Bloomberg Talks – Nvidia, Siemens CEOs Talk Building Industrial AI Operating System

Date: January 6, 2026
Host: Ed Ludlow (Bloomberg)
Guests: Jensen Huang (CEO, Nvidia), Roland Busch (CEO, Siemens)
(This summary focuses on the main content and excludes advertisements, intros/outros, and non-content segments.)

Episode Overview

This episode features an in-depth conversation between Nvidia CEO Jensen Huang and Siemens CEO Roland Busch, hosted by Bloomberg’s Ed Ludlow at the Consumer Electronics Show in Las Vegas. The discussion revolves around the two companies’ ambitious partnership to create an “industrial AI operating system” — a transformative set of technologies enabling digital twins, AI-enhanced manufacturing, and scalable industrial automation. The conversation touches on technical advancements, real-world deployment, energy challenges, software strategy, geopolitics, and future industrial frontiers.

Key Discussion Points & Insights

1. Industrial AI Operating System: Vision and Reality

• Siemens’ Digital Twin Deployment

  • Busch describes how Siemens’ tech already integrates digital twins for both products and manufacturing environments.
  • Examples: Optimization done digitally before building in real world (02:03).
  • AI on the shop floor goes beyond mere recommendations: “With the new models, you can bring that to the next level… really act on your behalf.” — Roland Busch [02:27]
  • The challenge: Scaling deployment is difficult and requires making technology more user-friendly for customers.

• Partnership Announcement

  • Nvidia and Siemens are deepening their work to accelerate Siemens’ EDA and simulation software, and to integrate Nvidia’s AI, including “agentic AI,” into Siemens’ platforms (03:30).
  • Immediate deployments include designing Nvidia chips, simulating AI factories’ thermal properties, and running automation in Foxconn and Nvidia’s factories globally.

  “We’re accelerating their EDA software, we’re accelerating their simulation software. We’re integrating AI technology, physical AI and agentic AI into their Teamcenter and their factory automation operating system.” — Jensen Huang [03:35]

2. Real-World Impact and Economic Efficiency

• Efficiency, Scale, and Complexity

  • Nvidia’s just-announced Vera Rubin system showcases the payoff: 10x energy and cost efficiency vs. the previous generation, with massive complexity compressed by digital design and simulation (04:49).

  “When we can…design entire Vera Rubin systems inside a Siemens digital twin, ... the ability for us to create much, much more complex systems will scale… This is really about being able to do the impossible—and being able to do the impossible right the first time.” — Jensen Huang [05:32]

• Edge Deployment

  • Siemens underlines the leap from AI in data centers to AI at the edge, running inference and optimization on shop floors in real time, thanks to GPUs in controllers and industrial PCs (06:27).
  • This real-world deployment is a driver of economic growth and productivity.

  “They can run algorithms trained in the cloud…on the shop floor and do all that trick, what we talked about... in real time optimization and running in a plant.” — Roland Busch [06:33]

3. Robots, Autonomy, and Manufacturing Transformation

• Full Autonomy and Skilled Labor Shortages

  • Digital/AI transformation crucial for ramping US manufacturing in face of tight labor markets (07:12).
  • True manufacturing autonomy offers higher yields and energy savings.

• The “ChatGPT” Moment for Robotics

  • Rapid progress is coming to robotic system development, easing the complexity with AI/ML, enabling robots to learn from demonstration rather than programming (07:47-08:33).

  “That software limitation is...the ChatGPT moment of [robotics] is now here. I think over the next couple to three years we’re going to make some really big breakthroughs.” — Jensen Huang [08:33]

4. Energy: The Bottleneck of the AI Era

• Energy as Structural Constraint

  • Both CEOs agree: Every industrial revolution is energy constrained; AI is no exception (08:55-10:01).
  • Efficiency is a must, but total supply is lagging growth. Demand for data centers and AI factories is accelerating power needs.

  “Whatever factory size you have, you’re limited by the power and…within that power constraint you want to have the most tokens or most AI per watt…every time we improve energy efficiency, we’re effectively improving…customer revenues.” — Jensen Huang [09:35]

• Policy and Infrastructure

  • Public policy and infrastructure (transformers, turbines) are just as critical; regional disparities create bottlenecks (12:30).

5. Supply Chains: Memory & Geopolitics

• Memory Bottleneck

  • Memory remains a challenge but Nvidia has strong partnerships with all HBM suppliers (13:51-14:20).

• China and U.S. Export Controls

  • Nvidia's approach: Work with company-level demand and compliance, no direct communication with Beijing required (14:20-14:38).

