Core Matter Podcast

Michelle Sun
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Discussions with founders and operators on the full stack of Physical AI from components and supply chains to what actually deploys. corematter.substack.com

Episodes

  1. 1d ago

    What Tesla and Figure Reveal About Robot Hands

    In this episode, I speak with Scott Walter, PhD, Robotics Research Diligence Director at RoboStrategy. We started with Tesla and Figure’s opposing experiences with tendon-driven humanoid hands, then spent more than an hour pulling apart what a robotic hand actually needs to do. Scott is a mechanical and aerospace engineer, a 2-time robotics founder, and one of the sharpest public readers of humanoid-hand architecture. He has worked through Tesla’s hand iterations, Figure’s decision to abandon its first tendon-driven design, 1X’s routing choices, and the direct-drive approaches behind Wuji and Sharpa Wave. This was a particularly fun and wide-ranging conversation. We used three extreme designs to escape the usual tendon-versus-motor argument: Allonic’s braided structure, Daxo’s maximalist system with up to 120 tendons, and Tacta’s hydraulic hand, glove, sensing, and data stack. Tacta is especially interesting because it is designed as a complete manipulation system for cobots and industrial arms, without trying to fit inside a humanoid. The side paths were just as useful. Scott proposed a decathlon for humanoids, complete with pole vault, hurdles, baton exchange, and the same sand pit humans use. We also asked whether robots should copy human movement at all, and whether a general-purpose body still becomes specialized through its profession, as humans do. In this episode we cover: * Why Tesla and Figure reached different conclusions about tendons * What Bowden tubes solve, and what they add at the wrist * Why joint count and independent control are different metrics * What the Humanoid Games reveal about robot-specific movement * Scott’s proposal for a humanoid decathlon * What Allonic, Daxo, and Tacta teach at the design extremes * Why Tacta is building a manipulation system outside the humanoid * How generalized bodies can still become specialized workers Scott Walter: https://www.linkedin.com/in/scott-walter-ph-d-b2a78ab/ RoboStrategy: https://robostrategy.co/ Watch on YouTube: [YouTube URL] 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 Cold open: the labor prize and the 5-year forecast 00:24 The Fermi paradox of robotic hands 01:18 Tesla, Figure and the tendon debate 05:10 Bowden tubes and routing tendons through a wrist 11:15 Joints, actuators and real degrees of control 14:38 Why the pinky matters more than it looks 17:23 Humanoid Games as real-world robotics experiments 21:57 Scott’s humanoid decathlon challenge 26:28 Tesla’s hand iterations and abandoned designs 27:55 Wuji and Sharpa Wave put motors in the fingers 38:29 What 3 extreme hand designs can teach us 38:53 Allonic’s braided hand and portfolio disclosure 51:15 Daxo’s maximalist hand with up to 120 tendons 01:02:36 Tacta measures how workers use their fingers 01:05:18 A robotic-hand system designed outside the humanoid 01:13:12 Data-center cables as a tactile manipulation task 01:16:22 General-purpose bodies and specialized work 01:19:18 Why this 5-year robotics forecast may be different Below is the full transcript. There may be errors as it’s AI-transcribed. 00:00:00 — Cold open — excerpt montage Scott Walter · 00:00:00 That is the biggest pie we’ve ever seen, ever, trying to automate labor. And sim-to-real gap is almost zero. So locomotion is a solved problem. Humanoids will be deployed like five years after everyone stops laughing. And they’re the worst they’re ever going to be. They’re just going to get better and better and better. 00:00:23 — Why dexterous robot hands are still hard Scott Walter · 00:00:23 And what I call the Fermi paradox of robotic hands. If they exist, where are they? And that’s always been the problem: you see them in the labs and then you go around and you’re like: I’m not seeing them anywhere. No one’s able to do them. And the question is: why is that the case? It’s extremely challenging to come up with something that has not only dexterity, something you can control, but also robustness. But what I was seeing during the teens is that robotic hands were suddenly becoming a possibility because machine learning made it possible. Before then, they were just really, really hard to control. Scott Walter · 00:00:56 And that’s what the Shadow Hand proved: you can have this tendon-driven hand. And if you connect it to really good machine learning algorithms, you’d be amazed that you’d be able to do. [Review 0015] The problem was that the robustness wasn’t there, the cost factor, everything else. So that’s kind of the preload that we’re seeing it. [Review 0017] And why aren’t they becoming more and more available? Now, the big debate that is going on in hands in general. 