Joining me is Jasmine Bai, Vice General Manager at FAIR Plus, where she runs international development. FAIR Plus is a Shenzhen exhibition co-organized by the Shenzhen Robotics Association and Messe Stuttgart, built for robot developers. Its second edition in April 2026 had more than 400 exhibitors and 60,000 visitors, roughly 3,000 of them international, across 100 countries.

Where demand is strongest in Physical AI

Component suppliers took 70% of their exhibition floor. Full robot makers, 20-25%. It maps to the typical archetype of visitors for FAIR Plus: researcher-founders. A growing number of them also came for the brain side of the stack.

Visitor behavior differs by region

Europeans arrive having already concluded they need a hardware supply-chain partner in Shenzhen. Southeast Asian buyers come to source finished robots to resell into Malaysia and Thailand. American visitors, the largest international cohort, mostly came to observe.

We also covered a German robotics company relocating R&D to Shenzhen, the humanoid makers that drew the most crowded sessions from attendees, and the coordination layer above deployed robot fleets that Siemens is positioning to own.

Follow FAIR Plus here: https://fairplus.cn/en/about-fairplus/

You can also watch the show on Youtube:

Every episode, I sit down with the founders, researchers, and operators building physical AI worldwide, tracing the full stack from components and supply chains to what actually deploys. See all published episodes here.Chapters

00:00 - Intro

01:41 - The strategic focus on robotic research and industry partnerships

03:03 - Surprising trends: American visitors’ prominence in China

04:45 - Regional motivations: Europe, Southeast Asia, and the US

06:52 - Insights into American visitor behavior and industry development

09:33 - The platform’s role in supporting robot developers and tech exchanges

12:07 - Types of visitors: universities, startups, and corporate innovators

13:36 - Academic researchers and their role in commercial robotics

14:34 - Trends in localization: German companies establishing R&D in Shenzhen

17:15 - Future directions: humanoid robots and industry adoption

19:14 - Popular sessions on collaborative research and supply chain innovation

22:23 - The increasingly unavoidable need to collaborate with China

23:17 - Notable exhibitors shaping future industry trends

24:23 - The open and collaborative industry environment fostered by companies like Siemens

Joining me is Eric Pan, one of the founding figures of China’s maker movement and the AI hardware partner behind many global makers’ products. He founded Seeed Studio in 2008, which provides hardware modules, prototyping, and small-batch manufacturing services to hardware entrepreneurs worldwide. Today Seeed is the company behind Reachy Mini’s production and an NVIDIA robotics partner. He also created the Chaihuo makerspace and brought the first Maker Faire to China. Before all of that, he worked on chipset quality at Intel, so he has seen the hardware world from both sides: US corporate process, and now nearly two decades embedded in the Shenzhen supply chain.

We recorded at Seeed Studio’s offices. I wanted this episode to work as a primer on two levels: for entrepreneurs, how to actually work with Shenzhen and how business gets done on the ground; for investors and operators, what makes Shenzhen’s manufacturing base hard to replicate. Most people can tell you Shenzhen’s advantage is cost. With reshoring back on the US agenda and capital flowing into US manufacturing startups, the more useful question is what actually sits underneath that cost advantage, and what it takes to build a robust manufacturing supply chain anywhere.

We talked through the Reachy Mini story and how Seeed absorbed a five-fold demand spike for Pollen Robotics, why supplier trust, not budget, is the binding constraint for hardware startups, the distinct mistakes hardware veterans and software founders make in Shenzhen, why Eric now tells founders not to build hardware at all, “design from manufacturer” as a method, the quality-cost-lead-time triangle and what reshoring can and cannot replicate, how a $1,000 open-source robot arm opens up the pan-industry beyond factories, humanoids versus vertical robots, and where Shenzhen sits in the physical AI story twenty years out.

Follow Seeed Studio here: https://www.linkedin.com/company/seeedstudio/ | Website: https://www.seeedstudio.com/ | Chaihuo: https://www.chaihuo.org/

You also can watch the show on Youtube.

