WEBVTT
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Hey, my name is Eva, and this is Blondon Quantum, the podcast that breaks down quantum technology into real-world business impact.
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Here we make the complex simple.
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No equation, no overthinking, just insight, innovation, and a bit of key log.
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So don't worry, you don't need a PhD in physics to follow.
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In each episode, I talk to funders, scientists, and investors about how quantum is reshaping the industry's today, not in the long distant future.
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Oh and if you heard a black cat boring in the background, that's my coffee.
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A very alive cat joining the conversation.
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Her name is Mun.
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Let's get started.
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Welcome everyone in the next episode of the startup series of a blunt and quantum.
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Today with me is the CTO of Orca Computing from the UK, Tien Wynn.
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Hey Tien, uh or T, as you prefer to be called.
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Thank you so much for being here today with us.
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Well, thank you so much for having me.
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Great.
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So, Tien.
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T.
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So obviously Orca Computing is building photon-based quantum computers.
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Um, but let's imagine that I'm a CEO with a zero physics background.
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What problem does Orca computing actually solve for me?
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Right.
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Well, I would imagine if you're a CEO of a large corporation, right, you have a lot of a lot of uh areas that you must be an expert of.
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Um but in general, you know that you need to be aware of some of the transformative capabilities of quantum computing technologies, and you want to understand how that maps to your business functions and what you care about as a business.
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Um so what Orca does is that we actually really facilitate that adoption, integration, but also utilization of quantum technologies for your business operations today.
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And so, unlike a lot of other companies, what we really focus on is delivering a product that is easy to use, easy to purchase, and easy to install.
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And we also have our engineers, our machine learning scientists on our end who will work with your team to help you understand how to build these quantum algorithms.
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Because at the end of the day, this field of hybrid quantum classical algorithms and technologies is very new, right?
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And we don't really expect any of our customers to be experts.
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Hundreds percent.
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And I'm glad you mentioned it because I think the biggest companies, the enterprise company, 500 versions, they already have the quantum teams, but that's not necessarily mean they are developing when if they have access, right?
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Um, through bracket or if they bought quantum computer or so on.
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So, yes, okay.
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But before we go to those details and talk a little bit more about the customers of yours and your very unique philosophy, because I think it's unique comparing to the other quantum companies.
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You guys are focusing much more on commercialization than just being in the lap and science and so on, right?
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So we're gonna talk about it in a second, but I want to ask you um, for the benefits of the audience, to explain a little bit more about the modality that you are guys are in.
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Um, because you chose photons over other quantum approaches.
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So why so?
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Why why photons?
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How the company started.
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If you can tell us a little bit of the history, right, sure.
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So the the company started in 2019.
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So we're a spin-out from the University of Oxford, Professor Ian Wamsley's quantum optics group.
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Um it with their focus is of course on optics.
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You know, we we made the very mindful decision of building a full-stack quantum computing company based around photonic qubits because of the intrinsic and inherent advantages of using photons as opposed to any other uh qubit modality.
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Um so primarily the coherence time for photons is very long.
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And more importantly, it's a much more practical or pragmatic qubit to be deployed as a commercial system.
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So the systems that we are able to build using photonic qubits can operate at room temperature.
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And then using optical fibers, which is already a very mature technology, we actually are blessed with the ability to have a highly connected network between all of our different optical modules that is also a very modular network.
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And that allows us, what that allows us to do is allows us to build and uh deploy these systems today and then scale them both in terms of our technologies, but also in terms of the products that we deliver to our existing customers over time by upgrading in place uh many of their systems to higher performant versions of the modules.
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Exactly.
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And uh a lot of experts are actually emphasize the fact that photon-based quantum computers may be very scalable in the future, or even the most scalable from across the all modalities.
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From the other so that's the the biggest advantage, I believe.
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But what's the bottleneck?
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What is the thing that haven't been solved yet in in terms of photons?
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Right.
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Well, you know, of course, every every component needs to be improved.
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But I would say that the number one metric that we, but also all the other photonic quantum computing companies are solving, is how to build this optical network of modules while still keeping the losses to near zero.
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The way that a photonic quantum computing works is that you have components at the beginning, which are your source components, generating these single photons, and those single photons transit through the network.
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And at the end of it, you need to detect and measure the state of all of those entangled photons.
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And so we can't uh really afford to lose too many along the way.
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Okay.
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And you mentioned previously that.
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So I want to also dig a little bit deeper on it because you are the quantum component that already ships the machine, which is already super unique, right?
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Not many, many components are doing it.
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But once you're shipping it, you can also plug them into existing data center, from my understanding, if that's correct.
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So you mentioned that there's no cryogenic cooling needed because you run it basically in the room temperature.
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So can you tell us a little bit more why this is a big deal and why this is really important and why this is useful?
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Well, I want to clarify that from the perspective of our customer, what we deliver is that we deliver these standard 36-inch racks that are filled with these optical compute modules that are networked together as a quantum computer using optical fiber.
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So, from the perspective of our customer, that black box operates at room temperature.
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So, what that means is they don't need to then build infrastructure specifically around our hardware to keep certain components or certain modules below a certain temperature.
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Um, and this is really important when you're actually delivering these products into functioning data centers, because data centers don't have the luxury if they're already operating, right?
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They don't have the luxury to shut down operation, to build the infrastructure that has your technology, and then to bring everything back up again.
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Um and then, in of course, in greenfield applications where the data center is being built from the ground up, of course, the less requirements that you place on the infrastructure of that building, the easier it is to deploy, the more cost-effective that data center will be.
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So is photonic then inherently more scalable or just differently difficult?
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Yeah, in a lot of ways, photonics is more scalable.
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I mentioned that we are able to leverage the very mature technology of interconnects using optical fiber.
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And that's really what allows it, that's really what allows us to scale horizontally extremely easily.
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Um, you can imagine that if you have, for example, one very good quantum light source, you can then replicate that horizontally to maybe tens, hundreds, or even thousands of these quantum light sources and then just integrate their output all together using optical fiber and some muxing switches.
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This is so cool.
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And when the mic was up, you mentioned that um you mentioned that Orca has this core philosophy to deliver quantum technologies to the customers early and often, right?
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Which means that you're going beyond the research and building uh true product, right?
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Which uh you are already selling.
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So let's talk about this because this is very exciting for me and I hope for our audience as well.
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Many even you know publicly listed companies are still working on the technology, they are far, far from thinking about commercialization.
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And you're much smaller, you're raising right now, so you and we're gonna come back to this as well, and you are already, already selling.
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So tell me a little bit more about the philosophy and tell me as well who are your customers.
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Yeah, absolutely.
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So quantum is undeniably hard tech and deep tech, right?
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And I think that a lot of times startups in the hard tech and deep tech space are very proud of, as they should be, very proud of their underlying technology.
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But in my opinion, they focus too much on that underlying technology and they spend too much time perfecting that fundamental technology before they even let anyone else see it.
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But similarly to how it's a very long path going from a good idea to developing a good technology, there's an even longer and more perilous path, bringing a good technology to a good product.
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And oftentimes there's a lot of challenges along the way that maybe people will hand wave and just say, oh, don't worry about it.
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It's just an engineering problem.
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Well, I can tell you right now, most of the hard issues that we're tackling are engineering problems in order to deploy and scale up these quantum technologies.
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Like it's not just an engineering problem, that is, that is a big part of the of what needs to be solved.
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And so our philosophy is to think, okay, well, we're going to lean into our strengths as a photonic quantum computing company, which gives us the ability to build these systems sooner and deploy them more easily and more cost-effectively effectively to our customers.
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And then by doing so, we actually have a great symbiotic relationship, right?
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Our customers then become our collaborators and our partners as well.
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And so together, right, we are learning from our customers in terms of how they're using our system, what kind of applications they're looking at, and we roll that back into developing the next generation of uh modules and products that we then deliver back to the customers.
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And so we have this very back and forth relationship that helps us both figure out this in this fog of potential futures, what's the best path forward together?
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This is very unique and very beautiful because you're basically following the standard startup pathway of iterating very fast and validating that with the customer, right?
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Which I would say most of deep tech companies are not doing and they're getting dispensed even from the venture capital because, like, oh, because it's so deep tech, you needed some time and so on and so on, right?
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That's why we we we do have um even you know publicly company, not only in quantum, but also in different deep tech verticals where where they do not commercialize yet, we need not sell or or make money really.
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So this is very interesting.
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So let's just talk about it.
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Who are your customers?
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Who are you selling?
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Who is buying today quantum computers?
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Yeah, that's a great question.
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The thing about the quantum computing space is that it's not, you know, it's a new technology, but it's an existing market.
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So all of our customers are exactly identical to the customers of traditional and classical high-performance compute architectures.
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So, you know, we have members of our team from uh Craig Computing, right, which is a traditional HPC company.
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And so we we engage with a lot of the same customers, right?
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Whether they are D labs for corporations, whether they're national labs, or whether they're uh data centers.
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So all three of those categories.
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And so far, can you can you draw some names for us?
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It is not a secret.
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If you have NDAs, then I then but it would be great.
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Yes, I think some some we're not allowed to we're not uh disclosing publicly yet.
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You know, I think we've announced that we've delivered systems to the NQCC, for example, which is the National Quantum Computing Center over in the UK.
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And also uh we have a great collaboration with the the PSEC over in Poland.
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And actually in that data center on Polish.
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Yeah, great.
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We we love we love uh we love the PSEC.
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And in that project, actually, it shows an example of a very symbiotic relationship where we have delivered systems to their data center, and beyond that, we've been working closely with their team, but also with Nvidia to stand up the the world's first multi-user, multi-GPU, multi-QPU environment that works seamlessly together as one system.
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So we actually have some publication that we'll be releasing about that in the congratulations on that.
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I think it's a huge success, and again, it is so unique in quantum worlds.
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I understand that some of these projects related to defense and so on may not be public and they should not be public for many reasons.
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But uh, if you can give us a little bit of spotlight on working with British government, because I think it's it's a very unique experience, and also the British government choose a different path.
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They don't invest directly like some other governments in Europe, but they offer those contracts.
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So please tell us more.
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Sure, yeah.
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You know, we we work very closely with the British government through multiple different grants and programs.
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I mentioned that we've delivered a system to the IQC.
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We've had previous projects as well, working with DSTL and some other arms of the UK government as well.
