Core Insights - The article highlights the launch of SenseNova V6, a new multimodal AI model by SenseTime, which enhances reasoning capabilities and cost efficiency in AI applications [2][4] - The model is designed to support various applications, including humanoid robots, and aims to improve human-robot interaction through advanced perception and reasoning [4][5] - The Chinese multimodal AI market is experiencing rapid growth, with projections indicating a market size of approximately 15 billion RMB in 2024, reflecting a year-on-year increase of about 30% [6] Group 1: Product and Technology - SenseNova V6 features breakthroughs in multimodal long reasoning chains, global memory, and reinforcement learning, significantly outperforming competitors like OpenAI's models [2] - The model supports in-depth analysis of mid-length videos and is positioned as one of the strongest in its category, comparable to Gemini 2.5 Turbo [2] - The technology enables robots to understand gestures, respond to environmental inquiries, and provide a more authentic interaction experience [4] Group 2: Industry Applications - SenseTime's end-to-end solutions for embodied intelligence address high data costs and fragmented toolchains, supporting over 10TB of data aggregation per day [4][5] - The AI supermarket project demonstrates the practical application of group intelligence, showcasing a complete AI development system from model training to inference evaluation [5] - The collaboration between Fourier's humanoid robot GRx and SenseTime's SenseNova V6 Omni enhances the robot's ability to understand complex scenarios through deep integration of various data types [5] Group 3: Market Trends - The demand for embodied intelligence in robotics has increased significantly, driven by technological innovation and the need for advanced data training solutions [6] - The multimodal AI market in China is expected to continue its rapid growth, with forecasts suggesting it will exceed 20 billion RMB by 2025 [6] - Industry competition is intensifying, with a focus on maintaining technological innovation, improving model generalization, and ensuring data security and privacy [7]