Oasis: A Universe in a Transformer
Oasis is an innovative AI model for real-time, open-world gameplay, generating interactions based on user inputs at 20 frames per second, with future enhancements planned for clarity and control.
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Oasis is a groundbreaking AI model that enables real-time, open-world gameplay entirely generated by artificial intelligence. It responds to user inputs, allowing players to interact with the environment through actions like moving, jumping, and item manipulation without relying on a traditional game engine. The model utilizes a transformer architecture, specifically a spatial autoencoder and a latent diffusion backbone, to ensure stable and fast performance. Oasis can generate diverse settings and mechanics, demonstrating capabilities in building, lighting physics, and inventory management. The model operates at 20 frames per second, significantly faster than existing text-to-video models, which can take much longer to produce a single second of video. Future developments aim to address challenges such as video clarity at distances, temporal consistency, and precise control over game elements. The creators believe that scaling the model and datasets will enhance performance, and they are exploring new inferencing technologies to improve efficiency and reduce costs. The Oasis code and a demo are now available for public use, marking a significant step towards more complex interactive AI-driven worlds.
- Oasis is the first playable, real-time, open-world AI model.
- It generates gameplay based on user inputs without a traditional game engine.
- The model operates at 20 frames per second, outperforming current text-to-video models.
- Future improvements will focus on video clarity, temporal consistency, and control precision.
- The code and demo for Oasis are publicly available for experimentation.
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- Users note the lack of persistent memory in the demo, leading to a transient experience.
- Some express skepticism about the model's effectiveness and energy consumption.
- There are comparisons to previous projects, suggesting a broader trend in AI-driven game development.
- Comments reflect excitement about the potential for generative AI to enhance gameplay mechanics.
- Concerns are raised about the tracking of state changes within the game environment.
12 comments81 comments, 241 points.
They made a great decision by letting me download the video of my journey when the demo ended. I saw some neat constructs and was thinking, "I wish I could show this to some friends." I can!
If you get lost in the dark like I did, just press E to bring up the items menu. Doing that a couple of times and moving around a bit brought some novelty back into view for it to work with.
Generative AI could be an interesting approach to the issue of solving the "what happens if you destroy [any particular element]" aspect.
For a lot of games you'd probably still want to have specific destinations set in the map; maybe now it's just much more open-ended as far as how you get there (like some of the ascend-through-matter stuff in Tears of the Kingdom, but more open-ended in a "just start trying to dig anywhere" way and you use gen AI to figure out exactly how much dirt/other material will get piled up for digging in a specific place?).
Or for games with more of an emphasis on random drops, or random maps, you could leverage some of the randomness more directly. Could be really cool for a roguelike.
I'd like to do a deeper dive into the two approaches, but on a surface level one interesting note is Oasis specifically mentions using a use-specific ASIC (presumably for inference?):
> When Etched's transformer ASIC, Sohu, is released, we can run models like Oasis in 4K.
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