Artificial Intelligence makes a lot of people nervous. That’s understandable.
Today we sit down with Ken Fujiwara of Hacarus to discuss why that is, and what this startup is doing to fix it.
As in so many other fields, when comparing AI in Japan and the West, we find that the technology is fundamentally the same, but the social attitudes and business strategies are very different.
Ken is a serial entrepreneur, but running an AI startup was never part of his original plan. He had bigger goals in mind, and we talk about how he plans to pivot back to them someday.
We also discuss Kyoto’s booming startup ecosystem and why one CEO has publically stated he wants to destroy it.
It’s a great conversation, and I think you’ll enjoy it.
- The problem with Deep Learning and how Hacarus is unique
- The importance of founder’s hidden failures
- Why Ken left Sony to start a startup
- How to know when you need to pivot
- Why pivoting is hard in Japan
- The integrator business model and why it works in Japan
- Pivoting a startup to back to your dreams
- The importance of explainable AI
- Why you need to know about Kyoto startups
- Why one company wants to destroy Kyoto’s startup ecosystem
- The reason you see so many interesting IoT startups coming out of Japan now
Links from the Founder
- Everything you ever wanted to know about Hacarus
Follow them on Facebook
Connect on LinkedIn
- Get in touch by email: [email protected]
Welcome to Disrupting Japan, straight talk from Japan’s most successful entrepreneurs.
I’m Tim Romero and thanks for joining me.
As you can imagine, I get asked a lot about how the Japanese startup ecosystem is different from others and I love that question.
The problem is that people usually aren’t really happy with my answers. It seems that everyone wants to hear stories about anime or strange gadgets, or cool trends in gaming, and yeah, there’s plenty of that in Japan too, but the things that are really unique and interesting like evocative machines and the integrator model, and the role enterprise has to play in supporting startups, those things take a lot of time to explain to anyone who doesn’t already understand Japan, at least a little bit, but they’re important.
Today, we sit down with Ken Fujiwara of Hacarus and we’re going to look at how Hacarus is using the integrator model to jointly develop AI products with large enterprises. Ken also explains how he had to pivot Hacarus away from his original vision and how he might be able to pivot back to it in the future. We talk about the challenges of pivoting and staying true to your mission, cover a few very good reasons why people don’t trust AI, and we talk about one CEO who has made it his mission to destroy a startup ecosystem.
Oh, and near the end of the show, we have a really interesting discussion about the startup ecosystem in Kyoto. There really are some amazing things going on in Kansai, but you know, Ken tells that story much better than I can, so let’s get right to the interview.
Tim: So, I’m sitting here with Ken Fujiwara of Hacarus, and thanks for sitting down with me today.
Ken: Thanks for having me.
Tim: Hacarus is a collection of AI platforms that’s targeted both at medical and industrial use but you can probably explain this a lot better than I can, so what exactly does Hacarus do?
Ken: Alright, so Hacarus is basically AI startups and provide AI desk applications for medical, such as AI-enabled diagnosis solutions and for manufacturing industry, we provide digital inspection services, and one of the core differences of our company is that we don’t use a mainstream AI technology called deep learning. We use something else.
Tim: I’ve noticed that, so you’ve talked a lot about your ability to create AI models based on very small data sets. How does that work? I mean, what exactly are you guys doing, if you don’t mind me asking what the “secret sauce” is.
Ken: Sure, yeah, I don’t mind talking about the “secret sauces.” So, in machine learning, in general, the basic assumption is that you need a lot of data or what we call training data, and these days, people, they use technology called deep learning. How deep learning works is that basically, you feed it tons of data and it can abstract the futures from that data set and it can create the model. Our technology called the sparse modeling is quite different, so it can do the same thing but it’s from small data sets. It’s been a while in academia run, like, year 2000, we had the one person who incorporated that technology and commercialized it, so that’s our core strength.
Tim: Okay, I can see how being able to operate on smaller data sets really opens up a lot of broader commercial possibilities because a lot of people just don’t have that much data. So, tell me about your customers. It seems like you’re dealing with quite a few different applications.
