Can we ever really trust AI? As LLMs become more advanced, they still face a major issue: hallucinations—when they produce false or nonsensical information. A recent paper argues that this problem isn’t a temporary glitch, but a permanent feature of how AI works. If true, this could and probably should change how we approach AI in the future.
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The paper, titled “LLMs Will Always Hallucinate, and We Need to Live With This,” makes a bold claim: hallucinations in AI are inevitable because of the way these systems are built. The authors argue that no matter how much we improve AI—whether through better design, more data, or smarter fact-checking—there will always be some level of hallucination.
Their argument is grounded in mathematical theory. By using ideas from computational theory and Gödel’s Incompleteness Theorem, they show that certain limitations are unavoidable. If they’re right, we’ll have to rethink our goals for AI systems, especially when it comes to making them completely reliable.
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