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KerfuffleV2 t1_jefkhxs wrote

Reply to comment by Dapper_Cherry1025 in [P] Introducing Vicuna: An open-source language model based on LLaMA 13B by Business-Lead2679

> Something about these distillations feels fundamentally different than when interacting with the larger models.

It may not have anything to do with size. ChatGPT is just adding a lot of comfort-phrases into its response instead of just responding. "Hmm, this is an interesting challenge", "Let's see", etc. Some of that may be based on the system prompt, some of it may be training to specifically produce more natural sounding responses.

All "Hmm", "interesting challenge" and stuff that makes it sound like a person isn't actually adding any actual information that's relevant to answering the query though. (Also, you may be paying for those extraneous tokens.)

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Dapper_Cherry1025 t1_jefywqj wrote

Well, that's probably because I specifically asked it to use an internal monologue. I think what I'm trying to say is that each part of its response does seem to flow in a logical way that I found easy to understand. Heck, when I refined my prompt down for 3.5 I was able to get it to admit that it couldn't come up with a solution when I tried to get a more complicated example.

I also find it very interesting that when chatgpt starts a sentence with something like "Yes, because..." I know right away that the answer is probably incorrect, because after it replies "Yes" it will then try to justify the yes even if it is wrong. However, if you can get it to investigate a problem like shown in the example it can actually try different things before arriving at a solution.

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