GPT-4 Generates an RPG: How a Neural Network Builds Locations and Characters

Two years ago, an attempt to build an RPG generator on GPT-4 and Stable Diffusion failed. The technology barely handled ASCII maps, and a consistent world was out of the question. Now the team is back with funding and a reworked pipeline. Modern neural networks generate locations, NPCs with dialogue, tiles, branching storylines, voice acting and music. The genre has changed to a turn-based 2.5D narrative RPG, and that is a deliberate architectural choice.

AI-processed from Habr AI; edited by Hamidun News
GPT-4 Generates an RPG: How a Neural Network Builds Locations and Characters
Source: Habr AI. Collage: Hamidun News.
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Two years ago, a developer tried to build a neural RPG generator on GPT-4 and Stable Diffusion. The result was poor, but he is back with funding and a rethought architecture that actually works.

Which neural networks do you need to create a game?

The developer uses GPT-4 for logic and content, and Stable Diffusion for visuals: locations, sprites and other game elements.

Can a neural network create a complete game from a single prompt?

Yes, in the new system. The user writes a prompt and gets a finished game with a world, characters, mechanics and gameplay, not just a chat.

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Key Questions Answered

Which neural networks do you need to create a game?

The developer uses GPT-4 for logic and content, and Stable Diffusion for visuals: locations, sprites and other game elements.

Can a neural network create a complete game from a single prompt?

Yes, in the new system. The user writes a prompt and gets a finished game with a world, characters, mechanics and gameplay, not just a chat.

ZK
Zhemal Khamidun — CPO at Alpina Digital, product manager of AlpinaGPT. Building AI products since 2019. Hamidun News is a pet project that grew into a production aggregator with 6,000+ readers.
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