NVIDIA AI Podcast – GTC Live Washington, D.C.: AI for Robotics and Manufacturing

Episode Date: November 11, 2025
Host: NVIDIA
Panelists:
• Peter Kurta (CTO & Chief Strategy Officer, Siemens AG)
• Young Liu (Chairman & CEO, Foxconn)
• Brett Adcock (Founder & CEO, Figure AI)
• Aki Jain (President & CTO, Palantir US Government)

Episode Overview

In this special GTC edition of the NVIDIA AI Podcast, leading figures from Siemens, Foxconn, Figure AI, and Palantir join to discuss the transformative power of AI and robotics in reshaping manufacturing, from Next-Gen “Industrial 5.0” to the dawn of general-purpose humanoid robots. The discussion explores technological breakthroughs, global competition, workforce implications, and the evolving government-industry relationship in driving the reindustrialization of America.

Key Discussion Points & Insights

1. AI’s Transformative Impact on Manufacturing

From Labor-Intensive to AI-Intensive (Foxconn) [02:08]
- Young Liu outlines Foxconn's progression from labor-intensive to automation, now entering the “AI-intensive” era.
- Quote:
  “With new generative AI technologies, we think the AI intensive manufacturing is coming…I call this industrial 5.0.” (Young Liu, 03:25)
- Foxconn is building new factories across Ohio, Texas, Wisconsin, and California to support this new era.
Digital Twins & Agile Factories (Siemens) [04:10]
- Peter Kurta explains Siemens’ use of digital twins: every factory is built first virtually, optimized, and then constructed physically.
- The virtual and real factories communicate—allowing rapid response to disruptions like supply chain shortages.
- Quote:
  “With digital models, you can look at it and say, what if actually this part is missing? … That gives you unprecedented speed… productivity … sustainability and energy efficiency.” (Peter Kurta, 05:20)

2. Humanoid Robotics: Progress & Promise

Building General Purpose Robots (Figure AI) [06:15]
- Brett Adcock describes the complexity of humanoid robots—control over 40 joints, leading to an almost infinite number of possible positions.
- Reliance on neural networks is critical; Figure AI gives “AI a body” and employs NVIDIA tech from pre-training to real-time inference, all running onboard without constant connectivity.
- Quote:
  “You can’t code your way out of that problem … We’re basically just in the physical world touching things. And Nvidia has been a very significant partner and investor of ours.” (Brett Adcock, 06:20)
From R&D to Deployment [07:55]
- Figure AI is refining the horizontal AI stack for general purpose, using commercial deployments to learn and iterate.
- Manufacturing at scale is underway with their California facility (BOTQ), managing everything from assembly to testing.

3. Data, Ontologies & AI Integration (Palantir)

Bridging Data Silos to Outcomes [10:01]
- Aki Jain explains Palantir’s “ontology” as a layer that connects disparate data systems (ERPs, MRPs, etc.), providing necessary “ergonomics” for human and AI agents to interact, optimize, and orchestrate operations.
- Quote:
  “If you reframe the data … into the ontology, you can reframe the operations of a factory—any process at scale.” (Aki Jain, 11:15)

4. Globally Competitive AI & Reindustrialization

Open Models, Customization & Edge AI [12:02]
- Palantir and Siemens both see industry moving from generic, “horizontal” open AI models to bespoke, fine-tuned, often closed systems needed for specific operational use-cases.
- Quote:
  “We’re seeing the trend of open models … quickly refine them and … solve a specific problem at a low swap [size, weight, and power].” (Aki Jain, 12:44)
Scaling American Manufacturing [14:17]
- Young Liu highlights three levels of AI intelligence in manufacturing—from simple, fixed tasks to flexible and complicated operations.
- Foxconn’s US investments are both to meet compute demands and to support talent pipelines with government cooperation.
- Quote:
  “We also need talented technicians and engineers … That’s another challenge …to have education that is steered towards this.” (Young Liu, 15:14)
US vs. China in Robotics [16:25]
- Brett Adcock contends the biggest hurdle is solving “general-purpose almost human-like intelligence in the physical world.” He claims Figure AI’s progress gives the US a global lead.
- Once the AI is cracked, scaling manufacturing via consumer electronics processes is “tractable.”
- Quote:
  “What is not solved is to be able to do real end-to-end general purpose robotics. … At Figure, we’re leading that head and shoulders globally.” (Brett Adcock, 17:55)

