Reading
Goodreads
If you’d like to share book recommendations, here is my goodreads link :)
Why you should read & how to read more
Well, let me start by saying that books just smell good. Jokes aside, I recommend you watch BOOKSTORES: How to Read More Books in the Golden Age of Content before reading this post. It motivates why you and I should read more books and how to do it. I really do hope that you give this video a shot, but be aware that it might really get you excited to find some good books to read, and then there is no stopping. You’ll be hooked as well. I also want you to consider all the benefits of reading:
- gain knowledge
- sparking of ideas
- forced meditation (increases attention span & trains focus) and reflection periods
- immersion & fun
- comfy activity (either read outside, in a cafe, in a library or in the evening with some nice ambience)
- low dopamine (reduces the baseline to make other productive activities more rewarding)
… so i would turn the question around and ask why shouldn’t you read! (If you come up with something, feel free to write a comment.)
Blogs that you might want to read
… if you are interested in AI and/or RL
This section has a lot of value, so don’t be too lazy to check them out :)
- https://horace.io/index.html (i like the homepage style)
- Max Tegmark’s homepage
- Will Dabney’s homepage and blog about Distributional RL
- Christopher Olah’s blog (really insightful, well explained - Transformers, NLP, Calculus on Computational Graphs, …)
- Sam Altman’s blog (tips on how to do well in research, fusion, startups and investing, building productivity and leverage)
- Lilian Weng’s blog (insight into OpenAI projects)
- John Schulman’s homepage and blog
- Antonin Raffin’s homepage (author of StableBaselines3, Learning to drive minutes project with an Autoencoder)
- Jeff Wu’s homepage/blog (Research engineer at OpenAI, blog some small thoughts that i liked)
- Juergen Schmidhuber’s homepage
- Danijar Hafner’s homepage (cool Model-based Reinforcement Learning papers)
- Julian Schrittwieser’s blog
- Andrej Karpathy’s blog and website
- Alexander Van de Kleut’s blog (nice visuals)
- Jessica Stringham’s blog (looks cool)
- Andrew Ng’s The Batch
- George Hotz’s blog and website
- Lex Fridman’s video transcripts
Theses that you might want to read
… same gist as above :)
- Rich Sutton’s thesis about temporal credit assignment in reinforcement learning
- David Silver’s thesis about reinforcement learning and simulation-based search in computer go (model-based rl with dyna and mcts, long and short-term memory, rave (?))
- Ilya Sutskever’s thesis about training recurrent neural networks
Legend
| Label | Dot |
| Currently reading this book. | 🟢 |
| Already read it. | 🔵 |
| Abandoned the book. | 🔴 |
| On my future reading list. | 🟡 |
What i’m currently reading
Philosophy
<🔵> Computing Machinery and Intelligence: Können Maschinen denken?
<🟢> Meditations by Marcus Aurelius
Artificial Intelligence (AI)
<🔵> Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World
<🔵> Neural Networks from Scratch in Python
Reinforcement Learning (RL)
<🟢> Reinforcement Learning: An Introduction (second edition)
<🔵> Foundations of Deep Reinforcement Learning
<🔵> Deep Reinforcement Learning Hands-On
<🔵> Deep Learning Illustrated
<🔴> Principles of Synthetic Intelligence
<🔴> Deep Reinforcement Learning in Unity
<🟢> Intelligent Agents with OpenAI Gym
<🟢> Deep Reinforcement Learning
<🟢> Reinforcement Learning: Industrial Applications of Intelligent Agents
<🟡> Distributional Reinforcement Learning (2023)
Physics
<🔵> Chaos: The amazing science of the unpredictable
<🟢> Surely you’re joking, Mr. Feynman!
<🟢> Carl Sagan: Cosmos
Writing & Presentation
<🟢> How to write clearly
<🟡> Research data visualization and scientific graphics
Math
<🔵> Konkrete Mathematik (nicht nur) für Informatiker
<🔵> Mathematik für angewandte Wissenschaften
<🔵> Funktionentheorie: Eine Einführung
<🔵> Pi und die Primzahlen
<🔵> Elementare Differentialgeometrie (nicht nur) für Informatiker
<🔵> Mathematics for Machine Learning
<🟡> Über die Hypothesen, welche der Geometrie zu Grunde liegen
Architecture & Design
<🔵> Kleine Häuser unter 100m²: Große Wohnqualität durch kreative Konzepte
<🟡> Homes for our time: Contemporary Houses around the World
Cryptocurrencies
<🔵> Blockchain: Grundlagen, Anwendungsszenarien und Nutzungspotenziale
<🔴> Bitcoin: Hard money you can’t fuck with
Future reading
<🟡> Carl Sagan: Contact
<🟡> Love & Math
<🟡> The daily stoic: Meditations on wisdom, perseverance, and the art of living
Research papers
<🔵> Monte-Carlo Tree Search (MCTS)
<🟢> Multi-Agent Pathfinding (-multiple papers )
<🟡> MuZero (Planning with a learned model)
<🟡> AlphaTensor
List of awesome people
Science people
Carl Sagan, Charles Hoskinson, Alan Turing and Richard Feynman.
Engineering & Business people
Sam Altman, Elon Musk, Steve Jobs and Larry Page.
AI people
Demis Hassabis, Max Tegmark, Geoffrey Hinton, Pieter Abbeel, Andrew Ng, Shane Legg, Richard Sutton, David Silver, Ilya Sutskever and Lex Fridman.
Film people
Hayao Miyazaki, Robin Williams, Stanley Kubrick, Quentin Tarantino, Steven Ulrich and Christopher Nolan.