6. Siemens’ Software Strategy and M&A

• Expanding Digital Capabilities

  • Siemens has invested ~$30B in software M&A to build digital twin and operational software leadership—focus on life sciences, simulation, industry backbones (15:26-16:48).

  “We will increase our software competence, our software portfolio...brings us to the point that…we can build the most comprehensive physics-based digital twin of whatever you want to build.” — Roland Busch [15:32]

7. Emerging Technologies: Grok Acquisition & AI in Space

• Grok and AI Hardware

  • Nvidia’s Grok collaboration is a hybrid of talent acquisition and licensing, focused on low-latency AI, hinting at new platform segments (16:48-18:08).

• AI Factories in Space

  • Speculation about data centers/AI factories in space, with unique challenges (energy, cooling, design) but fundamentally similar hardware as terrestrial systems (18:18-19:27).

  “There’s lots of energy in space…cooling is abundant in space…the system design will be radically different, the chips will be the same.” — Jensen Huang [18:50, 19:19]

8. Autonomous Vehicles: Nvidia vs. Tesla

• Mutual Respect and Technical Convergence

  • Both Nvidia and Tesla pursue vision-based AV stacks. Huang praises Tesla’s state-of-the-art approach, emphasizing similarity rather than rivalry (20:07-21:13).

  “Elon's approach is about as state-of-the-art as anybody knows...it's a stack that's hard to criticize.” — Jensen Huang [21:13]

9. On the Ground: Real Deployments

• Siemens’ Erlangen Site
  • AI-powered, highly automated manufacturing is under way at Siemens' Erlangen plant, with stepwise deployment (21:52).
  • Symbiosis: Nvidia uses Siemens tech in Foxconn, Siemens uses Nvidia in its factories—a practical partnership (22:26).

10. Silicon Valley Taxes and Talent

• No Impact from Taxes

  • Huang shrugs off concerns about a “billionaire’s tax” impacting Silicon Valley’s talent or Nvidia’s location (23:04).

  “We work in Silicon Valley because that’s where the talent pool is…whatever taxes I guess they would like to apply, so be it…never crossed my mind once.” — Jensen Huang [23:04]

Notable Quotes & Memorable Moments

• Digital Twins & Complexity:
  “15,000 engineering years came together to build this [Vera Rubin] system…” — Jensen Huang [04:49]

• On Industrial Automation:
  “The fact that we could now apply artificial intelligence physical AI technology…make [robots] easier to teach…” — Jensen Huang [07:47]

• AI’s Energy Demands:
  “Every industrial revolution will be energy constrained. And this industrial revolution is also energy constrained.” — Jensen Huang [10:23]

• Geopolitics:
  “If the companies are allowed to buy Nvidia products in China then there’ll be strong demand and we’re seeing strong demand.” — Jensen Huang [14:38]

• Space AI Factories:
  “There's lots of energy in space, right? And the cooling is abundant in space…The system design will be radically different. The chips will be the same.” — Jensen Huang [18:50–19:19]

• AV Competition:
  “Tesla stack is the most advanced AV stack in the world. And I think the Tesla operations is the most advanced in the world.” — Jensen Huang [20:22]

Key Timestamps

• Digital Twin, Scaling AI: 02:03–03:08
• Nvidia–Siemens Partnership Details: 03:30–04:34
• Vera Rubin, Energy/Cost Efficiency: 04:49–05:51
• AI at the Edge, Economic Growth: 06:29–06:49
• AI in Robotics, Software Breakthrough: 07:47–08:33
• Energy Efficiency Imperatives: 08:55–10:23
• Global Supply Chain Constraints: 12:30–13:42
• Memory Bottleneck: 13:51–14:20
• China/U.S. Export Policy: 14:20–14:38
• Siemens’ Software M&A Strategy: 15:26–16:48
• Grok, New AI Hardware: 16:48–18:08
• AI in Space: 18:18–19:27
• Autonomous Vehicles Stack: 20:07–21:13
• Siemens Manufacturing Deployment: 21:52–22:26
• Silicon Valley, Tax Policy: 23:04–23:40

Conclusion

This engaging conversation between two global tech leaders highlights the deep integration of AI into the fabric of manufacturing, energy, and industrial software — and the mounting challenges and opportunities at the intersection of digitization and the physical world. The partnership promises a future where design, simulation, autonomy, and real-world impact fuse, with energy and supply chain realities shaping the pace and scale. With both companies applying each other’s technology in their own factories, the “industrial AI operating system” is not a futuristic vision but an ongoing, accelerating reality.