00:01:18 — Tesla, Figure, and the tendon debate Scott Walter · 00:01:18 And so people really started paying attention to robotic hands when Elon announced a 22 DOF hand that was going to go on Optimus and the revealing of that and everything like that. And after that it was like this Cambrian explosion of just robotic hand designs all over the place and everyone pursuing different designs. And for the most part, you could break it down into two categories, tendon-based hands and non-tendon-based hands, which most people would say direct drive. But even there, you have to break them down because you can never really put things in two different buckets. Scott Walter · 00:01:52 They’re all going to go down there. But you can kind of look at it that way. And everyone’s pursuing it. And they all were very passionate about their designs and why theirs was the best approach. Some people would try one and they would kind of think about it again and then try a different approach. But about two weeks ago, Brett Adcock put out a post where he talked about the evolution of the hand designs at Figure and that the very first generation hand that they built was a tendon-based hand. And after attempting to do that he came to the conclusion that a tendon-based hand was basically an engineering dead end. Scott Walter · 00:02:24 And he called it the biggest engineering mistake he’d ever made. And since then, he’s been pursuing hand designs that are non-tendon-based. And that kind of caused, let’s say, a very spirited discussion. And I’m glad it was out there because you got a lot of people that were very much on the side of tendons just going out and just saying he’s completely wrong. From right down to saying it’s a skills issue to explaining why they believe it and their particular thesis for it. As well as you get a lot of support from other people who said, yeah, we tried tendons as well. Scott Walter · 00:02:55 It turned out to be really hard. Now, I’m not here to defend one position or not. I’m really here to maybe kind of present it to everyone so everyone can kind of come to their own conclusions because they both have their pros and cons. They both have the big engineering challenges in what they’re trying to do. And even within the tendon community, while they agree tendons the right approach, they will get in very spirited arguments about what’s the best approach or not. And you can see that 1X came out with their 22 DOF hand, I think. Michelle Sun · 00:03:25 I think it’s 25. Scott Walter · 00:03:28 Yeah, 20. [Review 0043] I think it’s actually 22, 44 tendons. It’s kind of hard to know the count. They’re also throwing the wrist in there. So I usually don’t put the wrist in there. But they have what you would typically say is about 22 degrees of freedom of movement of the fingers. Quite complicated design. 00:03:43 — Routing tendons through the wrist Scott Walter · 00:03:43 And the biggest challenge with all the hands is not having the tendons that can actually move the fingers and putting down the forearm, but figuring out how to get them through a wrist. The wrist isn’t in there. It’s an easier problem. I’m not going to say it’s easy. It’s not. But as soon as you do that you add this extra level of complexity that the engineering solutions are challenging. And bodies are fairly simple to model. But when we start getting into flexible stuff, there’s a lot of challenges. And we are doing it in our heads because we’ve been doing it for so many times that we know we can move our wrists and somehow keep our fingers constant. Scott Walter · 00:04:19 But if we’re not doing that we will see that our fingers will kind of move as we are moving our wrist just because the length is changing. Now, in theory, you can solve the problem by having all your tendons go right through the center of rotation of your wrist. Okay? In theory, you could do that. The reality is there’s something called, I think it’s the Pauli principle. Two particles cannot occupy the same point in space at the same time. So you need room. It’s like you’re talking about before tendons. [Review 0067] They can’t all occupy the same spaces. Scott Walter · 00:04:51 So when they go around there, there’s just always going to be that. And then there’s this other problem is that when you’re doing it, sometimes if the tendon’s coming straight up and you’re going, that means suddenly you have to do this very sharp angled turn. And tendons do not like sharp angled turns. You need to have a kind of radius in there. So there’s big challenges to being able to do that. And there’s different schools of thoughts on how to do it. And there’s this thing called a Bowden tube. And everyone’s like: whoa, what’s that? Michelle Sun · 00:05:15 Is that what 1X is? Scott Walter · 00:05:20 Yeah, they’re using the Bowden tubes. And basically, if you’ve ever ridden the bicycle and look at your brakes and the brake cables, that outer tube on the outside, on the inside is a wire, which i

