I think one of the biggest problems is the models are trained on 2D sequences and don't have any understanding of what they're actually seeing. They see some structure of pixels shift in a frame and learn that some 2D structures should shift in a frame over time. They don't actually understand the images are 2D capture of an event that occurred in four dimensions and the thing that's been imaged is under the influence of unimaged forces.

I saw a Santa dancing video today and the suspension of disbelief was almost instantly dispelled when the cuffs of his jacket moved erratically. The GenAI was trying to get them to sway with arm movements but because it didn't understand why they would sway it just generated a statistical approximation of swaying.

GenAI also definitely doesn't understand 3D structures easily demonstrated by completely incorrect morphological features. Even my dogs understand gravity, if I drop an object they're tracking (food) they know it should hit the ground. They also understand 3D space, if they stand on their back legs they can see over things or get a better perspective.

I've yet to see any GenAI that demonstrates even my dogs' level of understanding the physical world. This leaves their output in the uncanny valley.

They don't even get basic details right. The ship in the 8th video changes with every camera change and birds appear out of nowhere.

As far as I can tell it's a problem with CGI at all. Whether you're using precise physics models or learned embeddings from watching videos, reproducing certain physical events is computationally very hard, whereas recording them just requires a camera (and of course setting up the physical world to produce what you're filming, or getting very lucky). The behind the scenes from House of the Dragon has a very good discussion of this from the art directors. After a decade and a half of specializing in it, they have yet to find any convincing way to create fire other than to actually create fire and film it. This isn't a limitation of AI and it has nothing to do with intelligence. A human can't convincingly animate fire, either. It seems to me that discussions like this from the optimist side always miss this distinction and it's part of why I think Ben Affleck was absolutely correct that AI can't replace filmmaking. Regardless of the underlying approach, computationally reproducing what the world gives you for free is simply very hard, maybe impossible. The best rendering systems out there come nowhere close to true photorealism over arbitrary scenarios and probably never will.

What's the point of poking holes in new technology and nitpiking like this? Are you blind to the immense breakthroughs made today and yet you focus what irks you about some tiny detail that might go away after a couple of versions?

Neural networks use smooth manifolds as their underlying inductive bias so in theory it should be possible to incorporate smooth kinematic and Hamiltonian constraints but I am certain no one at OpenAI actually understands enough of the theory to figure out how to do that.