物理AI的“补完计划”：Genesis AI要用数据引擎驯服95%的体力劳动

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今天我们继续解读Genesis AI，Genesis AI 的定位是一家全球性实体人工智能研究实验室兼全栈机器人公司。今年以来物理人工智能成了一个很火的话题，不管是舆情还是投资热点都少不了它的影子。今天我们就来通过英语学习了解一下是Physical AI和Gensis AI 这家公司。

Key Words：

• Physical AI 定义：将AI算法与物理实体（机器人、无人机、智能设备等）结合，实现物理世界的感知、决策与行动。 

• Physical AI（物理人工智能）和Digital AI（数字化人工智能）是人工智能领域的两个重要分支

•   体力劳动为全球国内生产总值贡献了约 30 - 40 万亿美元，但由于目前自动化解决方案的局限性，其中超过 95% 的工作仍未实现自动化。

  
  

双语正文

原文: Physical labor contributes an estimated $30-40 trillion to the Global GDP, yet over 95% of it remains unautomated due to the limitations of current automation solutions. Today's robotic systems, such as industrial arms, rely on brittle, rigid, and overfitted software stacks. These systems are narrow in scope, costly to deploy, and challenging to scale. Genesis aims to revolutionize the next generation of general-purpose robots by unlocking unprecedented robustness, flexibility, and cost efficiency -- ultimately automating all physical labor.

翻译: 体力劳动对全球GDP的贡献估计达30-40万亿美元，然而，由于现有自动化解决方案的局限性，其中超过95%仍未实现自动化。当今的机器人系统，如工业机械臂，依赖于脆弱、僵化且过度拟合的软件堆栈。这些系统应用范围狭窄、部署成本高昂且难以扩展。Genesis旨在通过实现前所未有的鲁棒性、灵活性和成本效益，彻底革新下一代通用机器人——最终实现所有体力劳动的自动化。

原文: Genesis brings a data-centric, full-stack approach to physical AI -- building a scalable and universal data engine that unifies high-fidelity physics simulation, multimodal generative modeling, and large-scale real robot data collection. Its simulation stack, developed entirely in-house, will generate rich synthetic data at scale, together with a more efficient and scalable real-world data collection system. This dual engine of synthetic and real data bridges historically siloed domains to collect the largest-scale, most diverse, and highest quality data to train RFMs.

翻译: Genesis为物理AI带来了以数据为中心、全栈式的方法——构建一个可扩展的通用数据引擎，统一了高保真物理模拟、多模态生成建模和大规模真实机器人数据收集。其完全内部开发的模拟堆栈将大规模生成丰富的合成数据，同时配合一个更高效、可扩展的真实世界数据收集系统。这种合成数据与真实数据的双引擎，弥合了历史上各自为政的领域，以收集最大规模、最多样化、最高质量的数据来训练机器人基础模型（RFMs）。

原文: "General-purpose robots powered by physical AI will define the next major chapter of human history. While digital AI has made extraordinary progress, physical AI -- the intelligence that allows machines to perceive, understand, and interact with the real world -- has lagged behind," said Zhou Xian, CEO of Genesis. "We're here to change that. By building on the foundations laid by existing digital AI models, we're bringing human-level intelligence into the physical world. Genesis's unique approach by fueling digital AI knowledge to drive the emergence of physical AI will deliver unmatched capability, scalability, and cost-efficiency to unlock unlimited physical labor. With 75% of global companies struggling to fill jobs, physical AI is more essential than ever."

翻译: “由物理AI驱动的通用机器人将定义人类历史的下一重要篇章。虽然数字AI取得了非凡的进步，但物理AI——使机器能够感知、理解并与现实世界互动的智能——却一直落后，”Genesis首席执行官周贤（Zhou Xian）表示。“我们就是要改变这种现状。通过建立在现有数字AI模型奠定的基础上，我们将人类水平的智能带入物理世界。Genesis独特的方法，利用数字AI知识来推动物理AI的出现，将提供无与伦比的能力、可扩展性和成本效益，以解锁无限的体力劳动。在全球75%的公司难以填补职位空缺的情况下，物理AI比以往任何时候都更加重要。”

原文: Founded by top academic and industry technical talents from Mistral AI, Nvidia, Google, CMU, MIT, Stanford, Columbia and UMD, with deep expertise across the full stack of physics simulation, graphics, robotics, and large-scale AI model training and deployment, Genesis is well-positioned to rapidly execute its vision through a differentiated approach to physical AI. The company also plans to open-source components of its data engine and foundation model to empower developers, researchers, and partners to build on its breakthroughs and accelerate progress across the broader field of physical AI.

翻译: Genesis由来自Mistral AI、英伟达（Nvidia）、谷歌（Google）、卡内基梅隆大学（CMU）、麻省理工学院（MIT）、斯坦福大学（Stanford）、哥伦比亚大学（Columbia）和马里兰大学（UMD）的顶尖学术和工业技术人才创立，在物理模拟、图形学、机器人技术以及大规模AI模型训练和部署的全栈领域拥有深厚的专业知识。凭借在物理AI领域的差异化方法，Genesis完全有能力快速实现其愿景。该公司还计划开源其数据引擎和基础模型的组件，以赋能开发者、研究人员和合作伙伴在其突破性成果上继续构建，并加速整个物理AI更广泛领域的进展。

原文: "Even in the most 'automated' industries today, the robot-to-human ratio rarely exceeds 1:30, due to the long tail of tasks requiring dexterity, cognition, mobility, and real-world reasoning that current robots simply can't handle," said Eclipse Partner, Charly Mwangi. "General-purpose robotics is the breakthrough we've been waiting for and stands to impact trillions in labor value across sectors. Genesis has the vision, strategy, and world-class team to define the era of physical AI in order to unlock unlimited physical labor through general-purpose robotics."

翻译: “即使在当今‘自动化’程度最高的行业中，机器人与人的比例也很少超过1:30，这是因为存在大量需要灵活性、认知能力、移动性和现实世界推理的任务长尾，而当前的机器人根本无法处理这些任务，”风投机构Eclipse合伙人查利·姆万吉（Charly Mwangi）说。“通用机器人技术是我们一直期待的突破，它将影响跨行业数万亿美元的劳动力价值。Genesis拥有愿景、战略和世界一流的团队来定义物理AI的时代，以通过通用机器人技术解锁无限的体力劳动。”

原文: "Physical AI has yet to scale like LLMs because collecting and aligning real-world data can be operationally complex," said Kanu Gulati of Khosla Ventures. "Genesis is taking a full-stack approach by integrating best-in-class simulation data with real-world robotics data in a continuous, closed-loop system. Owning the entire data pipeline in-house gives them a unique data advantage. We're excited to back Genesis early as they work to build a universal foundation model for robotics."

翻译: “物理AI尚未像大语言模型（LLMs）那样实现规模化，因为收集和校准现实世界数据在操作上可能非常复杂，”Khosla Ventures的卡努·古拉蒂（Kanu Gulati）表示。“Genesis正在采取全栈方法，在一个持续的闭环系统中，将一流的模拟数据与真实世界的机器人数据相整合。内部拥有整个数据管道赋予了他们独特的数据优势。我们很高兴能在早期支持Genesis，因为他们致力于为机器人技术构建一个通用的基础模型。”

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