Ken: We focus on two industries, medical and manufacturing, and most of the time, as you said, they don’t have access to a big amount of data. For applications like autonomous driving, there’s an infinite amount of data because you let the car drive in the city. However, for applications like AI-based diagnosis for rare disease, basically, you don’t have a lot of data. For certain diseases, there are only 100-plus unique data, that’s it, that’s all we’re talking about. So, our customers are pharmaceutical companies who want to make AI-based diagnosis solutions using this small data set. For the manufacturing industry, most manufacturing companies, they do have a lot of data for non-defective products. However, it comes down to defective data, they don’t have access to a lot of data, so 1/10,000 production units, there’s only one defective, so again, if you want to do defect detection, you need a lot of defect data or non-okay images.
Tim: So, Hacarus is not creating a specific product. It’s mainly consulting and helping your clients use this sparse modeling to solve their problems?
Ken: At the moment, yes, so the majority of our revenue is based on what we call contract work or consulting work. So, we come in and we listen to the particular problem that the customer has and we provide a tailor-made solution to that customer. We’ve been doing more than 100 projects that we are trying to productize our knowledge and package them as sort of a license, so that we can sell it to another customer.
Tim: I think it’s interesting looking at Hacarus over the last six years and actually, I want to talk about some of your really interesting pivots you’ve done, but before that, I want to talk a little bit about you. You founded Hacarus more than six years ago now in 2014, but before that, you’ve been involved with quite a few startups before, haven’t you?
Ken: Yeah, actually, Hacarus is my fourth startup, that’s why I look so old right now, so yeah, so before this, I’ve launched three tech startups. This is not the first time doing a startup thing in my life.
Tim: It’s your fourth real startup, but you’ve also had a lot of other projects you’ve worked on that never quite got traction, right?
Ken: Yeah. I mean, like, my win rate is almost like 10%, so only one win out of 10 failures, that’s my success rate.
Tim: No, see, I don’t think people really appreciate that, so I’ve started four companies as well, but the thing is, I’ve also had probably 12 other projects that never quite got to financing and full-time employees, and I don’t know, I think people overlook the importance of having those.
Ken: Yeah, I mean, there’s a known saying that failure is a good teacher to success without failure. You don’t get success.
Tim: Yeah, I mean, that’s the only way you learn.
Ken: Yeah, of course.
Tim: So, what led you to start founding companies? Because before, you were at Sony and apparently thriving as a productive member of society, so why leave to start a startup?
Ken: To be honest, I never wanted to be an entrepreneur in my life. I was a computer geek when I was a teenager, but luckily, my father was a computer engineer as well, and basically, I was trained by him, so by the time I became 18 years old, I was pretty good at writing code or programming, so I decided not to join Japanese university, and instead, I went to the United States and I stayed in the US from 1995 until 1999. That was the dotcom bubble and everyone’s talking about starting their own company, like the next Google or next Yahoo, or next ~
Tim: What city were you in?
Ken: In Los Angeles. You understand the crazy atmosphere back then, and none of my classmates were actually trying to get a job at a big corporation, I was the only exception. I felt sane because I was the only person getting a nice job at a big corporation like Sony and I was considered a complete failure from their perspective.
Tim: I mean, but after you get into Sony, Sony is a great company to work for. Was it just sort of missing that college atmosphere and made you decide now, I want to go back and start a company after all?
Ken: Yeah, so I knew that I was going to launch my own startup in 20s but I had no idea how to run a company, just like everyone else, so I joined a big corporation with the only purpose to learn how to run a company, so yeah, so I stayed there for three years how a big company is operated.
Tim: Then went out on your own.
Ken: Yeah, exactly.
Tim: Your first couple of startups were B2B software, they didn’t have anything to do with AI, so what drew you to AI?
Ken: Let me say, AI in the early 2000s wasn’t usable. Before deep learning, there were two prior waves but they didn’t work successfully, so deep learning is a successful application of AI into the industry.
Tim: It’s interesting you say that because I mean, you were kind of hinting at this before but there’s very little in AI that’s genuinely new in terms of the algorithms and the research, right? It’s mostly just the available computing power and the sudden access we have to vast amounts of training data.
Ken: Yes, so it’s a combination of IoT or sensors that can collect that huge amount of data, and as you say, access to huge computing power like AWS or autocomputing and also enhancement of individual GPU. A combination of these elements made the third wave possible.
