Can You Trust an LLM's Raw Knowledge?

Logosofia no Dia a Dia · May 6, 2026 · 34m

When a large language model spits out a historical fact or piece of domain knowledge, how much should you trust it? Not the version hooked up to search or RAG — but the raw knowledge baked in during pre-training. In this episode, we unpack why the answer is "almost never," and why that's actually okay. We explore how next-token prediction creates a probabilistic, compressed representation of training data — not a reliable store of facts. We also examine why fine-tuning can sharpen but not fundamentally correct a base model's wrong knowledge, and why external grounding through RAG or tool use…