Every episode, I sit down with the founders, researchers, and operators building physical AI worldwide, tracing the full stack from components and supply chains to what actually deploys.

Chapters

* 00:00 Cold open

* 00:41 Seeed Studio in 2026: from modules to solution systems

* 01:48 The Reachy Mini scale-up with Pollen Robotics

* 03:01 Supply chain trust: why startups can’t build it alone

* 05:08 Common mistakes: hardware veterans vs software founders

* 07:56 “Don’t build hardware”: reference designs and open source

* 09:48 Anatomy of a failed Shenzhen project

* 11:18 Building trust on the ground: come as a student

* 12:20 Reshoring and the impossible triangle: quality, cost, lead time

* 14:24 Why Seeed built an open-source robot arm

* 16:42 $1,000 arms and the “pan-industry”

* 19:08 Humanoids vs vertical robots

* 20:38 Reopening San Jose: Bay to Bay 2

* 1:56 Shenzhen twenty years out: innovate with China

AI-generated transcript (for reference only)

Michelle Sun (00:00) You’ve watched so many Western founders come to Shenzhen to build their dream products. What is the most common mistake that you’ve seen them make?

Eric Pan (00:08) We try to convince people not to build hardware.

Michelle Sun (00:11) From the surface, Shenzhen’s competitive advantage is cost. But beyond cost, what is the true advantage of Shenzhen’s capability? Eric Pan started Seeed Studio in two thousand and eight selling hardware from his apartments. Today the company behind Reachy Mini’s production, NVIDIA’s robotics partner, and the AI hardware partner banner all over Shenzhen is telling the next generation of Western founders to stop making hardware. We’re in Shenzhen to find out why.

Eric Pan (00:35) For a startup to be able to trust over like hundreds of different suppliers is a nightmare.

Michelle Sun (00:41) Hi Eric. So from the inside, how would you actually describe the business today in two thousand twenty six?

Eric Pan (00:46) So we started with open source hardware and we still do so, but it’s evolving all the way from modules to devices now more into solution systems. And we see ourselves as a platform to incubate more hardware ideas into real products.

Michelle Sun (01:00) And you’ve described a business as two thirds of prototyping for early stage startups and a third for scale up production. So can you tell me more how that scale up production part actually works and how would a founder work with a team like yourself?

Eric Pan (01:11) I

think it’s actually a loop. We provide the open source modules and devices. Devices as the reference design, modules and the core components. So people buy them and they do the prototypings. Try them out to h infuse your ideas, software, data into the creation. Then the best option is come back to us and to scale that. Because we have all the supply chains, we have all the expertise. We just need to like change design files, remove some components for them, or remix several projects together.

to make the into their creations. So it’s very naturally growing from the two thirds of prototyping into one third of a scaling up. So

Michelle Sun (01:48) The Reachy Mini story where the Pollen’s demand spiked five times more than they expected. So how did you help the team and how did you work with the founder too?

Eric Pan (01:56) Yeah, we know Pollen Robotics for many years and they have been using our ReSpeaker, which is a microphone array from the very beginning. Okay. So it’s very organically they evolve into a device that they want to manufacture, they ask us for help. And we respect this project very much. So why not? And we host them as of our team. So they come to Shenzhen, stay here for three months and in this office. Nice and we s put our engineers to work them together, like side by side.

Michelle Sun (02:17) In this office or

Eric Pan (02:22) Basically we helped them to re engineer many parts of the design because we know the manufacturing better. Mm-hmm. And it’s more like an engineering process. They do the EVT. We help them to like fine tune the designs. We talk to the supply chain, know the re restrictions. And we had a a lot of injection modings or stampings for different kind of the parts. Because they have very clear goal how many they are going to ship, we how fast they should be doing that, and we put our project management team and engineers in full speed.

to support this happen. And it was kinda magic because they have the right team to work with. They know us, they trust us. So even it’s two companies we work as one team.