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But you but you know, I think fundamentally in terms of working with them, it's very similar to whether we're working with the UK government or whether we're working with um a larger company like uh EY or BP, right?
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So from your perspective, there's no difference.
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Project is project, client is client.
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That that's right.
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Well, it it's the same because they are all very eager, right, to incorporate quantum technologies into their workflow, into the work that they're already doing, but they also don't quite know how, right?
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And this is this is uh even if they have quantum machine learning experts on their team, right?
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And and uh it's just because the space is too new, right?
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There's just too much that we don't know about the underlying technology, and there's still too much to be explored in terms of well, what can we do with this technology?
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That's why I think all the governments are are just in the race right now, and and that's beautiful.
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But yeah, I was just just curious about this experience.
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Okay, so speaking about the use cases, even for the commercial client.
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Can you can you tell us more about it?
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Well, sure.
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Um, I mean it's it's pretty much everything under the sun, right?
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So we've had the opportunity to work with a lot of different commercial entities already in helping them understand, you know, how our technology works, how to interact with our technology, how to integrate our technology into their workflow, and then what they can do with it, right?
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So we've had multiple, you know, many, many different collaborations.
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Some notable ones are um a collaboration with BP, where we utilize our hybrid classical quantum uh generative AI models to solve the molecular confirmation problem, which is a computationally intensive problem.
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But we are using our hybrid architecture to attack it from a little bit of a different angle so that we can get to the correct answer more quickly.
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And another really exciting one, one that I think is personally extremely exciting, is our collaboration with DTU, which is a uh university over in Europe.
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And this is for this is for uh peptide generation.
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So what we were able to show with their team, right?
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So this is a collaboration, right?
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We're obviously not the experts in peptide generation.
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Through through this collaboration, we're actually able to demonstrate that we're able to accelerate and improve de novo peptide generation.
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So this is the construction of drugs essentially from the ground up, right?
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From first principles.
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Um and this is particularly useful for therapeutics.
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Um so you know, we we were able to demonstrate that our quantum-enhanced gen AI can outperform classical models, specifically and you know, specifically and interestingly, in designing highly immunogenic peptide uh peptides.
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So peptides that have the ability to help you, right, once uh once ingested.
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This is actually fascinating, and thank you for mentioning it because you know, whenever I speak with an industry expert, they're telling me that um, you know, pharma is one of the uh areas beneficial sides of quantum or should be or supposed to be and so on.
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But on the other hand, I hear a lot as well about gas and oil.
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You just mentioned the cooperation with BP.
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I spoke previously with Pascal and they had the cooperation with Saudi Aremkov.
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So it seems like you know, there's two cooperations there than gas and oil, and I see only one so far mentioning by you real use case on uh on the on the pharma.
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Which university was that that you mentioned?
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Uh this is DTU.
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DTU.
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Okay, where are the where are they based?
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They're in Denmark.
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Okay, yeah.
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Makes sense.
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Yeah, well, Denmark is actually I have heard, I'm not sure this is true.
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I have heard that Denmark actually have the biggest number of quantum engineers in the whole Europe.
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I've heard that too.
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Yeah, it's uh so either there is something in it or they have a good P.
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I had a chance to visit their their center um a couple of years ago.
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It was it's really, really impressive, and the government really also put a lot of a lot of emphasis on.
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Okay, but T.
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Let's assume that I am 500 fortune companies already who are interested in orca system, or maybe let's say interested in buying a quantum computer.
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Where is where does Orca computing win versus if I will compare you obviously with the other players on the market, like IBM, INQ, or even SciQuantum, which is the same the same modality, where do you win or where do you potentially may lose?
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Yeah, I would say that the most the the biggest advantage that we have, and you mentioned Fortune 500, and um I'm not going to name the name right now, but we we did recently deliver to a global Fortune 500 company.
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Congratulations, congratulations, so what will be the announcement?
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Sorry?
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When when we can expect the announcement.
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I'm not too sure.
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I'll leave that up to uh for for speculation and to build up some mystery for later.
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We're gonna observe the press once it's out, and please ping me as well.
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I would love to feature that as well.
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And congratulations, by the way.
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Thank you.
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Um but I think the main thing is this, right?
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When people talk about quantum computing technologies, especially if it's just a very uh initial conversation, there's only really one question, right?
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And in my opinion, it's actually the least relevant question.
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So the one question is how many qubits is your system, right?
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And the reason why people ask how many qubits a system is, is because the world of quantum is too complicated right now and too and too fragmented, right?
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And so that's the one line that people can draw around everything.
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But fundamentally, right, qubits don't do anything by themselves.
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Even if you make an explicit qubit, but you have a terrible UI, you don't have a compiler, you don't have an operating system, you haven't networked the back end of your quantum computer to Q2Q or to Python or to whatever else, there's no way you can use that qubit, right?
00:18:59.839 --> 00:19:02.400
So, in my opinion, that's not the most relevant question.
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Really, where we shine as Orca is that we are focused on discussing around the applications that we enable, around the performance increases that you can see with our hybrid classical quantum computing systems, and not just about the underlying photons themselves.
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And this is reflected in the engineering and the architecture of our hardware, but also in the ease of use and the maturity of our software SDK as well.
00:19:26.799 --> 00:19:33.839
Um, you know, I mentioned you have a special team helping those clients as well to develop specific use cases.
00:19:34.000 --> 00:19:36.000
How many people do you have right now in that in that team?
00:19:36.240 --> 00:19:40.000
Uh that team is is uh pretty modest at the moment, less than 10 people or so.
00:19:40.240 --> 00:19:46.480
But we need we are looking to grow uh that team, but also other teams after our next fundraising round as well.
00:19:46.720 --> 00:19:48.960
Okay, after you finish the fundraise.
00:19:49.279 --> 00:19:51.839
Okay, uh, which is in a couple of months, right?
00:19:52.000 --> 00:19:52.400
That's right.
00:19:52.480 --> 00:19:52.640
Yeah.
00:19:52.880 --> 00:19:53.359
Yeah, okay.
00:19:53.440 --> 00:19:59.200
So, guys, if if there are an investor on the audience, this is your last chance to be gone.
00:19:59.519 --> 00:20:03.279
Go and ping T on a LinkedIn or over the email.
00:20:03.359 --> 00:20:04.319
That's the last chance.
00:20:04.480 --> 00:20:06.640
Okay, um, so this is very interesting.
00:20:06.799 --> 00:20:09.839
Um, I also want to ask you on the approaches.
00:20:10.000 --> 00:20:11.839
What do you think in terms of the future?
00:20:12.079 --> 00:20:15.039
Would that be a winner takes all market?
00:20:15.200 --> 00:20:20.240
Or do you think that multiple quantum architecture will kind of coexist together?
00:20:20.480 --> 00:20:20.720
Yeah.
00:20:20.960 --> 00:20:22.880
You know, obviously it's hard to tell, right?
00:20:23.039 --> 00:20:33.359
But I would be surprised, I would be very surprised if multiple of the modalities didn't find a footing in the broad cloud computing, in the broad AI world.
00:20:33.599 --> 00:20:33.839
Sorry?
00:20:34.240 --> 00:20:34.799
Why is so?
00:20:34.960 --> 00:20:35.680
Why do you think so?
00:20:35.920 --> 00:20:40.720
Yeah, um, I well, I think we we recently heard about some news recently that was very interesting, right?
00:20:40.880 --> 00:20:45.039
So, you know, everyone let loves to talk about Shore's algorithm, everyone knows Shore's algorithm.
00:20:45.119 --> 00:21:00.880
And it seems like every year, the bar for the capabilities that we need to develop in order to execute Shore's algorithm, the bar keeps going down because very smart people come up with algorithms on how to more efficiently implement that algorithm, right?
00:21:01.039 --> 00:21:12.000
But one key thing that we saw, one key feature that allowed them to essentially compress the algorithm down so efficiently is by assuming all-to-all connectivity between the qubits, right?
00:21:12.240 --> 00:21:24.960
So beyond the raw number of physical or logical qubits, there's also this concept of connectivity that is becoming increasingly important as we consider how many qubits we need to implement what kind of algorithms.
00:21:25.119 --> 00:21:34.160
And depending on the modality that you choose, the degree of connectivity and the speed that you're able to entangle any arbitrary qubits together is drastically different.
00:21:34.319 --> 00:21:49.359
And so, as a function of which kinds of algorithms we develop, which kinds of algorithms and applications we find to be most useful in in this quantum world, that will determine which modalities will will uh eventually win out.
00:21:49.599 --> 00:21:58.640
So I what are you saying basically is that in the future, if I'm a big company, rather than choosing a modality, I will choose per use case.
00:22:00.720 --> 00:23:23.759
attached to specific modality that's that's very powerful and um i want that to emphasize for for our audience as well that you guys if you hear that again like the technology doesn't matter the use cases that you have matter and that will determinate the technology that is used that's very that's very cool okay and then T speaking that we will have a different modality how do you think the world will involve do we do you see the quantum being like centralized in the cloud and we're gonna use it like we today we use a cloud i mean from you know there's amazon there's google there's azure and so on and we know that Amazon already had a very powerful cloud for quantum called bracket that cooperate with many different startups and companies providing access to the quantum computers or we're gonna deploy it on premises in those data centers so how do you think this will evolve in the next 10 years I guess yeah I definitely think we'll have both and we talked about the different features of qubits being driven by the application right there's also the fact of like you mentioned cloud versus on-prem that will also determine which modalities will will get a stronger footing as well.
00:23:23.920 --> 00:23:47.519
So for example it's uh you know we've already demonstrated that we're able to build these uh uh quantum AI accelerators using photonic qubits that are very deployable on-prem uh whereas uh if you look at solutions from um some other modalities their solution is very very uh very involved requires a lot of infrastructure build out and that's unlikely to be deployed on prem.
00:23:47.920 --> 00:23:56.079
Okay so do you think those who are not able to be in the room temperature will high likely be on the cloud and the rest will be both.
00:23:56.319 --> 00:24:12.160
Yeah and of course everybody everyone's working very hard and of course they'll solve their engineering challenges as well but my point is that there will be a delineation between modalities of what they can offer as an on-prem solution versus what they can offer as a as a cloud solution.
