In plain English
This page is reference material: definitions, schemas, catalogs, templates, and implementation records.
- 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.
Editorial Methodology
Cognivirus.com uses an evidence-bound voice. It does not write as though catastrophe is inevitable. It does not anthropomorphize optimization when a capability-based explanation is sufficient.
Required distinctions
- Demonstrated result versus emerging preprint.
- Experimental observation versus universal claim.
- Architectural inferenceA conclusion or output produced from data. Open glossary definition versus measured incident.
- Metaphor versus literal biological or malware claim.
- Model lineageThe parent-child history of models, adapters, datasets, or releases. Open glossary definition versus behavioral inheritance.
Counterarguments
The site presents the strongest reasonable case for adaptive model ecologiesA changing AI system made from many connected parts, not just one model. Open glossary definition: specialization, lower cost, local deployment, replaceability, resilience, privacy, modular maintenance, capability isolation, reversible releases, and reduced dependence on one monolithic model.
Review standard
Every source-dependent page should say what is known, what is inferred, what remains unknown, and what evidence would change the assessment.