Schedule
Day 1 · Mon 9 Nov · Likely
Orientation, and the science of deep learning
Then the alignment ecosystem and who is who. What is alignment a problem of, and why now?
Day 2 · Tue 10 Nov · Likely
Solomonoff induction, and computational mechanics
Which structure must any optimal predictor of a process carry, and where do we find it in trained networks?
Day 3 · Wed 11 Nov · Likely
Classical learning theory, and singular learning theory
Agents, Lean, Zulip, a live demo, and how the 17:00 drop-in sessions will work. Which parts of your own work would you hand to an agent tomorrow, and which never?
Day 4 · Thu 12 Nov · Likely
Scaling laws, statistical mechanics, and interpretability
Day 5 · Fri 13 Nov · Likely
Learning dynamics
Day 6 · Mon 16 Nov · Likely
Reinforcement learning, and world models
Day 7 · Tue 17 Nov · Likely
Agent foundations, and mechanistic interpretability
What are the right objects (agents, beliefs, goals), what would a theory of agency have to explain, and which of the candidate formalisms (AIXI, logical induction, condensation, world models) answers which question?
Day 8 · Wed 18 Nov · Likely
Heuristic arguments, and open-source game theory
Day 9 · Thu 19 Nov · Likely
Scalable oversight, debate, and data attribution
Day 10 · Fri 20 Nov · Likely