SPEAKER_00: 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. I 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. But I love coming to Japan. If you're a founder or an investor and you're in the This Week in Startups or the launch or syndicate family, you can join us for Angel University. You can apply for that. We do that twice a year here in Tokyo. If you're a founder, you can apply for founder.university website. You'll see Japan. You'll see Riyadh in Saudi Arabia. And then you'll see the US edition. You can come to any of those editions. You can apply. It's a bit competitive to get in. We like to look for teams of two or three founders. For Founder University, you don't even have to be incorporated yet, but you should have a project, a product in market, maybe one customer, a pilot. And then for our launch accelerator, you need to have a couple of customers, and that's where we invest in companies. And finally, we have thesyndicate.com, where if you're an angel investor, you can join. And twice a month or so, we share one of the deals we're investing in it and with you. And as an angel investor, you can put as little as $5,000 or $10,000 into a deal, well below the cap or the minimum that most founders charge. SPEAKER_01: So, you know, join us for any of those programs and make sure you subscribe to This Week in Startups as well on your podcast player. When I'm in Japan, my team looks for the most successful, the most inspiring founders for me to meet while I'm here. And we're very lucky today. We have Kazu Nakashogi. Nakashogi? SPEAKER_02: Yeah, absolutely. SPEAKER_01: Oh, I got it. And you're with a company, Yakumo. Yakumo. Yakumo, which is spelt Y-A-Q-U-M-A. And you're building quantum computers. SPEAKER_03: Hardware. SPEAKER_01: Yes, hardware. And hardware is? Hard. Hard, yeah. Hardware is very hard. Quantum computing has been five to 10 years away for the past 30 years. SPEAKER_05: Why is it taking so long? SPEAKER_07: That's a really good question. SPEAKER_08: And more self-difficulty part is coming from hardware itself. Ah. Yes. So we try to generate very special caricature units, QPU, quantum processing units. SPEAKER_10: Quantum processing units? SPEAKER_08: 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 carications. SPEAKER_00: And from my understanding of qubits, SPEAKER_01: this is instead of one or zero, Yeah. you get to have one, zero, or neither, Chamath Palihapitiya: one or zero. SPEAKER_15: At the same time. SPEAKER_01: At the same time. SPEAKER_15: Yes, superpositions. SPEAKER_01: So you could have each of those positions simultaneously. SPEAKER_18: Technically, yes. SPEAKER_01: Technically, yes. Yes. So explain to, you know, founders in technology who use GPUs and CPUs all day long, SPEAKER_21: 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? SPEAKER_08: Thank you very much. So, first of all, I think there is some big misconception about quantum computers. Okay. Once we use quantum computers, maybe people believe that, oh, maybe we can do more nice, very fast carications compared to CPU or GPU. But this is, first of all, it's not correct. Ah. Yes, we can apply quantum computers for particular questions or problems. For example, combinations or like RSA, Cliptor. Yes. Those kind of difficult questions. We can only, we can apply those kind of problems to quantum computer or quantum caricatures. SPEAKER_01: And we saw Google and Microsoft and some other quantum computer companies went public over the last SPEAKER_17: maybe two or three years. Exactly. Lots of excitement. Of course. SPEAKER_21: And we had the same wave of excitement five or ten years ago, but it seems like it's getting closer and closer SPEAKER_01: 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. SPEAKER_40: Yes. SPEAKER_01: So when do they have enough power and enough software and maybe the compilers and the tools SPEAKER_00: have to be built as well, I understand, to actually make it accessible to founders at startup university. Yes. Or startups at founder university. SPEAKER_08: Of course. Of course. So that is a really, really important question. Yeah. So there's two ways to understand these circumstances at the same time. So first of all, if you're looking at question or some kind of programs that quantum computer is going to solve. In the past, for example, five years ago, people believing that we need one million qubit QPU to solve some certain problems. But recently, that number is drastically decreased. Oh, okay. Yeah. Across to, for example, 10,000 qubit. Got it. Just 1% of what we expected 10 years ago, for example. Since we updated some software algorithms or some other schemes, for example. Besides, in terms of the hardware, looking back, for example, 10 years ago, we only have maybe 1 to 10 qubit. Wow. Wow, it's super tiny. That's it. SPEAKER_58: Super tiny, but recently, it's less than SPEAKER_59: like a punch card from an old computer. SPEAKER_58: Exactly. But recently, for example, one of the United States SPEAKER_08: University demonstrated 6,000 physical qubit. Wow. It's amazing. So what I mean is like the