5. General Purpose Robots: Home & Factory

Lessons from Commercial Deployments [19:03]
- Figure AI has robots working independently for 10-hour shifts with steadily improving reliability.
- The vision: robots for both commercial and residential use, with staged rollouts after rigorous validation.
- Quote:
  “We have a robot running right now in our first commercial customer. …Performance has been rising every single month.” (Brett Adcock, 19:13)
- “We will not do it early… We want to be really confident it’s going to really work and it’s going to be really safe.” (Brett Adcock, 21:02)

6. Government-Industry Relations

Improved Engagement with US Government [22:05]
- Aki Jain and others praise recent administration openness to tech industry input, particularly for national security, innovation, and industrial policy.
- Quote:
  “You kind of have this perfect storm in the moment and the people. …The ability to say, hey, that doesn’t look right and to give feedback… is unparalleled.” (Aki Jain, 22:20)
Appreciation for Pragmatic Regulation [24:28]
- Peter Kurta notes a shift towards listening, action, and regulatory minimalism in B2B contexts, fostering faster innovation.
- Young Liu echoes the support for new technologies by the current government.
- Quotes:
  “The willingness to listen, but also then to take actions and to implement is really, really key.” (Peter Kurta, 24:28)
  “We felt the same way. I think this government is quite open to the technologies and very supportive to the new technologies right now.” (Young Liu, 25:00)

Notable Quotes & Moments with Timestamps

[03:25] Young Liu: “I call this industrial 5.0.”
[05:20] Peter Kurta: “With digital models, you can look at it and say, what if actually this part is missing? … unprecedented speed… productivity … sustainability and energy efficiency.”
[06:20] Brett Adcock: “You can't code your way out of that problem … We're basically just in the physical world touching things.”
[10:41] Aki Jain: “…the ontology ends up serving as an SDK for the AI, for the agents, for the models.”
[12:44] Aki Jain: “We're seeing the trend of open models…and get to something that solves a specific problem at a low swap is being really critical.”
[17:55] Brett Adcock: “…At Figure, we’re leading that head and shoulders globally and we hope to continue to pull away.”
[19:13] Brett Adcock: “We have a robot running right now in our first commercial customer. …Performance has been rising every single month.”
[22:20] Aki Jain: “You kind of have this perfect storm in the moment and the people. …The ability to say, hey, that doesn’t look right and to give feedback… is unparalleled.”
[24:28] Peter Kurta: “The willingness to listen, but also then to take actions and to implement is really, really key.”

Important Timestamps

[00:52] Introductions, framing the era of programmable physical world
[02:08] Young Liu on Foxconn’s AI manufacturing transformation
[04:10] Peter Kurta on digital twins for agile factories
[06:15] Brett Adcock on the complexity of humanoid robotics
[10:01] Aki Jain on Palantir’s role in unifying data and operations
[12:02] Panel on open models, hybrid approaches, and on-premise edge AI
[14:17] Young Liu on AI tiers and US investment
[16:25] Brett Adcock on the US-China robotics race
[19:03] Figure AI’s commercial deployments and reliability insights
[22:05] Government receptiveness and action: industry perspectives

Conclusion

This episode offers an expansive yet grounded look at the intersection of AI, robotics, and next-generation manufacturing. Speakers emphasized the urgency of collaboration, the centrality of digital-physical integration, and the pivotal role of both talent and open regulation. With unprecedented momentum, the blend of AI and robotics is poised to redefine manufacturing’s future—both in the US and worldwide.