Tim: Okay. Hey, listen, getting back to Hacarus, you originally started the company with the idea of, it was an IoT project, right? A smart scale for more healthy living.
Ken: Yeah. First of all, life is a series of pivots. You never know which direction you are going, but we haven’t changed anything, basically, because the company’s mission is to extend human life beyond 100 years old, so we tried different attempts to achieve that mission, and our first attempt is making our own IoT hardware, like kitchen scale, so by making that IoT hardware, we can collect the unique data set of how people are eating, but hardware is always hard – that’s why it’s called hardware, it’s hard, doing hardware is hard. We soon learned that we need a lot of money to do mass production and we changed our direction. Back then, we had a companion smartphone application that can work with IoT gadgets, so we decided to only keep that smartphone application and also, the AI running behind that application. So, that was the first pivot we went through.
Tim: Well, actually, I want to dig into this a bit because pivoting is hard in Japan. It’s something very few founders are able to pull off, certainly, compared to the US, and I’m curious, how did you know when it was time? How did it go?
Ken: So, the moment I noticed that we had to change our direction is when we did the first crowdfunding campaign using Makuake from CyberAgent and we didn’t get traction at all. At the time, there were a lot of IoT gadgets from competitors, and they weren’t successful either, so that was sort of like a-ha moment and we understood that we had to change our direction.
Tim: Did you get any resistance from the staff? Were there people who still believed in the original direction and wanted to keep going that way?
Ken: Yeah, of course, so there was a huge resistance from the existing employees as you can imagine. So, basically, I had let go of all these people. Basically, it was just me and a couple co-founders left at that moment, so we had to basically let go of all the hardware engineers because they had nothing to do at the moment.
Tim: I love that your mission is still helping everyone live to 120 years old.
Ken: Yeah, that’s our ultimate goal, yes.
Tim: So, speaking of pivots, like, from your blog, this is something you obviously really care deeply about – you spend a lot of time researching it and thinking about it, but these days, pivoting-wise, you’re doing a lot more on the industrial and the consulting side.
Tim: So, what’s kind of the ratio between the medical tech versus the industrial and training, and consulting?
Ken: I would say it’s 50-50. Of course, our main mission is as you say, to extend the human life expectancy beyond 120 years old, so our focus is always a little bit on the medical side, but doing just medical services or product is also difficult because you have to deal with regulators, you have to talk to authorities, you need the permission to sell any kind of product and service in that market, so this is the reason why we are also spending the rest or the 50% of our entire resources for other industries like manufacturing. We also focus on the long-term goal which is medical and also short-term goal which is non-medical.
Tim: Yeah, life sciences are still really hard for startups in Japan, both on the business and the funding side.
Ken: Yeah, used to.
Tim: You’ve been at this for the last six years, have you seen much of a shift in the way that the investors are thinking about life sciences between 2014 and 2020?
Ken: Yeah, I’m seeing an interesting shift in the ecosystem right now. I mean, before, people were making investments in biotech or life science studies, like VCs really understand that view, I mean, people with domain expertise, per se, but these days the VCs are coming from other industries like IT or just pure tech industry, even social media. The VCs from these industries are the ones making the investment in life science tech startups.
Ken: Yeah, so it doesn’t mean that they fully understand the domain, just look at ourselves, we are not exactly biotech or life science startups, you are basically coming from IT or tech, or computer science fields, but we are tackling the medical field.
Tim: But life science VCs, it’s a special breed because it’s all this really expensive upfront costs and you don’t know if it’s going to work for seven, eight years. It’s hard to find life science investors. I mean, they’re a unique group of people even in the US.
Ken: Yes, there too, yeah. So, people with different backgrounds are coming to the ecosystem, that’s one change that I’m seeing right now. The other effect or change I’m seeing right now is pharmaceutical companies are more open these days. They’re running an open innovation program, accelerator program within their organization. Actually, this is how we connect ourselves with pharmaceutical companies inside and outside Japan, so basically, many big pharma are running their own open innovation program and they’re quite active these days, and of course, they also make investments.
