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Y11
@seclink
找工作、找面试题、改简历、模拟面试。关注: 创业(冷启动) | 认知心理学|智能体 | 强化学习 | AWS RoboMaker、ROS、Gazebo | 具身智能 | 大模型后训练 (数据标注 | 数据采集 ) | 大模型专家评测 building:
Joined January 2011
669 Following    31.5K Followers
真实机器人交互数据是VLA落地关键瓶颈: 模型架构快速收敛,但泛化到仓库分拣、工厂装配、家庭服务等接触丰富长程任务,仍依赖大规模多样真机数据提升成功率与吞吐量。 少数公司有数千至上万小时专有数据(如Physical Intelligence公开超1万小时、Figure约500小时),形成收购护城河。 开源可验证:Open X-Embodiment(100万+轨迹,22种机器人)、DROID(约350小时)、ABC-130k(约3550小时双臂,Apache)、AgiBot World Beta(约3000小时,非商用许可)、BridgeData V2等。框架与代码见LeRobot、HF及对应GitHub。 以论文与数据集页面为准,避开单纯营销宣称。
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the biggest robotics acquisition target right now is whoever owns the best real-world manipulation dataset. the models are converging fast. the data isn't even close. hours of real robot interaction footage is the new oil and maybe 4 companies have enough of it to matter.
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