6/ Bottom line: LLMs can imitate careful responses. But they don’t know what’s true. The better they get at sounding cautious, the harder it is to spot the fakes. That’s the real hallucination.
GENERATIVE AI
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Tool calling, context engineering, RAG, and fact-checking help truth.
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7/ So what does help? Tool calling. Context engineering. Retrieval-augmented generation (RAG). External fact-checking. If you care about truth, offloading to real tools and live sources is your best shot.
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How prompts add caution, uncertainty bias, and unverified tags
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5/ So what’s really happening? • Prompt adds cautious words to the context vector
• Model predicts next token with a bias toward uncertainty
• It still pulls from patterns of fake info in the training data
• And slaps an [unverified] tag on top -
LLMs: No truth engine, no knowledge base, only probabilities
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4/ That’s the trick. LLMs don’t have a truth engine. They don’t even have a “knowledge base.” They only have probabilities: “What kind of thing usually comes next when people ask something like this?”
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Models add disclaimers instead of stopping hallucinations, a style issue.
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3/ Example: A prompt says: "Never present generated content as fact." The model doesn’t stop hallucinating. It just adds: “I cannot verify this information” – even if it’s entirely fake. This isn't honesty. It’s style.
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Asking AI to be cautious only mimics caution, not reliability
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2/ So when you prompt it to “be cautious” or “never state unverified info”… It doesn’t actually get more reliable. It just learns to write like someone trying to be cautious. Keyword: “trying.”
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LLMs: Predicting language, not understanding truth or facts.
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1/ Everyone says: "LLMs don’t understand language – they predict it." Correct. But that also means:
They don’t understand truth, accuracy, or even verifying a fact. They only learn how people talk about facts. -
LLMs: Predicting Language, Not Understanding Truth or Facts
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1/ Everyone says: "LLMs don’t understand language – they predict it." Correct. But that also means:
They don’t understand truth, accuracy, or even verifying a fact. They only learn how people talk about facts. -
LLMs improvise, not hallucinate: the uncomfortable truth
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LLMs don’t “hallucinate.” They improvise. Calling it a bug is just a polite lie. Here’s the uncomfortable truth about how AI really “thinks” And why your prompt can’t fix it :
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OpenAI Realtime API Launches Out of Beta for Voice Interactions
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☑️OpenAI’s Realtime goes live
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 8 septembre 2025
Out of beta, the Realtime API unifies speech + text for seamless natural voice interactions, ideal for customer support and beyond. pic.twitter.com/Kq1WXgyGeJOpenAI’s Realtime goes live Out of beta, the Realtime API unifies speech + text for seamless natural voice interactions, ideal for customer support and beyond.