Domestic AI Unicorn Unveils MiniCPM-Robot to Enhance Robot Memory at WAIC
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At the World Artificial Intelligence Conference (WAIC), a notable trend emerged in the robotics sector, with an increasing number of VLA models attempting to enable robots to execute longer task chains. A significant challenge has been the fundamental conflict between 'contextual memory' and 'real-time inference costs' in VLA models, which has hindered the completion of long-range tasks.
During WAIC, Mianbi Intelligence introduced and open-sourced its first series of embodied intelligence results, the MiniCPM-Robot, which includes the general VLA model MiniCPM-RobotManip and the tracking navigation model MiniCPM-RobotTrack. This model, with only 1.3 billion parameters, successfully completed long-range tasks like making sandwiches and achieved a significant lead over well-known models in the RMBench leaderboard, showcasing its advanced contextual memory capabilities.
The release of MiniCPM-Robot signifies Mianbi Intelligence's transition of its accumulated multimodal technology from the digital realm to the physical world. The MiniCPM-Robot series addresses a structural shortcoming in current embodied intelligence, allowing for efficient visual token compression that enhances real-time inference speed while retaining memory, thus overcoming a long-standing dilemma in VLA model development.
Original report
Breakthrough in Robot Memory at WAIC by Domestic AI Unicorn
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