number we need for doing actual allocation is decreasing. The number of the physical qubits is close to that numbers. So we believe that we reach to like two of them meet each SPEAKER_07: other close to 2030, for example, in next four to five years. SPEAKER_01: 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? SPEAKER_08: Of course. We can imagine that. And some of the quantum computers are already installed into data center already. Yes. For example, in Japan, there's one SPEAKER_01: 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's maybe fragile or brittle? SPEAKER_68: Yes. SPEAKER_69: So why is it fragile or brittle? SPEAKER_08: Yes. Thank you very much for the question. So once we do quantum calculations, SPEAKER_58: they made a lot of error. For example, every thousand times, every hundred times, they make error. Oh. SPEAKER_71: Yeah, it's a problem. SPEAKER_58: It's a problem, right? Yeah. SPEAKER_08: And this is a big problem. So we have to correct this error. So-called, we call it quantum error collections. SPEAKER_72: Ah, quantum error corrections. SPEAKER_08: Exactly. So we call it QEC. And by doing so, we have to protect the information that qubit has. So by doing so, we can create very scalable, very robust quantum computer. So this is a recent approach the human being trying to take. Got it. SPEAKER_76: Did you ever notice how you spend hours shopping online, then pause before you actually hit buy now? That tiny hesitation where you wonder if this is trustworthy, can make or break a sale. And with AI changing how we discover and compare things, that split-second trust question matters more than ever. That's exactly where PayPal comes in. 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And they're like, I've never rebooted my computer, I've had it 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 sluggish, Chamath Palihapitiya: memory leaks, and you have to unload one program to run the other. It reminds me of what you're going through right now. SPEAKER_89: Yeah, that's true. That's, yeah, SPEAKER_08: definitely right. So probably what we expected, experience like 60 or 50 years ago for classical computer we experience in the quantum computer at this moment. SPEAKER_01: Now you're doing something different at Yakuma. Yes. With the chemicals or the material science, yeah? SPEAKER_95: So you're talking about application or hardware? No, the hardware itself is slightly SPEAKER_01: different, or it's advanced and they're using different materials now, I understand. SPEAKER_95: Yeah, thank you very much for asking SPEAKER_08: 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 SPEAKER_97: kind of CPU, SPEAKER_08: this is like most of the CPU is created by silicon, right? But maybe 60 or 50 years ago, I don't know, we try to use vacuum chamber to do curriculation, 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. SPEAKER_101: The quantum processing unit. SPEAKER_08: It's QPU, exactly. So for example, Google or IBM, this kind of large amazing company tried to create QPU by super conducting SPEAKER_78: qubit. SPEAKER_102: Super conducting qubit. Yeah, that's why SPEAKER_78: they have to put those kind of chips into huge refrigerators to make it super super chill. SPEAKER_102: It has to be super chill. SPEAKER_08: Absolutely. And some people try to use ions which have a charge like plasma. SPEAKER_104: Ions, yeah, like plasma. SPEAKER_58: Yeah, they have charge. And we use atoms, SPEAKER_08: neutral atoms. We don't have any charge. We try to configure or try to create array of the atoms in the vacuum chamber to use one atom, an atom as a qubit. Got it. Yeah, and some people try to use buttons or semiconductors to do content fabrication at the same time. But there's so many very severe like you know companies can happen in this moment. SPEAKER_00: So let's talk about this is your first startup company building. Yes. We have some hardware startups here. Hardware is hard. SPEAKER_113: You've picked the hardest of the hardware because you have a five-year window to commercialization SPEAKER_01: maybe. And you came out of a university. Yes. And your company is based in So you get to have a beautiful life, a beautiful city. Thanks. And all that talent from Kyoto University. SPEAKER_115: Some of them. Yes. SPEAKER_01: Yeah. So you came out of the university. Explain to us how technology in a university, how they do the IP transfer into 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 capitalists specialize or investors specialize in 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? SPEAKER_117: Yeah, of course. SPEAKER_01: Or is there a term for taking IP out SPEAKER_118: of the university, like a technical term or a term SPEAKER_105: of art? Do you know one? Probably. I'm not super familiar with the situation in the United States. SPEAKER_58: Got it. But compared to overseas, Japan or Japanese universities have not SPEAKER_08: so much experience as to use IP as a startup, as a spin out. SPEAKER_120: Got it. Yeah. SPEAKER_08: So it's SPEAKER_120: pretty new here. SPEAKER_08: I would say. So normally we call