{
  "video_id": "reddit_1upofuw",
  "channel_slug": "MachineLearning",
  "channel_handle": "r/MachineLearning",
  "title": "MIRA: Multiplayer Interactive World Models trained on Rocket League [R]",
  "url": "https://www.reddit.com/r/MachineLearning/comments/1upofuw/mira_multiplayer_interactive_world_models_trained/",
  "external_url": null,
  "upload_date": "20260707",
  "published_at": "2026-07-07T07:59:10+00:00",
  "transcript": "We're happy to release MIRA, a collaboration between General Intuition, Kyutai, and Epic Games.\n\nMira was trained on 10k hours of synthetic Rocket League data. The model has 5B parameters and runs for 4 players at 20 fps on a single B200.\n\nWe've released a playable online demo, an in-depth technical report as well as a 1k hour dataset of 4-players gameplay:\n\n**Demo: https://mira-wm.com**\nTechnical report: https://mira-wm.com/paper\nRepo: https://github.com/mira-wm/mira\n\nIf you're at ICML, we're also running an interactive demo (booth 111) where you can play it with us using proper PlayStation controllers!\n\n\n\n--- Top Comments ---\n\n\n[7 upvotes] The team is here if you have questions !\n\n[5 upvotes] wait the demo actually works in browser? hitting 20fps on one b200 for all 4 players is pretty tight\n\n  \nthe 10k hours of synthetic data part is interesting, always wondered how far you can push world models on purely generated training data. curious how it handles the weird edge cases in rocket league, like when physics go janky near the walls\n\n  \nmight swing by booth 111 if i can escape the poster session\n\n[5 upvotes] What a great result. Congratulations teams! \n\n[4 upvotes] Very cool result! I only skimmed the paper so I may have missed it but I’m curious why 10k hours was used instead of some other number. ",
  "transcript_chars": 1322,
  "ingested_at": "2026-07-07T13:30:20.287726+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 51,
    "upvote_ratio": 0.96,
    "num_comments": 12,
    "author": "MasterScrat",
    "is_self": true
  }
}