How Quantum Computing Could Reinvent Supply Chain Sustainability

In this episode of the Sustainable Supply Chain podcast, I sat down with Dr Erik Garcell, Director of Quantum Enterprise Development at Classiq, to explore how quantum computing is moving from theoretical buzz to practical tool, and what that means for supply chains.

We talked about why quantum’s real strength lies in optimisation: solving incredibly complex problems like route planning, inventory management, or energy grid design far faster than classical systems ever could. Erik explained how quantum is already being used via cloud platforms (yes, even on AWS), and why enterprises, from BMW to Mitsubishi Chemicals, are experimenting with it now, not later.

We got into real-world use cases too: dynamic logistics recalculations in response to disruptions, quantum-enhanced digital twins for EV battery design, and how this tech might support real-time, low-carbon decision-making across vast supplier networks.

This isn’t about replacing classical computing, it’s about adding a powerful new tool to the box. Erik also gave practical advice for supply chain leaders: how to start engaging with quantum now, when upskilling your existing team makes more sense than hiring PhDs, and what pitfalls to avoid.

If you’re wondering when, or even if, quantum computing will matter to your business, this is the episode for you.

🎧 Listen now to understand why the smart money is investing in quantum today.

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Most of the time we're doing these kinds of, of processes either one-off simulations, which take huge amounts of computational power to try and simulate these systems, or you're doing it experimentally, which is again, a huge overhead cost to be trying to do this experimentally, both to have the, the resources in-house to do it experimentally the, the infrastructure and the, knowledge base. You'd have to have your employees, available to do this experimentally. Good morning, good afternoon, or good evening, wherever you are in the world. Welcome to episode 76 of the Sustainable Supply Chain Podcast, the number one show focusing exclusively on the intersection of sustainability and supply chains. A huge thank you to this podcast's, amazing supporters, Kieran Ognev, and Alicia Farag. You really help to make this podcast possible. If this podcast regularly brings you value and you'd like to help me keep the podcast going, support starts at just three euros or dollars a month, which is less than the price of a cup of coffee. And you can find the link in the show notes of this or any episode or at tinyurl.com slash sc pod. Now, you know that nightmare scenario where a ship blocks the Suez canal and suddenly your whole supply chain is in chaos? Imagine recalculating your entire global logistics strategy in real time before the coffee kicks in. That's the kind of future quantum computing is unlocking, and today's guest, Erik Garcell, is right at the heart of it. He helps Fortune 500's use quantum, not in some sci-fi lab, but right now to tackle the hardest optimisation problems in logistics, energy grids, urban planning, and even EV battery design. Erik's team at Classiq just raised the largest quantum software around in history, $110 million, and they're building the development platform right now that could become the Microsoft of Quantum. In this episode, we unpack what that means for sustainable supply chains, when you should care, and how soon your teams might need to upskill. This isn't hype. It's the next great leap in compute power, and it's closer than you think. But before we get into that, in the next few weeks, I'll be talking to Matt Trubow, who's the commercial director of Hidden. Ollie Carpenter, director of Environmental Risk for Risilience, Conrad Snover, CEO of Pro Curability, and Steve Saltzgiver, director of Fleet Success at RTA Fleet. But as I mentioned, my special guest today is Erik. Erik, welcome to the podcast. Would you like to introduce yourself? Yeah, absolutely. Thank you Tom. It's a pleasure to be here. My name is Dr. Erik Garcell. I'm the director of Quantum Enterprise Development for Classiq's operations, at least in the the North America geography here. And Classiq, the company I represent operates in the quantum computing software space. Classiq is spelled with a Q So it's A-C-L-A-S-S-I-Q. and We develop and offer a software development platform for quantum programming. We want to turn, quantum programming from something that's esoteric and intimidating to a lot of people and to something that's approachable and familiar for anybody with a computer science degree, you know, and programmers of all backgrounds. And at Classiq we we're doing that 'cause we believe that the democratisation of quantum computing is what's gonna enable this new technology space right, there's so many applications that this new tech can help out with and apply to, but if it's not widely accessible, if it's only accessible to the few with enough skills and deep education background required, it's not gonna do much societal use, right? It won't be widely utilised and it won't help out in the long term. And you mentioned you're making a software development platform for quantum computing. So analogous, I suppose, to Visual Studio for classic computers. Your product is similar except it's for quantum as opposed to classic computers. Why? As in, I can't exactly go on Amazon and buy a quantum computer. There are not a lot of them around. So where's the demand for your software platform coming from? Yeah, and it is funny you say that. it's, uh, It's quite expensive to be buying a quantum computer and have one, you know, sitting in a facility, right? That's millions of dollars to do at this Uh, There are companies that'll sell it to but, uh, funny you say Amazon, you can actually go on their cloud and the same way you would buy