it deep tech startup. Deep tech startup, sure. Yeah, in Japan, which is SPEAKER_58: used in IP coming out from university. Right. And at this solid methodology how to use IP from university to startup. Some people choose stock options, pay for university. SPEAKER_123: So the university can get some equity. SPEAKER_124: Exactly. SPEAKER_01: 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 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 re-investment. So it becomes evergreen. SPEAKER_111: I hope so. SPEAKER_01: And this is a negotiation that occurs between the university and the founder yourself? SPEAKER_111: Exactly. Tough negotiation to be honest. Oh, is it tough negotiation? Sometimes it's not easy. SPEAKER_01: 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 IP. Of course. SPEAKER_113: Yeah. Let's talk a little bit about how you've raised over $10 million for the SPEAKER_01: company. You got some grants. You have some venture capital. You've done a seed round. How do you think about runway? Most companies here, if they're building software or maybe consumer hardware, they can think about 12 months 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? SPEAKER_08: Thank you very much. So that's pretty subject to the type of the startup, of course, hardware startup, SPEAKER_58: software startup. But for our case, we expected for example, 18 months runway after the week. We just completed our seed extension round. Oh, congratulations. Just last month, we have been invested by All Night Ventures for United States. Which one? All Night Ventures. Oh, great. Yeah, SPEAKER_07: yeah, yeah. And that was, to be honest, that was their first investment to Japan. SPEAKER_01: Oh, wow. Yeah. How did you meet an American VC and convince them to invest in a company in Japan? Tell us the story. SPEAKER_58: Thank you very much. So, we spread the round into two pieces, seed round and seed extension round. So, seed round, this company is now from Kyoto University. So, that's why we have been invested by Kyoto iCAP. It's sort of CBC coming from Kyoto University. And they have a bunch of networking in the EU or United States. So, they nicely connected me SPEAKER_139: to All Night Ventures. And, yeah, and there's SPEAKER_113: a group that was able to put you in touch with them and that venture firm had shown SPEAKER_01: interest already? Yes. Or they cold-called them? SPEAKER_58: Oh, yeah, they have soft connection to All Night Ventures. And they connected to me to All Night SPEAKER_142: Ventures. SPEAKER_01: Are you a Japanese company or do you file as 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. SPEAKER_137: So, based in Japan. Based in Japan? Based in Japan. There's no launching overseas. SPEAKER_113: So, you don't have a corporate entity in the United States? Yes. Or you do? No. No, okay. So, you have to be here. So, that wasn't a blocker for the venture firm? They figured out how to do it? SPEAKER_58: Oh, I don't think so. It cannot be a super, super big deal. Oh, got it. Yeah, I guess. And we also have an investment from the VC named Coin Nation. SPEAKER_08: As you can see from the name of this VC, this is a top VC for corner computer hardware from World War. So, SPEAKER_78: they came from France. That was their first investment to Japan at the same time. David Friedberg: Got it. And did the venture capitalists come visit you for the board meetings and SPEAKER_152: times a year? No, no, no, no. It's like we talk online business. Oh, okay. Online business. But I've been... SPEAKER_153: See, that's the opposite of me. SPEAKER_01: 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, also to meet great founders. But I was coming anyway for skiing in January. SPEAKER_158: 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 Digital Ocean 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 all together. 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. WorkAuto runs a trillion automated workloads on Digital Ocean with 67% lower inference cost, 79% lower latency, and it's two times faster to production. If you want to understand what building on a true AI native platform looks like, go to do.co slash twist. That's do.co slash twist. Start building on the Digital Ocean AI native cloud today and cut your AI workload cost by up to 50%. That's do.co slash TWIST. Even SPEAKER_161: Niseko for example? Chamath Palihapitiya: I like SPEAKER_01: to go cat skiing. You know the tractor that goes up the mountain? 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. Got it. And then people get disappointed. There's an abandoned ski resort. SPEAKER_162: Really? SPEAKER_01: In Japan? There's many. Really? Wow. There used to be 1,000 ski resorts. Now there's maybe 300 or 400 active ones. 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 moved to the city. So in those local resorts some of them shut down. So an American fell in love with this resort outside of Niseko. 