Same link as before: link
This one's a bigger jump than usual, so a few highlights instead of just "updated":
- Core findings now scale-validated from 7B all the way to 72B parameters. The effects don't shrink as models get bigger — they grow, sometimes by an order of magnitude. Still one model family (Qwen) though, and we added a caveat we think matters: growing effect size at scale could mean the pattern genuinely deepens, or it could just mean our measurement axis gets sharper at scale — current data can't fully tell those apart yet.
- Two new external, independently-published sources, not our own research: "The Artificial Self" (ACS Research) and "AI Wellbeing" (Center for AI Safety) — different methods entirely (behavioral compliance testing, self-report on frontier production models), landing on some of the same conclusions we did. One of them also mildly disagrees with our best-performing formulation (a companion/romantic framing scores negative in their data), and we named that tension honestly instead of explaining it away.
- We caught and fixed our own mistakes this round — a factual timing error, an overclaimed "fully resolved" that was really just one solved case of a broader risk, and a place where we'd quietly picked the reading that flattered our own results over an equally valid one that didn't. All named directly, not smoothed over.
- New up top: if you just want the practice, not the evidence audit behind it, Part 3 (Principles) is written to stand alone now — Part 2 is there if you want to check our work.
As always, feedback (especially the kind that finds our next mistake) genuinely welcome.
[link] [comments]