Deepsick团队的算法破局，夺下2025中关村具身智能模型能力挑战赛大脑赛道一等奖

Core Viewpoint - The 2025 Second Zhongguancun Embodied Intelligent Robot Application Competition successfully showcased the application of embodied intelligence technology, emphasizing the transition from "laboratory algorithms" to "practical applications" in the industry [1][10]. Group 1: Competition Overview - The competition featured over 150 teams from renowned universities, research institutions, and innovative enterprises, culminating in 54 outstanding teams that set benchmarks for the application of embodied intelligence technology [1]. - The event was guided by various governmental bodies and organized by multiple institutions, aiming to foster the practical application of embodied intelligence [1]. Group 2: Core Challenge of Embodied Intelligence Models - The core challenge included two main tracks: the Embodied Brain Model Capability Challenge and the Embodied Small Brain Model Capability Breakthrough Challenge, focusing on optimizing the RoboBrain2.0 model [3]. - The Deepsick team excelled in the competition, achieving a 10% improvement in spatial reasoning tasks with their optimized RoboBrain2.0 model, securing the first prize in the brain track [3]. Group 3: Team Dynamics and Strategy - The Deepsick team, consisting of four members, operated with clear roles, functioning like a small "data-model" engine, emphasizing a systematic approach to problem-solving and iterative training [5]. - The team leader coordinated the research strategy and progress, while team members specialized in model training, evaluation, and technical discussions, ensuring a collaborative effort [5]. Group 4: Phased Approach to Model Optimization - The Deepsick team adopted a three-phase approach to optimize model performance: addressing weaknesses, enhancing specific capabilities, and achieving overall improvement [7][8]. - In the first phase, the team focused on diagnosing issues within the training set to avoid masking core problems, leading to effective solutions [7]. - The second phase emphasized data quality over quantity, with a strategy to uncover previously unseen data for better experimental results [8]. Group 5: Future Implications - The success of the Deepsick team reflects a broader trend in China's embodied intelligence industry towards practical innovation and application [10]. - The future is expected to see an increasing number of robots equipped with intelligent capabilities, playing significant roles in various settings such as factories, homes, and emergency sites [10].