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Disrupting JapanStraight talk from Japan's most innovative founders and VCs Author: Tim Romero
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What’s next for Physical AI in Japan?
Episode 251
Monday, 13 April, 2026
I have a short in-between edition for you today. Last month at Venture Cafe's big global gathering in Tokyo, I had a chance to sit down on stage with two old friends of the podcast, and we talked about where physical AI is heading in Japan. This conversation is with Chiamin Lai, general partner of First Light Capital, and Kaname Hayashi, founder and CEO of GrooveX, the makers of the absolutely adorable Lovet robot. Chiamin is one of the most savvy physical AI investors in Japan, and Kaname has been pushing the boundaries of human-robot interaction for years. It's a fascinating discussion, and there's some wonderful insights about Japan's unique strengths and challenges near the end. But don't skip to the end. The whole conversation is great, and I think you'll enjoy it. Leave a comment Transcript Tim: Okay, thank you so much, and thanks for coming. We're going to be talking about Japan and physical AI today. And it was not that long ago that Japan was the undisputed leader in robotics innovation. And while some people claim it still is, that claim is highly disputed today. So, we're going to talk about where we are and where we're going. And we're going to start with some brief, brief introductions, so you'll know who we are and why you should be listening to us for the next 40 minutes or so. So, my name is Tim Romero. I've been in Japan for about a little over 30 years now. I've started four startups here of my own. I've done a lot of angel investing. I helped TEPCO and JIRA spin up their CVC units. I've taught entrepreneurship and corporate innovation at NYU's Tokyo campus. I ran Google for Startups here for about four years. And I run a podcast called Disrupting Japan, which is just a labor of love. I've been doing it for 12 years. It's interviews with Japanese founders and VCs about innovation and what it's like to be an innovator in a culture that prizes conformity. So please give it a listen. Chiamin: Hi, everybody. My name is Chiamin Lai. I'm a general partner of a VC fund here at First Light Capital. A little bit of introduction about myself. So, my parents are Taiwanese, but I grew up here in Japan and studied here and also work here in Japan. But then I actually, after working in Japan for a few years, I was in Europe and then had the fortune to join venture capital. So, it's about 15 years ago, which I think it's hard for you guys to believe at that time compared to today. And then decide to do startups. I was a startup operator in China and Japan for seven years and came back to the industry five years ago. And right now I'm actually the board member of Japan Venture Capital Association, as well as running up my own fund here in Japan. Quick introduction about the fund. We are running two funds right now in Japan, about 120 million US dollars. And we're focusing on early stage and investment thesis is mainly focusing on Japan's demographic challenge, innovation for startup. And what we believe is, or what I believe is physical AI could be a very, very good potential for Japan, especially under the label shortage. So, I'm very excited to have opportunity to talk to you guys today. Thank you. Kaname: Yeah. My name is Kaname Hayashi. I’m the founder and CEO of GrooveX. GrooveX is a company that develops LOVOT. LOVOT is L-O-V-O-T, which you may see on our website. It’s kind of a small robot. We call it a family-type robot. Currently, around 18,000 units are working. Even though we shipped just a little bit more than 21,000 units, 18,000 are still working. This shows very good user retention, meaning the churn rate of our robot is just 0.4% per month. So, we believe our robot has achieved social implementation. And our aim is to enhance the resilience of people. It’s completely different from other robots that improve productivity. And the reason why I’m chasing this area is, I worked on Pepper before, which was a humanoid robot 10 years ago. And I learned a lot about humanoid robots and conversations between computers and people. So, I thought probably this area is interesting, but we can do something else in the non-verbal area. That was the reason why I founded the company 10 years ago. Before I worked on Pepper, I was working in the automotive industry. So, I worked in aerodynamics or product planning. I worked for Formula One in Germany or product planning for the European market or something like that. That’s all, thank you. Tim: Excellent. And I want to emphasize, so they brought one of their Lovet robots with them today. And after the session, it's over there in the corner and it is absolutely adorable. I encourage you to go play with this thing. It's just, you'll see what I mean. It's just something different about that. But to kick us off, to make sure we're all on the same page, physical AI is a term that's thrown around a lot these