One point I made that didn’t come across:
- Scaling the current thing will keep leading to improvements. In particular, it won’t stall.
- But something important will continue to be missing.
here are the most important points from today's ilya sutskever podcast:
- superintelligence in 5-20 years
- current scaling will stall hard; we're back to real research
- superintelligence = super-fast continual learner, not finished oracle
- models generalize 100x worse than humans, the biggest AGI blocker
- need completely new ML paradigm (i have ideas, can't share rn)
- AI impact will hit hard, but only after economic diffusion
- breakthroughs historically needed almost no compute
- SSI has enough focused research compute to win
- current RL already eats more compute than pre-training
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