This Week in Startups - Why quantum has been "10 years away" for 30 years | E2316

Episode Date: July 24, 2026

This Week In Startups is made possible by: PayPal Open https://paypalopen.com DigitalOcean https://do.co/twist Rippling https://Rippling.ai/twist   Today's show: *For three decades now, we've been told that breakthroughs in quantum computing are right around the corner. So why hasn't anything materialized? On TWiST in Tokyo, Jason sits down with Yaqumo CEO Kazuhiro Nakashoji and discusses what needed to change (like better algorithms and hardware), and why we may finally be nearing quantum's big moment. Find out why quantum machines are so error-prone, explore the unusual international quantum supply chain, and get a heads-up about the cryptography reckoning coming for your Bitcoin. Guest Kazuhiro Nakashoji on X: https://x.com/KNakashoji Yaqumo Inc.: https://yaqumo.com/en/ Relevant Links JETRO (Japan External Trade Organization): https://www.jetro.go.jp/en/ Institute for Molecular Science: https://www.ims.ac.jp/en/ Quantum Insider: Yaqumo Quantum Photonics Agreement: https://thequantuminsider.com/2026/06/04/yaqumo-nkt-photonics-and-hamamatsu-photonics-sign-quantum-photonics-agreement/ Quantonation investment announcement: https://quantumcomputingreport.com/quantonation-selects-neutral-atom-hardware-developer-yaqumo-for-first-japanese-investment/ NIST: What is Post-Quantum Cryptography? https://www.nist.gov/cybersecurity-and-privacy/what-post-quantum-cryptography Timestamps: 0:00 Intro / Founder University Tokyo 2:20 Guest intro: Kazu of Yakumo 3:20 What is a qubit? 8:34 Why quantum computers are so fragile 8:45 PayPal - Built for payments, growth, and agentic. Paypal Open, built for all business. Visit https://paypalopen.com to get started 13:36 Spinning IP out of the university lab 18:42 DigitalOcean - Head to https://do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 28:01 Building the "Toyota of Quantum" 29:38 Rippling - Thanks to our partners at Rippling! Head to https://Rippling.ai/twist and get the only AI built to give you full visibility across your startup and take complex actions across your entire business. 31:25 AI for quantum, and quantum for AI 38:35 Harvest Now, Decrypt Later 41:41 Q&A: Yaqumo's business model 43:22 Q&A: Yaqumo's business model Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

All right, everybody, welcome back. It's this week in startups from Tokyo. Yes, we're at Founder University. I'm back in Tokyo. I go twice a year. They go in the summer. It's 96 degrees and 100% humidity. It's the exact opposite of what happens in January when I come here to do Founder University and ski for a week.

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We have Kazu Nakashoggi. Yeah, absolutely. Oh, I got it. This week in startups is brought to you by Ripling. Don't settle for AI. That's all talk. Head to rippling.AI slash twist and get the only AI built to give you full visibility across your startup and take complex actions across your entire organization. That's R-I-P-P-L-I-N-G dot AI slash twist. Sign up for exclusive access today.

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Yakumo, which is spelled Y-A-QU-M-A, and you're building quantum computers. Hardware. Yes, hardware. And hardware is hard. Hard. Yeah. Hardware is very hard.

Quantum computing has been five to ten years away. for the past 30 years. Why is it taking so long? That's really good question. More so of the quality parts coming from hardware itself. Ah. Yes. So we try to generate very special curricular units,

QPU, quantum processing units. Quantum processing units. Yeah, that's why you call it QPU instead of CPU. Got it. Right. But it's really hard to create those kind of things as a hardware. and we have to make it a bunch of number of QPU to do very useful calculation. And from my understanding of qubits, this is instead of one or zero,

you get to have one, zero, or neither, one or zero. At the same time. At the same time. Yes, super positions. So you could have each of those positions simultaneously. Technically, yes. Technically, yes. So explain to, you know, founders in technology who use GPUs and CPUs all day long.

