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Playing a Neural Network's version of GTA V: GAN Theft Auto

sentdexRecommended by 3 HN commenters across 4 months, 2021–2025
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demo · general · 2021–2025 on HN

Sentdex demonstrates GAN Theft Auto, a GameGAN-based neural network that recreates GTA V so the network itself is the playable environment. He shows the results and releases the code.

Cited as an early, striking demo of neural networks acting as game engines and world models.

12 comments from Hacker News

@77341282024-08 · in “Diffusion models are real-time game engines”

What you're describing reminded me of this cool project: ▶ this video "Playing a Neural Network's version of GTA V: GAN Theft Auto"

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@eru2022-12 · in “Netflix: 30% bitrate saving using Film Grain Synthesis”

> You could directly encode the elements as understanded by the process used to generate them, rather than attempting to reconstitute things from a stream of bitmaps. You might like Gan Theft Auto: ▶ this video

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@ALittleLight2022-04 · in “DALL-E, the Metaverse, and Zero Marginal Content”

This YouTube video, to me, shows the promise of things to come. AI generated game worlds. Language models to generate plots and dialog, transformers and GANs to create illustrations. Imagine a game, a truly open world sand box, Grand Theft Auto meets AI Dungeon - every NPC is a "real" person with unlimited dialog options, the buildings you drive by you could easily walk in and investigate, unlimited play space - you could type in more general instructions and ideas to the plot generator ("add in a vampire romance and murder mystery angle") on the fly. ▶ this video

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@ALittleLight2021-08 · in “Where are the robotic bricklayers?”

This video really amazed me in terms of automated game development. My fantasies are something like this and GPT-3 plus a couple decades of progress. I think we'll get to genuinely open ended sand box games. ▶ this video

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@imtringued2025-11 · in “Spatial intelligence is AI’s next frontier”

>There's some progress in video generation which takes a short clip and extrapolates what happens next. That's a promising line of development. The key to "common sense" is being able to predict what happens next well enough to avoid big mistakes in the short term, a few seconds. How's that coming along? And what's the internal world model, assuming we even know? ▶ this video This has been a thing for a while. It's actually a funny way to demonstrate model based control by replacing the controller with a human.