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Developer trains playable diffusion world model for Pokémon Red

A developer has created a playable diffusion world model for Pokémon Red, capable of generating game frames based on button presses and past visuals. This model, trained on an RTX 4090, also incorporates a System 1/System 2 agent harness, similar to Krafton's approach for PUBG Ally, to navigate and interact within the game. The project includes an upscaler and colorizer to enhance the low-resolution, greyscale output of the diffusion model, and has successfully demonstrated the ability to win the first gym badge in the game. AI

IMPACT Demonstrates novel applications of diffusion models and agent architectures in interactive environments.

RANK_REASON The item describes a novel research project involving training a diffusion model for a game world and an agent harness, with potential for workshop submission. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Developer trains playable diffusion world model for Pokémon Red

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The item describes a novel research project involving training a diffusion model for a game world and an agent harness, with potential for workshop submission. [lever_c_demoted from research: ic=1 …
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/priyanshu123sah ·

    I trained a playable diffusion world model of Pokémon Red, plus a game agent harness on the same System 1/2 split as Krafton's PUBG Ally. Can this be ICLR-workshop worthy? [P]

    <table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1xqt0pk/i_trained_a_playable_diffusion_world_model_of/"> <img alt="I trained a playable diffusion world model of Pokémon Red, plus a game agent harness on the same System 1/2 split as Krafton's PUBG Ally.…