Cross-posted from my Substack.
Epistemic status: I’ve puzzled over this for a long time but I’m not sure I came to the right answers. I'm sharing this partly because it might help others work on resource allocation, but mostly because some smarter reader might tell me how to do it better.
TL;DR:
* I he...
With the AI windfall, mental health may be taken increasingly seriously by mainstream EA. There’s increasingly room to explore the cause area and answer some of the biggest uncertainties; at the same time, costs of the most effective interventions are continuing to fall. StrongMinds is now treating for ~$35, about a third of GiveWell’s best guess from a few years ago, and is expected to...
This post is part of the Cross-Cause Fund (CCF) series by Rethink Priorities — a sequence of articles dedicated to effective giving across philanthropic areas.
TL;DR:
There is a seemingly plausible argument that do...
Most AI-geopolitics analysis concentrates on frontier production. I've been exploring a complementary question: what happens to the capabilities the frontier leaves behind?
Downloadable models can persist after commercial support and meaningful developer control disappear. As inference and adaptation costs decline, some of these systems may become accessible to actors that could not have exploited them at release.
The longer piece develops this through the ideas of capability sedimentation, temporal capability arbitrage and “compute-poor but model-rich” states.
I'm especially interested in whether this should affect how the AI-governance community thinks about model-release decisions and proliferation below the frontier.
https://fabiofrettoli.substack.com/p/the-geopolitics-of-model-graveyards?r=sb1v&utm_campaign=post-expanded-share&utm_medium=web