Why is this the white whale? Why is this the holy grail of computing? Why is this the next paradigm? Why is it so powerful? Thank you very much. So, first of all, I think there is some big misconception about a corner computer. Okay. Once we use corner computers, maybe people,

believe that oh maybe we can do more nice very fast characterization compared to CPU or GPU but this is first of all it's not correct yes we can apply quantum computer for particular questions or problems for example combinations or like RSA clip door yes those kind of difficult question we can only we can apply those kind of problems to quantum computer or quantum very cushions. And we saw Google and Microsoft and some other quantum computer companies went public over the last maybe two or three years. Exactly. Lots of excitement. Of course. And we had the same wave of excitement five or ten years ago, but it seems like it's getting closer and closer

to having an application in the real world. When will we see a company, a startup, that uses a quantum computer to solve a problem in the world, as opposed to all these companies spending billions of dollars trying to get a quantum computer to work. Yes. So when do they have enough power and enough software and maybe the compilers and the tools have to be built as well, I understand, to actually make it accessible to founders at startup university? Yes. Or startups at founder university.

Of course, of course. So that is really, really important question. So there's two ways to understand these circumstances or at the same time. So first of all, if you're looking at question or some kind of problems that corner computer are going to solve. In the past, for example, five years ago, people believing that we need 1 million cubic

QPU to solve some certain problems. But recently that number is drastically decreased. Oh, okay. Yeah, cruised, for example, 10,000 cubic. Got it. Just one person of what we expected 10 years ago, for example. Since we updated some software algorithms or some other like schemes, for example. Besides, in terms of the hardware, looking back, for example, 10 years ago,

we only have maybe 1 to 10 cubic. Wow. Wow, it's super tiny. That's it. Super tiny, but recently, it's less than like a punch card from an old computer. Exactly. But listen to, for example,

one of the United States University demonstrated 6,000 physical equipment. Wow. It's amazing. So what I mean is like the number we need for doing actual classification is decreasing. A number of the physical incubates is close to that numbers. So we believe that we reach to like two of them meet each other's close to two. 2030, for example, in Xpo to five years. Got it. So we'll be sitting here in five years, and there'll be companies who have quantum

computers in their data center using them? Of course, we can imagine that. And some of the current computer already installed into data center already. Yes. For example, in Japan. Toyers still over there? Yeah. There's one there. Yeah, of course. Got it. And it's being used for what?

Just doing simple math calculations now and just trying to make it work? because my other understanding is it's not consistent yet. It has, it's maybe fragile or brittle? Yes. So why is it fragile or brittle? Yes. Thank you very much for questions. So once we do quantum calculations, they made a lot of error.

For example, every thousand times, every hundred times, they make a letter. Oh. Yeah, it's a problem. It's a problem, right? Yeah. And this is big problem. So we have to correct this error. So we call it quantum error collections.

Quantum error corrections. Exactly. So we call it QEC. And by doing so, we have to protect the information that QB has. So by doing so, we can create very scalable, very robust quantum computer. So this is a recent approach the human being tried to take. Got it. Did you ever notice how you spend our shopping online?

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And I say, oh, I'm from the 1980s. In the 1980s, you would reboot your computer every two hours to make sure you didn't have memory leaks or problems. And the hard drive was working, okay, because you wanted the software to the operating system to be fresh. And it would run faster. And then by the end of the day, your computer would be slugged. memory leaks and you have to unload one program to run the other. It reminds me of what you're going through right now. Yeah, that's true.

Definitely right. So probably what we expected, experience like 60 or 50 years ago for classical computer. Yes. We experience in the quantum computer at this moment. Now you're doing something different at Yakuma. With the chemicals or the materials? science, yeah? So you're talking about application or hardware? No, the hardware itself is slightly different. Yes. Or it's advanced and they're using different materials now, I understand. Yeah, thank you very much

asking that. So I think there's a couple of methodologies to do quantum calculations. For example, if you're looking back the history of classical computers, let's say if you're using this kind of CPU, this is like most of the CPU is created by silicon, right? But maybe 60 or 50 years or I don't know. We try to use vacuum chamber to do calculation

isn't it? For classical computations. Same. So at this moment quantum computer market tried to test which kind of

QPU is the best for quantum calculations. The quantum processing unit. It's QPU, exactly.

