Pretty impressed by this:
https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/
I will not bet in this market. I will look primarily at whatever benchmarks are most prominent at the time to determine which model is better.
The model does not have to be clearly superior to gpt-4, if it's just a bit better I will resolve YES. If anyone has suggestions for less subjective resolution criteria that won't be goodharted I am open.
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@SemioticRivalry I just noticed this question seems to have some similarity to this other one:
/_deleted_/will-a-15-billion-or-less-parameter
You seem to have a lot of knowledge about this subject and I very much do NOT. Would you be able to review my chain of comments in the other market and confirm them or refute them, and also see if they apply in any way to your own market here?
(My comments there are just completely flailing around, I have no idea what any of it means. Even though the market is resolved I am very willing to reconsider if someone knows more about the subject.)
if the model can be stored on 10b params but takes 100000x more time at inference time, because it searches through lots of possibilities or reprompts itself a bunch of times or similar tricks to improve its output, would that still count? In 2023 it would still not be practical to run, but it would still be smaller in the ‘# of parameters‘ sense