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It's actually terrible at parsing natural language. So bad that on a long enough text (or even short if you're unlucky) it will 100% of the time come up with to
by iLoveOncall 2y ago
It's actually terrible at parsing natural language. So bad that on a long enough text (or even short if you're unlucky) it will 100% of the time come up with tokens that are not present in the original text.
This sort of rethoric is exactly the same as with crypto "yeah ok it's bad now but think of the future".
- infecto 2y agoSorry you have had such bad experiences we won't be able to convince and nobody can see the future but there are exciting things happening at an amazingly short scale.
- willsmith72 2y agostrong disagree. what's "long enough" to you? i can find huge value out of it parsing natural language at even less than 1000 words. their context is way bigger than that already
- estebarb 2y agoReally? ChatGPT 3.5 and beyond models are fairly capable of understanding PoS and doing text analysis. I have never seen that issue yet with the more advanced models, although smaller/older ones tend to imagine fmthings about the text. Last year I wrote a paper about using LLMs for definition generation for unknown words based on context, and the models did a fairly good job. https://ieeexplore.ieee.org/abstract/document/10346136/ https://ieeexplore.ieee.org/abstract/document/10346136/ if someone is curious. I would like to read prompts where the models are failing in such way. The field is moving quite fast.