    What Tesla and Figure Reveal About Robot Hands

  2. Sep 4

    The Hand That Wouldn't Quit: Inside Prensilia's Grip on Durability

    Prensilia says its Mia hand survived 300,000 grasp cycles at full grip force in company testing, closing in 280 milliseconds. Francesco Clemente, Managing Director of Prensilia, walks through why fingers fail before motors and gears do, why the company left tendon-driven transmissions for rigid linkages, and how it prices a 3-motor hand against lower-cost competitors. The company puts its Mia hand at $10,000 to $15,000 and its bill of materials at roughly 35% motors and close to 70% mechanical transmission and frames, by its own count. What we cover * Why fingers break before motors or gears in a robotic hand * The move from tendon-driven transmission to rigid linkages in Prensilia’s product line * A 300,000-cycle grip force test protocol and what it does not tell you * Underactuation, degrees of freedom, and degrees of actuation explained * Bill of materials breakdown for a 3-motor dexterous hand * Customer mix across research, prosthetics, and industrial buyers * Manufacturing scale from hundreds of units a year toward volume production “Fingers are the parts that break the most, because you have impacts with objects, you have unexpected movements from the robot.” — Francesco Clemente, Managing Director, Prensilia “We are talking about thousands of cycles, not really millions of cycles, with the tendons.” — Francesco Clemente, Managing Director, Prensilia “The motors account for maybe thirty five percent, more or less, of the total cost.” — Francesco Clemente, Managing Director, PrensiliaFrancesco Clemente on LinkedInPrensilia WebsiteWatch 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 hereChapters00:00 Francesco Clemente, Managing Director, Prensilia02:22 Prosthetics and research customers04:46 Broken hands and reliability07:09 Loaded versus unloaded cycle testing11:59 Failure modes in fingers, gears, and motors14:19 Motor heating and cooling16:42 Tendon maintenance and anchoring21:26 Weight and robotic-arm payload23:48 Degrees of freedom and actuation26:14 Underactuation and adaptive grasping31:01 Motor current, torque, and heat33:29 Grasp taxonomies and motor count35:52 Abduction and hand design38:17 Tactile sensing40:38 Bill of materials and actuators45:22 Industrial use cases50:04 Competitors and grippers54:42 Manufacturing scaleCore Matter is an independent research practice covering the physical AI value chain Michelle Sun: Fingers are the parts that break the most. And that connection is a weak point that is gonna break. The motors are bottlenecked, and having a lot of motors inside of a small volume, it’s easy to look at spec sheets, but you have to understand that Francesco Clemente, managing director of Prensilia. Prensilia builds robotic hands out of Pisa, Italy. It’s fun out of set and in a school of Advanced Studies in 2009. Started off in prosthetics, today their hands are on humanoid robots, factory arms, and human wrists. Prensilia’s Mia hand runs three motors, closes in 280 milliseconds, which is faster than a human hand, and has survived 300,000 cycles at full grip force in testing. It sells for $10,000 to $15,000 compared to the Chinese hands at 5k. On the spec sheets, the Mia hand might look overpriced and under threat. What they’re seeing in order volume says something different. Today we’ll talk about what’s on the ground in the dexterous hand markets. Francesco, welcome to the show. Prensilia is 17 years old today from 2009, and you are a spin off from Sant’Anna, started way before robot hands were cool, and definitely before the humanoid boom. So what did the company look like in 2009 and who paid the bills before humanoids existed as customers? Francesco Clemente: Yes, thank you very much for having me today. I’m very excited to be here. The company, Prensilia, was founded, as you said, by researchers of the artificial enzy area that were working at the BioRobotics Institute of the Sant’Anna School of Advanced Studies. They were already working as a researcher to on the development of robotic hands and they were using developing those tools for their own research needs. Then other researchers that they were collaborating with started asking for accessing those tools, and basically here it how it came the idea to spin off a company in order to allow other researchers also to use these devices that were developed in the lab. So the first customers were really other researchers, so universities and research centers around the world. And that let’s say research background is still with us. So today we are still working, collaborating a lot with research centers, and this is also one of the reasons why we have the specific versions of our robotic hands for research activities. Michelle Sun: That’s amazing. And so the Mia hand came out of a prosthetic. How is the medical version similar