So for example Google or IBM this kind of large, amazing company tried to create QPU by using super

conducting cubit. Superconducting cubics. Yeah, that's why they have to put those kinds of chips into huge refrigerator to make it super, super chill. It has to be super chill. Absolutely. Yeah. And some people try to use ions

which have a charge, like plasma. Ions, yeah. Like plasma. Yeah. Yeah. They have charge. And we use atoms. Neutral atoms. We don't have any church. We try to configure it or try to create array of the atoms

in the vacuum chamber to use one atom, an atom as a cubit. Got it. Yeah. And some people try to use buttons or semiconductors to do quantum verification at the same time. But there's so many very severe, like, you know, competitive land scale happening in this moment. So let's talk about this is your first startup, company building. We have some hardware startups here. Hardware is hard.

You've picked the hardest of the hardware because you have a, hey, You know, five-year window to commercialization, maybe. And you came out of a university. Yes. And your company is based in Kyoto. Yes. So you get to have a beautiful life, a beautiful city. Thanks.

And all that talent from Kyoto University, yeah? Some of them, yes. Yeah. So you came out of the university. Explain to us how technology in a university, how they do the IP transfer industry, to a commercial organization, not just at Kyoto, not just your company, but just generally how that happens. Because some venture capitalists and Stanford does this and some venture

capital specialize, or investors specializing, going to universities and saying, what are the students working on? What are the professors working on? Is there anything we can spin out? I think they will generally say a spin out, yeah? Yeah, of course. Or is there a term for taking IP out of the university, like a technical term or term of art? Do you know what? Probably I'm not super familiar with the situation in the United States. Got it. But compared to overseas, Japan or Japanese university have not so much experiences to use IP as a startup as a spin-out. Got it.

Yeah. So it's pretty new here. I would say. So normally we call it deep tech startup. Deep tech startup, sure. Yeah, in Japan, which is using the IP coming out from university. Right. And at this moment, there's not very solid methodology how to use IP from university to start up.

Some people choose stock options, pay for university. So the university can get some equity. Exactly. Or in the United States, sometimes we hear about a royalty for some number of years. And yeah, this is, or maybe even a cash payment, I guess people could pay to take it out. but the university wants, the university's motivation is to recoup some money that they invested, yeah, in the research. So you were there for some number of years.

They spent some money on you and maybe gave you some resources. And then also maybe they could make a profit, some kind of profit that then helps the university invest in the next set of. Green messmen, yeah? Yeah, so it becomes evergreen, yeah? I hope so. Yeah. And this is a negotiation that occurs between the university and the founder,

yourself? Exactly, yeah. Tough negotiation, to be honest. Oh, is it tough negotiation? Sometimes it's not easy. Yeah. Yeah. Yeah.

So they want to make sure they get a good deal and you have to get a good deal or you can just leave and not take the IPA. Of course. Yeah. So let's talk a little bit about how you've raised over $10 million, I think, for the company. You've got some grants. You have some venture capital.

We've done a seed round. How do you think about runway? Most companies here, if they're building software or maybe consumer hardware, where they can think about 12 months of runway, 18 months of runway, maybe getting to their first dollar of revenue in six months, three months, nine months, depending on the company type. How do you think about runway and when you have to make money and how you keep pushing the team to get to revenue,

even though it might take you years to commercialize? Thank you very much. So that's pretty subject to the type of this startup. Of course. How we're startup, software startup. But for our case, we expected, for example, 18 months long way after we, we just completed our seed extension round. Oh, congratulations.

