Earlier quoted context omitted.
And I'm surprised how many people think they can confidently tell whether they're looking at an s-curve or an exponential function based on very limited data points. I don't even doubt that superintelligence is a very real possibility! But it might or might not happen, and if it does, it might or might not be based on deep learning. As a counterexample: The maximum speed of travel for the average person for millenia…
Maybe don't think of it as curves or functions. Just go through an LLM and think about all the things that could be improved. It's a long list once you get into the details. By and large...sota models are: a) trained on crappy data, including questionable RLHF feedback. b) trained with questionable embedding layers. c) trained with questionable loss functions d) trained with questionable optimizers e) trained at ques…
But when talking about future growth potential, I don't think you can get around making assumptions about the shape of the growth function.