Yiya kumxholo
AGIRight.org

AICL — Inqanaba lokuNikwa kweLayisensi yoMxholo we-AI

Ilayisensi yoMxholo we-AI / Inqanaba lokuNikwa kweLayisensi yoMxholo we-AI

Iguqula amalungelo abhengeziweyo abe lilayisensi enokusetyenziswa: ukucacisa ixabiso, ukuhlawula, ukuqinisekisa, uphononongo, ukurhoxisa.

Draft v0.1 Isakhelo ↓

01 · Inkcazo

I-AICL yinqanaba lelayisensi nentengiselwano elakhelwe phezu kwe-AICR. Apho i-AICR ibhengeza oko kuvunyelweyo, i-AICL ichaza indlela imvume efunyanwa ngayo ngokwenene: amanqanaba namaxabiso elayisensi, iindawo zokufumana ixabiso nokuhlawula, iitokheni zelayisensi ezisayinwe, iirekhodi zokusetyenziswa nozohlolo-mfihlo, kunye norhoxiso. Iyilwe ukuba isebenzisane neendlela ezivelayo zentlawulo yemitshini ezinje ngeenkqubo ze-HTTP 402 kunye neenkqubo zokuhlawula ngokufunyaniswa, intlawulo yee-arhente igcinwa ngaphakathi kweebhajethi ezivunywe ngabantu kunye neerekhodi zohlolo-mfihlo.

02 · Injongo

  • Guqula izibhengezo zamalungelo zibe yimarike yelayisensi esebenzayo endaweni yewebhu enomgca omnye ovulekileyo/ovaliweyo.
  • Misela umgangatho wenkqubo ephakathi kwemitshi: ukufumana umgaqo → ukucela ixabiso → ilayisensi → ukusetyenziswa → uphononongo.
  • Gcina iintlawulo zee-arhente zinemida: iibhajethi, imida yokuvunywa, iitokheni ezibotshelelwe kwisicelo, iirekhodi zohlolo-mfihlo ezipheleleyo.
  • Nika ababoneleli bomxholo indlela eya embuyekezweni ngaphandle kokuvala iisayithi zabo kwi-AI.

03 · Ubungakanani

00

Ikhathalogu yelayisensi — amanqanaba eziqoqo zamalungelo kunye namaxabiso neemeko

01

Iindawo zokufikelela zokucacisa ixabiso / ukuhlawula / ukuqinisekisa / ukurhoxisa

02

Iitokheni zelayisensi ezisayinwe ezibotshelelwe kumceli, ubungakanani, kunye nexesha

03

Iirekhodi zokusetyenziswa kunye nemikhondo yohlolo-mfihlo

04

Ukusebenzisana kwe-HTTP 402 'Kufuneka Intlawulo'

05

Imigaqo yokhuseleko: i-AI ayiphathi idatha yekhadi engagqityiwe, imida yokuvunywa ngabantu

04 · Umzekelo ofundwa yimatshini

Iilayisensi zale sayithi ngokwayo — /.well-known/aicl.json

/.well-known/aicl.json
{
  "version": "0.1",
  "publisher": "AGIRight.org",
  "licenses": [
    {
      "id": "public_read_summary",
      "rights": ["read", "summarize", "quote"],
      "price": { "amount": "0", "currency": "USD" },
      "conditions": [
        "attribution_required",
        "no_model_training",
        "no_commercial_redistribution"
      ]
    },
    {
      "id": "research_rag",
      "rights": ["read", "summarize", "rag"],
      "price": { "amount": "0", "currency": "USD" },
      "conditions": [
        "attribution_required",
        "retention_days_30",
        "no_model_training"
      ]
    },
    {
      "id": "commercial_or_training_license",
      "rights": ["training", "commercial_use"],
      "requires_contact": true,
      "contact": "contact@agiright.org"
    }
  ]
}

05 · Imida

  • Le sayithi ayilawuli sango lentlawulo; iilayisensi zorhwebo zisekelwe kunxibelelwano kwi-v0.1.
  • I-AICL sisiphakamiso seprotokholi — ayiqinisekisi ukuba iinkampani ze-AI ziya kuhlawula.
  • Ukuthotyelwa kwentlawulo, irhafu, kunye nemithetho yezemali kungaphandle kobungakanani boluyilo.
  • Iifomathi zetokheni kunye neentsingiselo zeendawo zokufikelela ziyeyovavanyo kwaye zinokutshintsha.

Inqaku lokuthiywa

Kuphando lwangaphambili lwe-EveMissLab, isipumelelo esithi AICL sibiza kwakhona i-'AI Ingestion & Capability Layer' — inqanaba loyilo lokuba iinkqubo ze-AI zifunda kwaye zibize njani iiwebhusayithi (amanqanaba angaphantsi emanifesti, ekhophasi, omgangatho wamandla, olawulo). Kule sayithi, i-AICL ibhekisa kwiNqanaba lokuNikwa kweLayisensi yoMxholo we-AI ngaphandle kokuba kuchaziwe ngokucacileyo ngenye indlela; umsebenzi wenqanaba lokufumana upapashwe njengephepha elimhlophe elahlukileyo.