时令 发自 凹非寺 量子位 | 公众号 QbitAI 黄仁勋大家都见得多了，但你见过他女儿讲具身智能吗？ 这不，黄仁勋女儿 Madison Huang 首次公开亮相直播访谈节目，作为英伟达Omniverse与物理AI高级总监，与光轮智能CEO谢晨，以及光 轮智能增长负责人穆斯塔法一起，对"如何缩小机器人在虚拟与现实之间的差距"展开深刻探讨。 在一个半小时的访谈时间内，三人提出了一系列重要观点： 下面具体来看。 利用合成数据和仿真来解决机器人数据障碍 访谈一正式开始，主持人Edmar Mendizabal（Omniverse社区经理）就开门见山抛出了一个许多人都很好奇的问题。 英伟达与光轮智能的合作关系是如何开始的？ Madison解答道， 英伟达内部很多项目都依赖于光轮智能的支持 。例如，Gear Lab正在构建通用智能体模型，西雅图机器人实验室正在开 展大量涉及接触操作和精密装配的任务。 合成数据对于解决机器人数据困境至关重要 。 光轮智能的SimReady资产不仅要视觉准确，更重要的是物理准确。 英伟达和光轮智能正在共同开发Isaac Lab Arena——一个用于基准测试、评估、数据收集和大规模强化学习 ...

Core Viewpoint - NVIDIA has made significant advancements in robotics by releasing multiple open-source technologies, including the Newton physics engine, which enhances robots' physical intuition and reasoning capabilities, addressing key challenges in robot development [1][4][10]. Group 1: Newton Physics Engine - The Newton physics engine aims to solve the challenge of transferring skills learned in simulation to real-world applications, particularly for humanoid robots with complex joint structures [4]. - It is an open-source project managed by the Linux Foundation, built on NVIDIA's Warp and OpenUSD frameworks, utilizing GPU acceleration to simulate intricate robot movements [4]. - Leading institutions such as ETH Zurich and Peking University have already begun using the Newton engine, indicating its adoption by top-tier robotics companies and universities [4][3]. Group 2: Isaac GR00T N1.6 Model - The Isaac GR00T N1.6 model integrates the Cosmos Reason visual language model, enabling robots to understand and execute vague commands, a longstanding challenge in the industry [5][6]. - This model allows robots to convert ambiguous instructions into actionable plans while performing simultaneous movements and object manipulations [6]. - The Cosmos Reason model has surpassed 1 million downloads, and the accompanying open-source physical AI dataset has exceeded 4.8 million downloads, showcasing its popularity and utility [6]. Group 3: Training Innovations - The Isaac Lab 2.3 developer preview introduces a new workflow for teaching robots to grasp objects, utilizing an "automated curriculum" that gradually increases task difficulty [8]. - This approach has been successfully implemented by Boston Dynamics' Atlas robot, enhancing its manipulation capabilities [8]. - NVIDIA has collaborated with partners to develop the Isaac Lab Arena, a framework for large-scale experiments and standardized testing, streamlining the evaluation process for developers [8]. Group 4: Hardware Infrastructure - NVIDIA has invested in hardware advancements, including the GB200 NVL72 system, which integrates 36 Grace CPUs and 72 Blackwell GPUs, already adopted by major cloud service providers [9]. - The Jetson Thor, equipped with Blackwell GPUs, supports multiple AI workflows for real-time intelligent interactions, with several partners already utilizing this technology [9]. - Nearly half of the papers presented at CoRL referenced NVIDIA's technologies, highlighting the company's influence in the robotics research community [9]. Group 5: Comprehensive Strategy - NVIDIA's "full-stack" approach, encompassing open-source physics engines, foundational models, training workflows, and hardware infrastructure, is redefining the landscape of robotics development [10]. - The advancements suggest that the integration of robotics into everyday life may occur sooner than anticipated [11].