Tim: Okay, well, actually, let’s talk about those engagements, so I think there’s one startup model in Japan, what I call the integrator model, so I mean, in the US, most startups are very product-focused; they have a definable, defensible, single product or service they offer and many Japanese startups do too, of course, but there’s also a lot of startups like Hacarus who are not selling a particular product. They’re selling knowledge and expertise, and consulting, integration services. So, I’m curious, what do these engagements look like? Are they strictly fees for services? Is it co-development of products? Do you get royalties? How are these engagements structured?
Ken: So, it really depends on which customer from what industry. For pharmaceutical companies, we tend to do co-development, so we make the AI and we license it, so they are the ones who will commercialize or even sell the solution to hospitals and doctors. For manufacturing industries, we have our package software for visual inspection and we customize it to meet the customer needs. So, it really depends on what customer we are talking about, but most of the time, we have to do some kind of customization or consulting.
Tim: That integrator model is really totally valid in Japan, but for Hacarus, what’s the future here? Where are you in 10 years? Are you a bigger, more successful integrator? Are you someone who’s launched their own product? Will you get back to your core mission of helping people live to 120? I mean, your heart really seems to be in that domain.
Ken: We actually never wanted to be considered as an AI startup and I have no intention to become an AI startup from day one. I mean, we are, obviously, but as we say, our core mission is to extend human life expectancy. So, right now, we’re using AI as just one of the tools that we can use to make that mission possible, but in the future, we might be using other tools to achieve that goal. For instance, we might be producing our own crude, maybe, or we might be producing our drugs based on AI technology, we might be trying to produce yet another IoT gadget or sensor, so we are focusing on AI because that’s our driving force at the moment, but in 10 years, we might be using other tools to achieve the company mission.
Tim: What is the path from here to there? Is that something you have mapped out or are you taking kind of an opportunistic approach of waiting for the right opportunity to present itself and you kind of move a little bit in that direction over time?
Ken: So, this is the reason we have an internal R&D department for focusing on these long-term goals or the topics that have nothing to do with our existing business model. So, it’s always a combination of going after short-terms goals and also going after long-term goals. The running company is always a mixture of both – you want some people focusing on making revenue today and also, you need completely other type of people focusing on making money for the future, in like, 10 years.
Tim: Okay. Alright, I also wanted to ask you about explainable AI. You mentioned the fact that Hacarus’s products result in explainable AI is really important. Why is that important?
Ken: Of course, it is important, I can give you one example. Let’s say you’re sick and you went to a hospital and you met a doctor and he said, “Hey, I think I need to open up your stomach because deep learning says so. Don’t ask me why.” That’s the current status of current technology. I mean, I know I’m making an extreme example here but that’s the problem that deep learning has today.
Tim: Actually, I don’t think that’s an extreme example at all. I agree with you, I’ve had discussions about explainable AI where people have said, “No, it lets you tune it better. It lets you,” but I think what you’ve hit is really it. It’s we humans, even if the black box is better, we’re just not set up to accept the fact that, I don’t know, this computer says to do it, so I’m going to do it, or no one wants to tell their boss, “Well, the computer told me to do it.” They want to say, “Well, here’s why.”
Ken: Yeah, everyone wants to know the why part, and the same story goes for non-medical field. Let’s say you are the head of a manufacturing factory and something just went wrong because of the AI and you have no clue what drove that problem, and you cannot report anything to your boss or the management because AI is completely black box.
Tim: Yeah, yeah, I mean, the problem’s are on our side. We are human side rather than the machine. In your opinion, are there technical advantages to it as well or is it simply explainable AI is easier for us humans to accept, and humans are the customer, so that’s what you’re going with?
Ken: I mean, humans, by nature, we want answers, right? And also the reasoning behind it, so I mean, life is all about finding answers, the reason, I mean, people want to understand why we exist. Yeah, I mean, life is all about finding the questions and answers, and reason behind it.
Tim: Is it the case that explainable AI is better suited to some problems and not explainable to others or will they solve similar problems in different ways?
Ken: These two types of AI applications are trying to solve different types of problems. For instance, for autonomous driving, you don’t need reasoning behind the AI decision. You just need the accuracy, right? But as I said, for medical applications, you always need some sort of a reasoning or explainability about why AI comes up with that decision.
