Agora-1
Agora-1 is a multi-agent world model released by the AI lab Odyssey on 18 May 2026.
World Models
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Showing 1-12 of 12 articles
GAIA-2 (Wayve)
GAIA-2 (Generative AI for Autonomy 2) is a controllable, multi-camera generative world model for autonomous driving, announced by the British self-driving company Wayve on 26 March 2025.
GAIA-3 (Wayve)
GAIA-3 is a 15-billion-parameter generative world model for autonomous driving released by Wayve on 2 December 2025, the third generation in the company's GAIA family.
GAIA-4 (Wayve)
GAIA-4 is a multimodal generative world model for closed-loop autonomous driving simulation, announced by the British self-driving company Wayve on 3 August 2026 as the latest generation of its GAIA family.
Genie 3
Genie 3 is a general-purpose foundation world model developed by Google DeepMind and announced on August 5, 2025, that generates interactive, navigable 3D environments from a single text prompt and runs in…
Lumo-2
Lumo-2 is a 4B-scale robot-learning model developed by Astribot. Astribot describes it as a latent world-action model: instead of rendering a future video before acting, it predicts an action-relevant…
NVIDIA Cosmos
NVIDIA Cosmos is a world foundation model platform developed by NVIDIA for physical AI applications, including autonomous vehicles and robotics.
Odyssey-2
Odyssey-2 is a family of real-time, interactive generative models built by the AI lab Odyssey.
Odyssey-3
Odyssey-3 is a foundation world model announced on September 15, 2026 by Odyssey, an AI lab founded in 2023 by Oliver Cameron and Jeff Hawke.
Starchild-1
Starchild-1 is a real-time audio-video world model built by the AI lab Odyssey. It generates synchronized video and sound autoregressively, chunk by chunk, while a user streams new text, speech and action…
V-JEPA 2
V-JEPA 2 (Video Joint Embedding Predictive Architecture 2) is an open-source video world model released by Meta AI on June 11, 2025 that learns to understand, predict, and plan in the physical world by…
World action model
A world action model (WAM) is a robot policy design that builds action generation on a video world model backbone rather than on a vision-language model, so that a single network jointly predicts how a scene…