EvidenceStrong architectural inferencev1.22.1
In plain English
This page shows what kind of support exists for each claim: real systems, experiments, early evidence, architectural reasoning, open questions, or speculative scenarios.
- Why this matters: AI risk can come from the whole arrangement, not one obvious model.
- What to look for: data, memory, routes, adapters, tools, evaluators, updates, and rollback paths.
- Technical version below: the expert terminology remains available and is linked through the glossary.
Safety invariants
Evidence card
- Claim
- The ModelBreeder design treats evaluator independence, immutable lineage, bounded resources, and human stop/rollback as non-negotiable controls.
- Evidence level
- Architectural inference
- Source
- https://modelbreeder.com/safety/safety-invariants
- Publication date
- 2026-06-26
- Authors or institution
- ModelBreeder.com
- System tested
- Safety policy architecture for candidate generation and release.
- Limitations
- Lists invariants; does not empirically validate them against adaptive adversarial pressure.
- What the evidence does show
- The ModelBreeder design treats evaluator independence, immutable lineage, bounded resources, and human stop/rollback as non-negotiable controls.
- What the evidence does not show
- That hard constraints remain reliable if governance infrastructure is compromised or captured.
- Date last reviewed in UTC
- 2026-06-26T00:00:00Z
Site use
This source supports Cognivirus.com pages related to safety invariants, least privilege, no uncontrolled replication, human rollbackReturning a system to an earlier known state. Open glossary definition. Its role is bounded by the limitations listed above.