Ndzavisiso

Mfanelo, minkarhi, vutihlamuleri, na vulawuri bya AI, AGI, na maagent — ku sukela eka switirhisiwa ku ya eka vanakulobye ku ya eka swiphemu leswi nga ha vaka kona nkarhi lowu taka. Leswi swi katsa na xivutiso xa xivikelo xa le hansi xa mahanyelo: milawu yihi leyi faneleke yi lawula vuxaka bya munhu na AI ku nga si tiyisisiwa swivutiso swa vumunhu.

What AI systems may do with content: read, summarize, transform, retrieve, train, commercialize, redistribute. The AICR ruleset and the AICL-C content-licensing layer make these rights declarable and transactable.

Loko AI yi nga dyondza, hi vun'we byihi, eka mintirho yihi, na hi minkoka yihi. Ku hlayiwa a swi fani na ku dyondziwa; "ku nga aliwi" a swi fani na "ku nga dyondzeka". AIRS na AILP swi hundzula mpfumelelo wo dyondza wu va xipandzepandze lexi hlayekaka hi matšhini, lexi nkomeke.

Ndlela leyi maagent ma fikelelaka masayiti ya wepu, ma-API, dathabase, tibhanga ta vutivi, na kontenti leyi hakheriwaka: vuxaka, mpfumelelo, swikombelo, nkhokhelo, ntsundzuxo, rhekhodo ra ku tirhisiwa, minkoma ya nsirhelelo, na nsirhelelo eka prompt injection.

What an Agent may DO once it holds tool or API capability, as distinct from what it may read or learn: action taxonomy, effect vectors, reversibility, blast radius, and multi-action composition risk. AARS gives content permission and action permission separate, independently-evaluable axes.

Who an Agent acts for, where its authority came from, whether it can hand that authority to another Agent, and how much of its internal state a verifier may demand. AADP separates principal from actor, bounds delegation to strictly narrow (never silently widen), and treats inspection as a bounded right, not an unlimited one.

Milawu ya vulawuri leyi matšhini ma nga yi kumaka na ku yi tirhisa: llms.txt, timanifest ta /ai/, tifayili ta pholisi ta /.well-known/, JSON Schemas, tokheni ta layisense leti sayiniweke, na swivumbeko swa rhekhodo ra audit. Sayiti leyi hi yoxe i xikombiso lexi tirhaka.

Ikhonomi-polotiki ya AI na kontenti: pay-per-crawl, swiavo swa data, timali ta AI ta tiko, mimbuxo ya nkhokhelo ya vatumbuluxi, makete ya data ya swiyenge, na ndlela leyi nkoka lowu tekiwaka eka vutivi bya vaaki wu nga tlhelaka wu ya eka lava wu humeseke.