告别物理幻觉：首个全模态物理AI基础模型OmniFysics问世

Group 1 - Fysics AI, in collaboration with Fudan University's Cognitive Intelligence Technology Laboratory, has launched the world's first multimodal physical AI foundational model, OmniFysics, aimed at addressing the "physical blindness" issue prevalent in generative AI [1][2] - OmniFysics operates on a lightweight architecture with only 3 billion parameters, incorporating physical perception and causal reasoning mechanisms, allowing it to accurately predict physical parameters such as density and Young's modulus [1] - The model features two unique data ecosystems, "FysicsAny" for static properties and "FysicsOmniCap" for dynamic properties, enabling the identification of physical attributes and understanding of physical causality in audiovisual contexts [1] Group 2 - The technical architecture of OmniFysics employs a four-stage progressive training method, initially training single-modal perception before integrating multimodal capabilities, effectively balancing task specialization and cross-modal collaboration [2] - To validate the model's understanding of physical concepts, the team introduced the FysicsEval evaluation benchmark, which assesses the AI's ability to recognize violations of physical common sense, such as "water flows uphill" [2]