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It varies a lot for me. One day it takes scattered documents, pasted in, and produces a flawless summary I can use to organize it all. The next, it barely manag
by Kye 2y ago
It varies a lot for me. One day it takes scattered documents, pasted in, and produces a flawless summary I can use to organize it all. The next, it barely manages a paragraph for detailed input. It does seem like Google is quick to respond to feedback. I never seem to run into the same problem twice.
- lambdaba 2y ago> It does seem like Google is quick to respond to feedback. I'm puzzled as to how that would work, when people talk about quick changes in model behavior. What exactly is being adjusted? The model has already been trained. I would think it's just randomness.
- Kye 2y agoMagic And fine tuning. Choose your fighter... High level overview: https://www.datacamp.com/tutorial/fine-tuning-large-language-models https://www.datacamp.com/tutorial/fine-tuning-large-language... More detail: https://www.turing.com/resources/finetuning-large-language-models https://www.turing.com/resources/finetuning-large-language-m... Nice charts: https://blogs.oracle.com/ai-and-datascience/post/finetuning-in-large-language-models https://blogs.oracle.com/ai-and-datascience/post/finetuning-... The big platforms also seem to employ an intermediate step where they rewrite your prompt. I've downloaded my ChatGPT data and found substantial changes from what I wrote. Usually for the better. Changes to the way it rewrites changes the results.
- brookst 2y agoSystem prompts have a huge impact on output. Prompts for ChatGPT/etc are around a thousand words, with examples of what to do and what not to do. Minor adjustments there can make a big difference.
- jaggs 2y agoI've found this as well. On a good day Gemini is superb. But otherwise, awful. Really weird.