UN THÈME, DANS SON CONTEXTE

AI system security and observability

Judgments in this source concerning AI system security and observability. Explorez 1 point de vue avec des éléments tirés de 1 source.

1 personnes · 1 sources · 1 opinions exprimées

Contenu mis à jour:

Explorer les liens ↗

Carte des points de vue

Explorer par personne. Sélectionnez deux ou trois personnes pour les comparer.

1 personnes · 1 sources · 1 opinions exprimées

Lilian Weng

Harness edits must be limited to editable surfaces, with read-only safeguards

Harness edits are restricted to the harness workspace only; the runs directory, tracer, verifier, and LLM configuration are read-only to prevent reward hacking—such as disabling the verifier, swapping the model, or raising the reasoning budget—ensuring gains remain attributable solely to harness changes.

Éléments favorables

Harness Engineering for Self-Improvement

Extrait original

Edits are only applied to the harness workspace. the runs directory, tracer, verifier, and LLM configuration are read-only, which disables a set of reward hacking (e.g disabling the verifier, swapping the model, or raising the reasoning budget) and thus it can keep every recorded gain attributable to harness edits.
Contexte

Decision observability : every edit is paired with a prediction for the next round to validate. An agent (“Evolve agent”) reads the repo and decides which component to edit, and then produces the edit and the reasoning behind it. Every edit is a file-level, falsifiable claim and can be verified in the next round, under two constraints: (1) (2) Edits are evidence-driven, with a manifesto entry: the failure evidence’s name, the inferred root cause, the targeted fix, and a predicted impact comprising both expected fixes and at-risk regressions.

Partager un aperçuVérifier cette affirmation

Il s’agit de points de vue individuels, non d’une mesure du consensus. Le matériel source reste dans sa langue d’origine.