Stanhope AI

Odyssey-3 is a foundation world model and learned dynamical system that predicts how objects move and interact through space and how situations evolve over time. Implemented as an autoregressive diffusion transformer, it learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations and uses that knowledge to simulate environments and train policies for physical systems. Odyssey-3 can generate embodied environments from a prompt and predict in real time how they change as a person or agent acts or introduces events, with first-person and third-person navigation and independent camera movement. Its learned world knowledge can be adapted to different systems by training an action decoder or policy on paired observations and actions. With relatively small amounts of task-specific data, Odyssey-3 has been used to control robot arms, power humanoids, drive vehicles, and generate synchronized multi-sensor observations.

NVIDIA Cosmos is a developer-first platform of state-of-the-art generative World Foundation Models (WFMs), advanced video tokenizers, guardrails, and an accelerated data processing and curation pipeline designed to supercharge physical AI development. It enables developers working on autonomous vehicles, robotics, and video analytics AI agents to generate photorealistic, physics-aware synthetic video data, trained on an immense dataset including 20 million hours of real-world and simulated video, to rapidly simulate future scenarios, train world models, and fine‑tune custom behaviors. It includes three core WFM types; Cosmos Predict, capable of generating up to 30 seconds of continuous video from multimodal inputs; Cosmos Transfer, which adapts simulations across environments and lighting for versatile domain augmentation; and Cosmos Reason, a vision-language model that applies structured reasoning to interpret spatial-temporal data for planning and decision-making.