time to use a supercomputer or, you know, some of their GPU assets on the, the AWS uh, cloud system, you can do the exact same thing for quantum computers. You can buy some credits and use quantum computers on the cloud. And, and a lot of these vendors, these cloud vendors have these quantum clouds, right? Microsoft has a quantum cloud, IBM has a quantum cloud, AWS has a quantum cloud. So you, you could, if you wanted to right now, buy some and uh, go and play around with it a little bit. Um, So you're, you're right though that it is a new technology and that we're developing something that is more visual studio based, kind of, you know, something that's a platform that looks familiar, feels familiar, and uh, to be something that's, that's useful in this way, because the way most people are programming these systems is almost the equivalent of Boolean logic for classical computing. Okay, so more drag and drop than actually hard coding as it were. So, why do we care? As in, first of all, this is the Sustainable Supply Chain podcast, not the quantum computing or the next great greatest thing in technology podcast. Why do listeners to this podcast and why do I care about quantum computing? Yeah, because it's, it has so many wide applications. And especially in optimisation, which is a huge part of, you know, both sustainability and supply chain. We talk about all this from a scientific standpoint 'cause things are, are still very scientific and, and dealing with some of these systems. We're getting to be more commercial in the industry. At the end of the day, what people need to know is that this is a new computing resource. In the same way that, you know, when GPUs came out, they didn't replace the CPU. It worked alongside CPUs to allow computers to do things that maybe they weren't able to do before, or were just too slow on that CPU. These new quantum resources, we can just call 'em, you know, QPU's right. These quantum computers are new processing resources that will more efficiently run certain types of algorithms. But we wouldn't be doing a podcast over a quantum computer. Right. That would be terribly inefficient. It's not what that technology is for. You're better served on, on your, your classical resources, but it's going to enable us to do things, you know, in real time, a little snippier a little faster, or do things that we didn't think were possible with compute resources before. So, there's lots of applications in the space and like I said, optimisation is one of the bread and butter applications for quantum computing that we know definitively, you know, we can do it mathematically on paper at quantum quantum resources, quantum computing will be able to solve optimisation problems exponentially faster than classical compute resources. You know, for the, for the same number of resource, you're gonna get an exponential speed up in your, your quantum processing. Right. Obviously. I'm not going to be using it for things like, as you mentioned, making podcasts, writing emails, not gonna get an exponential increase in the speed of writing or, or sending an email. but you mentioned optimisation problems, so go into that in a little more detail for me, for people listening to the show. What kind of optimisation problems would it be possible to solve exponentially faster with the likes of a quantum computer? Absolutely. So, you can think about things like, a traveling salesman problem is a classical mathematical problem where you have a, you know, a delivery driver coming from their, pickup spot where they have to load all the packages, they have to go to so many different facilities and back to their original home base. This is classically a very difficult problem for regular computers to solve, but one that quantum computers can solve quite easily and nimbly. And this kind of problem, right from one, you know, starting from one location, having to loop back to that same location, but meeting, you know, five, eight, a hundred, a thousand, different places you have to go along the way. The, the more places it has to go, the more computationally intensive it becomes, kind of the, the value of quantum computing starts showing up. But this problem is how your packages get delivered to your house, right. UPS, FedEx, they have to optimise this. This is how the, the drones at an Amazon facility move packages from one place to another without also colliding with each other. How do you optimise those routes? How do you do this faster? Cut costs? How do you route through commercial channels globally, right? Through airplanes, through shipping routes, and should a shipping route get blocked, which happens from time to time, right. The, the Suez Canal will get blocked. The, the Panama Canal will get blocked, and all of a sudden, all of these supply chain corporations have to figure out how do you reroute all of your operations in as minimal amount of time as possible without incurring you know, tremendous additional costs. These are the kinds of problems that quantum computers are gonna be able to, to help solve. And this actually gets a little bit away from a pure, what's called a traveling salesman problem, and gets into, you know, if you're looking at it from a mathematical standpoint, what's called the unit commitment problem. You know, how do you solve this and minimise costs while still, meeting the, the need you have at the end of the day. It's fascinating the, the number of applications you can apply this to. There's urban planning you can have also, right? How do you set up a city most efficiently, or how do you set up, charging stations for your electric vehicles in a city in a way that makes most sense in a way that's distributed and meets the needs of, the citizens in that city. Okay. And when we hear the term quantum computer, we often think of something that's way out in the future. Where are we really at in terms of real