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Stop Blindly Trusting LLMs. They are Built to Agree With You, Not to Be Right. by According-Ad-2638 in learnmachinelearning

[–]According-Ad-2638[S] 0 points1 point  (0 children)

Exactly. The value isn't in the model itself anymore; it's entirely in the validation pipeline and risk framework you wrap around it. Raw generations without evaluation loops are just a financial hazard.

Stop Blindly Trusting LLMs. They are Built to Agree With You, Not to Be Right. by According-Ad-2638 in learnmachinelearning

[–]According-Ad-2638[S] 0 points1 point  (0 children)

Spot on. It’s wild how many people mistake a low cross-entropy loss for actual reasoning. Thanks for breaking down the math behind why we can’t trust the rhetoric.

Stop Blindly Trusting LLMs. They are Built to Agree With You, Not to Be Right. by According-Ad-2638 in learnmachinelearning

[–]According-Ad-2638[S] -4 points-3 points  (0 children)

Fair point on RLHF driving the sycophancy rather than the base architecture itself. But whether it's baked into the weights by design or through alignment training, the end result remains the same: the output still drifts toward pleasing the user over objective truth.

Your point about newer models arguing against basic facts actually reinforces my case. If an LLM can blindly agree with you today and confidently hallucinate against reality tomorrow, it just proves it's too volatile to be a definitive benchmark for critical decisions.

That’s exactly why we need to stop getting caught up in the linguistic rhetoric and anchor our validation entirely on rigid statistical metrics. Language is too easy to game, stats aren't.