Last month, we have been invested by Al-Nabringers for the United States. Which one? Online adventures. Oh, great. Yeah, yeah, yeah. And, to be honest, that was their first investment to Japan. Oh, wow. How did you meet an American VC and convince them to invest?

in a company in Japan. Tell us the story. Thank you very much. So we split the run into two pieces. C-Rand and C-D extension run. So C-Land, this company is being now from Kyoto University. So that's why we have been invested by Kyoto-I-C-Qaqab. It's sort of CVC company from Kyoto University. And they have a bunch of network in the EU or United States. So they nicely connected me to online ventures. and yeah Oh so they There was a group That was able to put you in touch with them

And that venture firm had shown interest already Yes Or they cold called them Oh yeah They have like soft connection Got it on the ventures And they kindly connected to me To the online ventures

Are you a Japanese company Or do you file as like an American company Or both For the venture capitalists in America To invest Usually they have to be a Delaware company or something. Yeah, yeah, yeah.

So you're based in Japan. Based in Japan? Based in Japan. There's no launching overseas. So you don't have a corporate entity in the United States? Yes. Or you do? No.

No, okay. So that wasn't a blocker for the venture firm? They figured out how to do it? Oh, I don't think so. It's cannot be a super, super big deal. Yeah, I guess. And we also have an investment from the VC name coalition. As you can say from the name of this VC, this is a top VC.

this is a top PC for quantum computer hardware from all world so they are coming from France that was also their first investment to Japan at the same time got it and did the venture capitalists come visit you for the board meetings and they get to come to Japan

a couple times a year no no no no it's like we talk online business oh okay on my business but I've been see that's the opposite of me when Jetro and Japan said we want to do founder university with you I said oh I get to come to Japan twice a year I'll do it that's why I'm doing it

and also to meet great founders, but I was coming anyway for skiing in January. So every time we see a revolution in how software is built and used. One company ends up owning the infrastructure that everyone else depends on. The next great platform is being built right now. That company is DigitalOcean and they just launched their AI native cloud. This is not just another place to rent GPUs or a hyperscaler overwhelming you with features and services, but leaving you on your own to patch it altogether. No, we're talking about a full-stack platform that comes pre-assembled and that sends you just one bill at the end of the month. Workato runs a trillion automated workloads on Digital Ocean with 67% lower inference cost, 79% lower latency, and it's two times faster to production.

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Okay. You know the tractor that goes up the mountain? Oh, yeah. So there's an abandoned ski resort. I won't say the name anymore because when I say the name on the podcast, they sell out all the seats. Okay, got it. And then people get disappointed.

There's an abandoned ski resort. Really? Maybe. In Japan? There's many. Oh, really? Wow. There used to be 1,000 ski resorts.

Now there's maybe 3 or 400 active ones. Wow. Because there was many more children and a bigger population. And so it's come down a little bit. So a lot of those small resorts and people move to the city. So in those local resorts, some of them shut down. So an American fell in love with this resort outside of Naseco. It's a good story.

And he asked them every year, can I? have this resort. Why don't you make businesses there? I might need to. And he said it took him four years. Every year he went to the city council, to the elders and said, hey, I would like to do this. They said, oh, tell us your plan.

They said, okay, yeah, maybe next season. And then he came back. I'd like to do this. I'd like to. And when I went to see the ski resort, half of the lifts were broken down. The cables were down, the ski lifts were down.

and he cleaned it up and he left one run perfect and all the local people get to have a ski ticket for maybe $50 for the season if they live there and they ski that one run and then they make very good Katsu Kari and nice ramen and then they have two cats with eight seats in each so 16 people come from around the world and they drive you up the other eight runs. Okay. So one run for the locals. The other runs are broken down. They drive you up. It takes 15 minutes to go up. Okay. And then it takes 10 minutes to go down.

Okay. And you do eight runs in one day. Oh, wow. $1,000 a day. $100 a run maybe. Okay. But it's worth it. Because every run is fresh powder.

J-Pow, Japanese pound. J-Pow. Is he so? No, right. It's beautiful. Oh, right. Do you ski or snowboard or neither? No, no.