Michelle Sun (03:01) In terms of the supply chain partners, are they all over Shenzhen or do you have like a set, you know, list of people that you go to for like various components?

Eric Pan (03:08) Of course we have SRM, like supply chain relationship management, and we have the majority of them are around Shenzhen and Dongguan. But we still buy parts from like the east of China, from all over the world.

Michelle Sun (03:20) What would have happened to Pollen Robotics if they didn’t work with you guys? Like how would they meet that demand?

Eric Pan (03:24) I don’t know. There can be many folds. There can be like if they go to all the supply chain themselves, because to any of the supplier, they need a long time to trust the customers as well. Yeah. Not not only vice versa, but they need to understand you this is a startup, but they are not nobody. They can pay on time. They know the manufacturer and respect the process. So it’s taking a long time to build a trust. But if for a startup to build a trust over like hundreds of different suppliers, it’s a nightmare.

It’s not only about the budget. It’s also about the understanding of each other. Understanding of what’s limitations on manufacturing, why we cannot do this way. It’s also on the quality management. How do I set up the quality to make sure the factories knows what to deliver? Mm-hmm. Also it’s about need time. Need time is actually most of the need time is about waiting. Because the manufacturer cannot be empty until you come. They always have some cues. But why would they prioritize your projects?

So it’s a lot of like orchestrations in between and we are doing this job for eighteen years. We have our own product, we have our own supply chains, we have own factories, so that’s making this life much easier.

Michelle Sun (04:31) Mm-hmm. Yeah. And you have this like close relationship with various factories that you’ve worked with over the many years and so it kind of builds that trust over time. And when the startups go to you guys and then to the factories, then there’s one layer of support.

Eric Pan (04:45) Exactly. We are more like a future or middle ground of the trust. Because we need to understand the customers as well. Like we have selection of our customers very much. We don’t do consumer electronics because we think that’s going to be very fierce compet competitions. Has to be very large scale that corporations might be taking over. So we’re focusing on emerging technology. We’re focusing on more vertical or like industrial oriented stuff.

Michelle Sun (05:08) Mm-hmm, for sure. So you’ve watched so many Western founders come to Shenzhen to build their dream products. So what is the most common mistake that you’ve seen them make?

Eric Pan (05:17) Well, the mistakes are very uncommon. Each team have their like restrictions. Some of the like Apple experts, they’re working for Ample or Microsoft for hardware, they come to Shenzhen and they are demanding very much like a corporation, but they have very small volume and they have a very small supplier, versus previously they are working for Apple. So their methodology will fail. They have to change the methodology to more agile, more trustworthy, relationship based. Not

like contract based with with a lot of demanding weight. So this is one of the common mistakes for the hardware background people. But for the software background people, they don’t know manufacturing at all. So they will think, okay, if you it should be like a coding, I compile in five minutes and I can change it. But for hardware, any changes might take weeks. So you have to be have a lot of simulations, understandings of the process we call DFM. But for small teams, it’s not “design for manufacturer”, it’s “design from manufacturer”. If you’re Apple, they

the factories should be “you care for them. You change according to the needs.” But if you are a startup, the best way is not to design from scratch, is design from what’s already out there. For example, if you want to design a tablet, you go to a tablet factory, see what they have been working around and to change from that. Give it a model so it can move around or give it different extensions. But don’t build from scratch. Yeah. So that’s I think it should be a key lesson for the software team is look what’s already out there and design from that.

Michelle Sun (06:25) Interesting.

So it seems like a lot of people tend to come to Shenzhen with a certain expectation of, okay, this is the prototype that is from the 3D modeling and then like make it happen. And so it seems like it doesn’t really work like that way where it’s better to see on the ground what’s available and then do the design. I think it’s

Eric Pan (07:01) not a common mistake, but it’s a common takeaway is people should come to Shenzhen with openness. They should let go of their ego. They should respect more of what’s o already out here. The engineers are very expert. Even the workers, they have the expertise. So respect for their way they are doing things. By default they’re not doing wrong. By default, the creators might be wrong. Mm-hmm. Yeah, I think that’s the best way to avoid the mistake is coming to Shenzhen more often, to see already what’s happening.

