SANA-WM, a 2.6B open-source world model for 1-minute 720p video

Nice, now instead of just reading slop you'll soon be able to experience slop Worlds, in 3D! /s

It's honestly impressive, on the surface. The visuals are gorgeous... but it's still empty. What makes a "World" a world is precisely it's coherency. It's not about how it looks but rather how it "works". The plants in an ecosystems are a certain way because of the available resources, all the way to forces like gravity. It doesn't just "look" like that. To echo Konrad Lorenz a fish doesn't just swim in the water, rather the fish IS an efficient representation of the water it lives within. Here in such "worlds" there is nothing happening. There is minimal superficial coherence, no logic, nothing.

The ultimate liminal spaces.

One thing is robotics. Both for training robotics AI, and to let robots test hypothetical actions before comitting to them. I don't think world models are stable enough for either yet

The other is creating multi-modal models with a better understanding of our world. LLMs often fail at incredibly basic spatial reasoning ("someone left a package in front of your apartment, describe going there", or the "should I drive to the car wash or go there", etc). World models excel at these kinds of things (in theory). They develop a great understanding of physical spaces, object interactions, etc. They can simulate fluids, rigid body physics etc. You "just" have to get really good at making world models, then somehow marry them with an LLM in a way that ensures the LLM can benefit from the world model's training data. Nobody has managed to really do that yet

So lots of hopes for the future. Until then they get commercialized as video models, or ways to experience your favorite forest, or to have a really bad video game ... whatever can be sold on a short time horizon to finance the actual goals

what subreddits do _you_ subscribe to?

I've been doing some content with people at https://industrialallusions.com

World models will be how general purpose robots finally work. They are essentially learned simulators of the world. They will replace traditional robotics simulators which are not flexible enough to enable training of general robotics policies. Robot control policies will be trained and evaluated in learned simulators, and the policies themselves will also be world models in order to predict the consequences of their own actions and thus enable planning. Simulated data will scale much better than expensive real-world robot data, and will allow robot policies to reach LLM-level dataset sizes, and subsequently, LLM-level performance.

It is inevitable that learned simulators will replace hand-coded simulators, as it is a straightforward application of the Bitter Lesson: http://www.incompleteideas.net/IncIdeas/BitterLesson.html

By enabling general purpose robotics, world models will be one of the most useful inventions of all time. For examples of what I'm talking about in current research, check:

Dreamer 4: https://danijar.com/project/dreamer4/

DreamDojo: https://arxiv.org/abs/2602.06949

Tesla's world model: https://www.youtube.com/watch?v=LFh9GAzHg1c

Waymo's world model: https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-f...