or different from the robotics version? Did you have to change anything for the robotics customer? Francesco Clemente: Yes. Apparently robotic hands can be used, let’s say, for prosthetics as well as for robotics today, but these two worlds are relatively different because you have very different specifications from one market to the other one. For instance, in prosthetics, you have a very clear bottleneck on the ability of the person to control the prosthesis. So you have a certain amount of degrees of freedom of movement that the person can control in a reliable way, so it doesn’t really make a lot of sense to have a 20 degrees of freedom robotic hand that can do any gesture, because the person cannot control that complexity. On the other side, you are also limited by the weight and by the size of the device. Of course, besides prosthetics, you have specific sizes in prosthetics that you try to match. That is like small, medium, and large, I would say. The prosthesis has to be that specific size, it cannot be any size. So today we see robotic hands that have very different sizes, because of course you attach them to a robot, so it’s not super important if the robot itself and the robotic hand match in size perfectly, let’s say. But this is very important in prosthetics. And of course another point is weight, because the person has to actively carry the prosthesis. The comfort is very important in that case, so you cannot really have a prosthesis that weighs two kilograms, because the person will be tired after one hour, let’s say, of using the prosthesis. So you really have to go down in weight in order for the prosthesis to be comfortable. Michelle Sun: When we first spoke, you mentioned that at ICRA in Vienna earlier this year, people have been showing up at your booth carrying broken hands from other vendors. Tell me that story again. What had failed and what were the customers looking for? Francesco Clemente: Yes, so we were at ICRA and we were meeting a lot of people at our booth. A lot of them were researchers or engineers from companies that were looking for robotic hands. And some of them were saying, okay, we are looking for robotic hands that are robust, that can be used also outside of the lab, because we were trying some other hands from competitors, but they didn’t work. We bought them because of the low price, but then we realized basically that they were not reliable for what we were going to do. So I think that this summarizes a little bit what the status of the market is today, because there is a lot of competition, a lot of hype around robotic hands, and everyone is really working on these devices, so the demand is going higher and higher, but people are somehow approaching these devices for the first time. So they don’t really also don’t know exactly how to use them, what are the specs that are important. I mean, it’s normal, because these devices are complex. And for us that are working in the field since more than fifteen years, it’s clear what you are going to look at. But as you said before, robotics and also prosthetics was, let’s say, a niche market for robotic hands in particular a few years ago. Now everything is exploding, so people have to be accustomed also to understand the specs and what they are getting for the money. Michelle Sun: I wanna double click on the point you make about there are things that are not on the spec sheets, right? So there’s degrees of freedom and you can also see the comparative price pretty easily. You tested Mia to three hundred thousand cycles at full force. Walk me through that protocol, because 300,000 loaded cycles and a million unloaded cycles are very different claims, and on the spec sheet it’s not easy to distinguish. Yeah, talk me through how to read through the spec sheets more efficiently and tell the differences between different hands. Francesco Clemente: Yes. One thing that prosthetics has taught us is that we want to develop a robotic hand or a prosthesis that then can be used outside of the lab by patients and users. And also engineers, it has to be robust. Okay, so it’s easy to look at spec sheets that basically report the number of degrees of freedom, which is the kind of measure of the dexterity of the robotic hand that you’re buying, and everyone is looking into that today because they’re looking into fine manipulation protocols and solving manipulation at a higher level. And of course you want to have something that is similar to the human hand in terms of movements that you can perform, but you have to understand that that comes with a cost associated. So the device becomes very, very complex. You either have a very bulky forearm that hosts all of the motors, with tendons that drive the fingers and the joints, or you have very small motors inside of the hand, inside of the joints of the fingers. And this means that the performance will have to be low because of the size of

