Opening — Why this matters now Single-image 3D scene generation has quietly become one of the most overloaded promises in computer vision. We ask a model to hallucinate geometry, infer occluded objects, reason about spatial relationships, and place everything in a coherent 3D world — all from a single RGB frame. When it fails, we call it a data problem. When it half-works, we call it progress. ...
Opening — Why this matters now For all the raw intelligence of modern LLMs, they still feel strangely absent. Answers arrive instantly, flawlessly even—but no one is there. The interaction is efficient, sterile, and ultimately disposable. As enterprises rush to deploy chatbots and copilots, a quiet problem persists: people understand information better when it feels socially grounded, not merely delivered. ...
Embodied Intelligence: A Different Kind of Smart Artificial intelligence is no longer confined to static models that churn numbers in isolation. A powerful shift is underway—toward embodied AI, where intelligence is physically situated in the world. Unlike stateless AI models that treat the world as a dataset, embodied AI experiences the environment through sensors and acts through physical or simulated bodies. This concept, championed by early thinkers like Rolf Pfeifer and Fumiya Iida (2004), emphasizes that true intelligence arises from an agent’s interactions with its surroundings—not just abstract reasoning. Later surveys, such as Duan et al. (2022), further detail how modern embodied AI systems blend simulation, perception, action, and learning in environments that change dynamically. ...