You can read plenty of details in the blog post and tech report but the TLDR is that we trained a multiplayer world model on 10k hours of Rocket League data. We optimized it to be playable at 20fps on a single GPU.
So what you see in the demo is fully generated: there’s no graphics or physics engine. Instead it’s a 5b neural network that takes actions in and gives pixels out.
Having a direct transformation would enable some interesting experiments.
How is the latent state different when everything else stays the same, but you change one physics value, like player one velocity? Is there a cyclical pattern of activation that correlates strongly with the seconds digit of the clock? Can you decode the latent state, give players full boost, and then re-encode it for infinite boost, without losing continuity?
Edit: There sure are a lot of papers on interpretability.
What is the conversation like within Epic now? Is this still the view? What is the future for simulations like this?
I'd be interested in seeing if fine-tunes that include human gameplay data would be possible.