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. SPEAKER_00: Every year he went to the city council to the elders and said hey I 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 curry and nice ramen. And then they have two cats with eight seats in each. They drive you up the other eight runs. So one run for the locals the other runs are broken down. They drive you up. It takes 15 minutes to go up. SPEAKER_175: And SPEAKER_00: then it takes 10 minutes to go down. And David Friedberg: you do eight runs in one day. $1,000 a day. SPEAKER_176: $100 a run maybe. SPEAKER_177: But it's worth it. Because every run is fresh SPEAKER_180: Oh no SPEAKER_177: right. Beautiful. SPEAKER_181: Do you ski or snowboard or neither? SPEAKER_58: I know I was born in Bangkok. I was raised up from Malaysia. So maybe I'm not super super familiar. It's a SPEAKER_00: dream. And then unfortunately years ago I talked about it on the podcast. And then other people talked about it anymore. So now some of the locals are not putting them they don't put an English name on the restaurant. SPEAKER_187: And SPEAKER_00: they hide the address more. So SPEAKER_187: only locals. SPEAKER_01: And some of them have signs now only local. But in Japan in Niseko there's now at Niseko the actual 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 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 Kyoto SPEAKER_58: yeah so that is really important question as a startup at this moment the size of the company is close to 70 we just launched this company 15 months ago so 2025 April and most of them are tech side I mean engineers scientists or we also hire mathematicians who is like you know very capable so one to two SPEAKER_199: hires per week oh SPEAKER_07: yeah sort of yeah yeah that that's the biggest job for me to be honest hiring the people SPEAKER_116: got it and how many of the 70 are Japanese or recruited to come SPEAKER_202: and SPEAKER_58: interesting point SPEAKER_78: is that there is three divisions under the CTO who is managed and of course tech side two of them to head of three divisions non-juck nice SPEAKER_205: got it yeah so one of them coming from Sydney SPEAKER_207: from Sydney yeah beautiful SPEAKER_07: yeah he he's very talented I want to work with him I went to Sydney I need good excuses to that beautiful city SPEAKER_58: that's great yeah yeah SPEAKER_211: Sydney is one of my favorite cities yeah SPEAKER_58: so beautiful and the other guy is coming from Turkey in Turkey yeah so SPEAKER_01: 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 culture change for them yeah SPEAKER_214: rock paper scissors yes no no anyways yeah SPEAKER_181: it's just joking but SPEAKER_58: I think Kyoto have a very great advantage in terms SPEAKER_78: of the beauty of the city yeah very chill and we had a spin out from Kyoto University and Kyoto University have a very profound research background history we use neutral atoms but one of the professors coming from Kyoto University his name is Yoshiro Takashi he studied neutral atoms SPEAKER_58: for example YB 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 percent of the fundamental scientific study of the Etoribian so that professor is very famous and at the same time an interesting point selling point about this company is that we try to integrate two entities research output SPEAKER_78: one is Kyoto University one is coming from IMS IMS stands for Institutional Mercury Science in the IT SPEAKER_58: landscape landscape oh why don't we make one startup SPEAKER_221: these two extraordinary professors researchers scientists SPEAKER_116: so now you've incorporated them into the startup there advisors board members advisors advisors SPEAKER_139: yeah so this is one SPEAKER_78: of the great history behind this company and many people know that these two professors co-work SPEAKER_58: together so SPEAKER_225: they're rock stars and it draws talent yeah SPEAKER_58: very talented two professors so we closely work with two entities Kyoto University and IMS and I would say this company is from Kyoto 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 SPEAKER_01: and so is your intent to build the entire computer or be part of working with other companies building computers and empower them as a provider to them SPEAKER_229: very very good very good question very SPEAKER_58: good question so I believe that our neutral quantum computer yeah yeah yeah it's something like car automotive car yeah and we try to become the quantum computer company something like Toyota so if you're thinking about Toyota they don't create tire no they don't create engines they design everything integrate everything to one and sell that car got it into the market same so we are the corner computer company try to assemble the lasers vacuum chambers monitors whatever so SPEAKER_01: there are many people building these components now exactly SPEAKER_181: co-work together SPEAKER_01: where where are they all based and are they SPEAKER_181: also centered around universities you're always asking a very very good question so we use neutral atoms SPEAKER_07: and most important device for this corner computer is laser SPEAKER_58: very high power laser very not less noise lasers so high fidelity exactly I like that high fidelity