Tim: That makes sense. Let’s talk a bit about Kyoto, because I’m a huge fan of what’s going on in Kyoto right now and you guys are based in Kyoto and actually, Kyoto today reminds me a lot of Fukuoka five or six years ago, when the community was still just coming together and there’s this great energy and ideas and it was really exciting. So, what’s happening in Kyoto? How is the community coming together there?
Ken: Kyoto has been known as startup city for at least 50 years. There’s Nintendo, Kyocera, Omron, I mean, you name it. There are a lot of successful companies born out of Kyoto and they all used to be a startup from day one, of course. However, at the same time, I often say, we don’t need any ecosystem. I mean, Kyoto doesn’t need that kind of ecosystem like Fukuoka or Kobe, or Tokyo where people are trying to help entrepreneurs or aspiring entrepreneurs to launch their startup. I even met a couple of CEOs running the big corporations here in Kyoto who explicitly said that I’m here to destroy the startup ecosystem here in Kyoto.
Tim: What did he mean by that? What did he mean by that exactly?
Ken: Yeah, let me explain why these people are having that kind of thought. So, yeah, of course, when you build a strong ecosystem, you get a lot of startups, and at the same time, you get just okay people; you don’t get a lot of crazy people. I mean, you get ordinary people who launch this okay startup. Kyoto mindset is quite different, so all these people, the CEOs that exist in the companies, even the people from the government and cities, they are trying to let okay people go out of business and only keep the extraordinary people.
Tim: Yeah, startup ecosystem means something a little different today than it used to, so what I think is like the most important part of the ecosystem or the definition of an ecosystem. It’s not the mentors or the government employees or the big companies, it’s the startup founders themselves interacting with each other and supporting each other, and buying services and products from each other. To me, that always seemed the key.
Ken: Yeah, very true, yeah. So, let me rephrase just what I said.
Ken: You have to basically identify the mentors or the people you want to talk to by yourself. I’ve been doing my pilot startup in Tokyo, so I understand there’s a strong ecosystem in Tokyo and how Tokyo runs their own community. So, there are a couple groups and communities out there where you can just go there and hang out with mentors and other entrepreneurs. I know that, but here in Kyoto, there’s none. Basically, you are the one who has to find it out by yourself.
Tim: Okay, well, then why did you move back to Kyoto? Because I mean, your Sony job was in Tokyo and your first startup was in Tokyo, so why not stay in Tokyo? It’s a lot easier to raise money, more founders around you, why did you come back to Kyoto?
Ken: Yeah, first of all, I got too old, so Tokyo was just too busy for me, one of the reasons why I left Tokyo, but honestly speaking, I wasn’t focusing on fundamental problems when I was doing startup in Tokyo. I was basically chasing the trends, that’s all I was doing at the time. I wasn’t focusing on the core mission or even what I wanted to do for the rest of my life, so that’s the reason why I left Tokyo. Another reason is that Kyoto is sort of my semi home. I was born in a prefecture called Shiga that is located right next to Kyoto, so going back to Kyoto is almost like going back to my hometown. Yeah, really hands-on, hands down, that’s the kind of style I wanted to do.
Tim: And you know, when you say that, so when everyone talks about startup ecosystems, they always talk about the universities and the big companies, and the mentor support, and that’s all really important, but I think you hit on something that I think is so much more important than all of that, and that’s, like, people from Kyoto want to live in Kyoto. When their startup gets big, they’ll open a sales office in Tokyo but they want to stay in Kyoto, and like Fukuoka is kind of the same way, but most cities, like, when the startup starts to get big, they’ll move the whole company to Tokyo. So, I think there has to be this kind of, I don’t know, like, hometown pride or something to have a really good ecosystem.
Ken: Yeah. Well, you can call it pride, but I’m not looking at it that way.
Tim: Well, pride is maybe not the right word, but you know.
Ken: Yeah, I understand, yeah, but it’s all about keeping distance from the mainstream, so let’s say, if I were to launch the same startup in Tokyo, 100% for sure, I was using deep learning because that’s the mainstream, that’s the topic everyone is talking about. However, because I am based in Kyoto which is kind of far away from Tokyo, I had to be different, so that’s one of the reasons why I’m not following mainstream technology like deep learning. So, that kind of mindset or keeping some sort of a distance from the mainstream is what’s keeping people in here. This is the reason why you find so many Kyoto companies that are so unique.