NVIDIA AI Podcast – GTC Live Washington, D.C.: AI for Robotics and Manufacturing

Episode Overview

Key Discussion Points & Insights

1. AI’s Transformative Impact on Manufacturing

From Labor-Intensive to AI-Intensive (Foxconn) [02:08]
- Young Liu outlines Foxconn's progression from labor-intensive to automation, now entering the “AI-intensive” era.
- Quote:
  “With new generative AI technologies, we think the AI intensive manufacturing is coming…I call this industrial 5.0.” (Young Liu, 03:25)
- Foxconn is building new factories across Ohio, Texas, Wisconsin, and California to support this new era.
Digital Twins & Agile Factories (Siemens) [04:10]
- Peter Kurta explains Siemens’ use of digital twins: every factory is built first virtually, optimized, and then constructed physically.
- The virtual and real factories communicate—allowing rapid response to disruptions like supply chain shortages.
- Quote:
  “With digital models, you can look at it and say, what if actually this part is missing? … That gives you unprecedented speed… productivity … sustainability and energy efficiency.” (Peter Kurta, 05:20)

2. Humanoid Robotics: Progress & Promise

Building General Purpose Robots (Figure AI) [06:15]
- Brett Adcock describes the complexity of humanoid robots—control over 40 joints, leading to an almost infinite number of possible positions.
- Reliance on neural networks is critical; Figure AI gives “AI a body” and employs NVIDIA tech from pre-training to real-time inference, all running onboard without constant connectivity.
- Quote:
  “You can’t code your way out of that problem … We’re basically just in the physical world touching things. And Nvidia has been a very significant partner and investor of ours.” (Brett Adcock, 06:20)
From R&D to Deployment [07:55]
- Figure AI is refining the horizontal AI stack for general purpose, using commercial deployments to learn and iterate.
- Manufacturing at scale is underway with their California facility (BOTQ), managing everything from assembly to testing.

3. Data, Ontologies & AI Integration (Palantir)

Bridging Data Silos to Outcomes [10:01]
- Aki Jain explains Palantir’s “ontology” as a layer that connects disparate data systems (ERPs, MRPs, etc.), providing necessary “ergonomics” for human and AI agents to interact, optimize, and orchestrate operations.
- Quote:
  “If you reframe the data … into the ontology, you can reframe the operations of a factory—any process at scale.” (Aki Jain, 11:15)

4. Globally Competitive AI & Reindustrialization

Open Models, Customization & Edge AI [12:02]
- Palantir and Siemens both see industry moving from generic, “horizontal” open AI models to bespoke, fine-tuned, often closed systems needed for specific operational use-cases.
- Quote:
  “We’re seeing the trend of open models … quickly refine them and … solve a specific problem at a low swap [size, weight, and power].” (Aki Jain, 12:44)
Scaling American Manufacturing [14:17]
- Young Liu highlights three levels of AI intelligence in manufacturing—from simple, fixed tasks to flexible and complicated operations.
- Foxconn’s US investments are both to meet compute demands and to support talent pipelines with government cooperation.
- Quote:
  “We also need talented technicians and engineers … That’s another challenge …to have education that is steered towards this.” (Young Liu, 15:14)
US vs. China in Robotics [16:25]
- Brett Adcock contends the biggest hurdle is solving “general-purpose almost human-like intelligence in the physical world.” He claims Figure AI’s progress gives the US a global lead.
- Once the AI is cracked, scaling manufacturing via consumer electronics processes is “tractable.”
- Quote:
  “What is not solved is to be able to do real end-to-end general purpose robotics. … At Figure, we’re leading that head and shoulders globally.” (Brett Adcock, 17:55)

5. General Purpose Robots: Home & Factory

Lessons from Commercial Deployments [19:03]
- Figure AI has robots working independently for 10-hour shifts with steadily improving reliability.
- The vision: robots for both commercial and residential use, with staged rollouts after rigorous validation.
- Quote:
  “We have a robot running right now in our first commercial customer. …Performance has been rising every single month.” (Brett Adcock, 19:13)
- “We will not do it early… We want to be really confident it’s going to really work and it’s going to be really safe.” (Brett Adcock, 21:02)

