Recommended Media

Notes Foundational paper on algorithmic probability and universal induction. Basis for AIXI.

Notes Free condensed RL theory book; rigorous and compact. Alternative formal RL resource.

Notes Newer textbook presenting AIXI and related universal agent theory with updated structure; suitable after the core UAI book.

Notes Standard AI textbook covering search, logic, probabilistic reasoning, RL, multiagent systems, and more. Canonical comprehensive AI text.

Notes Later work on convergence properties of Solomonoff induction.

Notes Perspective of deep learning from applied math. Bridges math with neural nets.

Notes Free open-source deep learning book with code and math integrated. Interactive deep learning resource with runnable code.

Notes Explores analogy and cognition via computational models. Classic work on analogy and cognition modeling.

Notes Modern graduate ML text with causal inference, decision making, and ML foundations. Accessible free textbook with strong conceptual framing.

Notes Mathematical RL fundamentals (MDPs, value functions, dynamic programming, approximate methods). RL foundational text that bridges theory and practice.

Review Seminal blog post demonstrating the power of character-level RNNs. Shows Shakespeare generation, Wikipedia generation, LaTeX generation, and Linux kernel code generation. The visualizations of …

Notes Formal theory of universal agents combining Solomonoff induction and sequential decision theory; foundational for AGI theory.

Notes Classic exploration of self-reference, formal systems, and the nature of mind.

Notes Rigorous introduction to the numerical analysis of ODEs, including stability and stiffness.

Notes Applied Bayesian inference with computing methods. The standard Bayesian statistics reference.

Notes Rigorous graduate-level probability + statistics; useful for inference and ML foundations.

Notes Abstract, conceptual focus on vector spaces and linear maps. Avoids determinants until the end.

Notes Comprehensive advanced linear algebra reference.

Notes Intuition-rich introduction to qualitative behavior of dynamical systems.

Notes Practical matrix computations and numerical realities.

Notes Broad coverage of numerical algorithms in science and engineering. Classic cross-topic numerical algorithms.

Notes Definitive reference on modern ODE solvers and stiff systems.

Notes Standard rigorous text on estimation, hypothesis testing, and asymptotic theory.

Notes Collected notes on programming philosophy. Free PDF.

Notes The standard comprehensive reference on Kolmogorov complexity. Essential for understanding Solomonoff induction.

Notes Blends discrete mathematics with analysis and algorithm design.

Notes Rigorous foundations of generic programming. Connects algebra and algorithms. Stepanov’s magnum opus.

Notes History of mathematical ideas underlying generic programming. More accessible than EoP.

Notes Core computability and complexity theory.

Notes Collected essays on Bayesian rationality and decision theory.

Notes Assessment of long-term risks from advanced AI.

Notes Cognitive biases and dual-process reasoning relevant to rationality.

Notes Hard SF with deep cognitive science and consciousness themes.

Notes Physics-dense exploration of posthuman intelligence.

Notes Explores computation, identity, and emulated worlds.

Notes Humans are stuck in the ‘breeder’ phase - Earth is a lost colony. A member of the species in the Protector stage (stronger, smarter, utilitarian) finds humanity and mentors us behind …

Notes Short fiction with rigorous thought experiments.

Notes 18-part lecture series on efficient programming. Covers the intellectual foundations behind STL.

Notes Comprehensive lecture series covering RL foundations.

Notes Technical talk touching on universal induction and AI foundations.

Notes Lecture on AIXI and universal intelligence theory with deep insights.

Notes Classic deep dive into computation, abstraction, interpreters, and languages.

Notes Engineer-philosophical talk about the nature of system and language design.

Notes Classic talk on recognizing algorithmic patterns. ‘No raw loops’ - shows how rotate solves many problems elegantly.