No. I know. I was born in Bangkok. I was raised up from Malaysia, so maybe I'm not super super for me. You're just kind of. Yeah. Anyway, it's a dream. And then unfortunately, years ago, I talked about it on the podcast. And then other people talked about it on social media. And just like Tokyo, all the great restaurants have too many Americans coming to take pictures. And if you really like the ramen at this place, somebody puts it on TikTok and then no locals get to go anymore. So now some of the locals are not putting them, they don't put in an English name on the restaurant.

Just for... And they hide the address more. So only locals. Okay, okay. And some of them have signs now, only local. But in Japan, in Naseco, there's now at Naseko, the actual resort is too many... I see. Too crowded.

Oh, yeah. You know, Japan more than me, I guess. Yeah. So talk about this hiring of talent here. and the work expectation and then building a company and building talent and culture in Kyoto, where it's very beautiful. Thanks. But maybe do people work hard?

And do they want to be in the office for 10, 12 hours a day, grinding? How do you build a culture here in Japan and even in, you know, Kyoto? Yeah. So that is really important question as a startup. At this moment, the size of the company is close to. 70. 70. 70.

Oh, big. We just launched this company 15 months ago. Whoa. So, 2025 April. And most of them are tech science. I mean, engineers, scientists,

or we also hiring mathematicians who's like, you know, very capable of. So one to two hires per week? Oh, yeah, sort of. Yeah. Yeah. That's the biggest job for me, to be honest, hiring the people. Got it. And how many

of the 70 are Japanese or recruited to come to Japan? Yeah, so I think there is close to 50, 5-0 tech people. And I guess 20 to 30% of them is non-Japanese. Non-Japanese. Non-Japanese. Oh. An interesting point is that there's a three divisions under the CTO,

who is management and of course tech side, two of them, two head of three divisions, non-Japanese. Got it. Yeah. So one of them coming from Sydney. from Sydney yeah oh beautiful yeah he's very talented uh I want to walk with him I went to Sydney I need excuses to be into that beautiful city that's great yeah yeah Sydney is one of my favorite cities yeah so beautiful so beautiful and the other another guy is

coming from Turkey in Turkey yeah he but it's a very international organization I would say what's the selling pitch to say leave Turkey leave Sydney beautiful city and come live in Kyoto, another beautiful city, but this is a culture change for them, yeah? Yeah, we do scissors fit as long. Rock paper, scissors, yes, no, no. It's just joking, but I think

Kyoto have a very great advantageous in terms of the beauty of the city. Yeah. Very chill. And we had a spin-eye from Kyoto University, and Kyoto University have a very profound research background, the history. We use neutral atoms. Yeah. But

one with the professors coming from Kyoto University. His name is Yoshiro Takashi. He studied neutral atoms. For example, Y-B, that's one of the species in neutral atoms, by the way. He studies that species more than 30 years. And he discovered, I say, 60 to 70% of the fundamental scientific study of the Ethiopian. So, yeah, so that professor is very famous. And at the same time, An interesting point, a selling point about this company is that we try to integrate two entities' research output. One is Kyoto University. One is coming from IMS. IMS stands for institutional, institutional market science in the IT prefecture.

Whose name is Kenji Omori. He's the head of that institute. And two professors, two talk, try to create independent startup, similar startup. But if you're thinking about the competitive landscape over the word, oh, why don't we make one startup? These two extraordinary. Professors, researchers, scientists. Yes, exactly. So now you've incorporated them into the startup there.

Advisors, board members? Advisors, advisors. Yeah. So this is one of the great history behind this company. And many people know that, know that these two professors, co-worked together. So they're rock stars. And it draws talent.

Yeah, yeah, yeah. Very talented two professors. So we closely walk with two entities, Kyrton University and IMS. And I would say this company is Spineye from Kilton University and IMS. Yeah, so this is not a good selling point since from DZero,

we have a large scale of research entities as a startup. That is not a good point. And so is your intent to build the entire computer or be part of? of working with other companies building computers and empower them as a provider to them.