And another way to overpass the mistakes are don’t do hardware. From ten years ago we trying to have people to build their hardware, but ten years later we try and convince people not to build hardware. Because you’re a software team. You don’t need to build the hardware from scratch. You should look kind of because why we do open source hardware is for people to take it them as a reference design. So you have the reference design, you have the 3D printed enclosure, that’s good enough. You don’t need to compete with the world on the hardware.

Michelle Sun (07:37) Tell me more about that.

Eric Pan (07:56) The software team usually have their expertise on the like functions, on the user experiences, on the vertical knowledges. That’s their best competence. Yeah. So they should focus on that and using a more standardized hardware. Don’t put too much effort on like to make this hardware good enough as Apple. It’s not going to happen. So they should find really understand who they are and come to Shenzhen to find the right small enough complimentaries to their business.

Michelle Sun (08:21) Yeah. And why do you think that there are so many hardware founders that are from software background that is trying to innovate on the hardware side? Because the open source hardware is not a secret, right? Like it’s everyone knows that they exist and why don’t more people use that in your opinion? You’re saying that you’re trying to make people make hardware less and focus on the software. So what do you think is stopping these people from focusing on the software and still go to the hardware side and try to innovate there?

Eric Pan (08:47) I think it’s because most of the venture capitalists because we see wants to invest in hardware. And for more than ten years people think hardware might be the new software and they collapse. Yeah. And now I think for this trend we see a lot of drive is because of AI is e eating software. Yeah. People panic and want to find a a standing ground where hardware might be that. But I think it’s not about software and hardware. It’s more about public domain technology or like vertical domain technology.

So people should have the little one. If you’re on the public domain technology, you should be working for Apple or like Meta or Anthropic.

Michelle Sun (09:23) Can you share more about what you mean by public domain knowledge?

Eric Pan (09:26) Public

domain knowledge is you want to make a device that everyone knows how to make and everyone wants to use that. It’s like iPhone, the next iPhone. I think most of the team wants who wants to build the next iPhone will fail. Most of them. Most of for the companies. Even most of the hardware companies will fail on that. Mm-hmm. But for the verticals, for the more standard long term market, there are so many interesting things need to be renovated. Mm-hmm.

Michelle Sun (09:48) Can you tell me a specific story, you don’t have to share the name, of a Western founder that came to Shenzhen and failed. What did they think they understood and what did they actually miss?

Eric Pan (09:59) Yeah, I too many of them. Yeah, but a common story is like a western founder, they have a software knowledge, they have a lot of budget. They come to Shenzhen, they find a design house, and they want to build this into scale very fast. But they don’t know what will be the limitations. And so they could factory point at all varieties of things because they pay off good money if I listen to them. But they are not giving the right guidances. In the end the manufacturing will be slowed down, it’ll be too costly.

They don’t know how to set up the expectations about the quality. So the team will be delivered something like without clear understanding of the requirements. They don’t know how to comment the requirements and they don’t listen. So this is a very high failure rates. People will have very ideal expectations because they are in urgency, so they punch the factory too hard and they push to the limitations, sometimes beyond the limitations. Yeah. So the hardware cannot be made. In the end they don’t ship.

They have a lot of investment or back orders but they cannot ship and they failed. And they broke their reputations. Yeah. This happens a lot. But this happens often in the consumer electronics. Because for consumer electronics everybody is trusting the wave and everybody is fighting for the wave. They have to be fast. Yeah. They have to be differentiating. Mm-hmm. But I think most of them are failing. So we don’t want to have them.

