估值超390亿元，头部具身智能大模型创企发布最强VLA模型！

Core Viewpoint - The article discusses the launch of the latest visual-language-action (VLA) model π0.6 by Physical Intelligence (PI), which has achieved a significant breakthrough in robotic learning and performance, enabling robots to learn from mistakes and improve in real-world environments, achieving over 90% success rates in complex tasks [2][12]. Summary by Sections Model Development - Physical Intelligence has released the π0.6 model, which is built on the previous π0.5 model, and is valued at over $39 billion [2]. - The new model utilizes an innovative RECAP training method that allows robots to learn from errors and evolve through practice, significantly enhancing their task success rates [2][4]. Key Features of π*0.6 - The RECAP training framework combines offline reinforcement learning with online advantage-conditioned reinforcement learning, allowing robots to absorb large amounts of historical data while continuously improving in real deployments [8]. - The advantage-conditioned policy explicitly incorporates "advantage values" as input, simplifying the learning process and enabling effective policy iteration [10]. - A distributed value function and sparse rewards mechanism help the model accurately assess which actions lead to success in complex tasks, thus improving performance beyond that of human demonstrators [11]. Real-World Application - The model has been tested in three challenging real-world tasks: folding diverse clothing, assembling boxes in a factory setting, and making espresso, achieving over 90% success rates and doubling throughput while reducing failure rates by 50% [12]. - This marks a significant transition from merely demonstrating capabilities in laboratory settings to proving practical utility in real-world applications [14]. Industry Context - Since 2025, the dual-system architecture of VLA models has become mainstream in the field of embodied intelligence, with leading companies adopting this approach to tackle more complex and varied tasks [14]. - The article highlights the competitive landscape, noting that major tech companies like Google, OpenAI, and others are increasingly investing in embodied intelligence and robotics, indicating a shift towards practical applications and commercialization in the sector [19][20].