Then software 2.0 arrived, machine learning neural networks running on GPUs.

隨後，軟件 2.0 出現了，即在 GPU 上運行機器學習神經網絡。

This led to the big bang of generative AI, models that learn and generate anything.

這引發了生成式人工智能的大爆炸，即可以學習和生成任何東西的模型。

Today, generative AI is revolutionizing 100 trillion dollars in industries.

如今，生成式人工智能正在為 100 萬億美元的產業帶來變革。

Knowledge enterprises use agentic AI to automate digital work.

知識企業利用代理人工智能實現數字化工作自動化。

Hello, I'm James, a digital human.

大家好，我是詹姆斯，一個數字人。

Industrial enterprises use physical AI to automate physical work.

工業企業利用物理人工智能實現體力勞動自動化。

Physical AI embodies robots like self-driving cars that safely navigate the real world, manipulators that perform complex industrial tasks, and humanoid robots who work collaboratively alongside us.

物理人工智能體現的機器人包括：能在現實世界中安全導航的自動駕駛汽車、能執行復雜工業任務的機械手，以及能與我們協同工作的仿人機器人。

Plants and factories will be embodied by physical AI, capable of monitoring and adjusting its operations, or speaking to us.

工廠和工廠將由物理人工智能來體現，能夠監控和調整其運行，或與我們對話。

NVIDIA builds three computers to enable developers to create physical AI.

英偉達™（NVIDIA®）打造了三臺計算機，使開發人員能夠創建物理人工智能。

The models are first trained on DGX.

模型首先在 DGX 上進行訓練。

Then, the AI is fine-tuned and tested using reinforcement learning physics feedback in Omniverse.

然後，在 Omniverse 中使用強化學習物理反饋對人工智能進行微調和測試。

And the trained AI runs on NVIDIA Jetson AGX robotics computers.

訓練有素的人工智能在英偉達 Jetson AGX 機器人計算機上運行。

NVIDIA Omniverse is a physics-based operating system for physical AI simulation.

NVIDIA Omniverse 是一款基於物理的作業系統，適用於物理人工智能模擬。

Robots learn and fine-tune their skills in Isaac Lab, a robot gym built on Omniverse.

機器人在艾薩克實驗室（Isaac Lab）中學習和調整自己的技能，這是一個建在 Omniverse 上的機器人體育館。

This is just one robot.

這只是一個機器人。

Future factories will orchestrate teams of robots and monitor entire operations through thousands of sensors.

未來的工廠將協調機器人團隊，並通過成千上萬個傳感器監控整個營運過程。

For factory digital twins, they use an Omniverse blueprint called Mega.

對於工廠數字雙胞胎，他們使用的是一種名為 Mega 的 Omniverse 藍圖。

With Mega, the factory digital twin is populated with virtual robots and their AI models, the robots' brains.

有了 Mega，工廠數字孿生系統中就有了虛擬機器人及其人工智能模型，也就是機器人的大腦。

The robots execute a task by perceiving their environment, reasoning, planning their next motion, and finally converting it to actions.

機器人通過感知環境、推理、規劃下一步動作並最終轉化為行動來執行任務。

These actions are simulated in the environment by the world simulator in Omniverse, and the results are perceived by the robot brains through Omniverse sensor simulation.

這些動作由 Omniverse 中的世界模擬器在環境中模擬，機器人大腦則通過 Omniverse 傳感器模擬來感知結果。

Based on the sensor simulations, the robot brains decide the next action, and the loop continues, while Mega precisely tracks the state and position of everything in the factory digital twin.

根據傳感器模擬結果，機器人大腦決定下一步行動，循環往復，而 Mega 則精確跟蹤工廠數字孿生系統中所有設備的狀態和位置。

This software-in-the-loop testing brings software-defined processes to physical spaces and embodiments, letting industrial enterprises simulate and validate changes in an Omniverse digital twin before deploying to the physical world, saving massive risk and cost.

這種 "軟件在環 "測試將軟件定義的流程引入物理空間和實施，讓工業企業在部署到物理世界之前，在 Omniverse 數字孿生中模擬和驗證變化，從而節省大量風險和成本。

The era of physical AI is here, transforming the world's heavy industries and robotics.

物理人工智能時代已經到來，它將改變世界重工業和機器人技術。