> But the other side doesn't see it that way, specifically not the "something more" part. It's "just math" all the way down, in our brains as well. The "emergent phenomena" are not undefined in this sense - they're (obviously in LLMs) also math, it's just that we don't understand it yet due to the sheer complexity of the resulting system. But that's not at all unusual - humans build useful things that we don't fully understand all the time (just look at physics of various processes). You might not, but you don't have to look far in these very comments to be met with woo and mysticism on the emergent phenomena side, either. > The obvious explanation is that, between the limited amount of information that can be extracted from 2D photos that the NN is trained on, and the limit on the complexity of world modeling that NN of a particular size can fit, its model of the world is just not particularly accurate. I think the more obvious solution is that it's not modelling the world, because... why would it be? It seems obvious to me that this is a significantly more complex way to handle their given task than every other explanation that does not require them create a model of the world. > Pragmatically, at some point, you have to pick the most likely (usually this means the simplest) explanation to move forward. I agree completely with this, which is why the idea that this is modelling the world is absolutely bizarre to me, particularly when our understanding of their training is that it's all weighting for pixel nearest neighbors via ranking how well it does at denoising 2D images. It's not like de-rendering is something new, either. ShaderMap has existed since the mid 2000s and could get similar results from 2D images without any AI/ML, and we have other models that can generate it without anyone suggesting they model the world, e.g. arxiv.org/abs/2201.02279 People like LeCun don't think that even models where the stated goal is world simulation are able to do it, e.g. sora, either - twitter.com/ylecun/status/1758740106955… - so it seems even more unlikely when that isn't the goal that this has happened due to some emergent phenomenon.

Video, he says 1. The next frame is easy, but multiple frames is not 2. What works for text doesn't work for video. Then Sora comes out and shows multiple frames and someone tweets gotcha. He then tweets without saying he misspoke ..... goes on about the model doesn't understand physics. And his project, V-JEPA, is the best He keeps saying stuff about "sucks as a mental model" but doesn't say why that would not apply to text. twitter.com/ylecun/with_replies Me: If text doesn't need a mental model, I see no reason video needs it. His argument sucks or is badly worded.