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Comment by nine_k | Hacker News Reader

But it's not a game. It's a memory of a game video, predicting the next frame based on the few previous frames, like "I can imagine what happened next".

I would call it the world's least efficient video compression.

What I would like to see is the actual predictive strength, aka imagination, which I did not notice mentioned in the abstract. The model is trained on a set of classic maps. What would it do, given a few frames of gameplay on an unfamiliar map as input? How well could it imagine what happens next?

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> But it's not a game. It's a memory of a game video, predicting the next frame based on the few previous frames, like "I can imagine what happened next".

It's not super clear from the landing page, but I think it's an engine? Like, its input is both previous images and input for the next frame.

So as a player, if you press "shoot", the diffusion engine need to output an image where the monster in front of you takes damage/dies.

How is what you think they say not clear?

We present GameNGen, the first game engine powered entirely by a neural model that enables real-time interaction with a complex environment over long trajectories at high quality.

No, it’s predicting the next frame conditioned on past frames AND player actions! This is clear from the article. Mere video generation would be nothing new.

It's more like the Tetris Effect, where the model has seen so much Doom that it confabulates gameplay.

It's a memory of a video looped to controls, so frame 1 is "I wonder how would it look if the player pressed D instead of W", then the frame 2 is based on frame 1, etc. and couple frames in, it's already not remembering, but imagining the gameplay on the fly. It's not prerecorded, it responds to inputs during generation. That's what makes it a game engine.

They could down convert the entire model to only utilize the subset of matrix components from stable diffusion. This approach may be able to improve internet bandwidth efficiency assuming consumers in the future have powerful enough computers.

If it's trained on absolute player coordinates then it would likely just morph into the known map at those coordinates.

But it's trained on the actual screen pixel data, AFAICT. It's literally a visual imagination model, not gameplay / geometry imagination model. They had to make special provisions to the pixel data on the HUD which by its nature different than the pictures of a 3D world.

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