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Moreover, it's all about use case. If you need a high degree of reliability and reproducibility, don't use LLMs! Not yet, at least. That's fine though, because
by phillipcarter 3y ago
Moreover, it's all about use case. If you need a high degree of reliability and reproducibility, don't use LLMs! Not yet, at least. That's fine though, because there's a ton of value they offer in solving problems where that isn't needed.
- bugglebeetle 3y ago> If you need a high degree of reliability and reproducibility, don't use LLMs! This is true of pretty much all of machine learning. LLMs are just getting singled out because their outputs are not getting the same level of validation that typicall occurs with older approaches. BERT models will also spit out whacky stuff, depending on how they’re trained/fine-tuned/used/etc
- 3abiton 3y agoI wonder if there will be a new metric implemented in evaluating LLMs: Hallucination score.