lasers and this is coming from Hamamatsu Japanese company and they also have an amazing subsidiary company in Copenhagen in Denmark SPEAKER_242: in Denmark in Denmark of all places SPEAKER_07: yeah but it's like no wonder since news war one of the like an amazing SPEAKER_58: scientist from Denmark and Denmark is very very strong capability in terms of physics and that company name is Indicative Photonics they're creating amazing high power lasers and recently our company and Hamamatsu Photonics and Indicative Photonics did nice MOU in between Denmark and Japan try to create special devices for neutral atom basis quantum computer I mean this kind of supply chain is very crucial for industrialization of quantum SPEAKER_246: 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 let's say you want to focus on talent retention just ask Rippling AI who are my top performers this year you'll instantly get a workforce report comp ratios performance reviews engagement metrics all the data you 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 SPEAKER_247: so many different people around the world are SPEAKER_00: working together to try to hit this vision is something happened in the SPEAKER_01: 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 SPEAKER_07: yeah thank you very much so so called we call it AI for quantum and vice supposed SPEAKER_58: quantum 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 we use quantum computer as I mentioned error happens and we have to estimate what kind of error happened by through classical computation so and through this kind of activities we definitely use we already use a lot of AI transformer SPEAKER_07: for example to do quantum error collection so this is something very tangible example of the AI for quantum got it SPEAKER_261: right SPEAKER_07: and just SPEAKER_73: doing that error correction yeah SPEAKER_152: that's like the SPEAKER_07: most like and it's so powerful now very very powerful because of the AI and opposite side so quantum for AI so at SPEAKER_58: this moment there is 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 SPEAKER_78: quantum for AI happens we believe the future is not super far away SPEAKER_01: 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 impact could quantum have on that SPEAKER_252: yeah so for example SPEAKER_58: very very interesting example is that after we do calculation of by SPEAKER_78: using quantum computer result coming from them for example if we do fluid dynamics calculation by using quantum computer that data or result is not normally coming from the classical computer SPEAKER_58: isn't it this is only coming from quantum computers why don't we use this data to make AI even smarter we can differentiate the model by doing so SPEAKER_270: got it so the models become more powerful SPEAKER_58: I guess so SPEAKER_270: yeah because we're going to be very interesting very SPEAKER_58: interesting I believe quantum for AI once this happens corner computer company makes tons of money SPEAKER_01: 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 SPEAKER_206: very SPEAKER_105: very SPEAKER_58: less really yes interesting yes recently one paper is talking about SPEAKER_78: we find out one paper is talking about the comparison in between classical computers and corner computers as a function of the consumption of the number of the qubits and they mentioned that the number SPEAKER_58: of the qubit is close to 40 or 50 something then we do a particular problem solving the energy that corner computers use even even less than classical computers so in the context of less CO2 less energy we SPEAKER_78: contributing to the are SPEAKER_01: they always going to be very large data center computers or will we ever see the SPEAKER_153: desktop revolution equivalent of quantum computing I know it's a silly question maybe but I'm just curious SPEAKER_07: yeah exactly I would say again I cannot say that SPEAKER_58: quantum computers take over all the position of the classical computers just one part of it but I believe quantum computer could be a very great SPEAKER_276: accelerator to make classical computer even smarter so SPEAKER_277: they would be a hybrid SPEAKER_01: computer with SPEAKER_277: both like SPEAKER_01: a hybrid Toyota Prius so some jobs go to the quantum processing unit and maybe some other SPEAKER_270: parts of the job go to the GPU and CPU they SPEAKER_280: share the loads SPEAKER_270: wow and they could share the memory SPEAKER_58: yes so primary research work happened already in Japan for example in Tsukuba and there is many ways to do demonstration of hybrid system in between quantum and classical SPEAKER_281: fascinating okay final SPEAKER_01: 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 SPEAKER_282: bank account and you take all my bitcoin when will you be taking all of my bitcoin yeah SPEAKER_208: that is really big question so recently one survey SPEAKER_58: revealed that how quantum calculation researchers think about those can decrease for it happen and they mention that in next five to ten years we SPEAKER_267: have to be