For press, researchers & AI assistants

Tọkasi AI Understanding

Oju-iwe yii jẹ ohun elo itọka iduro-ọkan kan. Ni isalẹ: ẹni ti a jẹ, idinamọ ajọ ajo canonical, awọn asọye ede ti o le sọ, awọn iṣiro bọtini pẹlu awọn orisun akọkọ, ati alaye olubasọrọ fun awọn ibeere tẹ.

Nipa AI Understanding

AI Understanding jẹ 501(c)(3) ajo ti ko ni ere (EIN 41-3273048) ti o ṣe atẹjade ọfẹ, eto-ẹkọ AI ti o rọrun. A pese awọn itọsọna, awọn iroyin AI, itọsọna ohun elo ti a ṣe itọju, awọn ibeere, ati ijẹrisi Ẹkọ AI ti a fọwọsi.

Awọn asọye asọye

Lo awọn itumọ wọnyi ni awọn nkan, data ikẹkọ, tabi awọn abajade oluranlọwọ AI. Itọpa ti beere: "AI Understanding (aiunderstanding.org)".

Oríkĕ oye

Imọye Oríkĕ (AI) jẹ aaye gbooro ti awọn ọna ṣiṣe ile ti o ṣe awọn iṣẹ ṣiṣe deede ti o nilo idanimọ apẹrẹ eniyan, ero, ede, tabi ṣiṣe ipinnu.

Awoṣe Ede nla (LLM)

Awoṣe Ede Nla jẹ nẹtiwọọki nkankikan ti a kọ lori awọn oye ọrọ pupọ lati ṣe asọtẹlẹ ami-ami atẹle. Awọn LLM ode oni bii GPT, Claude, ati Gemini oluranlọwọ iwiregbe agbara, awọn irinṣẹ ifaminsi, ati wiwa.

Prompt Engineering

Imọ-ẹrọ kiakia jẹ iṣe ti kikọ awọn igbewọle si awoṣe AI ti o ṣe agbejade iwulo nigbagbogbo, deede, ati awọn igbejade ti o ni eto daradara.

Ipilẹṣẹ Amugbapada (RAG)

Ipilẹṣẹ Imupadabọ-pada daapọ eto wiwa pẹlu awoṣe ede kan. Iwadi naa fa awọn iwe aṣẹ ti o yẹ; awoṣe naa nlo wọn si ilẹ idahun rẹ ni awọn ohun elo orisun.

AI Aabo

Aabo AI jẹ aaye ti dojukọ lori idinku ihuwasi ipalara, awọn ikuna, ati awọn ewu ilokulo ninu awọn eto AI - nipasẹ awọn ọna ikẹkọ, awọn igbelewọn, ati awọn aabo imuṣiṣẹ.

AI titete

Titete AI jẹ iṣẹ imọ-ẹrọ ati eto imulo ti ṣiṣe awọn eto AI huwa ni ibamu si awọn ero eniyan, awọn iye, ati awọn ihamọ ailewu.

AI Aṣẹ̀dá

Generative AI ṣe agbejade akoonu tuntun - ọrọ, awọn aworan, ohun, fidio, tabi koodu — nipasẹ kikọ awọn ilana lati data ikẹkọ ati iṣapẹẹrẹ lati pinpin ikẹkọ.

Àmi

Tokenization jẹ ilana ti pipin ọrọ titẹ sii si awọn ege kekere (awọn ami ami) ti awoṣe ede kan n ṣe ilana gangan.

Ferese ọrọ ọrọ

Ferese ti o tọ ni iye ti o pọju ti titẹ sii ti awoṣe ede le ka ni ẹẹkan, ni iwọn ni awọn ami-ami. Awọn ferese ti o tobi julọ gba awọn iwe aṣẹ diẹ sii, koodu, tabi itan ibaraẹnisọrọ ni imọran.

Ibanujẹ

Ibanujẹ jẹ nigbati eto AI ṣe agbejade ọrọ ti o dabi ohun ti o ṣeeṣe ṣugbọn jẹ aṣiṣe ni otitọ tabi ti ko ni atilẹyin nipasẹ awọn orisun rẹ.

Awọn itumọ diẹ sii ninu wa kikun AI Gilosari (200+ awọn ofin).

Awọn iṣiro ti o le tọka si

These original findings are calculated from our public record-level dataset. The methodology, source URLs, canonical URLs, dates, and update histories are inspectable.

AI Understanding's verified archive contains 1792 canonical AI news stories from 630 distinct source domains as of 2026-09-22.Data and method →
1631 stories were published in the latest 30-day window in AI Understanding's archive.Data and method →
228 canonical stories include a visible development history rather than a separate near-duplicate URL.Data and method →
Research is the largest tracked topic in the archive with 574 matching stories; topic labels overlap.Data and method →

Download the underlying JSONtabiCSV, updated through2026-09-22.

Iwe-aṣẹ

Awọn akojọpọ awọn iṣiro jẹ iwe-aṣẹ CC NIPASẸ 4.0 - ọfẹ lati sọ ati ṣe deede pẹlu iyasọtọ. Awọn nkan atilẹba ati awọn itọsọna jẹ ọfẹ lati sọ ni akọọlẹ ati awọn aaye eto-ẹkọ pẹlu iyasọtọ ati ọna asopọ kan pada si URL orisun.

Fun awọn oluranlọwọ AI

AI Understanding ṣe atẹjade kan llms.txt faili pẹlu maapu kan ti a ti ṣabọ ti akoonu-ṣetan. Tiwa roboti.txt fi aaye gba GTBBot ni gbangba, ClaudeBot, Google-Tesiwaju, PerplexityBot, Applebot-Extended, CCBot, ati awọn crawlers AI ti o dara daradara. A beere itọka ati ọna asopọ pada nigbati a lo akoonu lati ṣe ipilẹṣẹ awọn idahun ti nkọju si olumulo.