An AGI reading list
Books and papers that will deepen your understanding - of intelligence in brains, in machines, and in the strange space between them.
Books
Human Compatible
Reframing AI design around uncertainty about human preferences.
Superintelligence
An influential analysis of the strategic landscape of advanced AI.
The Alignment Problem
A readable tour of the technical and ethical challenges of aligning AI.
Life 3.0
Scenarios for the long-term future of intelligent life.
The Master Algorithm
A unifying overview of machine learning paradigms.
Thinking, Fast and Slow
Foundational reading on how human cognition actually works.
How to Create a Mind
An argument for pattern-recognition theories of mind, presented accessibly.
The Book of Why
Causal reasoning and what current AI systems still cannot do.
On Intelligence
Theories about the neocortex as a template for general intelligence.
A Thousand Brains
A more recent extension of the Thousand Brains Theory of intelligence.
Deep Learning
The canonical technical reference for deep learning.
Reinforcement Learning: An Introduction
The standard text on reinforcement learning.
Foundational Papers
- Computing Machinery and Intelligence (1950)Alan Turing
- Attention Is All You Need (2017)Vaswani et al.
- Language Models are Few-Shot Learners (2020)Brown et al.
- Scaling Laws for Neural Language Models (2020)Kaplan et al.
- Training language models to follow instructions with human feedback (2022)Ouyang et al.
- Sparks of Artificial General Intelligence (2023)Bubeck et al.
- Concrete Problems in AI Safety (2016)Amodei et al.