TechTakes

The promptfarmers can push the hallucination rates incrementally lower by spending 10x compute on training (and training on 10x the data and spending 10x on runtime cost) but they're already consuming a plurality of all VC funding so they can't 10x many more times without going bust entirely. And they aren't going to get them down to 0%, hallucinations are intrinsic to how LLMs operate, no patch with run-time inference or multiple tries or RAG will eliminate that.

And as for newer models... o3 actually had a higher hallucination rate because trying to squeeze rational logic out of the models with fine-tuning just breaks them in a different direction.

I will acknowledge in domains with analytically verifiable answers you can check the LLMs that way, but in that case, its no longer primarily an LLM, you've got an entire expert system or proof assistant or whatever that can operate independently of the LLM and the LLM is just providing creative input.