Michelle Sun (11:18) You mentioned a point earlier about building trust. You know, let’s say I’m someone that’s coming to Shenzhen to build my dream product. How would you advise me to build trust with the partners that I’m working with like locally, like the factories and basically the whole part of a supply chain?

Eric Pan (11:34) I think the best way is first to come as a student. As if you are a student. You are like a road climber, but you are the first time to the mountain. Mm-hmm. You have to trust your coach, you trust your guides. Go to the factories to see what’s happening, to gain as much knowledge as possible. And go to Huaqiangbei to see what’s already been built. Understand the methodologies, understand the material, the process, they use, and come back and to rethink your Do I really want to build this?

Can I just tolerate what’s already out there? It’s not perfect, but should I just change a little bit to be different? Yeah. Don’t build it from scratch, but rebuild. You are like shopping in the whole center area. Yeah. Find the right ground to start with.

Michelle Sun (12:20) So be a student and go on the ground and pick from what’s available and try not to change everything from the start. Exactly. So there’s been a lot of talks in the West about reshoring. So bringing back manufacturing facilities and capabilities back to the West. And from the service, we all know that Shenzhen’s competitive advantage is, you know, one of them is cost, right? Everything is a fraction or a hundredth of what it will cost in the West.

But beyond cost, what is the true advantage of Shenzhen’s capability?

Eric Pan (12:52) We usually see it as three parts, quality, cost and lead time. So and this impossible triangle, if you need a cost, usually you need to have very long lead time to prepare for that. Shenzhen I think if I talk about cost but under the cost, it’s all the engineering complexities. Mm-hmm. It’s a full like a tree of supplies that it needs to be responsive. So Shenzhen is like a jungle with enough biodiversities.

You can find engineer with all kinds of background, all kinds of skill sets. So if you want hardware, you can find the right spaces to remingle to whatever you want. I think that’s first reflecting to speed. Secondly, cost really matters to quality and volume. If you have small volume, you can expect the cost to be low anywhere. But in Shenzhen, you can get a relatively much lower cost on the small volume and bigger volume because there’s enough competitions.

There’s enough demand and supplies. I think what really matters about reshoring is can we replicate the demand and supply in United States, Europe or anywhere. In some time we are facing the global demand and we are trying to supply according to that needs. So I think in short term you cannot just remove the whole jungle and to redeploy that on the Mars. That’s not gonna happen. Of course the reshoring can happen on some stages for semi assembled products. You redo that

to recombine them into the finished product. That can happen in Vietnam, in the States, in Japan. We’re trying to do that as well. Mm-hmm.

Michelle Sun (14:24) So the global demand coming to Shenzhen is enabling that speed, that lead time, the cost advantage. So the question is how to replicate that elsewhere, anywhere where the cost is so high to make a certain components, especially the bespoke ones. So tell me about robots. You mentioned that you’re trying to have more people make less hardware and focus on the software side. And tell me w how you decide to build robots and the story behind.

Eric Pan (14:53) for robot it’s kind of I would say unexpected. We didn’t plan to do robots in the very beginning. We focused on the open source hardware, it’s on the AI part. But gradually we made the edge computing, like the Jetson devices. So people come back to us looking for more parts around the computations. But we like robots so much. Our team says, Okay, how about we make a robot arm? I say no, we don’t we’re not good at robot arms. But in the end we it’s like internal

Alpha projects, it’s like for hobbyists, for internal explorations. After a few months we we share that on GitHub. Say, okay, would you guys like to build an open source robot arm with us? And we see a lot of interest. Nice. And this is a new market to us. We look into that, okay. There are so many robot arms, but most of them are closed sourced. The professionals are all closed sourced and they’re super expensive. Because they were from the older industry way. They were not beautiful for the AI part. They have beautiful automations.

Michelle Sun (15:49) Is like the open

arm or you know?

