Doom Running on a Neural Network Is a Surreal Dreamscape

We’ve already seen the iconic 1993 video game Doom being played on devices ranging from a candy bar to a John Deere tractor to a Lego brick to E. Coli cells. Now, researchers at Google and Tel Aviv University have taken the viral trend even further, by using a generative AI model to run the game instead of a conventional video game engine. The results are about as trippy as one would expect, as seen in a video shared by the researchers, with bad guys morphing in and out of existence and walls shifting unnvervingly. Visual weirdness aside, it’s still an impressively faithful rendition of the 1993 video game and a striking demonstration of the power of the tech. “Can a neural model running in real-time simulate a complex game at high quality?” the researchers wrote in their yet-to-be-peer-reviewed paper. “In this work, we demonstrate that the answer is yes.” “Specifically, we show that a complex video game, the iconic game Doom, can be run on a neural network,” they added. Conventionally, video game engines react to user inputs and visually render the scene according to a manually programmed set of rules. But by harnessing the power of diffusion models, used by most mainstream AI image generators like Stable Diffusion and DALL-E, the researchers found they could ditch the approach in favor of AI. Their new diffusion model, dubbed GameNGen, is based on Stable Diffusion’s open-source version 1.4 and was trained on 900 million frames taken from existing Doom gaming…Doom Running on a Neural Network Is a Surreal Dreamscape

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