world deployments? I mean, you mentioned there are some cloud ones available through some of the big tech companies. But if I were to start writing a program now to run on a quantum computer. Am I going to be at the very, as it's called, a bleeding edge, is it gonna be painfully expensive? Would I be better off waiting three, four years until there's more quantum computers and the price comes down? Great question. Right? And it depends on what kind of corporation you are, the size of your corporation, and how much having kind of this first mover impact matters. Hmm. Right? There. There are quantum computers that are being sold today. There's quantum computers. without going too deep into, you know, the differences between all these systems, there's quantum computers sold by companies like, D-Wave ion Q, Qra, IQM. There's plenty of companies you can buy these systems from today, have 'em deployed in your system. There's even, you know, third party integrators that'll help you put all the pieces together for you, like a company called Trek that will take the hardware and the software and your infrastructure and make sure it all works, you know, cohesively together. So we, we have the ecosystem and the model to put it together, but you would be on the bleeding edge if you wanted to start using it today. Right. You would be one of these, you know, first movers to be utilising this technology. But one of the things to consider too is, how long will it take for your company to implement this technology, right? Because if you wanted to start using it today, you needed to have started this journey three years ago. Okay. you can't just turn around and say, I want to start using it. So, starting investigating this technology won't be, you're not gonna be putting it into your products tomorrow. You know, or the advantages thereof. It, it's a bit of a digital transformation roadmap. It's gonna be a bit of time to make sure that, you know, this new compute resource works alongside your CPUs and GPUs. That it goes through all of your, your SOC two security, all right? That you're not breaking any MSA agreements with your clients if it's integrated into those kind of things or applying to them. There are very interesting applications happening. Unless you're a Fortune 1000 company, I wouldn't consider buying hardware today. I would consider using, using the resources on the cloud. And as they increase, you can just pay for the credits on the new systems as they come out, because the technology is moving very quickly. So for, for most users of this technology, I would definitely advocate use it on the cloud as they advance, and evolve with the cloud, as those new resources get advanced and move forward. So, so there's lots of different applications and it depends on, you know, how many resources you need on that quantum system to do the thing you want to. And how different are the different cloud provided quantum computers from one another? In other words, if I decide to go down the D Wave route or the ionic one, or the Microsoft one, or the Alibaba one or whatever, do I need to worry about vendor lockin? Do I need to, if I want to move from one to the other in three years time is all the work that I've done in one thrown out and I have to start again? A little bit of column A and a little bit of column B on that answer. I think it's first important to say that there are two types of quantum computers being developed. Right. There's a type of quantum computer being developed that's called a quantum annealer, and that's the kind of quantum computing system that is being produced by D-Wave. And there is the type of quantum computer called a gate based or a universal gate based quantum computer that's being produced at first kind of the likes of IBM and now many other companies. So, we have these two types of, of programming and, and quantum systems being developed. Okay. And. Coming back to supply chains, Mm-hmm. given this is the Sustainable Supply Chain podcast, there's there's a lot of talk in the supply chain space recently around resilience. Do you see any way that quantum could help make supply chains more adaptable and robust in the event of shocks? Absolutely. Yeah. One of the things that quantum computing, uh, it's not gonna be a near term application for quantum computing, but this is definitely one of them is real time adapting to to scenarios. Solving these very, very large, mathematical problems. At the end of the day, these graph theory problems with many, many nodes and routes between them, you know, your destinations and, and how long it's gonna take or the costs incurred hugely computationally intensive to, to figure out the best or most optimal path. And as soon as one of those routes is disrupted, it disrupts the entire industry. It disrupts your entire system because it's not an easy task to recompute that. It's not a fast task, it's not a cheap task. And to get to an answer with any kind of confidence means that that algorithm probably has to chug for a long time to get to something with a high enough, confidence interval, you know, mathematically. So, quantum computing is gonna speed that up by making that class of problem not as computationally intensive. If you run it on a quantum computer, means that it's now something you can run in more of a real time scenario. And as the the hardware gets larger and larger, you're gonna be able to more dynamically run these optimisation algorithms time and time again. You know, it might be that in a year you'll only be able to do it once a month. Then, you know, in six months you'll be able to run it once a week and you'll get to a point where the hardware is large enough you have enough of these compute resources where you can have an on demand recalculation of your optimisations. So, it's going to make it more robust in this way, but also in the identification of, almost new nodes on