Eric Pan (15:50) It’s before that, it’s like KUKA, it’s like ABB there were like the traditional skills. Then we have the like education arms, like Dobot, like Elephant Robotics, they have different kind of servo based arm. And then we should okay, with all the robot industry popping up in China, the p motors, the process becoming cheap enough, affordable enough. So we will on behalf of all the ecosystem, we customize from this supply chain to build an open source arm and evolve with everyone. Is that

Michelle Sun (15:53) Those are like huge scale.

Also

servos?

Eric Pan (16:21) No, this is brushless. Yeah,

and with all the drivers, all the the P I D controls. But we will open source everything. We already open source everything. So I think it’s becoming a trust ground, a reference design for people to be to different sizes, different activities. And we are more like platform to incubate more embodied or basic AI parts from this.

Michelle Sun (16:42) What are some projects that are built building upon this that stood out to you?

Eric Pan (16:46) It’s a very interesting involvement. Previously with a expensive like a twenty thousand dollar robot arm, you can only do heavy industry, professional ones. But with cheap enough like one thousand dollar robot arm, you can think of a lot of domains cheap enough to replace human labor or a dangerous environment that not suitable before. We call them what we call the “pan-industry”. It’s like not professional industry but it’s more like for retail, for agriculture. Not industry industry, but it’s like for everyday usages.

Michelle Sun (17:16) Yeah,

more like commercial use. Commercial use. In a shop or

Eric Pan (17:17) Yeah, yeah,

like It can it can be very pervasive. It’s like personal computer. Yeah. In the beginning we don’t think personal computer is not a must. But the in the end, personal computer people think of all the usages. We benefit from that. I think it’s a similar stage for personal robots. But it’s not necessarily to be a robot that works for you like a humanoid, that’s too expensive in the beginning. Maybe you can start with a personal robot arm to help you give you extra hands on many things. It can be pick-and-place for a sorting machine, it can be your coffee maker, you could be working as your chef in the restaurants for barbecue. Mm-hmm. So we see these possibilities. And we are pushing that very much into cooking. Because cooking is what we are talking about. Yeah. But cooking is also a very diversity of actuations and sensing. Yeah. Different food, different questions have their different processes. But how can autonomous machines do that?

So it’s a very interesting challenge. Yeah. And we don’t have a fixed one answer. That’s where we like it. Yeah. With all the diversities you might be making noodles, you might be making barbecue, you might be making sushi. But people can challenge us with different models, different methodologies. But in the end, we hope that people can really use it in the practical situation.

Michelle Sun (18:28) Do you think this will go together at some point? Yeah, sure.

Eric Pan (18:30) Sure.

These actually they go together, but just not on this model. This is a very cheap robot hand with limited actuation or freedom. But if we twelve ish? Twelve okay.

Michelle Sun (18:40) How many do you left?

Okay.

And what’s the cost for that like

Eric Pan (18:47) I think the cost is a hundred dollars ish. Yeah, yeah, yeah.

Michelle Sun (18:50) That’s really cheap. Wow.

How’s that possible? Like I teach I see. Okay.

Eric Pan (18:54) Just the small servers. And they’re

very easily engineered, very clear smartly engineered. Mm-hmm. So I believe these guys are not for venture capitalists, but they are more for small business to start humbly to do something for real. Yeah. It’s a different approach. Yeah.

Michelle Sun (19:08) That’s great.

So humanoids. Everyone’s talking about them. And so in the US, a lot of these humanoid companies are vertically integrated, so platform first as well. And f in China I see a lot of just start small, a narrow use case, and then deploy it and expand. So is that how you see it and what’s the winning strategy?

Eric Pan (19:30) I think there’s no winning and losing between these two kinds because they are different creatures. So they’re different in it’s like a biosystem. They are in a different position. For the humanoids want to dominate the world, have all the human egos, I don’t know them. I don’t know how they are going to win or lose. But they have their mythologies, at least they have enough capital to pursue that possibility. But what we are looking at is we believe the majority of the robots are not humanoids.