00:24:12.480 --> 00:24:51.279
And it's also a matter of cost I guess as well right cost, usability infrastructure build out power consumption all of these boring uh KPIs that uh that we don't talk about enough in in the world of quantum yeah you're right but they are crucial from adaptation right yeah nobody you're right nobody's focusing on them right now but exactly but but the thing is like if you talk to any CIO right from a data that manages a data center or a large corporation that'll be the first question they ask right and so it's it's like we're not we're not really talking on the same wavelength right uh as an industry for the most part.
00:24:51.519 --> 00:24:56.079
Yeah because we are not there yet but it it's it's coming I think it's coming.
00:24:56.319 --> 00:25:05.359
Okay um a little bit change of topic and you mentioned that you already have very interesting cooperation with Nvidia on GPU.
00:25:05.759 --> 00:25:17.359
Nvidia is working also in the synergy of hybrid quantum and classical AI um but so the public information they present out on many quantum conferences.
00:25:17.599 --> 00:25:30.799
I wanted to ask you on your view of that matter on a synergy between hybrid quantum and classical AI how does it actually look like in practice today?
00:25:31.039 --> 00:25:35.119
Yeah so that that's exactly the focus of the system that we're building right now.
00:25:35.359 --> 00:25:45.839
So to be clear the systems that we're building and we're deploying right now are not universal architectures they're quantum accelerators specifically designed for Gen AI.
00:25:46.079 --> 00:26:09.920
Wow wow okay so okay okay so I want you during now to give me um real life example how can I use it as a company where's the defense how can I uh if you can let us know where is the difference on me as a company using uh only separate quantum computers or quantum computers with synergy of AI.
00:26:10.160 --> 00:26:26.319
Right so the difference is in the the computational architecture right so the way that our systems work is that we co-train the classical machine learning model with the quantum model of sorry with the quantum hardware and the quantum output all together it has one.
00:26:26.480 --> 00:26:36.000
And so in operation the way it works is that the classical model will call for inputs from the from the quantum system that was trained all together.
00:26:36.319 --> 00:26:45.200
Amazing so this is like on the hardware level integration I wasn't aware of I thought it was like there would be a software layer on that this is so cool.
00:26:45.519 --> 00:27:01.759
I mean it is software right so we so the the the classical model runs in in software right on hardware but it's in software and at certain points it'll call for an output from the quantum computer measure it and then input inject that as part of the operation of the machine learning model.
00:27:02.240 --> 00:27:02.559
Okay.
00:27:03.039 --> 00:27:28.319
So the way to think about it is that there's certain applications that favor quantum you know uh the the quantum I guess uh mathematical relationships a bit more than classical mathematical relationships and uh by by forming this hybrid system we're able to essentially improve the output accuracy of the Genai models by incorporating some of this quantumness in at strategic points in the neural network.
00:27:29.039 --> 00:27:36.799
And and yeah this is this is a model that we find to be very successful given the maturity of where we are today with our with our technologies.
00:27:37.039 --> 00:28:07.759
Okay so another question pop up as you spoke in my mind so in that case what is needed for for that synergy or integration of quantum and ai to move from a pile up to the production and following on question I'm sorry for that if we already as an industry working on that integration is there a risk that we may skip the adaptation of quantum computer separately just for you know the the integration variant?
00:28:08.079 --> 00:28:09.279
Yeah that's a that's a good question.
00:28:09.359 --> 00:28:11.920
I I I don't think it's so much that you would skip one or the other.
00:28:12.000 --> 00:28:14.240
I think they would just grow into their own applications.
00:28:14.480 --> 00:28:14.720
Okay.
00:28:14.880 --> 00:28:54.079
Simultaneously yeah so you know the the world of HPC and the world of AI is very large right and as we see we're we're starting to get more specialized hardware and specialized algorithms for specific tasks that have high utility right and so as as as the technologies continue to develop and as the technologies continue to be adopted by uh HPC and data centers and and AI factories, what we'll see is that um depending on the specific clientele that that data center is looking to service the specific applications that they're looking to optimize and run, they'll bring in different technologies to um to make that more efficient.
00:28:54.319 --> 00:29:00.720
Now in terms of you know you you asked the question of what would it take to go from pilot to production, right?
00:29:00.880 --> 00:29:04.720
I would argue they're we're we're pretty much on the cusp of production right now.
00:29:04.880 --> 00:29:09.680
But I would, you know, the main thing is just um the same with the with a lot of different technologies, right?
00:29:09.839 --> 00:29:32.000
From the perspective of the data center, are you helping them offer something to their clients in a way that is less expensive from a capex and from an opex perspective right so better performance for less capex and opex than other options they have right and so what that means in the world of data centers is that um you know if they're looking to upgrade their model, right?
00:29:32.079 --> 00:29:47.119
Yeah should they go out and should they purchase 10 more racks of Nvidia GPUs or could they purchase four more racks of Nvidia GPUs plus a quantum accelerator to work with everything in concert and still reach the same performance.
00:29:47.440 --> 00:29:48.640
So that's that's the clocks.
00:29:48.880 --> 00:29:53.599
And I think the question up here will be obvious right we will we'll go for this connection.
00:29:53.920 --> 00:30:18.319
Right right yeah and um you know uh you know we're we're we're working on that right now right so our we have two generations of our PT series out right now PT1 and PT2 and later this year for the for the audience you can explain PT is the name of your computer or accelerator okay that's right so um the PT series is the name for our hybrid quantum classical accelerators.
00:30:18.400 --> 00:30:23.359
Um and then we will later introduce a PA series as well and that's our universal gate base architect.
00:30:23.599 --> 00:30:23.759
Okay.
00:30:23.920 --> 00:30:49.279
Sorry for interrupting this yeah so the PT3 that we're releasing later this year will be a really exciting inflection point for us because actually that will be the transition from pilot to production because that is the system that we know will actually have what what we consider to be commercial advantage right so from the not from the perspective of the number of photons or qubits or Q modes or anything like that, but specifically thinking about the end application, right?
00:30:49.440 --> 00:31:01.680
That PT3 system will be performant enough where it will outperform a GPU cluster for that model for left CapEx and OpEx making it an easy decision uh in terms of it.
00:31:02.079 --> 00:31:07.519
Yep because and the end of them is the bottom line right when we compare and this is super cool.
00:31:07.599 --> 00:31:07.759
Okay.
00:31:08.160 --> 00:31:09.200
This is very nice.
00:31:09.359 --> 00:31:19.279
Um congratulations on it and um keep my fingers crossed um looking forward again for yet another announcement from Officer super exciting.
00:31:19.519 --> 00:31:29.839
Okay I would love to change a little bit direction of our discussion right now and I wanted to pick your brain a little bit more about your view on the whole industry itself.
00:31:30.400 --> 00:31:38.480
So if you can be honest with me how much to the quantum industry is a hype versus a real progress?
00:31:38.720 --> 00:31:50.880
Yeah you know honestly it's a lot of both you know there's obviously a lot of hype but at the same time there's a ton of progress being made today on both the algorithm side as well as the hardware side it's incredible.
00:31:51.039 --> 00:32:03.519
You know um we have the company Slack channel for example obviously and it's always being you know there's always notifications from the Slack channels in terms of this group just published this paper this group just demonstrated this.
00:32:03.599 --> 00:32:05.359
It's just almost every day it's incredible.
00:32:05.440 --> 00:32:15.200
It's a very exciting and dynamic industry but I think you know I I'm not sure if we if we mentioned it how many people do you have in Orca right now?
00:32:15.440 --> 00:32:16.880
So we're about 50 people or so.
00:32:17.119 --> 00:32:40.240
Wow amazing so one fifth you said up to 10 people are working specifically on use cases so one fifth of the company this is also very hard and very roughly showing like your mind how the company is structured by by you and the rest of senior executive uh team of in orca right like you guys are really focused on commercialization and that's that's the unique and that's beautiful.
00:32:40.559 --> 00:32:51.440
Okay so uh gonna meet in five years from now what what would be the winning for Orca how would you see Orca winning in five years?
00:32:51.759 --> 00:33:12.880
Yeah I think I think a really clear indication is when people don't think of Orca as a quantum company at all right okay and you just think of Orca as a an a fundamental technology for HPC's data centers as well as AI factories and and everything else right so we're so interwoven essentially into the fabric of information processing.
00:33:13.119 --> 00:33:34.079
Do you have any specific goals in the next five years that I don't know you want to reach that's volume of sales or um the specific number of clients we have some goals internally but we'll we'll we'll keep those to ourselves like we'd love to work with more more companies who are willing and ready to take in our technology and and change the world with it.
00:33:34.160 --> 00:33:34.319
Right.
00:33:34.480 --> 00:33:53.359
I mean after all that's that's why we're here right um you know fun clients is is is of course you know interesting and and compelling but it's so much more gratifying when you know that you're working on something that other people will then take and make transformative technologies with or or be able to really move the needle with.
00:33:53.599 --> 00:34:08.480
And this breakthrough technology you are 100% right on this I think it is the next big thing after AI that everyone is looking at um like if you look at the whole adaptation it's we'll we're still early last three years were super busy as you said.
00:34:09.519 --> 00:34:14.800
But a lot of investors said oh you know I have missed the ship with the AI.
00:34:15.119 --> 00:34:20.559
Can you tell me what's the biggest misconception people may have about photonic button computing today?
00:34:20.880 --> 00:34:29.199
I think the biggest misconception from my mind is knowing exactly how these quantum computers will be used.
00:34:29.440 --> 00:35:12.639
Mm-hmm I think that there's excellent and amazing examples so far that we're able to point at right so for example Schore's algorithm will completely change how IT infrastructure works as well as Grover's algorithm right um improving these uh these search algorithms with Grover's algorithm would be very great as well but those are just two examples right and I think I think there's such a big misconception or or maybe people just don't talk about it but we just don't know what's possible right as with any new technology and you can argue that quantum is one of the newest technologies we've ever introduced as humankind aside from the original transistor right is such a big fundamental shift in how we would do things that we just there's just so much we don't know.
00:35:12.800 --> 00:35:15.599
Right and this goes back exactly to Orca's philosophy.
00:35:15.679 --> 00:35:30.880
That's exactly why we prefer to get products into customers' hands early and often engage with them frequently so that we can learn together so that we give our customers what will help them find the next thing and then we'll continue to build off of that.
