---
title: "Jensen Huang Signed Toyota, Fanuc, Kioxia, and 5 Other Japanese Industrial Giants Into Nvidia's Physical AI Coalition This Week. Nvidia Has $1 Trillion in Confirmed Demand Through 2027."
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/293819623.md"
description: "Nvidia CEO Jensen Huang has onboarded major Japanese industrial giants, including Toyota and Fanuc, into its Physical AI Coalition to integrate AI into manufacturing. While data centers remain the primary growth driver with $1 trillion in confirmed demand through 2027, Nvidia is positioning physical AI as a significant long-term opportunity. The company offers full-stack solutions for robotics and edge computing, aiming to maintain its competitive advantage against rivals like AMD and Broadcom."
datetime: "2026-07-25T09:56:50.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/293819623.md)
  - [en](https://longbridge.com/en/news/293819623.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/293819623.md)
---

# Jensen Huang Signed Toyota, Fanuc, Kioxia, and 5 Other Japanese Industrial Giants Into Nvidia's Physical AI Coalition This Week. Nvidia Has $1 Trillion in Confirmed Demand Through 2027.

**Nvidia** (NVDA \-1.01%) stock is up 12% year-to-date, outperforming the **Nasdaq**'s roughly 9% return at the time of writing, but the company is not sitting still. With competition in the semiconductor industry heating up, CEO Jensen Huang wants to keep Nvidia at the frontier of artificial intelligence (AI) technology.

In that effort, Huang is positioning the company to lead the race in physical AI, including robots. He recently met with the leaders of several Japanese industrial giants -- including **Toyota**, **Fujitsu Limited**, **Kawasaki Heavy Industries**, **Fanuc**, and **Kioxia** \-- to discuss how they can implement physical AI in their factories.

As Huang stated, "The next frontier of AI is in the physical world, and this is a once-in-a-generation opportunity for Japan." Three major robotics and automation players -- Kawasaki, Fanuc, and **Yaskawa** -- are already using Nvidia's technology. This all fits with its strategy to be at the center of every major transition in the world of computing.

Image source: Nvidia.

## What does this mean for Nvidia's prospects?

Nvidia has changed how it will report its financial results to align with its future growth drivers. Based on this new reporting framework, the data center segment reported revenue of $75 billion last quarter, up 92% year over year. The new edge computing segment (robotics, automotive, and PCs) is small by comparison, generating only $6.4 billion in revenue, up 29%.

Physical AI is not going to move the needle for the stock right now. In data center, management expects to book $1 trillion in revenue from its Blackwell and Rubin chips from 2025 through calendar 2027. Its chips and networking products for AI data centers are still its main growth drivers.

But in the long run, physical AI is the next logical step for this technology, and that spells significant growth potential for Nvidia's edge computing business. Similar to its strategy in data centers, Nvidia has put together a full-stack offering that includes its DGX computing systems (Blackwell/Vera Rubin), its Jetson robotics computing platform, and Cosmos for simulating the physical world to accelerate robot development.

As **Advanced Micro Devices** and **Broadcom** try to chip away at Nvidia's lead in data centers, Huang is positioning the company for the next big transition in AI. Nvidia's tailored computing solutions for specific industries such as manufacturing give it a competitive advantage. So do its relationships with enterprises and AI researchers around the world.

The recent announcements out of Japan are bullish for Nvidia's long-term prospects, but the data center business will remain the key catalyst for the stock in the near term. The shares do look attractive right now, trading at just 23 times forward earnings, with analysts projecting around 44% annualized earnings growth over the next few years. Investors don't seem to be paying any premium for the long-tail growth potential of the physical AI market over the next few decades.

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