Rocket league is one of my favourite games, and I'm pretty decent at it (rank champion 1). I kinda felt like my controller was a bit broken when playing this, a lot of commands were just ignored, and forget doing stuff like speed flips. But I did feel like was controlling the car, and everything about the game looked very much like the real thing. Ball movement was on point, I didn't notice any weird bounces or anything.

The lack of opponents pulling triple flip resets and double-tapping musty's (musties?) was the most notable difference from the real thing

Side-effect of the data: clearly the model is better than I normally am at playing, as it spontaneously did several things I had not told it to do and wouldn't really know how to do (at least not with a keyboard).

Really remarkable, congrats!

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.

It often feels like the model is ignoring my inputs and just doing what it would expect the bot to do (which is unsurprising if the model could predict what would happen next during training without paying attention to the inputs)