00:35:31.039 --> 00:35:33.199
But there's just still much and it is very exciting.
00:35:33.440 --> 00:35:38.880
Yeah and I and I this was my summary as well that's why I think the whole industry is so exciting.
00:35:39.039 --> 00:36:05.440
It is because we don't know yet and with all the new technology there's always so many different potential use cases and that's that's make it beautiful I personally wait for um a lot of adaptation in the health tech because that's my background and I I can't wait you know I used to work for the last couple of years on the autoimmune disease problem it's very complicated and also lack of data on top of it.
00:36:05.840 --> 00:36:11.440
But I I I can wait for you know us having capabilities to solve problems like that.
00:36:12.079 --> 00:36:20.559
Why yeah yeah and I see the enthusiasm on on your side I see like you are the real passion like so that's that's very that's very amazing.
00:36:21.039 --> 00:36:33.760
Another question I think we we shortly wrapping up looking at the at the time to also respect your time but if you can tell me what may surprise people about quantum computing the next three years three years.
00:36:33.920 --> 00:36:48.000
So short period now I think I can answer that by saying that I think most people would be surprised that quantum computing you know building technologies and building products using our understanding of quantum mechanics is already out in the market today.
00:36:48.159 --> 00:36:50.079
And I think I don't think that most people realize that.
00:36:50.159 --> 00:37:03.679
So that's that's already surprising right and so you know taking that to the next step, what we're doing is we're looking to master coherence, entanglement and superposition so that we can build compute capabilities with our understanding of quantum mechanics.
00:37:03.840 --> 00:37:19.599
And I think that most people will be very surprised three years later to realize that what you know one query that they did or maybe one task that they used already had some quantum accelerator in the background that they just didn't know about because to their perspective all they did was write some Python code.
00:37:19.840 --> 00:37:43.199
Oh the same will be the same yeah one it's just a little bit there but the output may yeah yeah that's actually that's very interesting yeah that's very interesting what you say okay okay okay okay um last question I'm just looking for some of my notes to see what I can ask you we spoke with many of the topics that I missed with myself.
00:37:43.360 --> 00:37:47.840
What should business leaders start doing today to not fall behind?
00:37:48.079 --> 00:38:02.400
Yeah I think I think the key thing is just to get started right so the first thing is to purchase the quantum computer of course that's more feasible with certain solutions and versus certain other ones right we like to think that our solution is very consumable.
00:38:02.800 --> 00:38:24.159
And the second thing is to install it locally and this is very important because by installing it locally those business leaders and those companies will be able to train a team on how to integrate maintain and develop using this new technology not as its own thing right but as a full solution with their existing classical compute architecture.
00:38:24.320 --> 00:38:28.159
And I think the main thing for them to know is that it's not it's not impossible.
00:38:28.800 --> 00:38:29.920
It's not 10 years away.
00:38:30.000 --> 00:38:41.519
They can reach out to Orca and we can discuss this but we can have a system delivered on-prem to their to their site and have their engineers work with our team of engineers to develop algorithms today.
00:38:41.760 --> 00:38:44.480
This is something that they can engage with us already on.
00:38:44.559 --> 00:38:52.320
And not only that but going back to the photonic qubit discussion as we improve our technology because everyone knows right the technology is moving very quickly.
00:38:52.400 --> 00:38:56.960
They don't want to be left behind but they don't also don't want to be left with hardware that's useless.
00:38:57.199 --> 00:39:05.199
Well the the nice thing about a photonic quantum computer is that let's say that we improve our quantum processor next year, which we we will do, right?
00:39:05.360 --> 00:39:12.159
So this is very pertinent example of what we can do is we can then go in and install the new module in place.
00:39:12.320 --> 00:39:19.519
So we'll take out the old module we'll put in the new one and it's we basically do a upgrades free upgrade which is which is beautiful.
00:39:19.920 --> 00:39:28.159
So let me ask if I as a CEO of the company order an Orca computer right now how long do I need to wait for the delivery that's a good question.
00:39:28.400 --> 00:39:35.760
A lot of it uh depends on when when that discussion takes place how long we know about it but I would say on the order of six to nine months.
00:39:36.000 --> 00:39:37.920
Six to nine months that's not that bad.
00:39:38.079 --> 00:39:40.400
That's a pretty defective and how much do I need to pay for it?
00:39:40.719 --> 00:39:42.559
That's also something that we can discuss.
00:39:42.800 --> 00:39:49.920
Well what I can say is that a lot of our competitors price their systems in the tens to hundreds of millions and we're about an order of magnitude less.
00:39:50.159 --> 00:39:53.039
Wow okay so you're competitive on that point as well.
00:39:53.360 --> 00:40:01.840
We are yeah we're price competitive and not just against other quantum technologies right we're we're very mindful that we're competing against traditional compute capabilities.
00:40:02.079 --> 00:40:21.119
Yeah I think T what you said about you know not losing the point of not falling back and using this technology but also not staying with useless hardware in the future and in your system of upgrading it this is very powerful and I think this is something we should emphasize a lot.
00:40:21.360 --> 00:40:38.960
I have sometimes impression that some of the big companies may regret you know that they were too early some technologies were not developed yet and now they just don't know the choice they invest more on what they have already right yeah um so so that's that's very important as well.
00:40:39.199 --> 00:41:06.000
Okay last question now just for fun maybe we can create a wheel from that finish the sentence quantums become truly useful when quantum is truly useful when it's taken for granted right so it's going back to the whole boring concept right boring doesn't mean that it doesn't have huge impact boring means that it's reliable is trustworthy and it's ubiquitous and that's that's exactly when we know quantum has has made it that's true.
00:41:06.639 --> 00:41:42.800
Thank you so much I really enjoy um the discussion today and with this beautiful um summary let's make quantum boring that's right let's finish our discussion thank you thank you that was Blonde and Quantum thank you for joining me on this journey through the quantum business frontier if you like the episode please review another Spotify or Apple Podcast and help more people discover the quantum world without needing to untangle the theoretical physics see you next time unless the caption
00:00:00.719 --> 00:00:09.839
Hey, my name is Eva, and this is Blondon Quantum, the podcast that breaks down quantum technology into real-world business impact.
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Here we make the complex simple.
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No equation, no overthinking, just insight, innovation, and a bit of key log.
00:00:18.879 --> 00:00:22.079
So don't worry, you don't need a PhD in physics to follow.
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In each episode, I talk to funders, scientists, and investors about how quantum is reshaping the industry's today, not in the long distant future.
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Oh and if you heard a black cat boring in the background, that's my coffee.
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A very alive cat joining the conversation.
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Her name is Mun.
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Let's get started.
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Welcome everyone in the next episode of the startup series of a blunt and quantum.
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Today with me is the CTO of Orca Computing from the UK, Tien Wynn.
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Hey Tien, uh or T, as you prefer to be called.
00:01:03.920 --> 00:01:06.159
Thank you so much for being here today with us.
00:01:06.400 --> 00:01:07.599
Well, thank you so much for having me.
00:01:07.920 --> 00:01:08.159
Great.
00:01:08.319 --> 00:01:08.959
So, Tien.
00:01:09.680 --> 00:01:09.840
T.
00:01:10.480 --> 00:01:14.879
So obviously Orca Computing is building photon-based quantum computers.
00:01:15.040 --> 00:01:20.719
Um, but let's imagine that I'm a CEO with a zero physics background.
00:01:21.120 --> 00:01:25.120
What problem does Orca computing actually solve for me?
00:01:25.439 --> 00:01:25.680
Right.
00:01:25.840 --> 00:01:32.879
Well, I would imagine if you're a CEO of a large corporation, right, you have a lot of a lot of uh areas that you must be an expert of.
00:01:33.040 --> 00:01:45.040
Um but in general, you know that you need to be aware of some of the transformative capabilities of quantum computing technologies, and you want to understand how that maps to your business functions and what you care about as a business.
00:01:45.200 --> 00:01:54.319
Um so what Orca does is that we actually really facilitate that adoption, integration, but also utilization of quantum technologies for your business operations today.
00:01:54.400 --> 00:02:03.040
And so, unlike a lot of other companies, what we really focus on is delivering a product that is easy to use, easy to purchase, and easy to install.
00:02:03.280 --> 00:02:12.159
And we also have our engineers, our machine learning scientists on our end who will work with your team to help you understand how to build these quantum algorithms.
00:02:12.240 --> 00:02:17.919
Because at the end of the day, this field of hybrid quantum classical algorithms and technologies is very new, right?
00:02:18.000 --> 00:02:20.240
And we don't really expect any of our customers to be experts.
00:02:20.560 --> 00:02:21.360
Hundreds percent.
00:02:21.520 --> 00:02:33.919
And I'm glad you mentioned it because I think the biggest companies, the enterprise company, 500 versions, they already have the quantum teams, but that's not necessarily mean they are developing when if they have access, right?
00:02:34.080 --> 00:02:38.080
Um, through bracket or if they bought quantum computer or so on.
00:02:38.319 --> 00:02:39.439
So, yes, okay.
00:02:39.599 --> 00:02:52.240
But before we go to those details and talk a little bit more about the customers of yours and your very unique philosophy, because I think it's unique comparing to the other quantum companies.
00:02:52.479 --> 00:02:59.360
You guys are focusing much more on commercialization than just being in the lap and science and so on, right?
00:02:59.520 --> 00:03:10.000
So we're gonna talk about it in a second, but I want to ask you um, for the benefits of the audience, to explain a little bit more about the modality that you are guys are in.
00:03:10.080 --> 00:03:14.400
Um, because you chose photons over other quantum approaches.
00:03:14.560 --> 00:03:16.000
So why so?
00:03:16.159 --> 00:03:17.520
Why why photons?
00:03:17.680 --> 00:03:18.879
How the company started.
00:03:18.960 --> 00:03:21.280
If you can tell us a little bit of the history, right, sure.
00:03:21.360 --> 00:03:23.520
So the the company started in 2019.
00:03:23.680 --> 00:03:28.960
So we're a spin-out from the University of Oxford, Professor Ian Wamsley's quantum optics group.
00:03:29.360 --> 00:03:31.840
Um it with their focus is of course on optics.
00:03:32.000 --> 00:03:46.159
You know, we we made the very mindful decision of building a full-stack quantum computing company based around photonic qubits because of the intrinsic and inherent advantages of using photons as opposed to any other uh qubit modality.