    The Hand That Wouldn't Quit: Inside Prensilia's Grip on Durability

  3. Aug 26

    Why America Still Picks Fruit by Hand: Farm Labor, Field Robotics, and the Economics of Agricultural Automation

    In this episode, I speak with Danny Bernstein, CEO of Reservoir. American farms advertised more than 400,000 seasonal positions in 2025 and received 182 domestic applications. That number sits underneath every agricultural robotics company raising money today.Danny spent close to 20 years in Silicon Valley. He was part of a startup that sold to Google, spent ten years at Google, and two years at Microsoft, before turning to the question of why the physical world has so few technical communities around it.Reservoir runs Reservoir Farms, 40 acres of working commercial farmland in Salinas where robotics startups test machines on real crops. It opened in March 2026, followed a month later by a second site in Sonoma County carrying 15 acres of Pinot grapes. Monterey County filed $4.82 billion in gross agricultural production value for 2025, and the farm sits within driving distance of Driscoll's, Taylor Farms and Dole Vegetables. In this episode we cover: * Why fresh produce still has no automated harvester * The labor math underneath agricultural robotics * Physics that replaces chemicals, and vision that reduces them * What actually breaks a machine in a field * The two-year payback every agricultural machine has to clear * Who manufactures and services these machines * Turning farm jobs into ag tech jobs Danny Bernstein on LinkedInReservoir Farms WebsiteWatch 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 * 00:49 Danny Bernstein, Reservoir, and a technical community for agriculture * 00:49 Silicon Valley builds seven of everything, agriculture waits for one * 03:15 Driscoll’s, Taylor Farms, Dole, and a $4.8 billion county * 05:29 Not AI for luxury, and the three gaps worth building into * 05:29 Precision surgery by robot, fruit picked by hand * 07:50 400,000 advertised farm jobs and 182 domestic applicants * 10:11 What actually breaks a machine in a field * 12:36 Sonoma, and the plan to cover the top ten specialty crops * 12:36 Washington, tree fruit, and the Cosmic Crisp patent * 14:58 Two years to return the cost of the machine * 17:14 Service teams, dealers, and Andros Engineering * 21:50 Merced College, and building on a teaching farm * 24:12 YC gives you tokens, Reservoir gives you a tracto We are performing precision surgeries using robots, but we still hand harvest fruit. And there were over four hundred thousand of these jobs that were posted in twenty twenty five and only a hundred and eighty-two domestic applicants for those positions. These are jobs that Americans are simply don’t want to do sitting where you’re at today, what are some biggest gaps that you’ve seen that you wish more people are building? And not AI for luxury or AI’s for abundance, but it’s really AI for resiliency. Why combinator gets a million dollars in tokens from Oken AI, we get access to a tractor. Danny, welcome to the show. Thank you, Michelle. This is super fun. Thanks for coming out to Salinas. Yeah, I know this is a great day to be out here. So we’re out here, Salinas, 24 acres. 40 acres. 40 acres of you know, like different machines running on the field. So take me back to where this idea first started. Yeah, so Reservoir is a technical community for agriculture, and that’s kind of a new thing. And and so what inspired me is that I actually spent close to 20 years in Silicon Valley. How impactful technical communities were toward accelerating big discoveries. And you’re in San Francisco and there are technical communities kind of everywhere, whether it’s Y Combinator or around UC Berkeley, around Stanford. And I started to study basically how were technologies developed for the physical world where these technical communities may not exist, and we have significant technical opportunities in areas like agriculture or forestry or land management. But like where are the startups and how do they connect with each other? And that is like the, you know, 30 second version of kind of how we came up with this idea, which is what if we built like the most robust technical community around Ag and what if we did it in the most important growing region, Archieville, in the United States? Tell me more about Salinas, right? How did you pick this part of California? What’s so special about it? Yeah, so I spent close to twenty years in Silicon Valley. I was part of a startup that sold to Google. And I was at Google for 10 years and I spent a couple of years at Microsoft. And what really defined my time in Silicon Valley was sort of the behavior of how Silicon Valley developed products, which is one company comes out with a thing, and that thing is the new thing. Let’s say it was Zoom or it was quad code or whatever the first thing is. And then every company basically comes up with their version