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Home > Disrupting Japan > What’s next for Physical AI in Japan?


	Podcast:		Disrupting Japan
	Episode:		What’s next for Physical AI in Japan?
	Category:		Business
	Duration:		00:00:00
	Publish Date:		2026-04-13 20:00:37
	Description:		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 the GrooveX. GrooveX is a company to develop a robot. Robot is L-O-V-O-T, which you may see in the website. It's kind of a small robot. We named the family type robot. Currently around the 18,000 units are working. Even we shipped just 21, a little bit more than 21,000 units, still 18,000 keep on working. This is very good for the retention, means churn rate of our robot is just 0.4% per month. So, we believe our robot is really good for the social implementation, but it's really different from the humanoid robot or dog type robot. And our aim is, how I can say, enhance the resilience of the people. It's completely different from other robot to improve the productivity. And the reason why I'm chasing this area is, I worked for the Pepper, which is a humanoid robot 10 years ago. And I learned a lot about the humanoid and also conversation between computer and the people. So, I wonder probably this area is also really interesting, but we can do something else for the non-verbal area. Then that was the reason why I associated company 10 years ago. Before I worked for the Pepper, I was an automotive industry. So, I worked for the aerodynamics or product planning. Sometimes I worked for the Formula One in Germany or product planning in Belgium 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 is several understanding, but for me, a robot working in the open environment could be the one, how I can say, important point. Because before a robot is working in the designed condition, controlled condition, like a factory or some certain area. But for example, our case, a robot is shipped to somewhere else, sometimes overseas, and we never know what kind of environment it is. But still, a robot has to keep working. So, our robot daily active user is really high, over 90%. And it means a robot can adapt to the environment somehow. So of course, it's better to use AI, but sometimes AI is not mandatory, but AI have more potential to adapt to more environment. 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 robot have to have a capability to adapt to any environment. So, humanoids look like that. I mean, you can dream. It's human shape. So, you can expect it could work like a human. So, that was a very good, how I can say, trademark for the physical AI. But actually, current humanoids is really different from the real, how I can say, the physical AI, which I mentioned, because they are focusing to the kinetics. So for example, you already see lots of movie, very great backflip humanoid. But all of the robots have an issue of the heat. You never see robot is working eight hours continuously. Because, you know, I worked for the Pepper, then I learned a lot about how motors are very sensitive. If you'd like to use a leg, leg have to have a motor's power. And motor is, how I can say, consuming the power and making the heat. So, all the demonstration, it's working for 10 minutes. Maximum 30 minutes. But after that, cooling down is getting important nowadays still. But for the future, of course, if all the technology solved, we can expect to have a robot which can work like a people. But before that, probably without leg. 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.
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