Marble represents a shift from language-centric AI to spatial intelligence, enabling the creation of editable 3D environments from text, images, and spatial inputs. Built on Gaussian splats, it supports real-time rendering across devices and allows precise camera control, making it valuable for gaming, film, robotics, and design. The discussion emphasizes that while LLMs excel at abstract reasoning, they lack embodied understanding of physics and space—capabilities essential for true world modeling. The team advocates for integrating physics engines into neural networks to move beyond pattern matching toward causal reasoning. They also highlight the importance of academic innovation despite resource disparities with industry, and reframe transformers as set-based models, opening new architectural possibilities. Marble is not meant to replace language models but to complement them in multimodal systems. Current applications span creative industries and synthetic data generation for embodied AI, with long-term potential in science and decision-making. World Labs continues to push boundaries, seeking talent to advance this vision of intelligent, interactive 3D worlds.