your graph, right? If you're talking about sustainability, right? If we look at energy grids, what you can do right now is identify a weak point in your energy grid, right? If this, if this plant goes down, or if this one line between, you know, my, my grid goes down, it disconnects the city into these two wholly separate parts that aren't talking to each other anymore. We can use quantum computing to identify more readily these vulnerabilities, right? Where is there a weak point in my energy grid infrastructure? How might I shore it up? And where would I put a new node, a new plant, a new generator or new electrical lines to shore up these vulnerabilities? And Classiq, you've worked with names like BMW and Rolls Royce. What lessons have you taken from those kind of projects that could apply more broadly to supply chain sustainability? We're finding that once you start looking at quantum computer as fundamentally as a new compute resource, once you start thinking about quantum computing as a n engineer or a computer scientist would, that's what starts opening up the applications for what you can do with this technology and goes, okay, I, I get this, now I get the applications for it. We, we worked with BMW, they were a fabulous group. They, they already knew how to program in quantum computing. We had a, I think a one week intensive workshop with them to do something. They, they came to us with an academic paper and said, Hey, we thought that this application that was talked about in a paper was really cool. How do we do that actually with a quantum computer? How do we do this, this, you know, hypothetical thing practically, Hmm. and we showed 'em in our platform. You know, how do you put that kind of algorithm together? How do you use it and how do you move forward? So we were solving that, that unit commitment problem we were talking about, you know, they wanted to look at cooling systems and their, and their engines, right? And their, their cars. So if you have an engine, if you have these different parts, if you have a car battery all running, how do you cool these systems as efficiently as possible? Where do you put the cooling systems, to make that optimised? How do you do that with a quantum computer? How do you program that in? And once they start getting this, okay, now I, now I get how to think about quantum computers and how to use it. How to put these algorithms together. Now, BMW feels more confident to run and perform other projects that use these kinds of frameworks, right? Right You can think about the problem, as a problem, right? As the, the challenge you're facing at, at the forefront. So, you know, we worked at BMW in this way. We worked with a, a Rolls-Royces avionics division, doing computational fluid dynamics, and plenty of others, right? We talked about some already here. I know we worked with Mitsubishi Chemicals on some interesting chemistry applications. Sure. it just uses less resources and it's easier to do than having a classical computer pretend to behave quantumly. Okay. yeah. So, talking about chemistry, things like making higher energy density batteries for and for utilities for energy storage or on the intro call, I, I mentioned the Haber Bosch process, for example, these kind of things those would be ideal, I assume, for quantum computers. Exactly. These are the kind of problems that quantum computers are gonna unlock, right? These problems were very difficult to solve. You know, these problems, you know, for, for electric batteries, even for, for drug discovery and things like this. Most of the time we're doing these kinds of, of processes either one-off simulations, which take huge, amounts of computational power to try and simulate these systems, or you're doing it experimentally, which is again, a huge overhead cost to be trying to do this experimentally, both to have the, the resources in-house to do it experimentally the, the infrastructure and the, the, the knowledge base. You'd have to have your employees, available to do this experimentally. So quantum computing is gonna unlock the ability to do chemistry, chemistry simulations, chemistry modeling, computationally. It's gonna make that much easier. So you're gonna be able to use quantum computing to simulate what's the band gap if I put this chemical and this chemical together? How would that work out practically? What's the heat dissipation look like if I also put that together in a, in an infrastructure, right? You start mixing in these problems, there's the chemistry side of it. There's, you know, we're talking about heat dissipation, that's the, the computational fluid dynamics part of things. Quantum computing is gonna be able to put these pieces of the puzzle together to make it so that you can solve things like the Haber-Bosch problem or, carbon capture. Also, how do we, you know, what chemicals, what can we put together that would be able to both capture and store carbon for longer periods of time? What can we do that would enable that? You're gonna be able to simulate systems that will be able to solve these problems. So whether you're, you're trying to solve the Haber Bosch or carbon capture or, I can't say definitively, but I, I know most our automotive manufacturers are looking at quantum computing already for building better batteries, both for having, you know, a more storage but also faster charging of these batteries 'cause no client of their, ev cars or wants to wait 20 hours for that car to charge. You wanna get to 80% charge within an hour. How do you get there? What will get you there And store Most, most EVs can do it. Now. Most new EVs can go to 80% now in 30 minutes or less. Exactly. These kinds of things are what's being investigated and can absolutely help out with, I've used some of them in, in my graduate career called like a comsole of these other platforms you can use that do multiphysics simulations. But