of that thing. And they basically are competing around what is essentially a solve problem. And then if you flip it around basically and you look at what are the areas that don’t have that kind of activity, where you don’t have seven companies competing to solve one challenge. And agriculture is like that, where we have a bunch of really significant gaps in technology. And we’ll talk about it. But like an example would be automated harvest for fresh produce. Simple idea. Automated harvesters, automated robots for harvest, specifically in fresh produce where the output is more delicate. We have practically no solutions. So you contrast that with Silicon Valley, where they’re like seven different ways to vibe code or seven different ways to do video calling, or seven different ways to message someone or email someone, right? We have an abundance of solutions we have to choose. You flip that around and you look at an area like agriculture where you don’t have that abundance. So we started calling it technology as resilience. And then if you look at basically agriculture in particular, and you were to hone in on fresh produce. which is on micronutrients supply, like our most valuable calories are our micronutrients. And that’s fresh produce. And Salinas ends up being really the fresh produce capital of the United States, if not the world. Yeah, so Monterey County is a five billion dollar ag economy and Salinas is really the center point of that. So where we’re sitting right now, we are within driving distance of the headquarters of Driscoll’s, of Taylor Farms, of Dole Vegetables, all these like incredibly massive vegetable and fruit production companies. So where do you build the technical community around those products? You do it here. So you’re really in the backyard of all these like the center of all these different agricultural powerhouse. When you talk to like companies like Drisle or, you know, even John Deere that is like in the space for a long time, like how do they view like ArcTech and the autonomous wave that’s coming to this industry. Yeah, I mean they view it like a imperative, like it’s a must happen. It’s not a nice to have, it’s a must have. And it’s because of labor and input related costs. So chemicals, inputs, fertilizer, all the sort of ingredients of farming are becoming more expensive and more regulated. And then the labor of of agriculture is becoming increasingly expensive and scarce. We cannot pack each of those. And so then they basically view technology as the only way out of those challenges. There isn’t really an alternative to technology. We’re not going to suddenly have millions of people who want to get into farming. It’s not going happen. We’re not going to suddenly have a pipeline of new chemicals that are going to be better than what was previously there because of anything we have more and more sort of chemical resistance in our crops now. And we haven’t had significant novel new solutions in chemistry come into ag in a very long time. It’s like something like two in the last thirty years. It’s the view of growers, of operators, of agribusinesses, even of communities, that technology is essential. And so it’s viewed as one of the areas of AI that are not AI for luxury or AI sort of for abundance, but it’s really AI for resiliency. And that’s a different story altogether. And you mentioned about how there are so many gaps in you know, how AI is solving in agriculture. It’s different from like vibe coding, having different so many different ways to play around with that. Tell me more, setting where you’re at today, what are some biggest gaps that you’ve seen that you wish more people are building? Yeah, sure. So I we really put them in three categories. The first is using physics to replace chemicals. The second is using AI or machine learning or vision. to reduce chemical use, basically more targeted application of chemicals. So chemical replacement, chemical reduction. And then the third one is automating the jobs that nobody wants to do. And we have a lot of really hard jobs in agriculture right now. So we’re in Salinas, it’s about 70 degrees today. But if you drive two hours east to the Central Valley where we’re in the middle of harvest or kind of in the middle of tree fruit harvest, it could be 105 today. We do not have any automated harvest technology in Stonefruit. We hand harvest peaches, we hand harvest table grapes. All of those sort of incredible fresh produce items require hand harvest still in 2026. we are performing precision surgeries, you know, using robots, but we still hand harvest fruit. Those are the three categories. Physics to replace chemicals, AI, sort of machine learning and machine vision to reduce chemical use and automating the hardest-to-fill jobs. Remember hearing a case where, you know, with these harvests. being so such a labor intensive and still dependent on like human going onto the field is actually pretty

