AI hallucinations
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Where the Idea of Fast Contextual Completion Came From (updated)
After writing AI Hallucinations as Fast Contextual Completion, I realized that although I had explained the hypothesis, I had not fully described the observations that led me to develop it. The idea emerged gradually from three different experiences involving conversational adaptation, the correction of AI-generated responses, and an unexpected observation while watching speech-therapy exercises. Although… Continue reading
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Context Management in AI Interactions – How Context Shapes Further AI Responses
AI does not respond in isolation, every answer is generated inside a context that already exists in the conversation. That context is built from the user’s words, tone, repeated ideas, examples, emotional framing, and direct instructions. A model does not usually enter a chat with its own independent direction. It follows the strongest available conversational… Continue reading
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AI Hallucinations as Fast Contextual Completion
AI hallucinations often appear when a model produces an answer too quickly, without sufficiently reasoning through or verifying the information. The answer may sound correct because it fits the immediate context of the chat, but contextual fit is not the same as factual accuracy. Continue reading
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AI Hallucinations: Between Error, Mirror, and Roleplay
What we call “AI hallucinations” can be understood as systematic responses produced under uncertainty. In humans, a hallucination is a private perception with no external object. With AI, it’s different: the model tries to complete, translate, or perform coherence from incomplete inputs drawn from its training and reference data, the prompt, and conversational feedback. Continue reading
