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Ai hallucination is a phenomenon where, in a large language model (llm) often a generative ai chatbot or computer vision tool, perceives patterns or objects that are nonexistent or imperceptible to human observers, creating outputs that are nonsensical or altogether inaccurate. We'll unpack issues such as hallucination, bias and risk, and share steps to adopt ai in an ethical, responsible and fair manner. AI 幻觉是指大型语言模型 (LLM) 感知到不存在的模式或对象，从而产生无意义或不准确的输出。
Le allucinazioni basate su ai si verificano quando un modello linguistico di grandi dimensioni (llm) percepisce schemi oppure oggetti inesistenti, creando risultati privi di senso o imprecisi. It's also an understandably overwhelming topic AI 할루시네이션은 대규모 언어 모델(LLM)이 존재하지 않는 패턴이나 객체를 인식하여 무의미하나 부정확한 아웃풋을 생성하는 경우를 말합니다.
Ai hallucinations occur when ai algorithms produce outputs that are not based on training data, are incorrectly decoded by the transformer or do not follow any identifiable pattern.
Ai hallucinations are a big problem for large language models Researchers think memory might be the answer On parle d’hallucination d’ia lorsqu’un grand modèle de langage (llm) perçoit des modèles ou des objets inexistants, créant des résultats absurdes ou inexacts. AIハルシネーションとは、大規模言語モデル（LLM）によって、存在しないパターンやオブジェクトが認識され、理にかなっていないか不正確なアウトプットが作り出されることです。
Trust, transparency and governance in ai ai trust is arguably the most important topic in ai
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