Yeah, your working cleaners. This should be like a extra like nav that can corresponding to your actions. Even look we look in the this room, it’s like a robot. We’re in the belly. Yeah. It’s called a smart home. But it can be more active, proactive. The air should be responding to you. If it should be agentic. Mm-hmm. So I think in the future, like most of the devices we have today will be a robot. Yeah. Even the camera, it should be moving automatically. It should be understanding your like podcast needs and to adjust itself. It’s a robot as well. Yeah. But it does not need to be a humanoid.

Yeah. So our our passion and I think f through the open source and maker culture is we can enable more startups who want to build more vertical things that the big company don’t care about.

Michelle Sun (20:38) So you reopened the San Jose office earlier this year and you hosted this embodied AI hackathon in around GTC. So tell me more about your thoughts on the US market for seed and what are you thinking?

Eric Pan (20:51) Yep, we have the US office in Bay Area ten years ago. We closed down because of COVID, because nobody’s doing hardware for a few years. But now AI is back. People are talking about physical AI and people building robots. So we want to build a a channel, a portal between the Bay Area and Shenzhen Bay. So I think the because the economy, the talents are very complementary. The software is very strong, application, the venture capitalist is very strong in San Francisco area.

But in Shenzhen, we have all the engineering solid ground, supply chains. So it’s very naturally complementary to each other. But how do we shorten the distance? Not only hosting people flying from San Francisco, but we should go to the Bay Area to really sharing what’s already out there to help people to build the hardware easier. So they don’t need to raise a lot of big chunk of money to build something. We can go to the front end and the one button to get things made. So that’s our strategy to do that. And the US is still the biggest market.

And we have a lot of friends, relationships, but we need to have a mechanism to fasten the connections.

Michelle Sun (21:56) Yeah, save a lot of flights for for your customers. Exactly. Twenty years from now, when someone writes the history of how physical AI is done and what role do you think Shenzhen would play in that history?

Eric Pan (21:59) Yeah. Yeah.

I guess Shenzhen should be the biggest incubator for all the hardware. But it’s not incubating for Shenzhen teams only. It should be an incubator for the global teams. So what are we envisioning twenty years from now is not a one gen company in China conquers the world with their products. I don’t think that’s the most reasonable way. It should be teamed from all over the world. They come to Shenzhen, maybe work with us, maybe not. To build their stuff for their own like a business, for their own people.

They control all the like data or the models or the supply chains. So the this should be used as a service. And we s we from fifteen years ago we’re keeping advocating is innovate with China. It’s not made in China or made in the States. It’s a it’s already like a hybrid very one piece of the industry. It’s closed supply, but we should be more open. And at least the city is doing the all the opennesses and we are just trying to

Michelle Sun (22:59) No, it’s a close partnership.

Eric Pan (23:08) contribute our parts and for people to choose I need this or not.

Michelle Sun (23:12) Thank you, Eric. This is great.

Thanks for reading Core Matter! This post is public so feel free to share it.

I’m speaking at Autonomous in SF this week! Check out the event if you are in town.

AUTONOMOUS is a one-day premier conference on the future of robotics and physical AI, taking place July 16th in San Francisco. It brings together 500 founders, engineers, investors and operators who are actually building and funding the industry, across two stages and four content tracks: Physical AI Frontier, Humanoid Moment, Building & Deploying, and Capital Stack. The speaker lineup includes Deepak Pathak (CEO, Skild AI), Samir Menon (CEO, Dexterity), Jamie Shotton (Chief Scientist, Wayve), Paul Mikesell (CEO, Carbon Robotics), Ed Mehr (CEO, Machina Labs), Andrew Wooten (Co-Founder, Rhoda AI), and Russ Tedrake (Professor, MIT CSAIL), alongside investors from Khosla Ventures, DCVC, and Red Glass Ventures.Beyond the stages, the day includes dedicated networking during breakfast, lunch, and a happy hour reception, plus a startup showcase featuring some of the most exciting early-stage companies in the space. If you're building, funding, or covering the physical AI industry, this is the event to attend.