[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"aihot-art-87260":3},{"itemId":4,"vertical":5,"category":6,"source":7,"score":8,"title":9,"summary":10,"analysis":11,"url":12,"coverUrl":13,"direction":13,"marketSignal":13,"publishedAt":14},"87260","ai","模型发布\u002F更新","Elvis Saravia",58,"LingBot-VLA 2.0 开源具身模型发布","LingBot-VLA 2.0 开源具身模型发布，基于 6 万小时数据训练，提升长时域任务表现。","LingBot-VLA 2.0 开源具身模型发布，提升机器人长时域任务表现。\n· 该模型在多种机器人配置上训练，从单臂机器人到人形平台。\n· 将 6 万小时精选的机器人和人类数据打包成一个通用策略。\n· 开源发布，便于社区使用和改进。\n· 显著提升了机器人在困难长时域任务上的表现。\n影响\u002F看点：LingBot-VLA 2.0 的开源将加速具身智能研究，通用策略的泛化能力是迈向通用机器人的重要一步。","https:\u002F\u002Fx.com\u002Fomarsar0\u002Fstatus\u002F2077404813055185320",null,"2026-07-15 22:47:58"]