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

Additional readings

Consequence of AI

How NLP was killed by Transformers/ LLMs in Quant magazine 2025 April

Blogs, newsletters

Blog post by Posit Text Summarization, Translation, and Classification using LLMs: mall does it all
Simon Willis blog post LLM and coding
Ethan Mollick substack: One useful thing
Alpha Signal newsletter
How Andrej Karpathy is adopting AI assisted coding.
Blog by Anthropic Claude explains – cool collection on ideas for coding with Claude

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

--- title: "Beyond: suggested readings and resources to learn more" Date: "2025-06-02" --- ::: {.hero-section} ::: {.container} ::: {.hero-title} Learning more ::: ::: {.hero-subtitle} 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](https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/) - Anton Korinek "Generative AI for Economic Research: Use Cases and Implications for Economists," [Journal of Economic Literature 61(4) December 2024 Update 1–74](https://doi.org/10.1257/jel.20231736) ### Important reviews - Review of LLMs by [Simon Willison](https://simonwillison.net/2024/Dec/31/llms-in-2024/) - Machines of Loving Grace [Dario Amodei](https://darioamodei.com/machines-of-loving-grace) ### Prompting * AI Frontiers in Plain English: Prompt Engineering guide from Google with LM Notebook [Part 1. LLM output configurations](https://creators.spotify.com/pod/profile/steven-ge/episodes/Prompt-Engineering-guide-from-Google-Part-1--LLM-output-configurations-e31eqel) + others ### Understanding LLMs - Glossary of LLM terms [Glossary of LLM Terms](https://www.vectara.com/glossary-of-llm-terms) - [Financial Times: How AI Large Language Models Work](https://ig.ft.com/generative-ai/) - [The Economist: How Large Language Models Work](https://www.economist.com/science-and-technology/2024/07/11/researchers-are-figuring-out-how-large-language-models-work) - [Thinking like AI](https://www.oneusefulthing.org/p/thinking-like-an-ai) - What's an LLM context window and why is it getting larger? [IBM research on context window](https://research.ibm.com/blog/larger-context-window) ### AI and business / management - Strategy in business [Build a winning AI strategy, HBR 2023](https://hbr.org/2023/07/build-a-winning-ai-strategy-for-your-business) - Interview with Rafella Sadun on [Reskilling workforce with AI](https://sloanreview.mit.edu/audio/reskilling-the-workforce-with-ai-harvard-business-schools-raffaella-sadun/) from MIT Sloan Review ## Additional readings ### Consequence of AI How NLP was killed by Transformers/ LLMs in [Quant magazine 2025 April](https://www.quantamagazine.org/when-chatgpt-broke-an-entire-field-an-oral-history-20250430/?) ### Blogs, newsletters * Blog post by Posit [Text Summarization, Translation, and Classification using LLMs: mall does it all](https://posit.co/blog/mall-ai-powered-text-analysis/) * Simon Willis blog post [LLM and coding](https://simonwillison.net/2025/Mar/11/using-llms-for-code/) * Ethan Mollick substack: [One useful thing](https://www.oneusefulthing.org/) * [Alpha Signal](https://alphasignal.ai/) newsletter * How [Andrej Karpathy](https://x.com/karpathy/status/1915581920022585597) is adopting AI assisted coding. * Blog by Anthropic [Claude explains](https://www.anthropic.com/claude-explains) -- cool collection on ideas for coding with Claude ### Video Resources on AI - Andrej Karpathy [Introduction to Large Language Models](https://www.youtube.com/watch?v=zjkBMFhNj_g) -- 1hs overview, a great start - Andrej Karpathy [Deep Dive into LLMs like ChatGPT](https://www.youtube.com/watch?v=7xTGNNLPyMI) -- 3hs comprehensive updated version of the Intro video - Andrej Karpathy: ["Let's build GPT: from scratch, in code, spelled out"](https://www.youtube.com/watch?v=kCc8FmEb1nY) - Interview with a great [Sendhil Mullainathan on direction AI](https://youtu.be/z_svj3NP968?si=cWUoVAImTF4PZ_aw) ## Deeper stuff on AI * Artificial intelligence learns to reason in [Science](https://www.science.org/doi/10.1126/science.adw5211)