Thank you for visiting Generative AI models may generate inaccurate or illogical information What is this challenge called A AI hallucination B Interpretability C AI bias D Explainability. This page is designed to guide you through key points and clear explanations related to the topic at hand. We aim to make your learning experience smooth, insightful, and informative. Dive in and discover the answers you're looking for!
Answer :
A. AI hallucination is the challenge where generative AI models may generate inaccurate or illogical information.
AI hallucination refers to instances when generative AI models produce content that is factually incorrect or nonsensical. This phenomenon occurs because these models, like those based on large language models, generate text by predicting the next word in a sequence based on learned patterns from vast datasets.
Despite their impressive capabilities, these models lack true understanding and can create plausible-sounding yet incorrect information. This issue is distinct from AI bias, which involves systematic errors in the output due to prejudiced training data, and from interpretability and explainability, which pertain to understanding and clarifying how AI models make decisions.
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