6. Government-Industry Relations

Improved Engagement with US Government [22:05]
- Aki Jain and others praise recent administration openness to tech industry input, particularly for national security, innovation, and industrial policy.
- Quote:
  “You kind of have this perfect storm in the moment and the people. …The ability to say, hey, that doesn’t look right and to give feedback… is unparalleled.” (Aki Jain, 22:20)
Appreciation for Pragmatic Regulation [24:28]
- Peter Kurta notes a shift towards listening, action, and regulatory minimalism in B2B contexts, fostering faster innovation.
- Young Liu echoes the support for new technologies by the current government.
- Quotes:
  “The willingness to listen, but also then to take actions and to implement is really, really key.” (Peter Kurta, 24:28)
  “We felt the same way. I think this government is quite open to the technologies and very supportive to the new technologies right now.” (Young Liu, 25:00)

Notable Quotes & Moments with Timestamps

[03:25] Young Liu: “I call this industrial 5.0.”
[05:20] Peter Kurta: “With digital models, you can look at it and say, what if actually this part is missing? … unprecedented speed… productivity … sustainability and energy efficiency.”
[06:20] Brett Adcock: “You can't code your way out of that problem … We're basically just in the physical world touching things.”
[10:41] Aki Jain: “…the ontology ends up serving as an SDK for the AI, for the agents, for the models.”
[12:44] Aki Jain: “We're seeing the trend of open models…and get to something that solves a specific problem at a low swap is being really critical.”
[17:55] Brett Adcock: “…At Figure, we’re leading that head and shoulders globally and we hope to continue to pull away.”
[19:13] Brett Adcock: “We have a robot running right now in our first commercial customer. …Performance has been rising every single month.”
[22:20] Aki Jain: “You kind of have this perfect storm in the moment and the people. …The ability to say, hey, that doesn’t look right and to give feedback… is unparalleled.”
[24:28] Peter Kurta: “The willingness to listen, but also then to take actions and to implement is really, really key.”

Important Timestamps

[00:52] Introductions, framing the era of programmable physical world
[02:08] Young Liu on Foxconn’s AI manufacturing transformation
[04:10] Peter Kurta on digital twins for agile factories
[06:15] Brett Adcock on the complexity of humanoid robotics
[10:01] Aki Jain on Palantir’s role in unifying data and operations
[12:02] Panel on open models, hybrid approaches, and on-premise edge AI
[14:17] Young Liu on AI tiers and US investment
[16:25] Brett Adcock on the US-China robotics race
[19:03] Figure AI’s commercial deployments and reliability insights
[22:05] Government receptiveness and action: industry perspectives

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GTC Live Washington, D.C. - Chapter 5: AI for Robotics and Manufacturing

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Summary

NVIDIA AI Podcast – GTC Live Washington, D.C.: AI for Robotics and Manufacturing

Episode Overview

Key Discussion Points & Insights

1. AI’s Transformative Impact on Manufacturing

2. Humanoid Robotics: Progress & Promise

3. Data, Ontologies & AI Integration (Palantir)

4. Globally Competitive AI & Reindustrialization

5. General Purpose Robots: Home & Factory

6. Government-Industry Relations

Notable Quotes & Moments with Timestamps

Important Timestamps

Conclusion

Summary

NVIDIA AI Podcast – GTC Live Washington, D.C.: AI for Robotics and Manufacturing

Episode Overview

Key Discussion Points & Insights

1. AI’s Transformative Impact on Manufacturing

2. Humanoid Robotics: Progress & Promise

3. Data, Ontologies & AI Integration (Palantir)

4. Globally Competitive AI & Reindustrialization

5. General Purpose Robots: Home & Factory

6. Government-Industry Relations

Notable Quotes & Moments with Timestamps

Important Timestamps

Conclusion