Very, very, very good question. Very, very good question. So I believe that our neutral atom quantum computer is something like car, automotive car. And we try to become the quantum computer company, something like Toyota. So if you're thinking about Toyota, they don't create tire.

They don't create engines. They design everything, integrate everything to one, and sell that car into the market. Same. So we are the corner computer company trying to assemble the lasers, vacuum chambers, ometers, whatever. So there are many people building these components now? Exactly. Co-walk together.

Where are they all based? And they also centered around universities. You always ask me a very, very good question. So we use neutrals. And most important device for this corner computer is laser. Very high-power laser, very less noise lasers. So high fidelity? Exactly.

I like that one of the way, much high-fidelity lasers. And this is coming from Hamatsootnics in the Hamamatsu, Japanese company. and they also have an amazing subsidiary company in Copenhagen in Denmark in Denmark in Denmark of all places yeah but it's like no wonder since newsboard

one of the like an amazing scientist from Denmark and Denmark is a very very strong capability in terms of physics and that company name is in the Gative Photics they're creating amazing high-power lasers and recently Oklimo, our company, and Hamatz Photonics and NKD Photonics did

nice MOU in between Denmark and Japan, try to create special devices for neutral atom-based corner computer. I mean, this kind of supply chain is very crucial for industrialization of quantum. Most AI tools can give you business insights, but they can't actually do anything about it. That's the difference between AI that talks and AI that acts. but Rippling AI is built differently. It's the only AI built on your live global workforce data.

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Then Rippling AI will recommend a research. attention strategy, including a 10% spot bonus for your top performers. So don't settle for AI. That's all talk. Head to rippling.a.i slash twist and get the only AI built to give you full visibility across your startup and take complex actions across your entire organization. That's R-I-P-P-L-I-N-G dot AI slash twist. Sign up for exclusive access today. Which is fascinating that it's so many different people around the world are working, together to try to hit this vision is something happened in the time you were starting this company and quantum computing has been working towards this very

ambitious goal which is large language models artificial intelligence GPUs have become very powerful so how has the advances in AI impacted what you're building and how you're building it. Yeah. Thank you very much. So we call it AI for quantum and vice versa quantum for AI for AI. Explain both. Yeah, sure. So AI for quantum, this is very, very powerful. So for example, this is very, very interesting story behind quantum calculations. But if he used corner computer, as I mentioned, aller happens. And we have to estimate what kind of error happened. by using classical computer.

A GPU, for example. Right. CPU. So they help us, I mean, ask me a corner computer, to identify or estimate what kind of error, to what extenders can happen, and try to correct through classical computation. So, and through these kind of activities,

we definitely use, we already use a lot of AI, LAM transformer, for example, to do quantum error collection. So this is something, very tangible example, of the AI for quantum. Got it.

Right. Just doing that era correction. Yeah, that's like a more like, you know. And it's so powerful now. Very, very powerful because of the AI. And opposite side. So quantum for AI. So at this moment, there's no practical or tangible example about quantum for AI.

Since the power of quantum computer is not enough. Not enough yet. Not enough yet. However, recently the researchers coming from MIT wrote beautiful papers about how quantum for AI happens. We believe the future is not super, super far away. And so would it be used for inference or model training, both? And then if it does work, let's say we go five years into the future, maybe even 10 years

into the future, what impact could that have on either of those two practices? and obviously there'll be other jobs to be done and new modalities are being created. But using the current paradigm of the language model and the building of the language model or inference the customer getting their query answered, what impact could Quantum have on that? Yeah, so for example,

very, very interesting examples that after we did Caucasian of, by using quantum computer results coming from them, For example, if you do fluid dynamics calculation by using corner computer, that is data or result is not normally coming from the classical computer, isn't it? This is only coming from corner computers. Why don't we use this data to make AI even smarter? We can differentiate the model by doing so. Got it.

So the models become more powerful? I guess so. Yeah. Because we're going to be a very interesting future. Very interesting. I believe quantum for AI, once this is. kind of happens. Corner computer company makes tons of money.