days. It's a little bit of a trendy term, but to make sure we're all talking about the same thing. When you're talking about physical AI, what do you mean? How's it different from traditional robotics or IoT? Kaname: Right. Probably there are several understandings, but for me, a robot working in an open environment could be an important point. Because before the physical AI boom, a robot was typically working in a designed condition, a controlled condition, like a factory or some certain closed area. But for example, in our case, LOVOT is shipped anywhere, sometimes overseas, and we never know what kind of environment it is. But still, LOVOT has to keep working. The ratio of daily active users remains high, over 90%. And it means a robot can adapt to the environment somehow. Surely AI has big potential to adapt to more various environments, but using AI is not the purpose. Tim: Okay. Chiamin? Chiamin: Since I'm an investor, so I'm going to use through you different kind of words there. But so basically what I see physically AI right now, if you read a lot of news, people were putting physical AI equal to humanoid. And I have a totally different definition. For me, physical AI equal to the system, that the system will have see, thinking, and action. And everything needs to be automated. That's my definition of physical AI. What do I mean by that? Existing robots, as what Kaname-san was saying, it doesn't really actually understand the environment. That's one. Two is it doesn't have any action. When I say action, it doesn't necessarily mean that you need a humanoid to do the action. Action means that the machine, anything that can help you to finish the action. It could be picking something from the shelf. It could be holding your coffee, whatever. That's how I define physical AI in the personal level. But at the business level, you can also consider if you have a software, that the software can actually help human to do an action. That is also physical AI from my point of view. Tim: Okay. So, it sounds like we are in a surprising amount of agreement here. So, physical AI, it requires a certain amount of autonomy. It requires a certain amount of flexibility and the ability to deal with new and unprogrammed environments and situations. Excellent. It's nice when we agree. I think things are about to diverge. So, with that in mind, robotics in general, IoT are really well established. They're deep global markets. So physical AI, this ability to interact autonomously and flexibly, what are the new markets that this opens up? Why is this an important new development? Kaname: Basically, if we would like to use a robot in your home, then a robot must have a capability to adapt to any environment and stay always-on. So, humanoids look like they can do it. I mean, you can easily dream it because of the human shape. So, you naturally expect it could work like a human. So, that was very good as a trademark for physical AI. But current humanoids are different from the expectation, because they are focusing on a few tasks with precise kinetics. So, for example, you already can see lots of movies of very great backflipping humanoids, but all of the robots have an issue with heat for always-on. You never see a humanoid robot working eight hours continuously under autonomous control. While I worked on Pepper, I learned a lot about how motors are very sensitive. If you’d like to use a leg instead of wheels, the leg must keep supplying motor power to keep posture. The motors consume power and generate heat. So, in all the demonstrations, it’s working for 10 minutes or maximum 30 minutes, but after that, cooling down is still important even nowadays. But for the future, of course, all the technology evolution will solve these issues, and we can expect to have a robot which can work like a human. But before that, probably being without legs might be a better solution for most cases. Tim: But so, I mean, Pepper's a really good example, because that was fascinating technology that they couldn't bring to market, really. Boston Dynamics, kind of facing the same problem. They're developing this amazing technology, which has some of the most viral YouTube videos. But it's really hard to bring a product to market beyond kind of a proof of concept stage. So physically, I mean, what are the markets that are opening up for this? Are we looking at healthcare? Are we looking like home helpers? Chiamin: So, I know where you want to head into. So, because all of you pop out in the tech industry, so I kind of want to give you a kind of overview. I don't believe the physical AI will be such popular if we don't have a chat GPT, if we don't have a transformer. So basically, the momentum change is in 2020 to 2023 after ChatGPT. And what does that mean? And everybody today using LLM to do your work. And a lot of developers are using LLM to develop your code. That also means software become commodity. I know a lot of you reading like X, you know that SaaS is dead, software is dead. I think one thing what I want to say before I come back to your question is,
