Author: Backlinks Hub

Large language models hallucinate. Not occasionally, but regularly. They’ll cite research papers that don’t exist, reference case law that was never written, and recommend products that aren’t in your inventory. All delivered with the exact same confidence as factually correct responses.  This isn’t getting fixed in the next model update. It’s a fundamental core to how these systems operate. They’re prediction engines, not knowledge databases. When the pattern recognition runs into ambiguity or gaps, the model doesn’t say “I don’t know.” It fills the gap with something that sounds right.  This creates an interesting problem for enterprises actually trying to…