00:03:46.240 --> 00:03:49.599
Um so primarily the coherence time for photons is very long.
00:03:49.759 --> 00:03:55.439
And more importantly, it's a much more practical or pragmatic qubit to be deployed as a commercial system.
00:03:55.599 --> 00:04:00.400
So the systems that we are able to build using photonic qubits can operate at room temperature.
00:04:00.479 --> 00:04:13.520
And then using optical fibers, which is already a very mature technology, we actually are blessed with the ability to have a highly connected network between all of our different optical modules that is also a very modular network.
00:04:13.599 --> 00:04:31.519
And that allows us, what that allows us to do is allows us to build and uh deploy these systems today and then scale them both in terms of our technologies, but also in terms of the products that we deliver to our existing customers over time by upgrading in place uh many of their systems to higher performant versions of the modules.
00:04:31.839 --> 00:04:32.319
Exactly.
00:04:32.399 --> 00:04:45.199
And uh a lot of experts are actually emphasize the fact that photon-based quantum computers may be very scalable in the future, or even the most scalable from across the all modalities.
00:04:45.360 --> 00:04:48.560
From the other so that's the the biggest advantage, I believe.
00:04:48.720 --> 00:04:50.240
But what's the bottleneck?
00:04:50.480 --> 00:04:55.920
What is the thing that haven't been solved yet in in terms of photons?
00:04:56.240 --> 00:04:56.480
Right.
00:04:56.560 --> 00:04:59.439
Well, you know, of course, every every component needs to be improved.
00:04:59.519 --> 00:05:11.279
But I would say that the number one metric that we, but also all the other photonic quantum computing companies are solving, is how to build this optical network of modules while still keeping the losses to near zero.
00:05:11.439 --> 00:05:21.920
The way that a photonic quantum computing works is that you have components at the beginning, which are your source components, generating these single photons, and those single photons transit through the network.
00:05:22.000 --> 00:05:26.319
And at the end of it, you need to detect and measure the state of all of those entangled photons.
00:05:26.480 --> 00:05:30.319
And so we can't uh really afford to lose too many along the way.
00:05:30.560 --> 00:05:30.879
Okay.
00:05:31.199 --> 00:05:33.199
And you mentioned previously that.
00:05:33.279 --> 00:05:41.279
So I want to also dig a little bit deeper on it because you are the quantum component that already ships the machine, which is already super unique, right?
00:05:41.439 --> 00:05:43.199
Not many, many components are doing it.
00:05:43.439 --> 00:05:50.480
But once you're shipping it, you can also plug them into existing data center, from my understanding, if that's correct.
00:05:50.720 --> 00:05:58.560
So you mentioned that there's no cryogenic cooling needed because you run it basically in the room temperature.
00:05:58.720 --> 00:06:05.600
So can you tell us a little bit more why this is a big deal and why this is really important and why this is useful?
00:06:05.920 --> 00:06:19.759
Well, I want to clarify that from the perspective of our customer, what we deliver is that we deliver these standard 36-inch racks that are filled with these optical compute modules that are networked together as a quantum computer using optical fiber.
00:06:20.000 --> 00:06:24.319
So, from the perspective of our customer, that black box operates at room temperature.
00:06:24.480 --> 00:06:34.240
So, what that means is they don't need to then build infrastructure specifically around our hardware to keep certain components or certain modules below a certain temperature.
00:06:34.399 --> 00:06:43.199
Um, and this is really important when you're actually delivering these products into functioning data centers, because data centers don't have the luxury if they're already operating, right?
00:06:43.279 --> 00:06:50.399
They don't have the luxury to shut down operation, to build the infrastructure that has your technology, and then to bring everything back up again.
00:06:50.560 --> 00:07:03.199
Um and then, in of course, in greenfield applications where the data center is being built from the ground up, of course, the less requirements that you place on the infrastructure of that building, the easier it is to deploy, the more cost-effective that data center will be.
00:07:03.439 --> 00:07:09.199
So is photonic then inherently more scalable or just differently difficult?
00:07:09.519 --> 00:07:11.920
Yeah, in a lot of ways, photonics is more scalable.
00:07:12.160 --> 00:07:19.279
I mentioned that we are able to leverage the very mature technology of interconnects using optical fiber.
00:07:19.439 --> 00:07:24.160
And that's really what allows it, that's really what allows us to scale horizontally extremely easily.
00:07:24.319 --> 00:07:39.439
Um, you can imagine that if you have, for example, one very good quantum light source, you can then replicate that horizontally to maybe tens, hundreds, or even thousands of these quantum light sources and then just integrate their output all together using optical fiber and some muxing switches.
00:07:39.680 --> 00:07:40.639
This is so cool.
00:07:40.879 --> 00:07:54.639
And when the mic was up, you mentioned that um you mentioned that Orca has this core philosophy to deliver quantum technologies to the customers early and often, right?
00:07:54.959 --> 00:08:00.720
Which means that you're going beyond the research and building uh true product, right?
00:08:00.800 --> 00:08:02.319
Which uh you are already selling.
00:08:02.399 --> 00:08:08.560
So let's talk about this because this is very exciting for me and I hope for our audience as well.
00:08:08.800 --> 00:08:18.560
Many even you know publicly listed companies are still working on the technology, they are far, far from thinking about commercialization.
00:08:19.600 --> 00:08:27.519
And you're much smaller, you're raising right now, so you and we're gonna come back to this as well, and you are already, already selling.
00:08:27.759 --> 00:08:32.960
So tell me a little bit more about the philosophy and tell me as well who are your customers.
00:08:33.200 --> 00:08:34.000
Yeah, absolutely.
00:08:34.159 --> 00:08:38.240
So quantum is undeniably hard tech and deep tech, right?
00:08:38.399 --> 00:08:48.240
And I think that a lot of times startups in the hard tech and deep tech space are very proud of, as they should be, very proud of their underlying technology.
00:08:48.480 --> 00:08:57.759
But in my opinion, they focus too much on that underlying technology and they spend too much time perfecting that fundamental technology before they even let anyone else see it.
00:08:58.000 --> 00:09:09.440
But similarly to how it's a very long path going from a good idea to developing a good technology, there's an even longer and more perilous path, bringing a good technology to a good product.
00:09:09.600 --> 00:09:16.240
And oftentimes there's a lot of challenges along the way that maybe people will hand wave and just say, oh, don't worry about it.
00:09:16.320 --> 00:09:17.440
It's just an engineering problem.
00:09:17.600 --> 00:09:25.919
Well, I can tell you right now, most of the hard issues that we're tackling are engineering problems in order to deploy and scale up these quantum technologies.
00:09:26.080 --> 00:09:31.039
Like it's not just an engineering problem, that is, that is a big part of the of what needs to be solved.
00:09:31.200 --> 00:09:46.320
And so our philosophy is to think, okay, well, we're going to lean into our strengths as a photonic quantum computing company, which gives us the ability to build these systems sooner and deploy them more easily and more cost-effectively effectively to our customers.
00:09:46.480 --> 00:09:50.639
And then by doing so, we actually have a great symbiotic relationship, right?
00:09:50.799 --> 00:09:55.279
Our customers then become our collaborators and our partners as well.
00:09:55.440 --> 00:10:10.320
And so together, right, we are learning from our customers in terms of how they're using our system, what kind of applications they're looking at, and we roll that back into developing the next generation of uh modules and products that we then deliver back to the customers.
00:10:10.480 --> 00:10:20.159
And so we have this very back and forth relationship that helps us both figure out this in this fog of potential futures, what's the best path forward together?
00:10:20.480 --> 00:10:31.360
This is very unique and very beautiful because you're basically following the standard startup pathway of iterating very fast and validating that with the customer, right?
00:10:31.519 --> 00:10:44.639
Which I would say most of deep tech companies are not doing and they're getting dispensed even from the venture capital because, like, oh, because it's so deep tech, you needed some time and so on and so on, right?
00:10:44.799 --> 00:10:57.519
That's why we we we do have um even you know publicly company, not only in quantum, but also in different deep tech verticals where where they do not commercialize yet, we need not sell or or make money really.
00:10:57.759 --> 00:10:59.039
So this is very interesting.
00:10:59.200 --> 00:11:00.480
So let's just talk about it.
00:11:00.639 --> 00:11:02.000
Who are your customers?
00:11:02.159 --> 00:11:03.039
Who are you selling?
00:11:03.120 --> 00:11:05.200
Who is buying today quantum computers?
00:11:05.440 --> 00:11:06.399
Yeah, that's a great question.
00:11:06.639 --> 00:11:12.320
The thing about the quantum computing space is that it's not, you know, it's a new technology, but it's an existing market.
00:11:12.559 --> 00:11:19.039
So all of our customers are exactly identical to the customers of traditional and classical high-performance compute architectures.
00:11:19.279 --> 00:11:25.039
So, you know, we have members of our team from uh Craig Computing, right, which is a traditional HPC company.
00:11:25.200 --> 00:11:27.919
And so we we engage with a lot of the same customers, right?
00:11:28.000 --> 00:11:33.840
Whether they are D labs for corporations, whether they're national labs, or whether they're uh data centers.
00:11:34.080 --> 00:11:35.360
So all three of those categories.
00:11:35.519 --> 00:11:38.639
And so far, can you can you draw some names for us?
00:11:39.279 --> 00:11:40.320
It is not a secret.
00:11:40.399 --> 00:11:42.879
If you have NDAs, then I then but it would be great.
00:11:43.120 --> 00:11:47.279
Yes, I think some some we're not allowed to we're not uh disclosing publicly yet.
00:11:47.440 --> 00:11:55.039
You know, I think we've announced that we've delivered systems to the NQCC, for example, which is the National Quantum Computing Center over in the UK.
00:11:55.360 --> 00:12:00.720
And also uh we have a great collaboration with the the PSEC over in Poland.
00:12:00.879 --> 00:12:03.919
And actually in that data center on Polish.
00:12:04.080 --> 00:12:05.360
Yeah, great.
00:12:05.440 --> 00:12:08.399
We we love we love uh we love the PSEC.
00:12:08.559 --> 00:12:31.039
And in that project, actually, it shows an example of a very symbiotic relationship where we have delivered systems to their data center, and beyond that, we've been working closely with their team, but also with Nvidia to stand up the the world's first multi-user, multi-GPU, multi-QPU environment that works seamlessly together as one system.
