this post was submitted on 05 Sep 2024
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The model, called GameNGen, was made by Dani Valevski at Google Research and his colleagues, who declined to speak to New Scientist. According to their paper on the research, the AI can be played for up to 20 seconds while retaining all the features of the original, such as scores, ammunition levels and map layouts. Players can attack enemies, open doors and interact with the environment as usual.

After this period, the model begins to run out of memory and the illusion falls apart.

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[–] [email protected] 25 points 1 week ago (7 children)

It's cool but it's more or less just a party trick.

[–] [email protected] 10 points 1 week ago (4 children)

Is it though? We can show an AI thousands of hours of something and it can simulate it almost perfectly. All the game mechanics work! It even makes you collect keys and stock up on ammo. For a stable diffusion model that's pretty profound emergent behavior.

I feel like you're kidding yourself if you don't think this has real world applications. This is the kind breakthrough we need for self-driving: the ability to simulate what would happen in real life given a precise current state and a set of fictional inputs.

Doom is a low-graphics game, so it's definitely easier to simulate, but this method could make the next generation of niche "VidGen" models extremely accurate.

[–] [email protected] 2 points 1 week ago

Honestly I thinkyour self driving example is something this could be really cool for. If the generation can exceed real time (I.e. 20 secs of future image prediction can happen in under 20 secs) then you can preemptively react with the self driving model and cache the results.

If the compute costs can be managed maybe even run multiple models against each other to develop an array likely branch predictions (you know what I turned left)

Its even cooler that player input helps predict the next image.

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