if you're doing a large system, you're only gonna be able to either simulate a small part of your system with a high granularity, or if you're simulating your whole system, you're gonna have it be very low resolution to be able to do your whole system you know, with any confidence. So, quantum computers is gonna make it so that you can do your whole system with a higher granularity, with more confidence, or with, you know, finer time stamps. Sure. you don't wanna find out in the air that your airplane vibrated at a certain frequency you weren't aware of when hit by a certain wind turbulence at a certain angle, that's, that's a bad thing to find out. Sure. you didn't figure it out because the, the grid sizes of your mesh on your simulation, right, the areas you're doing your physics on, were too large to actually see that in the modeling. Sure. You know, are the things that, that quantum computing is gonna help out with and really help speed up and enable. Right? Right? So, so much of what quantum computing is gonna help out with is almost gonna feel like, like how AI has helped out in ways. It's been in most every product we've used already. Right. You know, when you, when you do a phone typing. And you get all those, you know, auto corrects on your phone. That was ai. I think quantum computing will probably evolve in the same way. It's gonna be used in a lot of these background calculations. It's gonna be used in ways that most everyday users of technology won't see or even realise quantum computing is being used or implemented until it hits a level of computational power and ease that, anybody can, can go ahead and start doing some fun things with it. Do businesses now need a whole new team of quantum scientists or, you know, can they upskill existing people? You know, if I'm a, a manager now I'm saying to myself, this sounds cool, but I don't have a quantum PhD in staff. Where do I even begin? Yeah, that's, that's a great question actually.'cause every Quantum conference I go to, there's at least one panel talk or, or one topic or session on the quantum talent shortage, right? The need for those skilled in this industry, is growing faster than those skilled in this industry, the people gaining these skills, so while universities are spooling up their programs to train students on how to program and use this new technology, right? You see tons of these new university offerings popping up on, on quantum education and quantum software development. But this, this need is booming in such a way that managers are having to figure out right now, should I pay for one of these, frankly very expensive new graduates, with the skillset? Or can I upskill my existing team? And there's advantages there too,'cause your existing team knows your infrastructure very well. They know the problems you're trying to solve. They know your clients and, and what's needed and how the rest of your system works together. So, it would be highly advantageous for these managers to upskill their current employees. If you're using a platform like Classiq or any of our competitors that are trying to move quantum computing to this higher abstracted level, right, to something that's more analogous to classical computing, it's much easier to upskill your current engineers. It becomes a much, much cheaper prospect, a much more feasible prospect.'cause it takes frankly, less training time, right? It, it doesn't, it's not as big a lift to train somebody to program c plus plus than it would in pure Boolean logic. Right. It, it's just a, a less heavy lift. It's gonna cost less, it's gonna take less time, and it's easier for a manager to say yes to upskilling that than you know, those current engineers. So, it depends on what you're trying to do in quantum computing. I think you do need somebody who understands where quantum computing will help your infrastructure and help your company. Mm-hmm. where it won't is equally as important to understand from the, the set, from the, the starting point. So, You can do that in a couple of different ways. You can hire somebody to help you out with this. One of these students who are educated in this. You could work with a number of companies that will facilitate that investigation that help that work on figuring out where in your corporation might quantum computing assist with, where won't it help with, what are the timelines we're looking at for this? For most of the development thereof, we're getting to a place where you can upskill your current workforce. You can take your current software developers take a day a week for them to do some training on this new way of programming and how to connect that to their classical resources. We're working already in a place where quantum computing and classical computing are connecting. They're not disparate systems. But in this way, you know, your engineers are probably gonna be more sophisticated in your current HPC stack than somebody new you hire. While somebody new would have the expertise and a know-how of quantum computing, you still need your, your in-house software developers to learn these skills to upskill and help that newcomer figure out how do you connect all the cool things you're doing with our HPC stack. I still think you need somebody who can help you kind of understands the ins and outs, but this point we're getting to a place where most managers can and should upskill their, their current workforce. And if you put on your futurist hat, what's the moonshot potential of quantum computing for supply chain sustainability over the next decade? If I, if I could have my magic wand and say what would be the really cool application for this for logistics and supply chain? I think it would be real time dynamic logistic calculations. I think it would be phenomenal to say, there's a road outage that just happened. There's inclement weather that's impacting certain routes or for