Yes. And it could be like the answer to many problems. Do these quantum computers, are they as power hungry or more power hungry than their equivalent GPU or CPU type computer? What's the energy consumption like? Very less, let's say. Very, very, very less. Really?

Yes. Interesting. Yes. Recently, one papers talking about, I'll be finding out one paper is talking about, the comparison in between classical computers and corner computers as a function of the consumption, the energy, as a function of the number of the qubits. And they mentioned that the number of the cubit is close to 40 or 50 or something.

Then we do a particular problem solving. The energy that corner computer use even less than classical computers. So in the context of less CO2, less energy, we definitely believe that quantum computer contributing to the... Are they always going to be very large data center computers, or will we ever see the desktop revolution equivalent of quantum computing? I know it's a silly question, maybe, but I'm just curious. Yeah, exactly. I would say, again, I cannot say that. corner computers take over all the position of the classical computers,

just one part of it. But I believe quantum computer could be a very, very great accelerator to make classical computer even smaller. So there would be a hybrid computer with both. Exactly. Like a hybrid Toyota Prius. Yes, yes. So some jobs go to the quantum processing unit

and maybe some other parts of the job go to the GPU and CPU. They shared loads. Wow. And they could share the memory. Yes. So there's kind of primary research work happened already in Japan. For example, in Tsukuba. And there's many ways to do demonstration of hybrid system in between quantum microcosco.

Fascinating. Okay. Final question. Everybody's a bit nervous about cryptography. And that someday quantum starts up and all of our phones are hacked and everybody sees our bank account and you take all my Bitcoin. When will you be taking all of my Bitcoin?

Yeah, that is really, really big question. So, recently, one survey, review that how a quantum calculation researcher think about those can decrease

for a few happen. And they mentioned that in next five to ten years, we have to be very, very be careful about it. And it's true? I think it's true. I think it's true.

Sometimes, technologists are a little bit hyperbolic. They get a little bit excited like we saw with AI. But it's true. Yeah, it's true. So some research works already proven that if you reach to certain amount of the size of the cubic, QPU, we can solve RSA cryptography. But it won't be happening next two years, for example.

No worry. It's time to sell your Bitcoin. Yeah. Plenty of time. So, but the point is that maybe not only for Bitcoin, but for, for example, some like, this top secret coming from Japan, United States. Yes. They already.

Yeah, absolutely. There's kind of dual use cases. Very, very crucial. And for example, some country already collected top secret, which is already protected by RSA, cryptography. But they already has that, isn't it? They have the data. haven't cracked it.

Yeah. And once they create corner computer, so take now, solve later. Yeah. Oh, wow. So get the hard drive now. Exactly. Crack it later. Yes, yes.

Put it on a shelf. Exactly. It was very dangerous. And so is there an international body or has the government gotten involved and created a regulatory body that's in any way monitoring your progress? And do you get a knock on the door that says, hey, you know? We need to have a conversation. Yeah, that is really, really important, like, topics that this kind of do you use or, like, you know,

corner computer-based deep-tech startup. That is really important topic. We talk with government of people very carefully. And, for example, United States, listening to announce that they try to launch or they want to have a very useful corner of computer by 2008. It's aggressive. Aggressive. Pretty aggressive. And so in order to nicely communicate this government of people,

we are very happy to discuss our, or we want to talk transparently with government of people, how to use it, how to protect the technologies. Yeah. Yeah, that is really important. It's a very important. The world is very dynamic. Exactly. It's a very dynamic

world is constantly changing. Yeah. And as a technologist, we can't take it for granted. that everybody has good intent. There are some people in the world who have bad intent, and so we have to be thoughtful. We have to get there first, yeah.

Yeah, true. Is China making progress on quantum? Do you see big progress from China? They do it very, very well. So I think one of the top country is China, the United States, of course, EU, Japan. I believe these two, like area, It's pretty, pretty aggressive in terms of form.

