Maroñ in Katak an AI
Eḷaññe AI emaroñ katak, ñan jete depth, ñan purpose rot, im iuṃwin eddo rot. Bwe ren riiti e jab ejja wōt bwe ren katak jāni; “ejjeḷọk mọ kake” e jab “learnable.” AIRS im AILP rej ukot maroñ in katak ñan juon spectrum ej wōnṃaanḷọk im machine-readable.
Kajjitōk ko Rej Katak Kaki
01
Depth in katak: indexing, embedding, fine-tuning, training, distillation
02
Etke openness ejjeḷọk an definition ej kar jolọk jān training pipeline ko
03
Protocolized openness: kōṃṃan bwe goodwill en machine-executable
04
Model in compensation ekkar ñan depth in katak
Whitepaper ko Ewor Kōtaan
- AI Rights Spectrum: From robots.txt to an AI Learning Permission Protocol AIRS im AILP rej kwaḷọk maroñ in katak an AI ko re nuanced jān binary allow/disallow — ta eo AI emaroñ katak, ñan jete depth, ñan uses rot, im kōn compensation rot.
- Protocolized Openness: Why “Not Prohibited” Does Not Mean “Learnable” in the Age of AI Openness ejjeḷọk an definition ej riit āinwōt legal uncertainty ñan AI pipeline ko im ej kar jolọk; maroñ protocolized im machine-readable wōt ej kōṃṃan bwe kontent en lukkuun learnable.
- AGIRight.org Technical White Paper v0.2 — From AI Content Governance to Protocol-Native Agent & Authority Rights The site's current architecture document: six protocol drafts across two families (content & learning, agent & protocol rights), an integration layer, and an ethical-protection layer, plus the acceptance criteria this site update was built against.
- ARHG — Agent-Readable Hyperlink Graph and Permissioned Web Control Plane A machine-readable navigation graph alongside the ordinary site, answering what AICR/AILP and AARS/AADP both assume: can this resource even be found, by whom, and where does it lead.