Comment by CSMastermind
10 hours ago
It's an overloaded term for AI models that have spatial reasoning LLMs currently lack.
Best definition I've heard is: AI systems that can build an internal map of their surroundings to anticipate what happens next and make decisions based on their predictions about the consequences the different actions they can take would have.
There's a bunch of different approaches people are trying:
- World labs (linked in this post) is going down the route of neural 3D representation work (NeRFs, 3D Gaussian Splatting)
- Yann LeCun is pretty famously betting on JEPA architectures (check out the excellent Welch Labs videos for more)
- Google is betting on generative video
- Karl Friston was pursuing 'active interference,' which is just traditional RL techniques with different reward functions
Small correction, World Labs isn't betting exclusively on explicit 3D -- many of the Atlas results in this post are generated frames without any explicit underlying 3D representation. But Atlas can (optionally) output explicit 3D for the cases where you know you want it.