Tim: Yeah, I think you do have to get some distance from financial and political power to really do anything innovative.
Ken: Yeah. Nowadays, you have access to whatever information you want to know using the Internet, right? So, I never thought that being in Kyoto has some kind of disadvantage in terms of fundraising or hiring people, even access to the information. It’s more of a choice.
Tim: But you also are one of the co-founder of Maker’s Bootcamp in Kyoto, right?
Tim: So, that’s an ongoing startup community out there.
Ken: Yeah, so that contradicts with what I just said. So yes. The answer is yes, I was trying to launch the ecosystem, but this is how Hacarus was started as an IoT company, because Maker’s Bootcamp and Hacarus were almost like the two sides of the coin. Now, the company changed the name as Monozukuri Ventures, but yeah, I’m still one of the co-founders of the company as well.
Tim: Now, I think they’re doing great things and I think there’s so much interesting stuff going on in IoT in Japan. A lot of it is, I have no idea if it’s ever going to be commercially viable but it’s just so much interesting and creative ideas are going on right now, it’s so cool.
Ken: Yeah, yeah, I agree. I think that’s partly because first of all, Japan is still known as one of the best manufacturers in terms of brand, products and quality. These days, we’re seeing a lot of IoT or hardware startups founded by people who used to work at big corporation like Sony and Panasonic, Honda, Toyota, I mean, we didn’t see these kinds of people jumping into startup water before, but now, we do, so that’s part of the reason why we are seeing a lot of interesting IoT and hardware startup coming from Japan these days.
Tim: Yeah, I think so too and I think that especially with hardware, it’s great if you got a team of two 20-something college grads with some great clever ideas who want to make some hardware great, but if you got a team, and you see a lot of these now, like, two clever 20-something college grads and one guy in his 50s who has been doing production and supply chain for the last 30 years, that’s a powerful combination. I think you’ve got to have that expertise to do hardware.
Ken: Yeah, right, I agree, yup. Making hardware itself is hard enough, but making a service on top of these is even harder, so these days, hardware alone cannot make any kind of business. People are expecting to receive some kind of service using the hardware. So, I still say that Japanese IoT and hardware startups need to improve the service development part or even provide good experience using their own hardware, that’s the part that we are still missing today.
Tim: Well, listen, Ken, before I let you go, I want to ask you my “Magic Wand” question. If I gave you a magic wand and I told you that you could change one thing about Japan, anything at all – the education system, the way people think about risk, the way people look at startups – anything at all to make things better for startups and innovation in Japan, what would you change?
Ken: I will say I want to make a change in the education system. To be more precise, I want to force all the college students to spend four years outside Japan. You can go to any Japanese university, but you’re not allowed to stay in Japan.
Tim: Four years?
Ken: Four years, entire college days, you have to be outside Japan.
Tim: What would that do? What good things would happen because of that?
Ken: That mindset is coming from my personal experience when I studied in the United States for five years, so that’s how I learned how to speak English, that’s how I met crazy people from the startup world and also, that’s how I met all these interesting people, not just from the United States but from all over the world, so spending some good amount of time outside Japan gives you so many different ways to look at things in Japan. I mean, you’re from the United States, so you know what I’m talking about. So, I really want to change that system and force all the students to spend, let’s say at least, like, two years, let’s say two years, not four years, two years outside Japan, so they have to speak languages other than Japanese.
Tim: Yeah, I guess, and it forces you to learn new ways of thinking and new ways of approaching problems.
Tim: But I gotta say even before COVID hit, the trend in Japan was kind of going in the other direction where we’re having fewer Japanese study abroad.
Ken: Yeah, I agree. I think we are the peak of exchange students from Japan, and since the year 2000, there are less and less students studying in the United States or abroad in general. I don’t know what’s making people stay inside Japan, but yeah, the people studying abroad are decreasing.
Tim: But at the same time, the number of foreign students studying in Japan is really going up.
Tim: Is that something you think we’re going to see reverse itself? Do you think there’s going to be more of an interest?