00:12:31.279 --> 00:12:36.320
So we actually have some publication that we'll be releasing about that in the congratulations on that.
00:12:36.399 --> 00:12:40.960
I think it's a huge success, and again, it is so unique in quantum worlds.
00:12:41.120 --> 00:12:49.200
I understand that some of these projects related to defense and so on may not be public and they should not be public for many reasons.
00:12:49.360 --> 00:12:59.919
But uh, if you can give us a little bit of spotlight on working with British government, because I think it's it's a very unique experience, and also the British government choose a different path.
00:13:00.080 --> 00:13:05.440
They don't invest directly like some other governments in Europe, but they offer those contracts.
00:13:05.519 --> 00:13:06.639
So please tell us more.
00:13:06.879 --> 00:13:07.360
Sure, yeah.
00:13:07.519 --> 00:13:12.240
You know, we we work very closely with the British government through multiple different grants and programs.
00:13:12.480 --> 00:13:14.960
I mentioned that we've delivered a system to the IQC.
00:13:15.360 --> 00:13:20.320
We've had previous projects as well, working with DSTL and some other arms of the UK government as well.
00:13:20.559 --> 00:13:32.000
But you but you know, I think fundamentally in terms of working with them, it's very similar to whether we're working with the UK government or whether we're working with um a larger company like uh EY or BP, right?
00:13:32.320 --> 00:13:34.159
So from your perspective, there's no difference.
00:13:34.320 --> 00:13:36.080
Project is project, client is client.
00:13:36.320 --> 00:13:36.960
That that's right.
00:13:37.120 --> 00:13:49.200
Well, it it's the same because they are all very eager, right, to incorporate quantum technologies into their workflow, into the work that they're already doing, but they also don't quite know how, right?
00:13:49.440 --> 00:13:55.519
And this is this is uh even if they have quantum machine learning experts on their team, right?
00:13:55.759 --> 00:13:58.960
And and uh it's just because the space is too new, right?
00:13:59.039 --> 00:14:07.200
There's just too much that we don't know about the underlying technology, and there's still too much to be explored in terms of well, what can we do with this technology?
00:14:07.519 --> 00:14:12.320
That's why I think all the governments are are just in the race right now, and and that's beautiful.
00:14:12.399 --> 00:14:15.440
But yeah, I was just just curious about this experience.
00:14:15.679 --> 00:14:20.480
Okay, so speaking about the use cases, even for the commercial client.
00:14:20.720 --> 00:14:22.480
Can you can you tell us more about it?
00:14:22.799 --> 00:14:23.200
Well, sure.
00:14:23.279 --> 00:14:26.159
Um, I mean it's it's pretty much everything under the sun, right?
00:14:26.240 --> 00:14:40.480
So we've had the opportunity to work with a lot of different commercial entities already in helping them understand, you know, how our technology works, how to interact with our technology, how to integrate our technology into their workflow, and then what they can do with it, right?
00:14:40.720 --> 00:14:44.159
So we've had multiple, you know, many, many different collaborations.
00:14:44.559 --> 00:14:58.639
Some notable ones are um a collaboration with BP, where we utilize our hybrid classical quantum uh generative AI models to solve the molecular confirmation problem, which is a computationally intensive problem.
00:14:58.879 --> 00:15:06.080
But we are using our hybrid architecture to attack it from a little bit of a different angle so that we can get to the correct answer more quickly.
00:15:06.320 --> 00:15:16.320
And another really exciting one, one that I think is personally extremely exciting, is our collaboration with DTU, which is a uh university over in Europe.
00:15:16.559 --> 00:15:19.679
And this is for this is for uh peptide generation.
00:15:19.840 --> 00:15:22.159
So what we were able to show with their team, right?
00:15:22.320 --> 00:15:23.519
So this is a collaboration, right?
00:15:23.600 --> 00:15:25.919
We're obviously not the experts in peptide generation.
00:15:26.159 --> 00:15:32.879
Through through this collaboration, we're actually able to demonstrate that we're able to accelerate and improve de novo peptide generation.
00:15:33.039 --> 00:15:36.960
So this is the construction of drugs essentially from the ground up, right?
00:15:37.039 --> 00:15:38.080
From first principles.
00:15:38.159 --> 00:15:41.120
Um and this is particularly useful for therapeutics.
00:15:41.360 --> 00:15:53.120
Um so you know, we we were able to demonstrate that our quantum-enhanced gen AI can outperform classical models, specifically and you know, specifically and interestingly, in designing highly immunogenic peptide uh peptides.
00:15:53.200 --> 00:15:58.000
So peptides that have the ability to help you, right, once uh once ingested.
00:15:58.320 --> 00:16:14.240
This is actually fascinating, and thank you for mentioning it because you know, whenever I speak with an industry expert, they're telling me that um, you know, pharma is one of the uh areas beneficial sides of quantum or should be or supposed to be and so on.
00:16:14.480 --> 00:16:17.919
But on the other hand, I hear a lot as well about gas and oil.
00:16:18.240 --> 00:16:20.559
You just mentioned the cooperation with BP.
00:16:20.879 --> 00:16:25.360
I spoke previously with Pascal and they had the cooperation with Saudi Aremkov.
00:16:25.600 --> 00:16:34.399
So it seems like you know, there's two cooperations there than gas and oil, and I see only one so far mentioning by you real use case on uh on the on the pharma.
00:16:34.720 --> 00:16:36.639
Which university was that that you mentioned?
00:16:36.879 --> 00:16:38.080
Uh this is DTU.
00:16:38.480 --> 00:16:39.039
DTU.
00:16:39.120 --> 00:16:40.799
Okay, where are the where are they based?
00:16:40.960 --> 00:16:41.840
They're in Denmark.
00:16:42.159 --> 00:16:42.639
Okay, yeah.
00:16:42.799 --> 00:16:43.360
Makes sense.
00:16:43.600 --> 00:16:47.120
Yeah, well, Denmark is actually I have heard, I'm not sure this is true.
00:16:47.360 --> 00:16:52.000
I have heard that Denmark actually have the biggest number of quantum engineers in the whole Europe.
00:16:52.480 --> 00:16:53.519
I've heard that too.
00:16:53.759 --> 00:16:57.440
Yeah, it's uh so either there is something in it or they have a good P.
00:16:58.639 --> 00:17:01.919
I had a chance to visit their their center um a couple of years ago.
00:17:02.000 --> 00:17:07.200
It was it's really, really impressive, and the government really also put a lot of a lot of emphasis on.
00:17:07.680 --> 00:17:08.559
Okay, but T.
00:17:09.039 --> 00:17:20.240
Let's assume that I am 500 fortune companies already who are interested in orca system, or maybe let's say interested in buying a quantum computer.
00:17:20.640 --> 00:17:37.759
Where is where does Orca computing win versus if I will compare you obviously with the other players on the market, like IBM, INQ, or even SciQuantum, which is the same the same modality, where do you win or where do you potentially may lose?
00:17:38.000 --> 00:17:50.640
Yeah, I would say that the most the the biggest advantage that we have, and you mentioned Fortune 500, and um I'm not going to name the name right now, but we we did recently deliver to a global Fortune 500 company.
00:17:50.960 --> 00:17:55.119
Congratulations, congratulations, so what will be the announcement?
00:17:55.440 --> 00:17:56.079
Sorry?
00:17:56.319 --> 00:17:58.400
When when we can expect the announcement.
00:17:58.640 --> 00:17:59.200
I'm not too sure.
00:17:59.920 --> 00:18:04.160
I'll leave that up to uh for for speculation and to build up some mystery for later.
00:18:04.720 --> 00:18:08.960
We're gonna observe the press once it's out, and please ping me as well.
00:18:09.119 --> 00:18:11.119
I would love to feature that as well.
00:18:11.200 --> 00:18:12.480
And congratulations, by the way.
00:18:12.720 --> 00:18:13.119
Thank you.
00:18:13.279 --> 00:18:14.960
Um but I think the main thing is this, right?
00:18:15.119 --> 00:18:22.720
When people talk about quantum computing technologies, especially if it's just a very uh initial conversation, there's only really one question, right?
00:18:22.880 --> 00:18:25.519
And in my opinion, it's actually the least relevant question.
00:18:25.680 --> 00:18:28.640
So the one question is how many qubits is your system, right?
00:18:28.799 --> 00:18:37.279
And the reason why people ask how many qubits a system is, is because the world of quantum is too complicated right now and too and too fragmented, right?
00:18:37.440 --> 00:18:40.640
And so that's the one line that people can draw around everything.
00:18:40.799 --> 00:18:44.319
But fundamentally, right, qubits don't do anything by themselves.
00:18:44.559 --> 00:18:59.680
Even if you make an explicit qubit, but you have a terrible UI, you don't have a compiler, you don't have an operating system, you haven't networked the back end of your quantum computer to Q2Q or to Python or to whatever else, there's no way you can use that qubit, right?
00:18:59.839 --> 00:19:02.400
So, in my opinion, that's not the most relevant question.
00:19:02.559 --> 00:19:17.359
Really, where we shine as Orca is that we are focused on discussing around the applications that we enable, around the performance increases that you can see with our hybrid classical quantum computing systems, and not just about the underlying photons themselves.
00:19:17.519 --> 00:19:26.640
And this is reflected in the engineering and the architecture of our hardware, but also in the ease of use and the maturity of our software SDK as well.
00:19:26.799 --> 00:19:33.839
Um, you know, I mentioned you have a special team helping those clients as well to develop specific use cases.
00:19:34.000 --> 00:19:36.000
How many people do you have right now in that in that team?
00:19:36.240 --> 00:19:40.000
Uh that team is is uh pretty modest at the moment, less than 10 people or so.
00:19:40.240 --> 00:19:46.480
But we need we are looking to grow uh that team, but also other teams after our next fundraising round as well.
00:19:46.720 --> 00:19:48.960
Okay, after you finish the fundraise.
00:19:49.279 --> 00:19:51.839
Okay, uh, which is in a couple of months, right?
00:19:52.000 --> 00:19:52.400
That's right.
00:19:52.480 --> 00:19:52.640
Yeah.
00:19:52.880 --> 00:19:53.359
Yeah, okay.