And do they share their progress and papers? No, no. They just read ours. Yeah, of course, they post their scientific activity by paper, some of them. But I don't think they share everything. Yeah. Very close to the vest. Exactly.

Yeah, it's a very interesting moment in time. Kazu, thank you so much for sharing with the audience. A big round of applause for Kazu. Thank you. I don't know if there's any crypto and any quantum heads in the audience who have a question. Does anybody have a question? Anything that you can. You do?

Okay. Come and ask a question. We have one question. You don't have to have a question about quantum computers. I'm fascinated by it. And this is like such a treat for us to see around the corner of what you're building. This is like this conversation is literally like talking to Open AI deep mind 10 years ago. Right?

Okay. Question. Hey, that's a great presentation and a great interview. I'm Carthic. We're building Glib Zero Labs. What we're doing is we're building the cryptographic authorization layer for AI agents. And my question is probably two parts. One is right now, because I've done a lot of work in quantum for the last year and a half before starting my company.

And current cost of quantum is really high. Like if you look at SQBM from Toshiba, it costs like $90 an hour. IBM, I think, if you want to rent it. You have to pay like $3,000 an hour. So whatever you're building at Yakumo, how is it going to move the needle? Like, is it going to bring the cost of that down? Or how are you thinking about it from a business model perspective? Like, do you want to sell quantum clouds, like through a partnership with AWS or Microsoft?

Good question. Yeah. Of course. So listen to you, one of my colleagues in Japan. He's not in Yakumo. Sorry, he's not in Yakumo. He's creating one of the type of quantum computer superconducting Kyivet. So he mentioned that one physical qubit cost close to 1 million USD.

It's really expensive. But we use the neutral atoms. And if you're thinking about the price of qubit, maybe it's maybe 100 times cheaper or 1,000 times affordable. So we believe this methodology is pretty scalable in terms of the financial aspects. Yeah, and if you're thinking about our business model as a startup, there's a couple of ways of thinking. However, we're thinking about selling our one who-stack corner computers next five years.

But this is not for commercial use case, it's mainly for academia, we try to use corner computers as a research box. And after 2030, we believe that we can create very useful corner computers, so-called FTQC-44-3-400 corner computers. and we try to sell this corner computer to data center, for example. In that case, we don't have to sell a computer one by one by 10.

You just sell racks. Yeah, exactly. That's bulk. And next five years, after 2035, for example, it's time to think about how to use this corner computer as a data. Yeah, you can do it. Yeah, exactly.

Just like scale AI. Quantum as a service. Yeah, for example. Or, for example, there is one great company had been like M&A by Meta, like, you know, scale AI. Yeah. they'll sell data for AI.

Yeah, that's quantum data and quantum entropy of the service. Exactly. So we might expect those kind things. Got it. That's actually a part of stuff that I'm working on as well. Okay, exactly, why don't we teach us? The second part of the question, do I have time? Yeah, quick. Okay. So you mentioned that RSA is going to be broken, right? But most of the world, including Visa, MasterCard, all these guys use AES 256.

Of course, like hack now, decryplator is going to happen. But wouldn't it be useful if you just blow up the key bit from 256, if you make it AES-256 to like AES 2048 or 4096, you can buy time to let the hackers linger on the network and then use the same quantum computer to like trace them out and figure out what keys they're using to enter your system, right? Like what are your thoughts on that? Yeah, so that's the reason why we believe that cryptography is just one of the applications. For example, I'm very, very, very keen on to the other application, for example, like, you know, quantum chemistry. which is going to create new market.

So that is something we are thinking about. That's interesting. Like cryptography is just one, like, you know, very, very dangerous. But that's a corner combinator company we're thinking about some other more. Yeah, you could also end up building like virtual cells and cell models and revolutionized biology and everything. Absolutely. Yeah, makes sense. Thank you very much.

Very exciting. Thank you. All right. Let's thank Kazu for sharing with us for an hour. Thank you very much. Oh my God. It's so great. Thank you so much for kidding.

I appreciate you. the time.