Given a SotA large model, companies want the profit-optimal distilled version to sell—this will generically not be the original size. On this framing, regulation passes the misuse deployment risk from higher performance (/higher cost) models to the company. If profit incentives, and/or government regulation here continues to push businesses to primarily (ideally only?) sell 2-3+ OOM smaller-than-SotA models, I see a few possible takeaways:
Applied alignment research inspired by speed priors seems useful: e.g. how do sleeper agents interact with distillation etc.
Understanding and mitigating risks of multi-LM-agent and scaffolded LM agents seems higher priority
Pre-deployment, within-lab risks contribute more to overall risk
On trend forecasting, I recently created this Manifold market to estimate the year-on-year drop in price for SotA SWE agents to measure this. Though I still want ideas for better and longer term markets!
Given a SotA large model, companies want the profit-optimal distilled version to sell—this will generically not be the original size. On this framing, regulation passes the misuse deployment risk from higher performance (/higher cost) models to the company. If profit incentives, and/or government regulation here continues to push businesses to primarily (ideally only?) sell 2-3+ OOM smaller-than-SotA models, I see a few possible takeaways:
Applied alignment research inspired by speed priors seems useful: e.g. how do sleeper agents interact with distillation etc.
Understanding and mitigating risks of multi-LM-agent and scaffolded LM agents seems higher priority
Pre-deployment, within-lab risks contribute more to overall risk
On trend forecasting, I recently created this Manifold market to estimate the year-on-year drop in price for SotA SWE agents to measure this. Though I still want ideas for better and longer term markets!