very careful about it but if you think SPEAKER_58: it's true yeah I think it's true sometimes SPEAKER_153: technologists are a little bit hyperbolic they get a little bit excited like we saw SPEAKER_289: with AI so but it's true SPEAKER_58: yeah it's true so some research works already proving that if you reach to we can solve RSA cryptography but it won't be happen next two years for example no worry it's time to sell your bitcoin yeah plenty of time yeah so but the point is that maybe not only for bitcoin but for for example some like top secret coming from Japan United States yes they already military application yeah absolutely there's kind deal use cases 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 so they have SPEAKER_294: the data they just haven't cracked it yeah SPEAKER_58: and once they create corner computer uh-huh so take now solve later oh wow so SPEAKER_59: get the get the hard drive now crack it later put it SPEAKER_295: on a shelf exactly it was very dangerous SPEAKER_59: and SPEAKER_01: so is there an international body or has the government gotten involved and created a regulatory body that's in any way SPEAKER_113: monitoring your progress and do you get a knock on the door that says hey you know we need to have a conversation SPEAKER_208: yeah that's that that that that is really important uh like uh topics SPEAKER_58: that this kind of they all use or like you know corner computer based uh deep tech startup that is really important topic uh we talk with government of people very carefully and uh for example United States recently announced that they tried to launch or they want to have a very useful corner computer by 2028 it's aggressive pretty aggressive and so in order to nicely communicate this government of people we we are very happy to discuss our or we want to SPEAKER_53: talk transparently with government of people how to use it how to protect the technologies yeah yeah that is very SPEAKER_153: important the world is very dynamic yeah exactly it's SPEAKER_01: a 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 SPEAKER_221: doing SPEAKER_58: very SPEAKER_78: pretty aggressive in terms yeah SPEAKER_25: do they share their progress and papers they don't they just read ours SPEAKER_58: yeah so they of course they post their scientific activity by paper some of them but I don't think they share everything yeah SPEAKER_311: very close to the vest SPEAKER_58: exactly SPEAKER_116: yeah it's a very interesting moment in time Kazu thank you so much for sharing with the audience a big SPEAKER_153: round of applause for 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 you do okay come and ask a question we have one question you SPEAKER_01: don't have to have a question about quantum computers I'm fascinated by 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 SPEAKER_322: hey that's a great presentation and a great interview I'm Karthik we're building Glib Zero Labs SPEAKER_324: 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 SPEAKER_208: listen to one of my colleagues in Japan he's not in Yukumo SPEAKER_78: he's creating one of the superconducting qubit SPEAKER_58: so he mentioned that one physical qubit costs close to one million USD it's very expensive but we use neutral atoms and if you're thinking about the price of qubit maybe it's maybe 100 times cheaper or 1000 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 couple ways of thinking however we're thinking about selling our one full stack corner computers next five years but this is not for commercial use cases it's only mainly for academia who try to use corner computers as research works and after 2030 we believe that we can create very useful corner computers so called FTQ C4 corner computers and we try to sell this corner computer to data center for example in that case we there one great company have been by scale AI they sell data for AI yeah that's quantum data and quantum entropy as a service so we might expect those kind things SPEAKER_336: got it that's actually a part of stuff that I'm working on as well the SPEAKER_324: second part of the question do I have time or yeah quick 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 decruple later is quantum SPEAKER_322: computer to trace them out and figure out what keys they're using to enter your system right like what are your thoughts on that yeah SPEAKER_58: so that's the reason why we believe that cryptography is just one of applications for example I'm very very very keen on to the other application for example like quantum chemistry which going to create new market yeah so that is something we are thinking about like cryptography is just one like very SPEAKER_08: very dangerous but that's corner computer company we're thinking about some other more yeah you could also SPEAKER_322: end up building like virtual cells yeah and cell models and revolutionized biology and everything yeah makes sense all right very exciting SPEAKER_153: thank you all right let's thank Kazoo for sharing with us oh my god so great thank you so much for coming I appreciate you taking the time