World Models with NVIDIA Cosmos: Physical AI - AI Build & Learn

​Welcome to AI Build & Learn, a weekly AI engineering stream where we pick a new topic and learn by building together.

​This event goes bigger on world models with NVIDIA Cosmos, an open family of world foundation models built for physical AI. Where DreamerV3 learns a small world model for a single agent, Cosmos is a large generative model that simulates the physical world itself: predicting future video, running action-conditioned rollouts, and generating synthetic data to train robots and autonomous machines. It ties directly back to the Isaac Sim event.

​Cosmos 3 (released 2026) exposes two surfaces: a Reasoner for understanding and planning, and a Generator for world simulation and future prediction. The weights are open (OpenMDW license) and available on Hugging Face.

​Some things to look up to get started:

​Model:

• ​NVIDIA Cosmos (open platform of world models): /nvidia/cosmos

• ​Cosmos overview: https://www.nvidia.com/en-us/ai/cosmos/

• ​Cosmos Cookbook (runnable recipes): https://nvidia-cosmos.github.io/cosmos-cookbook/

​Reources

• ​GitHub: /sagecodes/ai-build-and-learn

• ​Events Calendar: https://luma.com/ai-builders-and-learners

• ​Slack (Discuss during the week): Flyte Slack Group

• ​Hosted by Sage Elliott: /sageelliott

​In this stream

• ​Intro to topic

• ​Community Discussion

• ​Practical examples

​Community challenge (optional)

​Try spending 30–90 minutes during the week learning or building something related to the topic, then share what you’re working on in Slack.

​Note on Flyte / Union

​You may see Flyte used in some demos. Flyte is an open-source AI orchestration platform maintained by Union (where I work) for building scalable, durable, and observable AI workflows. You do not need to use Flyte to participate.

• ​Union: https://www.union.ai/

• ​Flyte: https://flyte.org/

​Drop a comment with ideas for future topics (agents, RAG, MLOps, robotics, frameworks, and more).