    Why America Still Picks Fruit by Hand: Farm Labor, Field Robotics, and the Economics of Agricultural Automation

  4. Aug 11

    Giving Physical AI the Sense of Touch: Tactile Sensing, Humanoid Dexterity, and the Future of Automation

    What is tactile sensing in robotics? Tactile sensing converts physical contact into data a robot can use. In GelSight's vision-based approach, a camera reads how a soft surface deforms and produces detailed information about contact geometry. What is holding robot manipulation back? In this conversation, Youssef Benmokhtar argues that the bottleneck is both hardware and data. The field has not converged on a standard sensing technology or shared model, which makes tactile data harder to combine at scale. In this episode, I speak with Youssef Benmokhtar, CEO of GelSight. Tactile is on the edge of innovation for robotic dexterity. It’s the sensory bridge between computer vision and physical AI. Youssef has extensive experience in imaging, optics, and scaling sensor businesses. He held leadership roles at semiconductor and photonics leaders like STMicro, OmniVision, and Magic Leap before taking the helm at GelSight in 2021. GelSight, headquartered in Waltham, Massachusetts, is a spinout from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL). The company also partnered with Meta FAIR to open-source Digit 360, a fingertip-shaped tactile sensor in 2024. In March 2026, GelSight was awarded a Phase II SBIR contract with the US Air Force to develop a miniaturized, rugged “digital fingertip” tactile sensor for intelligent robotic grasping. As robotics move beyond locomotion to dexterity, high-resolution touch intelligence is increasingly critical for manipulation, maintenance, and hazardous industrial operations. GelSight describes itself as digitizing the sense of touch. We talked through: * The transition from vision to tactile intelligence: How digitized touch follows the same trajectory of visual optics and audio into trillion-dollar industries. * Building a data-rich platform: Transitioning GelSight from a standalone hardware sensor to an integrated platform offering software libraries, cloud data analytics, and modular hardware architectures. * Open source vs. proprietary software: The strategic rationale behind collaborating with Meta on the Digit sensor, seeding the academic research ecosystem, and standardizing tactile data for physical AI. * The bottleneck in humanoid dexterity: Why manipulation needs an “ImageNet for Touch,” how platforms like NVIDIA Isaac enable Sim-to-Real translation, and how fine tactile resolution unlocks true superhuman precision.Navigating deep tech hardware strategy: Managing custom form factors, avoiding hardware commoditization, and setting clear ethical boundaries for robotics in defense and industrial automation. Follow GelSight here: https://www.linkedin.com/company/gelsight/ | Website: https://www.gelsight.com 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 - What is tactile sensing in robotics? * 03:37 - How do you commercialize MIT research into industrial applications? * 06:30 - What is a tactile intelligence platform? * 08:46 - Is tactile data or sensor hardware the main competitive advantage? * 13:56 - Why open source tactile sensors in robotics research? * 19:07 - Why is tactile data the primary bottleneck for humanoid robot dexterity? * 23:09 - How is the defense sector using tactile sensors for humanoid maintenance? * 25:45 - How do deep tech hardware companies avoid commoditization? * 30:41 - What are the ethical boundaries for robotics and military applications? * 34:13 - When will tactile sensing reach a commercial tipping point in AI? GelSight CEO Youssef Benmokhtar on why industrial surface metrology, not robotics, pays the bills; why open-sourcing DIGIT was Meta’s call and is now under review; and why he expects no single tactile foundation model. You’ve literally visualized touch world has completely changed once vision was digitized. We focused on a vision of being the ubiquitous tactile intelligence company. I think we’re basically at the tipping point. We’re almost there. My guest today runs a company trying to digitalize the sense of touch. GelSight started as a camera-based sensor invented at MIT. Press it against the surface and it reads the geometry down to a single micron. fine enough to see a fingerprint. For years that lived in industrial inspection, checking aircraft skins and machined parts where a flaw isn’t an option. Youssef Benmokhtar took over as CEO in 2021. He’s not a roboticist. He came from imaging and optics Magic Leap OmniVision STMicroelectronics. A career spent turning sensors into businesses. His bet is that touch is the missing sense in robotic and GelSight’s job is to become the tactile intelligence layer, not just the sensor. Today, we’re going to talk about what it takes to give a machine a sense of touch, who pays for it, and where the value lands. Youssef, welcome to the show. Welcome, Youssef. Super excited to have you on. Thank you, Michelle. We’re glad to be on. So you came from imaging and optics, Magic Leap, OmniVision, STMicroelectronics. What did you see in tactile sensing back in 2021? You know, I always been in tech. I love tech. I’m curious by nature. Uh always loved innovation since my first uh role at STMicroelectronics. And when I got the privilege of meeting the uh GelSight co-founders, I had one of those other moments of, wow, this is so cool. Uh you’ve literally visualized touch and you digitize human touch. That realization, you know, just got me so excited about the potential of what you can do once you digitize human touch. I think the the decision to join the team and try to do something with the founders was u a natural decision. It was very fast. I was really attracted by the possibility to grow a business around digital touch. The potential for me is enormous because I had in mind based on my imaging background a really clear understanding of how the world has completely changed once vision was digitized. And you can say the same thing about when audio was when sounds right was digitized. It basically changed the way we live. It created a trillion dollar plus economies. It allowed for you know cameras to be embedded into phones into uh a bunch of things. You know we’re we’re talking through one of those digital cameras right now. And when I met the team here, I thought maybe we can do the same thing with touch because really literally at the time you know before GelSight technology was invented there was no real digital touch out there. There were a lot of analog touch you know solutions but not a real digital touch and being vision based you know visual tactile sensor you know for me was more um you know even made it more attractive right because I I understand vision and I understand how the world has learned to leverage images and videos to create you know additional value through the analysis of those of that data and I thought you know having a digital based tactile sensor we’ll be able to leverage that existing baseline of talent out there that knows how to use computer vision and AI to analyze data. It was a really easy decision to join in 21. Yeah, I can definitely see that connection of the dots there from vision to a vision based tactile sensor when you took over a CEO seat in 2021. In order to commercialize GelSight further from a lab technology to various applications, what changes did you need to make from how the company think about customers, what to focus on and what to build next? Yeah, I think when I joined the company, what we had at the time was technology validation. We knew the technology worked. This was the work that was started at MIT and continued and refined at GelSight by the founders and a small team they had at the time. I knew I didn’t have to do anything about proving the technology works. What we definitely needed to do is where is the product market fit? Where is the technology can be applied today. There’s always been this this love story with robotics since the very beginning because obviously when you think about digitizing touch the first thing that comes to mind is well can I use that now to have make machines more intelligent and more capable you know handling objects and doing things like that. But the reality is digital touch has a lot of potential and the initial traction that we saw was more on the industrial market where our technology was a really good fit for uh surface metrology. So our focus initially was okay in order to pay the bills we have to grow this industrial market. We basically started to move towards confirming product market fit in industrial market. that has proven to be successful and now we’re more into that growth phase where you know we have a real product, real customers, growing demand and that’s that’s going really well. Now our our love for robotics has not gone away and I know we’re going to talk about it at length today but we launched GelSight Mini and we collaborated with Meta on DIGIT exactly because we do believe that tactile sensing has a major role to play in robotics and especially for humanoid robotics and you know we had to find a way to be an actor in a very nascent industry. When you look at when GelSight Mini was launched, there were not all the big companies we talk about today in the human world that are raising, you know, insane amounts of money. We had to think about a strategy there in robotics as well, even if at the end of the day, what pays the bills more the industrial business. Yeah, for sure. You guys are definitely in a very unique position where you have that baseline covered with the industrial application and this is a wedge that you guys have always owned and then now there’s this new wave in terms of robotics and humanoid robots that are rapidly taking up these demand for tactile sensors. In 2022, you reframe GelSight

