I used to think AI made mistakes because it wasn't trained well enough.
Turns out, that's only part of the story.
Large Language Models aren't trying to "know" the correct answer the way humans do.
Their primary goal is to generate the most likely sequence of words based on patterns they've learned.
That explains why AI can sometimes create fake references, imaginary statistics, or incorrect explanations while sounding completely certain.
It isn't trying to fool anyone.
It's simply doing what it was designed to do.
I wrote a simple breakdown for anyone who's curious.
🔗 Full article: https://pressearn.it.com/blog/2026/05/29/why-ai-hallucinates-and-why-you-shouldnt-trust-every-answer/
(https://pressearn.it.com/blog/2026/05/29/why-ai-hallucinates-and-why-you-shouldnt-trust-every-answer/)
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