Audience
Alignment researchers, model behavior teams, safety leads
Chris Royse field notes
Teleological Constellation Training In Plain English
A target identity or style can be defined as frozen centroid vectors, then checked at generation time instead of trusted by vibe.
Signal / PAPER + alldata.md / 9:25
Core idea
Teleological means the model is pulled toward a defined end state: the frozen constellation. The output either stays near it or gets flagged.
TCT
Watch on YouTube· 9:25
Teleological Constellation Training In Plain English
This gives frontier readers a concrete mechanism to inspect: not a learned scalar reward, but a geometric predicate over frozen embedders.
Watch videoOpen the full video on YouTubeWhat to take from it
The videos are raw build context. These notes translate them into the shortest useful frame for creators, companies, and AI lab readers.
The target is a frozen centroid panel.
Training and verification use the same embedder family.
The claim is panel-relative, not universal identity truth.
Continue this thread.
Related notes stay inside the same problem area first, then move to the next useful context.
Watch + read / 11:23
The Data Wall Is A Meaning Extraction Problem
Why frontier labs should look for more signal inside existing data before defaulting to synthetic data loops.
Watch + read / 11:34
The 13-Embedder Context Graph
Semantic, temporal, causal, code, graph, typo-tolerant, paraphrase, entity, and late-interaction lenses in one memory system.
Watch + read / 11:49
Why One Input Can Produce Up To 91 Signals
The paper's core accounting move: N embedders create N single-lens signals plus pairwise interactions from the same fixed input.
Make it concrete.
Send the audience, data type, target task, proof bar, and sharing limits.