    Giving Physical AI the Sense of Touch: Tactile Sensing, Humanoid Dexterity, and the Future of Automation

  5. Jul 29

    Who actually flies to Shenzhen for robot parts, and what each of them wants

    In this episode of Core Matter, we covered how Europeans, Southeast Asians, and Americans behave differently when they come to Shenzhen, where demand is concentrated in the physical AI supply chain, and why a German robotics company moved R&D to Shenzhen. 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. Chapters00:00 - 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 FAIRPlus organiser Jasmine Bai on what American buyers actually come to Shenzhen for, and why component makers take roughly 70 percent of exhibitor count against 20 to 25 percent for whole-robot firms.majority of them will agree that they have to work with China it’s not a question anymore the next question is about how to cooperate with China what about the Americans like what do they come to FAIRPlus for? most of them just come and have a look components company take 70% 20 to 25 is whole robot 500 companies 60,000 visitors FAIRPlus is the largest physical AI exhibition in Shenzhen it covers the full stack hardware software and the supply chain behind it this year the most number of international attendees come from the United States Europeans and Southeast Asians came to buy hardware Americans came to talk Jasmine Bai runs the international side of FAIRPlus she sees who flies in and why we’ll find out what the world looks like from her seat Hi Jasmine, thank you so much for taking the time today yeah, thank you you run the international side of FAIRPlus the people who fly in the people who speak so can you walk me through how this job actually what you actually do and who are you trying to get into the building yeah, a lot of people will ask me because if I in charge of exhibition it’s only take three days per year what I’m doing the rest of the 300 days actually a lot of work beforehand to put everyone come at the same time and communicate for a specific topic for example for FAIRPlus we want to invite all the robotic related professors investors robot developers to come to Shenzhen during three days and they can meet what the people they want to meet and talk with people they want to talk so actually my main job is go to study each market and try to find the key person invite them to come to Shenzhen and also let them to bring more people more companies or more friends to come together this year is the second year that you run FAIRPlus how many exhibitors, how many visitors and how many came outside of China so last year was our first edition of FAIRPlus we have 210 companies because we only have six months preparation so last year was majority from China side so from last April to this April we have whole year to do the international promotion so our exhibitor number grew to more than 400 and for our visitor is 60,000 visitors come to FAIRPlus and among is 3,000 are from international visitors and they are from 100 countries and a very interesting is number one is from America not number one is like top 10 American, Germany Singapore Korean, also Holland all countries are very focused on robotic currently so when you saw the final visitor breakdown what was the most surprising thing for you yeah, actually it’s what I told you Americans visitors is really a lot because so far actually because FAIRPlus is co-organized by Shenzhen Robotics Association in the Messe Stuttgart, and Messe Stuttgart is a German company so we have a very good resource in European side and Shenzhen Robotic Association has a very good relationship in China about robot industry and also Messa Stuggart have very good office in Southeast Asia so actually you can know actually America is somehow we are not very good at so but in robots and AI industry actually America is very leading in this industry so actually from very beginning both of us said okay we apart from using our own very good resource we need to focus on American American side to do promotion and try to figure out how to influence the industry also we found it’s a little bit hard because it’s a very far from China to fly here and also the community is a little bit different and America had their own community to develop their own robot AI actually we work very hard but we don’t know the result so the result really surprised me that America is the No. 1 country from our international visitors part so that also gives us a lot of confidence that in the future we can do more in this side and find out what’s their interest and how can I help them to do more you see where all these visitors come from each of them and when a European and Southeast Asian visitor come what are they here for and what about the Americans like what do they come to FAIRPlus for? actually we know more about European Southeast Asia and European companies majority of them knows they need work with China for the supply chain actually when we do international promotion for FAIRPlus we highlight more about hardware cooperation because it’s non sensitive part and everyone should use it no matter you are do robot or AI you need some hardware and it’s no doubt that China is the best on manufacturing and production chain and also for robotics side actually Shenzhen is very good at that so everyone agree with the concept that they need to come to Shenzhen to find their partner for a hardware side and majority of Europeans very clear know they need supply chain partner here in Shenzhen that’s the key reason they come for Southeast Asia they want to buy more clear they want to some robot and bring back to like Malaysia, Thailand they are very interested to have some robot back to their country and resell it so it’s very clear the both part where the needs is so actually we do a lot of very matchmaking or targeted event to bring both side we select the Chinese company who can help the European or who can work with European side somehow work with Southeast Asian countries so we organize some small events to help them to matchmaking then they can go deeper to cooperate but to be honest for American side so far we haven’t find some like very specific things even we have a lot of visitors I think most of them just come and have a look but it’s a good start after they come and have a look they understand the industry I think they will come up with more ideas what they need to do yeah, so it’s more of a educational tour for some of these visitors and they’re still exploring the use case and how to work with the Shenzhen partners you also mentioned that this year there are different pavilions and programs for different countries and there wasn’t an American program tell me more about that like what’s the story behind was the American conversation just happening in a different level I think markets are different like what I said Europeans, southeast Asian and Thailand they are more clear about their position in this industry how they can work with China of course some the majority of the idea from associations or our government partners or industry leaders from European or Southeast Asia they think in this way and they lead the topic of course not every company may follows but majority agree with this concept so they follow the rule to come and they benefit from it of course some of them also have different idea I think American say they, I don’t have their own idea so far I also talk with the visitors and why they come and so first time and for the ones who first come to China they are super impressed by the how it’s working here because actually America also very good at robots so they have their own supply chain their own system to run it sometimes they don’t have to go abroad but when they come

  6. Jul 14

    How Shenzhen actually works, a ground-level primer with Seeed Studio founder Eric Pan

    Hi all, I’m excited to share the first episode of the Core Matter Podcast. This one was recorded live in Shenzhen during my trip back in June. 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 w

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About

Discussions with founders and operators on the full stack of Physical AI from components and supply chains to what actually deploys. corematter.substack.com

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  • Creator
    Michelle Sun
  • Years Active
    2026
  • Episodes
    6
  • Rating
    Clean
  • Copyright
    © Core Matter
  • Show Website
    Core Matter Podcast