, a great start
- Andrej Karpathy Deep Dive into LLMs like ChatGPT – 3hs comprehensive updated version of the Intro video
- Andrej Karpathy: “Let’s build GPT: from scratch, in code, spelled out”
- Interview with a great Sendhil Mullainathan on direction AI
Deeper stuff on AI
- Artificial intelligence learns to reason in Science