NVIDIA，COSMOS和BYTOAL AI：建立机器人技术的未来

探索NVIDIA的COSMOS平台及其对物理AI的影响，从而通过高级模拟和AI模型更快地开发机器人和自主系统。

NVIDIA's advancements in physical AI are reshaping robotics and simulation. The Cosmos platform, with its World Foundation Models, offers a streamlined approach to developing sophisticated AI systems. Let's dive in!

NVIDIA在物理AI方面的进步正在重塑机器人技术和模拟。 Cosmos平台凭借其世界基础模型，为开发复杂的AI系统提供了简化的方法。让我们潜入！

The Rise of NVIDIA Cosmos in Physical AI

NVIDIA COSMOS在物理AI中的兴起

NVIDIA has introduced the Cosmos World Foundation Models (WFMs) to empower developers in accelerating physical AI development. This platform allows customization of pretrained models for robotics, autonomous vehicles, and industrial AI, reducing the complexity of creating accurate simulations and digital twins.

NVIDIA推出了Cosmos世界基金会模型（WFM），以增强开发人员的能力加速物理AI开发。该平台允许定制用于机器人技术，自动驾驶汽车和工业AI的验证模型，从而降低了创建准确的模拟和数字双胞胎的复杂性。

A key element is the NVIDIA Cosmos Curator framework. It efficiently filters, annotates, and deduplicates massive sensor data, enhancing the quality of training data for AI models. This curated data is invaluable for physical AI applications like factory automation and autonomous driving.

关键要素是NVIDIA COSMOS策展人框架。它有效地过滤，注释和重复了大量传感器数据，从而增强了AI模型的培训数据质量。该策划的数据对于物理AI应用程序（例如工厂自动化和自动驾驶）非常宝贵。

Cosmos: Predict, Transfer, Reason

宇宙：预测，转移，理性

The Cosmos platform includes three foundational models:

宇宙平台包括三个基础模型：

• Predict: Generates continuous video sequences based on inputs and prompts.
• Transfer: Simulates environments and lighting conditions, augmenting data for 3D inputs.
• Reason: A customizable Vision Language Model that helps AI agents understand operations in real-world settings.

These models collectively improve AI systems' ability to perceive, reason, and act in complex environments.

这些模型共同提高了AI系统在复杂环境中感知，推理和行动的能力。

Omniverse Libraries and Digital Twins

Omniverse图书馆和数字双胞胎

NVIDIA's Omniverse libraries, powered by RTX PRO Servers and DGX Cloud, enable developers to construct physically accurate digital twins. These digital twins are crucial for training AI agents and physical AI models. The libraries support data interoperability between OpenUSD and MJCF, facilitating cross-platform simulation of robots and industrial AI systems. The RTX ray-traced 3D Gaussian splatting technique enhances the realism of simulations by reconstructing real-world environments from sensor data.

由RTX Pro服务器和DGX Cloud提供支持的Nvidia的Omniverse库，使开发人员能够构建物理准确的数字双胞胎。这些数字双胞胎对于培训AI代理和物理AI模型至关重要。这些库支持OpenUSD和MJCF之间的数据互操作性，从而促进了机器人和工业AI系统的跨平台模拟。 RTX射线追踪的3D高斯脱落技术通过从传感器数据中重建现实世界环境来增强模拟的现实主义。

NVIDIA's Vision for the Future

Nvidia对未来的愿景

According to Rev Lebaredian, NVIDIA envisions a future where AI and computer graphics converge to revolutionize robotics, potentially reshaping industries worth trillions. The Omniverse libraries and SDKs are available for developers to build and deploy robotics and industrial AI applications.

根据Lebaredian牧师的说法，NVIDIA设想了一个未来，AI和计算机图形融合了革命机器人技术，可能重塑价值数万亿的行业。 Omniverse库和SDK可供开发人员构建和部署机器人和工业AI应用程序。

The Broader Impact and Market Confidence

更广泛的影响和市场信心

NVIDIA's new Nemotron and Cosmos models are enhancing productivity with AI agents and humanoid robots. Companies like CrowdStrike, Uber, and Zoom are already leveraging these models. These advancements are projected to deliver significant revenue gains and cost savings by 2028.

NVIDIA的新nemotron和Cosmos模型正在通过AI代理和人形机器人提高生产力。像CrowdStrike，Uber和Zoom这样的公司已经在利用这些型号。这些进步预计将在2028年之前带来可观的收入收益和成本节省。

Final Thoughts

最后的想法

NVIDIA's Cosmos WFMs mark a significant leap in physical AI, enabling developers to create more accurate and scalable AI systems. With ongoing advancements, NVIDIA is solidifying its role in driving AI-driven robotics and simulation technologies. The blend of AI and CG is a game changer, and NVIDIA is leading the charge. It's gonna be a wild ride, folks!

Nvidia的Cosmos WFMS标志着物理AI的显着飞跃，使开发人员能够创建更准确，可扩展的AI系统。随着持续的进步，NVIDIA正在巩固其在驱动AI驱动机器人技术和仿真技术中的作用。 AI和CG的混合物是改变游戏规则的人，Nvidia领导了这一指控。伙计们，这将是一个疯狂的旅程！