{"href":"https://api.simplecast.com/oembed?url=https%3A%2F%2Fa16z.simplecast.com%2Fepisodes%2Ffei-fei-li-the-race-to-build-world-models-for-ai-tvIN7XfT","width":444,"version":"1.0","type":"rich","title":"Fei Fei Li: The Race to Build World Models For AI","thumbnail_width":300,"thumbnail_url":"https://image.simplecastcdn.com/images/0d97354a-306b-45f5-bf26-a8d81eef47ec/ed2664df-9371-438e-8baf-dd2ee0fdde87/thea16zshow-podcastcoverart-3000x3000.jpg","thumbnail_height":300,"provider_url":"https://simplecast.com","provider_name":"Simplecast","html":"","height":200,"description":"World Labs co-founders Fei-Fei Li, Justin Johnson, and Ben Mildenhall join a16z General Partner Martin Casado to discuss Atlas, their latest world model, and what it reveals about the pursuit of spatial intelligence.\nAt the center of Atlas is what the team calls “new view prediction”: given images or views of a scene, the model predicts what that environment should look like from a different position in space and time. This brings generation and 3D reconstruction into the same model, and raises a broader question about whether predicting views could become a useful primitive for understanding the physical world.\nThey discuss the technical bets behind the model, what it can and can’t yet capture, and the importance of dynamics, editability, and simulation as world models develop. The conversation also explores applications in creative work, architecture, and robotics, where Fei-Fei argues that one of today’s biggest constraints is access to real-world training data.\n"}