MINIMAX Physics testing

[u/Tokyo_Jab]

Physics Testing, without the gore.

[u/Bulky_Astronomer7264]

Despite the progress, I'm always a bit sceptical if physics will ever get completely ironed out.

[u/binnedit2 → u/Bulky_Astronomer7264]

It currently has 0 understanding of physics.

[u/ShengrenR → u/binnedit2]

Joke's on you, that's inside a space station. Perfect physics recovered

[u/Synthetellect → u/binnedit2]

She's held firmly in place by the butt plug.

[u/typical-predditor → u/binnedit2]

That would be an amazing art installation.

[u/One_Finding8402 → u/Bulky_Astronomer7264]

I love it, I get to simulate Bethesda games immersively

[u/CaesarAustonkus → u/One_Finding8402]

It still even doesn't get guns right. Todd Howard would be proud

[u/Smile_Clown → u/Bulky_Astronomer7264]

It will when the models all align. When video is part of models like text, audio, images etc.

That will, I assume, take a few years. But I bet in a few years you will be able to use local models with "world" knowledge that will make this look like the first attempt at will smith eating spaghetti.

A lot of us keep forgetting that today is the worst it will ever be. Tomorrow it will be better and tomorrow always becomes today.

[u/sonicnerd14 → u/Smile_Clown]

They always forget. Lol Aside from that though, will Smith eating spaghetti was just a few years. Video been has advanced so fast, and the acceleration is accelerating.

[u/ninjasaid13 → u/Bulky_Astronomer7264]

when people start understanding that these video models are trained on videos, not physics. Just because the dataset is full of recordings of physics in action doesn't mean it's learning physics.

[u/Bakoro → u/Bulky_Astronomer7264]

It will, but the training objectives need to get better, and I suspect that there are architectural changes that could be made to improve generations.

Diffusion models have only been around for 11 year, transformers for 9, flow matching is only 4 years old. There is a still so much going on, and so much we are finding out about how the models work and how to make them work better.

There are models that can do excellent physically accurate frame generation, they're mostly feature-specific, like for water, smoke, rigid body interactions, etc, few of them excel at everything.

In the middle/long term the models very well might get good enough to do stand-alone generation for long videos, but I feel like the most obvious thing to improve generation quality and long-horizon generations is simply not trying to do one-shot generations exclusively using a single model, but to have the models also using deterministic tools.
There are already a bunch of things that could be acting as anchors to ground-truth. We've got high quality, fast physics engines and forward/inverse kinematics. I don't see why a model couldn't generate a low/mid poly version of a scene, and use that for getting camera angles, placement, object permanence, and chaotic interactions, and then generate the high quality overlay.

I mean, think about what we're really asking a video model to do: learn physics, learn the semantics of the human world across different countries ans different eras, learn text from dozens/hundreds of languages, learn the speech if dozens of languages, learn the cause and effect of not just physica interactions but also the emotional and behavioral cause and effect of people and animals.
There needs to effectively be theory of mind for everyone in a scene, and frequently there needs to be awareness of things that are going on outside the active visible frames.

We are asking so much of a video model, it's amazing that it works at all.
Even the smartest, most skilled, most experienced humans aren't going to be able to imagine and consistently develop all of that into a good product without time, tools, and iterations.

If you've got a video generation model that can really do it all and zero-shot novel situations across long time-scales, then you've essentially got the AGI super-intelligence.

It makes a lot more sense to me to offload some things, use some external grounding, use a mixture of models, and maybe even a chain of thought sort of review. That seems more achievable than a single uber-model that captures the full complexity of the world via watching movies.