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MIRA

Multiplayer World Model Trained on Rocket League

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HN · launched Jul 7, 2026 · 12 upvotes (top 40%) · 0 views

Niche: ai game generation and simulation tools · 122 launches, 13 in the last 7 days ▲ +18% · Explore this niche →

Category and tags

  • Media & entertainment
  • Content generation
  • B2C
  • AI-native
  • Hobby / open-source project

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Could you build this?

No Training a multiplayer generative world model for high-speed, 3D physics-driven games like Rocket League demands novel video/physics foundation model research, massive GPU clusters, and high-frequency real-time inference infrastructure.

What it would actually take: Requires collecting millions of hours of gameplay telemetry and video frames, training auto-regressive or diffusion-based generative video models with action conditioning (similar to Oasis/Genie), and optimizing low-latency distributed inference. It demands senior AI research scientists, distributed ML systems engineers, and tens to hundreds of thousands of dollars in GPU compute.

Discussion

6 comments analyzed.

Concerns raised: Out-of-distribution generalization capability unclear, Model may have learned training distribution rather than deeper world understanding, Doesn't handle hidden information or theory of mind, Multi-player view desynchronization risks

Feature requests: Analyze latents to understand what model learned, Apply to data-constrained settings like robotics, Single-player mode with hidden object occlusion

Competitors

Other products that read as similar to this one : 2231 launches clear the similarity bar, closest 8 shown.

Attention rank: #834 of 2232 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 250 days after the earliest competitor.

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