Ken: Yeah, that has to do with our own economy, I guess. Japan is still sustainable by itself, meaning that we can just launch products and services for Japanese people and you can still do good business just within Japan. Let’s say if you’re in Israel, there’s no domestic market. You’re forced to do business outside Israel, so that forces people to study abroad and do business outside Israel, even interact with people outside Israel.
Tim: Yeah, I think so. I think Japan’s big market, both for startups and society as a whole, it’s like a blessing and a curse at the same time. It is its wonderful test market where you can develop expertise and refine products before going overseas that, say founders in Israel or Singapore don’t have that option.
Ken: I agree.
Tim: But it does give you the option of being kind of lazy and saying, “No, no, this is enough. Why? We’ll worry about the overseas markets later,” and Japanese investors often don’t like startups going overseas because it’s risky and takes a lot of capital.
Ken: Yup, I agree, so I hope that situation will change in the future, but our company is also focusing on international market as you know, and one-third of all the employees are not Japanese, so English is the default language within our company. We do a standard meeting every day, every morning in English only, so we are willing to go outside Japan basically from day one, and we want to be a showcase company that can change a perspective on the Japanese market.
Tim: Well, I have noticed that even if the number of students studying abroad is going down, the number of startup founders who are doing international expansion is certainly going up, so that’s a good sign.
Ken: Yeah, that’s a good sign, yeah. But I know that all of these companies are also struggling to expand the market outside Japan, especially North America.
Tim: Ah, well, the US is the hardest, it’s so competitive and it requires so much capital to make headway there, but in the end, that’s the market you gotta play in to really win at the game, right?
Ken: Yeah, yeah, right. We also are definitely looking at North American market, but not necessarily United States. This hardware for AI is basically coming from Canada, not from the United States, so we are looking at the Canadian market first to enter the North American market.
Tim: Excellent. Well, listen, Ken, I want to thank you so much for sitting down and talking with me. It’s been really interesting.
Ken: Thanks for having me.
And, we’re back.
Ken’s comment that he never really wanted to start an AI startup is interesting, and it’s actually something founders of AI startups say in private a lot more than you might think.
When they say that, they usually mean it in one of two ways. Sometimes, they’re reacting to trends and buzzwords. They’ve adopted AI to attract an investor or customer interest, or to differentiate themselves from current solutions.
And sometimes, and this seems to be the case with Ken and Hacarus, sometimes, midway, they realize that AI can actually achieve their overall goal and let them create genuinely new ways to solve problems, and so they try it, and if it works, it becomes the cornerstone of their startup.
Now, the funny thing is that from outside, unless you can actually sit down and talk with a CEO, it can be really hard to tell the difference between a startup using AI as a marketing tool and a startup using AI to solve meaningful in new ways.
And also, Ken’s return to Kyoto and his comments about needing to get away from Tokyo to really be innovative and solve problems the way he wanted to solve them, that really hit home with me. It’s something I’ve always believed and an important reason why we should pay special attention to what’s happening in places like Kyoto, Fukuoka, and Kobe.
Remember, the innovation powerhouse that is Silicon Valley did not arise in New York or Washington DC, no, it developed in the suburbs of a relatively small city. At that time, San Francisco was not even one of the 10 largest cities in the US.
I think you need to get a certain distance away from political and financial power to really be innovative. If you’re too close, that financial and political power will always be pulling you back towards the status quo. The rewards for working within the system will always be greater than the rewards for trying to change it.
But get away from that power and working within the system becomes a path to mediocrity, and now, now, you have the freedom and the incentives to create something amazing.
If you want to talk more about AI or pivoting, Ken and I would love to hear from you, so come by DisruptingJapan.com/show176 and let’s talk about it. If you leave a comment, I guarantee that Ken or I, or maybe both will respond, and hey, if you get the chance, check us out on LinkedIn or Facebook, but even better, if you like the show, tell people about it. Disrupting Japan is my labor of love. It’s free forever. People hear about the podcast because listeners like you enjoy it and they tell their friends about it.
But most of all, thanks for listening. And thank you for letting people interested in Japanese startups and innovation know about the show.
I’m Tim Romero and thanks for listening to Disrupting Japan.