00:19:53.440 --> 00:19:59.200
So, guys, if if there are an investor on the audience, this is your last chance to be gone.
00:19:59.519 --> 00:20:03.279
Go and ping T on a LinkedIn or over the email.
00:20:03.359 --> 00:20:04.319
That's the last chance.
00:20:04.480 --> 00:20:06.640
Okay, um, so this is very interesting.
00:20:06.799 --> 00:20:09.839
Um, I also want to ask you on the approaches.
00:20:10.000 --> 00:20:11.839
What do you think in terms of the future?
00:20:12.079 --> 00:20:15.039
Would that be a winner takes all market?
00:20:15.200 --> 00:20:20.240
Or do you think that multiple quantum architecture will kind of coexist together?
00:20:20.480 --> 00:20:20.720
Yeah.
00:20:20.960 --> 00:20:22.880
You know, obviously it's hard to tell, right?
00:20:23.039 --> 00:20:33.359
But I would be surprised, I would be very surprised if multiple of the modalities didn't find a footing in the broad cloud computing, in the broad AI world.
00:20:33.599 --> 00:20:33.839
Sorry?
00:20:34.240 --> 00:20:34.799
Why is so?
00:20:34.960 --> 00:20:35.680
Why do you think so?
00:20:35.920 --> 00:20:40.720
Yeah, um, I well, I think we we recently heard about some news recently that was very interesting, right?
00:20:40.880 --> 00:20:45.039
So, you know, everyone let loves to talk about Shore's algorithm, everyone knows Shore's algorithm.
00:20:45.119 --> 00:21:00.880
And it seems like every year, the bar for the capabilities that we need to develop in order to execute Shore's algorithm, the bar keeps going down because very smart people come up with algorithms on how to more efficiently implement that algorithm, right?
00:21:01.039 --> 00:21:12.000
But one key thing that we saw, one key feature that allowed them to essentially compress the algorithm down so efficiently is by assuming all-to-all connectivity between the qubits, right?
00:21:12.240 --> 00:21:24.960
So beyond the raw number of physical or logical qubits, there's also this concept of connectivity that is becoming increasingly important as we consider how many qubits we need to implement what kind of algorithms.
00:21:25.119 --> 00:21:34.160
And depending on the modality that you choose, the degree of connectivity and the speed that you're able to entangle any arbitrary qubits together is drastically different.
00:21:34.319 --> 00:21:49.359
And so, as a function of which kinds of algorithms we develop, which kinds of algorithms and applications we find to be most useful in in this quantum world, that will determine which modalities will will uh eventually win out.
00:21:49.599 --> 00:21:58.640
So I what are you saying basically is that in the future, if I'm a big company, rather than choosing a modality, I will choose per use case.
00:22:00.720 --> 00:23:23.759
attached to specific modality that's that's very powerful and um i want that to emphasize for for our audience as well that you guys if you hear that again like the technology doesn't matter the use cases that you have matter and that will determinate the technology that is used that's very that's very cool okay and then T speaking that we will have a different modality how do you think the world will involve do we do you see the quantum being like centralized in the cloud and we're gonna use it like we today we use a cloud i mean from you know there's amazon there's google there's azure and so on and we know that Amazon already had a very powerful cloud for quantum called bracket that cooperate with many different startups and companies providing access to the quantum computers or we're gonna deploy it on premises in those data centers so how do you think this will evolve in the next 10 years I guess yeah I definitely think we'll have both and we talked about the different features of qubits being driven by the application right there's also the fact of like you mentioned cloud versus on-prem that will also determine which modalities will will get a stronger footing as well.
00:23:23.920 --> 00:23:47.519
So for example it's uh you know we've already demonstrated that we're able to build these uh uh quantum AI accelerators using photonic qubits that are very deployable on-prem uh whereas uh if you look at solutions from um some other modalities their solution is very very uh very involved requires a lot of infrastructure build out and that's unlikely to be deployed on prem.
00:23:47.920 --> 00:23:56.079
Okay so do you think those who are not able to be in the room temperature will high likely be on the cloud and the rest will be both.
00:23:56.319 --> 00:24:12.160
Yeah and of course everybody everyone's working very hard and of course they'll solve their engineering challenges as well but my point is that there will be a delineation between modalities of what they can offer as an on-prem solution versus what they can offer as a as a cloud solution.
00:24:12.480 --> 00:24:51.279
And it's also a matter of cost I guess as well right cost, usability infrastructure build out power consumption all of these boring uh KPIs that uh that we don't talk about enough in in the world of quantum yeah you're right but they are crucial from adaptation right yeah nobody you're right nobody's focusing on them right now but exactly but but the thing is like if you talk to any CIO right from a data that manages a data center or a large corporation that'll be the first question they ask right and so it's it's like we're not we're not really talking on the same wavelength right uh as an industry for the most part.
00:24:51.519 --> 00:24:56.079
Yeah because we are not there yet but it it's it's coming I think it's coming.
00:24:56.319 --> 00:25:05.359
Okay um a little bit change of topic and you mentioned that you already have very interesting cooperation with Nvidia on GPU.
00:25:05.759 --> 00:25:17.359
Nvidia is working also in the synergy of hybrid quantum and classical AI um but so the public information they present out on many quantum conferences.
00:25:17.599 --> 00:25:30.799
I wanted to ask you on your view of that matter on a synergy between hybrid quantum and classical AI how does it actually look like in practice today?
00:25:31.039 --> 00:25:35.119
Yeah so that that's exactly the focus of the system that we're building right now.
00:25:35.359 --> 00:25:45.839
So to be clear the systems that we're building and we're deploying right now are not universal architectures they're quantum accelerators specifically designed for Gen AI.
00:25:46.079 --> 00:26:09.920
Wow wow okay so okay okay so I want you during now to give me um real life example how can I use it as a company where's the defense how can I uh if you can let us know where is the difference on me as a company using uh only separate quantum computers or quantum computers with synergy of AI.
00:26:10.160 --> 00:26:26.319
Right so the difference is in the the computational architecture right so the way that our systems work is that we co-train the classical machine learning model with the quantum model of sorry with the quantum hardware and the quantum output all together it has one.
00:26:26.480 --> 00:26:36.000
And so in operation the way it works is that the classical model will call for inputs from the from the quantum system that was trained all together.
00:26:36.319 --> 00:26:45.200
Amazing so this is like on the hardware level integration I wasn't aware of I thought it was like there would be a software layer on that this is so cool.
00:26:45.519 --> 00:27:01.759
I mean it is software right so we so the the the classical model runs in in software right on hardware but it's in software and at certain points it'll call for an output from the quantum computer measure it and then input inject that as part of the operation of the machine learning model.
00:27:02.240 --> 00:27:02.559
Okay.
00:27:03.039 --> 00:27:28.319
So the way to think about it is that there's certain applications that favor quantum you know uh the the quantum I guess uh mathematical relationships a bit more than classical mathematical relationships and uh by by forming this hybrid system we're able to essentially improve the output accuracy of the Genai models by incorporating some of this quantumness in at strategic points in the neural network.
00:27:29.039 --> 00:27:36.799
And and yeah this is this is a model that we find to be very successful given the maturity of where we are today with our with our technologies.
00:27:37.039 --> 00:28:07.759
Okay so another question pop up as you spoke in my mind so in that case what is needed for for that synergy or integration of quantum and ai to move from a pile up to the production and following on question I'm sorry for that if we already as an industry working on that integration is there a risk that we may skip the adaptation of quantum computer separately just for you know the the integration variant?
00:28:08.079 --> 00:28:09.279
Yeah that's a that's a good question.
00:28:09.359 --> 00:28:11.920
I I I don't think it's so much that you would skip one or the other.
00:28:12.000 --> 00:28:14.240
I think they would just grow into their own applications.
00:28:14.480 --> 00:28:14.720
Okay.
00:28:14.880 --> 00:28:54.079
Simultaneously yeah so you know the the world of HPC and the world of AI is very large right and as we see we're we're starting to get more specialized hardware and specialized algorithms for specific tasks that have high utility right and so as as as the technologies continue to develop and as the technologies continue to be adopted by uh HPC and data centers and and AI factories, what we'll see is that um depending on the specific clientele that that data center is looking to service the specific applications that they're looking to optimize and run, they'll bring in different technologies to um to make that more efficient.
00:28:54.319 --> 00:29:00.720
Now in terms of you know you you asked the question of what would it take to go from pilot to production, right?
00:29:00.880 --> 00:29:04.720
I would argue they're we're we're pretty much on the cusp of production right now.
00:29:04.880 --> 00:29:09.680
But I would, you know, the main thing is just um the same with the with a lot of different technologies, right?
00:29:09.839 --> 00:29:32.000
From the perspective of the data center, are you helping them offer something to their clients in a way that is less expensive from a capex and from an opex perspective right so better performance for less capex and opex than other options they have right and so what that means in the world of data centers is that um you know if they're looking to upgrade their model, right?
00:29:32.079 --> 00:29:47.119
Yeah should they go out and should they purchase 10 more racks of Nvidia GPUs or could they purchase four more racks of Nvidia GPUs plus a quantum accelerator to work with everything in concert and still reach the same performance.
00:29:47.440 --> 00:29:48.640
So that's that's the clocks.
00:29:48.880 --> 00:29:53.599
And I think the question up here will be obvious right we will we'll go for this connection.
00:29:53.920 --> 00:30:18.319
Right right yeah and um you know uh you know we're we're we're working on that right now right so our we have two generations of our PT series out right now PT1 and PT2 and later this year for the for the audience you can explain PT is the name of your computer or accelerator okay that's right so um the PT series is the name for our hybrid quantum classical accelerators.
00:30:18.400 --> 00:30:23.359
Um and then we will later introduce a PA series as well and that's our universal gate base architect.
00:30:23.599 --> 00:30:23.759
Okay.
00:30:23.920 --> 00:30:49.279
Sorry for interrupting this yeah so the PT3 that we're releasing later this year will be a really exciting inflection point for us because actually that will be the transition from pilot to production because that is the system that we know will actually have what what we consider to be commercial advantage right so from the not from the perspective of the number of photons or qubits or Q modes or anything like that, but specifically thinking about the end application, right?
