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> Yes, any language model with a true/false output trained for one step with a successful decrease in the loss on the full spectra of text satisfies this criter
by medo-bear 4y ago
> Yes, any language model with a true/false output trained for one step with a successful decrease in the loss on the full spectra of text satisfies this criterion
I understand that LLMs seem impressive but they still fail on human behaviour that is sufficiently outside of training sample
And to be sure, I agree that we can model human behaviour in various succesful ways. But I think it is wrong to dismiss NFL. Instead the real challange is defining and structuring the problem domain. If you do that successfuly then all talk about NFL becomes irrelevant
- tbalsam 4y agoAgain, you've got to look at the mathematical foundations here. Shannon and frequentist statistics will help in particular. I'd encourage you to go back to the mathematical roots and take a good gander over it. I find it to be a very rewarding journey in and of itself.
- medo-bear 4y agoI read through few simple explanations that might help you. This seems like a good candidate https://towardsdatascience.com/what-no-free-lunch-really-means-in-machine-learning-85493215625d https://towardsdatascience.com/what-no-free-lunch-really-mea...
- medo-bear 4y agoI work in the field