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Nvidia的Les Karpas加入2026年Disrupt大会议程Nvidia’s Les Karpas joins the agenda lineup at Disrupt 2026
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摘要
Nvidia全球物理AI负责人Les Karpas将在TechCrunch Disrupt 2026上发言，讨论机器人领域的当前挑战和机遇。他的演讲将重点关注推动物理AI技术发展的全面数据集的显著缺口。Karpas旨在将机器人技术的进展与大型语言模型（如ChatGPT）的突破进行对比，强调机器人实现类似创新水平所需的条件。
Les Karpas, Nvidia's Global Head of Physical AI, is set to speak at TechCrunch Disrupt 2026, where he will address the current challenges and opportunities in the field of robotics. A key focus of his session will be the significant gap in comprehensive datasets necessary for advancing physical AI technologies. Karpas aims to draw parallels between the advancements in robotics and the breakthroughs seen in large language models, such as ChatGPT, highlighting what is needed for robotics to achieve similar levels of innovation.
要点
Nvidia的Les Karpas将在一个重要的科技活动中讨论机器人的未来。
Nvidia's Les Karpas will discuss the future of robotics at a major tech event.
会议将重点关注物理AI中对更好数据集的关键需求。
The session will focus on the critical need for better datasets in physical AI.
Karpas将探讨机器人如何实现类似于语言模型的突破。
Karpas will explore how robotics can reach breakthroughs akin to those in language models.
为何重要
Karpas在Disrupt 2026上的讨论强调了解决机器人领域数据限制的重要性，这对该领域的增长和创新至关重要。随着AI的不断发展，分享的见解可能为物理AI应用的新进展铺平道路。
The discussion led by Karpas at Disrupt 2026 underscores the importance of addressing data limitations in robotics, which is essential for the field's growth and innovation. As AI continues to evolve, the insights shared could pave the way for new advancements in physical AI applications.
产品经理
对于产品经理而言，了解机器人中的数据挑战可以为产品开发策略提供信息，并突出数据收集和管理解决方案的投资领域。
For product managers, understanding the data challenges in robotics can inform product development strategies and highlight areas for investment in data collection and management solutions.
开发者
开发者和工程师应关注Karpas分享的见解，因为这些可能揭示利用改进数据集在机器人领域创造创新解决方案的新机会。
Developers and engineers should pay attention to the insights shared by Karpas, as they may reveal new opportunities for creating innovative solutions that leverage improved datasets in robotics.
学生与求职者
学生和求职者应注意机器人领域对数据的重视，因为这突显了一个日益增长的研究和开发领域，可能为未来在AI和机器人领域的职业机会铺平道路。
Students and job-seekers should note the emphasis on data in robotics, as this highlights a growing area of research and development that could lead to future career opportunities in AI and robotics.
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