00:30:49.440 --> 00:31:01.680
That PT3 system will be performant enough where it will outperform a GPU cluster for that model for left CapEx and OpEx making it an easy decision uh in terms of it.
00:31:02.079 --> 00:31:07.519
Yep because and the end of them is the bottom line right when we compare and this is super cool.
00:31:07.599 --> 00:31:07.759
Okay.
00:31:08.160 --> 00:31:09.200
This is very nice.
00:31:09.359 --> 00:31:19.279
Um congratulations on it and um keep my fingers crossed um looking forward again for yet another announcement from Officer super exciting.
00:31:19.519 --> 00:31:29.839
Okay I would love to change a little bit direction of our discussion right now and I wanted to pick your brain a little bit more about your view on the whole industry itself.
00:31:30.400 --> 00:31:38.480
So if you can be honest with me how much to the quantum industry is a hype versus a real progress?
00:31:38.720 --> 00:31:50.880
Yeah you know honestly it's a lot of both you know there's obviously a lot of hype but at the same time there's a ton of progress being made today on both the algorithm side as well as the hardware side it's incredible.
00:31:51.039 --> 00:32:03.519
You know um we have the company Slack channel for example obviously and it's always being you know there's always notifications from the Slack channels in terms of this group just published this paper this group just demonstrated this.
00:32:03.599 --> 00:32:05.359
It's just almost every day it's incredible.
00:32:05.440 --> 00:32:15.200
It's a very exciting and dynamic industry but I think you know I I'm not sure if we if we mentioned it how many people do you have in Orca right now?
00:32:15.440 --> 00:32:16.880
So we're about 50 people or so.
00:32:17.119 --> 00:32:40.240
Wow amazing so one fifth you said up to 10 people are working specifically on use cases so one fifth of the company this is also very hard and very roughly showing like your mind how the company is structured by by you and the rest of senior executive uh team of in orca right like you guys are really focused on commercialization and that's that's the unique and that's beautiful.
00:32:40.559 --> 00:32:51.440
Okay so uh gonna meet in five years from now what what would be the winning for Orca how would you see Orca winning in five years?
00:32:51.759 --> 00:33:12.880
Yeah I think I think a really clear indication is when people don't think of Orca as a quantum company at all right okay and you just think of Orca as a an a fundamental technology for HPC's data centers as well as AI factories and and everything else right so we're so interwoven essentially into the fabric of information processing.
00:33:13.119 --> 00:33:34.079
Do you have any specific goals in the next five years that I don't know you want to reach that's volume of sales or um the specific number of clients we have some goals internally but we'll we'll we'll keep those to ourselves like we'd love to work with more more companies who are willing and ready to take in our technology and and change the world with it.
00:33:34.160 --> 00:33:34.319
Right.
00:33:34.480 --> 00:33:53.359
I mean after all that's that's why we're here right um you know fun clients is is is of course you know interesting and and compelling but it's so much more gratifying when you know that you're working on something that other people will then take and make transformative technologies with or or be able to really move the needle with.
00:33:53.599 --> 00:34:08.480
And this breakthrough technology you are 100% right on this I think it is the next big thing after AI that everyone is looking at um like if you look at the whole adaptation it's we'll we're still early last three years were super busy as you said.
00:34:09.519 --> 00:34:14.800
But a lot of investors said oh you know I have missed the ship with the AI.
00:34:15.119 --> 00:34:20.559
Can you tell me what's the biggest misconception people may have about photonic button computing today?
00:34:20.880 --> 00:34:29.199
I think the biggest misconception from my mind is knowing exactly how these quantum computers will be used.
00:34:29.440 --> 00:35:12.639
Mm-hmm I think that there's excellent and amazing examples so far that we're able to point at right so for example Schore's algorithm will completely change how IT infrastructure works as well as Grover's algorithm right um improving these uh these search algorithms with Grover's algorithm would be very great as well but those are just two examples right and I think I think there's such a big misconception or or maybe people just don't talk about it but we just don't know what's possible right as with any new technology and you can argue that quantum is one of the newest technologies we've ever introduced as humankind aside from the original transistor right is such a big fundamental shift in how we would do things that we just there's just so much we don't know.
00:35:12.800 --> 00:35:15.599
Right and this goes back exactly to Orca's philosophy.
00:35:15.679 --> 00:35:30.880
That's exactly why we prefer to get products into customers' hands early and often engage with them frequently so that we can learn together so that we give our customers what will help them find the next thing and then we'll continue to build off of that.
00:35:31.039 --> 00:35:33.199
But there's just still much and it is very exciting.
00:35:33.440 --> 00:35:38.880
Yeah and I and I this was my summary as well that's why I think the whole industry is so exciting.
00:35:39.039 --> 00:36:05.440
It is because we don't know yet and with all the new technology there's always so many different potential use cases and that's that's make it beautiful I personally wait for um a lot of adaptation in the health tech because that's my background and I I can't wait you know I used to work for the last couple of years on the autoimmune disease problem it's very complicated and also lack of data on top of it.
00:36:05.840 --> 00:36:11.440
But I I I can wait for you know us having capabilities to solve problems like that.
00:36:12.079 --> 00:36:20.559
Why yeah yeah and I see the enthusiasm on on your side I see like you are the real passion like so that's that's very that's very amazing.
00:36:21.039 --> 00:36:33.760
Another question I think we we shortly wrapping up looking at the at the time to also respect your time but if you can tell me what may surprise people about quantum computing the next three years three years.
00:36:33.920 --> 00:36:48.000
So short period now I think I can answer that by saying that I think most people would be surprised that quantum computing you know building technologies and building products using our understanding of quantum mechanics is already out in the market today.
00:36:48.159 --> 00:36:50.079
And I think I don't think that most people realize that.
00:36:50.159 --> 00:37:03.679
So that's that's already surprising right and so you know taking that to the next step, what we're doing is we're looking to master coherence, entanglement and superposition so that we can build compute capabilities with our understanding of quantum mechanics.
00:37:03.840 --> 00:37:19.599
And I think that most people will be very surprised three years later to realize that what you know one query that they did or maybe one task that they used already had some quantum accelerator in the background that they just didn't know about because to their perspective all they did was write some Python code.
00:37:19.840 --> 00:37:43.199
Oh the same will be the same yeah one it's just a little bit there but the output may yeah yeah that's actually that's very interesting yeah that's very interesting what you say okay okay okay okay um last question I'm just looking for some of my notes to see what I can ask you we spoke with many of the topics that I missed with myself.
00:37:43.360 --> 00:37:47.840
What should business leaders start doing today to not fall behind?
00:37:48.079 --> 00:38:02.400
Yeah I think I think the key thing is just to get started right so the first thing is to purchase the quantum computer of course that's more feasible with certain solutions and versus certain other ones right we like to think that our solution is very consumable.
00:38:02.800 --> 00:38:24.159
And the second thing is to install it locally and this is very important because by installing it locally those business leaders and those companies will be able to train a team on how to integrate maintain and develop using this new technology not as its own thing right but as a full solution with their existing classical compute architecture.
00:38:24.320 --> 00:38:28.159
And I think the main thing for them to know is that it's not it's not impossible.
00:38:28.800 --> 00:38:29.920
It's not 10 years away.
00:38:30.000 --> 00:38:41.519
They can reach out to Orca and we can discuss this but we can have a system delivered on-prem to their to their site and have their engineers work with our team of engineers to develop algorithms today.
00:38:41.760 --> 00:38:44.480
This is something that they can engage with us already on.
00:38:44.559 --> 00:38:52.320
And not only that but going back to the photonic qubit discussion as we improve our technology because everyone knows right the technology is moving very quickly.
00:38:52.400 --> 00:38:56.960
They don't want to be left behind but they don't also don't want to be left with hardware that's useless.
00:38:57.199 --> 00:39:05.199
Well the the nice thing about a photonic quantum computer is that let's say that we improve our quantum processor next year, which we we will do, right?
00:39:05.360 --> 00:39:12.159
So this is very pertinent example of what we can do is we can then go in and install the new module in place.
00:39:12.320 --> 00:39:19.519
So we'll take out the old module we'll put in the new one and it's we basically do a upgrades free upgrade which is which is beautiful.
00:39:19.920 --> 00:39:28.159
So let me ask if I as a CEO of the company order an Orca computer right now how long do I need to wait for the delivery that's a good question.
00:39:28.400 --> 00:39:35.760
A lot of it uh depends on when when that discussion takes place how long we know about it but I would say on the order of six to nine months.
00:39:36.000 --> 00:39:37.920
Six to nine months that's not that bad.
00:39:38.079 --> 00:39:40.400
That's a pretty defective and how much do I need to pay for it?
00:39:40.719 --> 00:39:42.559
That's also something that we can discuss.
00:39:42.800 --> 00:39:49.920
Well what I can say is that a lot of our competitors price their systems in the tens to hundreds of millions and we're about an order of magnitude less.
00:39:50.159 --> 00:39:53.039
Wow okay so you're competitive on that point as well.
00:39:53.360 --> 00:40:01.840
We are yeah we're price competitive and not just against other quantum technologies right we're we're very mindful that we're competing against traditional compute capabilities.
00:40:02.079 --> 00:40:21.119
Yeah I think T what you said about you know not losing the point of not falling back and using this technology but also not staying with useless hardware in the future and in your system of upgrading it this is very powerful and I think this is something we should emphasize a lot.
00:40:21.360 --> 00:40:38.960
I have sometimes impression that some of the big companies may regret you know that they were too early some technologies were not developed yet and now they just don't know the choice they invest more on what they have already right yeah um so so that's that's very important as well.
00:40:39.199 --> 00:41:06.000
Okay last question now just for fun maybe we can create a wheel from that finish the sentence quantums become truly useful when quantum is truly useful when it's taken for granted right so it's going back to the whole boring concept right boring doesn't mean that it doesn't have huge impact boring means that it's reliable is trustworthy and it's ubiquitous and that's that's exactly when we know quantum has has made it that's true.
00:41:06.639 --> 00:41:42.800
Thank you so much I really enjoy um the discussion today and with this beautiful um summary let's make quantum boring that's right let's finish our discussion thank you thank you that was Blonde and Quantum thank you for joining me on this journey through the quantum business frontier if you like the episode please review another Spotify or Apple Podcast and help more people discover the quantum world without needing to untangle the theoretical physics see you next time unless the caption
