3 ms·
Not too shocking for me after this paper. https://arxiv.org/abs/2211.09066 https://arxiv.org/abs/2211.09066 You can teach GPT-3 arithmetic - https://imgur.com/
by famouswaffles 4y ago
Not too shocking for me after this paper. https://arxiv.org/abs/2211.09066 https://arxiv.org/abs/2211.09066
You can teach GPT-3 arithmetic - https://imgur.com/a/w3DAYOi https://imgur.com/a/w3DAYOi
Basically 100% accuracy up to about 13 digit addition and >90 after that.
What else can you teach GPT without changing weights ?
- mirashii 4y ago> 100% accuracy up to about 13 digit addition The graphs you just posted do not support that, they'd support at most 100% accuracy up to 4 digits.
- famouswaffles 4y agoIt's 100 at 13 and extremely close to it prior to that. Maybe basically 100 is better.
- sharemywin 4y agoit's GPT so 13=4
- cs702 4y agoI meant shocking in the sense that it makes me gape in awe, but as I wrote, it's also, simultaneously, completely unsurprising given all the new emergent capabilities we keep discovering. We're in agreement :-)
- famouswaffles 4y agoOh. yes well that's fair
- gopalv 4y ago> and >90 after that This is such a circular thing, that I feel like it is amazing to see it. The reason LLMs use a NN is because they're trying to encode a probability function for generating the passage. And now, you are encoding another n-gram follower exercise (i.e 1+1 = 2) on top of it :)
- Paul-Craft 4y agoYeah... and I'm kind of suspicious of the whole "without changing the weights" deal, because adding working context to the model, like telling it the algorithm for adding numbers really sounds like there's some model state that's getting mutated, even if it's not stored in a file called weights.dat or whatev.