NVIDIA，COSMOS和BYTOAL AI：建立機器人技術的未來

探索NVIDIA的COSMOS平台及其對物理AI的影響，從而通過高級模擬和AI模型更快地開發機器人和自主系統。

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方面的進步正在重塑機器人技術和模擬。 Cosmos平台憑藉其世界基礎模型，為開發複雜的AI系統提供了簡化的方法。讓我們潛入！

The Rise of NVIDIA Cosmos in Physical AI

NVIDIA COSMOS在物理AI中的興起

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世界基金會模型（WFM），以增強開發人員的能力加速物理AI開發。該平台允許定制用於機器人技術，自動駕駛汽車和工業AI的驗證模型，從而降低了創建準確的模擬和數字雙胞胎的複雜性。

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.

關鍵要素是NVIDIA COSMOS策展人框架。它有效地過濾，註釋和重複了大量傳感器數據，從而增強了AI模型的培訓數據質量。該策劃的數據對於物理AI應用程序（例如工廠自動化和自動駕駛）非常寶貴。

Cosmos: Predict, Transfer, Reason

宇宙：預測，轉移，理性

The Cosmos platform includes three foundational models:

宇宙平台包括三個基礎模型：

• 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.

這些模型共同提高了AI系統在復雜環境中感知，推理和行動的能力。

Omniverse Libraries and Digital Twins

Omniverse圖書館和數字雙胞胎

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服務器和DGX Cloud提供支持的Nvidia的Omniverse庫，使開發人員能夠構建物理準確的數字雙胞胎。這些數字雙胞胎對於培訓AI代理和物理AI模型至關重要。這些庫支持OpenUSD和MJCF之間的數據互操作性，從而促進了機器人和工業AI系統的跨平台模擬。 RTX射線追踪的3D高斯脫落技術通過從傳感器數據中重建現實世界環境來增強模擬的現實主義。

NVIDIA's Vision for the Future

Nvidia對未來的願景

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.

根據Lebaredian牧師的說法，NVIDIA設想了一個未來，AI和計算機圖形融合了革命機器人技術，可能重塑價值數万億的行業。 Omniverse庫和SDK可供開發人員構建和部署機器人和工業AI應用程序。

The Broader Impact and Market Confidence

更廣泛的影響和市場信心

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模型正在通過AI代理和人形機器人提高生產力。像CrowdStrike，Uber和Zoom這樣的公司已經在利用這些型號。這些進步預計將在2028年之前帶來可觀的收入收益和成本節省。

Final Thoughts

最後的想法

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標誌著物理AI的顯著飛躍，使開發人員能夠創建更準確，可擴展的AI系統。隨著持續的進步，NVIDIA正在鞏固其在驅動AI驅動機器人技術和仿真技術中的作用。 AI和CG的混合物是改變遊戲規則的人，Nvidia領導了這一指控。伙計們，這將是一個瘋狂的旅程！