Notes

Rough notes taken on stuff I read. These are compiled into flashcards, and studied with spaced repetition.

• Alignment.
• Interpretability.
• Machine learning.
• Math.
• Shakuhachi.
• Climate change.
• Misc.
• Course notes:
  • Introduction to Reinforcement Learning by David Silver.
  • Information Theory, Pattern Recognition, and Neural Networks by David MacKay.
  • Linear Algebra by Gilbert Strang.
  • AGI Safety Fundamentals.
  • Power and Politics in Today’s World by Ian Shapiro.
  • Homotopy Type Theory.
  • Introduction to Real Analysis.
  • Principles of Deep Learning Theory.
  • Distilling Singular Learning Theory.
  • Neural Network Training Dynamics.
• Also see my reading list.