grounding
2 free lessons tagged grounding across AI. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Grounding and Detection: Catching It Before the User Does
Since a model cannot judge its own output, detection has to compare it against something external. This lesson covers grounding through retrieval and why it reduces rather than eliminates the problem, then the detection methods that work: self-consistency sampling, entailment checking against sources, claim decomposition, and chain-of-verification.
What a Hallucination Is, and Why It Happens
Hallucination is not a bug that will be patched out. This lesson covers why a next-token predictor produces confident falsehoods, the dual-axis taxonomy separating intrinsic from extrinsic and factuality from faithfulness, why fluency carries no signal about truth, and the theoretical result that the problem cannot be fully eliminated.