Mirage 2 – Generative World Engine
Posted5 months agoActive5 months ago
demo.dynamicslab.aiTechstory
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Generative AIGame DevelopmentWorld Modeling
Key topics
Generative AI
Game Development
World Modeling
The Mirage 2 demo showcases a generative world engine that creates immersive environments based on input images, with users discussing its potential for game development and noting its current limitations.
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- 01Story posted
Aug 21, 2025 at 5:25 PM EDT
5 months ago
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Aug 21, 2025 at 8:04 PM EDT
3h after posting
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Aug 26, 2025 at 9:21 PM EDT
5 months ago
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ID: 44978286Type: storyLast synced: 11/20/2025, 5:36:19 PM
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Starlight Village just has Scar the lion from Lion King right there at the bottom lol
The interesting possibility is that all you may need for the setting of a future AAA game is just a small bit of the environment to nail down the art direction. Then you can dispense with the army of workers to place 3D models on the map in just the right arrangment to create a level. The AI model can extrapolate it all for you.
Clearly the days of fiddly level creation with a million inscrutable options and checkboxes in something like Unreal, or Unity, or Godot editors are numbered. You just say what you want and how you want to tweak it, and all those checkboxes and menus are disposable. As a bonus that's a huge barrier to entry torn down for amateur game makers.
The tech alone of being able to take prefabs and just prompt your way to a world is amazing. Now to get that in blender...
Might have potential, but I wasn't terribly impressed by the lack of consistency.
For those wanting to see it in action, the wait times are wildly inaccurate. Wait five or six minutes and you'll probably get through.
Hackers screenshot + file system context = Ideal navigation
https://i.imgur.com/dBXdcd9.png
- Infra/systems: I was able to connect to a server within a minute or two. Once connected, the displayed RTT (roundtrip time?) was around 70ms but actual control-to-action latency was still around ~600-700ms vs the ~30ms I'd expect from an on-device model or game streaming service.
- Image-conditioning & rendering: The system did a reasonable job animating the initial (landscape photo) image I provided and extending it past the edges. However, the video rendering style drifted back to "constrast-boosted video game" within ~10s. This style drift shows up in their official examples as well (https://x.com/DynamicsLab_AI/status/1958592749378445319).
- Controls: Apart from the latency, control-following was relatively faithful once I started holding down Shift. I didn't notice any camera/character drift or spurious control issues, so I guess they are probably using fairly high-quality control labels.
- Memory: I did a bit of memory testing (basically - swinging view side to side and seeing which details got regenerated) and it looks like the model can retain maybe ~3-5s of visual memory + the prompt (but not the initial image).