safety reasons, it's not good to go that way. Quantum computing tied into essentially many different data repositories. Being able to chug all that big data, analytical data on weather, on road, traffic, on real time costs incurred about one versus another traffic route or vendor that you're buying from, and having it be a dynamic real time calculation to both save in the time and cost incurred in any logistics operation. I think that would be kind of the end point. The really cool place to get with quantum computing and where I can see it bringing a lot of good to logistics. Sure and optimising for reduced carbon as well, obviously. Absolutely. Yeah. So, thank you for that. Right. The one route's gonna be shorter, so I mean, it depends on what your company's most interested in, right? And having that be part of that calculation, right? There's the cost incurred, but there's also carbon, right? Even in Google Maps today, you can choose, do I want the shortest distance? Do I want the fastest distance? And, uh, I think now they, they have a little button that says, right, this is the eco-friendly route. Okay, We're, we're gonna have that too with, with logistics, you know, how important is the cost savings versus the carbon emission of this route versus that route, or sending certain parts of your, your, your, fleet of, of trucks. Should I send the EV trucks? Should I send the, the gas trucks? Maybe you have some gas trucks on reserve for certain situations. When should I deploy them? These are the kinds of things that I can definitely see quantum computing helping out with, having a big impact, and ultimately optimising these so we have lower costs, lower emissions, faster times to delivery, faster times to accomplishing your goals, whatever they may be. There's been a lot of talk as well about quantum breaking encryption. Should supply chain leaders be losing sleep over this? This is one where, I think that is the application that's getting definitely the government's attention. RSA being broken is a big deal and a big deal for a lot of companies, right? RSA encryption is how we encrypt most of the data on every computer you're using. Right. Your, your laptops are using RSA encryption for how it communicates to other computers, how you're, you're doing most everything. It is true that quantum computers are going to break RSA encryption. It's not an if, it's a when it statement. One of the big cloud vendors finished putting a, a publication saying, Hey, we just came out with a, an optimal way to program what's called Shores algorithm, which does RSA encryption, which actually just sped up the timeline for when RSA will be broken by quantum computers. So, it is something you have to worry about with caveats. Any company now has to look and say, how long does my company's data matter for? Will my data that I have in store today securely have any value to my corporation or cause any legal issues if it got out in five and 10 years? If the answer is in five years, the data I'm storing today has no value. You don't need to worry. You're good. Corporations, and government institutions like in the US where I'm at, NIST, the National Institute for Standards and Technology has already been investigating quantum computing, safe security protocols, figuring out which are the most robust, easiest to implement, and coming up with new standards for what to transition into and how to do that transition. And once they come up with their standard third party integrators are gonna come out and help you with that transition once it's standardised. So if your data doesn't matter for more than five years, if it's not gonna bring you value more than five years. Wait for your government to come out with new standards. Wait for those third parties to, to come out and they will, you know, you can pay for their service. They'll help you migrate. Do migrate when that happens. Absolutely. Or your data will be available to be decrypted. I wouldn't say you have to worry anytime soon for that. Now, if your data does have value in the next five, 10 years, if you're a government contractor. If you are a government entity, right? Your data matters and what bad actors are doing right now, I would say, is what's called, take now, decrypt later. They're taking data, storing it, even if it's encrypted. They can't break into it right now. When computers get powerful enough in five or 10 years to do this. Then they'll be able to break into it and see the data that they collected five years ago. So if that data still has value, then you're in trouble.'cause now you can consider anything that you have that is of high value almost as if it's already been broken into. Right. So you do have a bit of a, a lead, on that. So you, as long as you shore up your systems now. Most people are good, but, we are in a hairy place where if, if you have high value data, it may have already been gathered and in five or 10 years it's probably gonna be public or, or used by, by a bad actor in some way. So that's why governments are so worried about it. As a corporation for this quantum breaking RSA encryption, how long does your data matter for? If it matters and brings you value or create some kind of a security issue for you in five or 10 years, you do have to worry if it brings you that value. If your data doesn't matter at all in five years, who cares who sees it in five years? You know, you should be holding onto it and keeping it secure, but it's not gonna cause any issues, any regulatory, any cost incurrred to your corporation within the next five years. You're fine. Move over when your country says to move over, move over when these third parties are there and available to help you migrate your current RSA to, to further protocols. Okay. Fair enough. Left field question for you. All right. Oh, I like these. If you could have any person or character, Yeah. alive or dead, real or fictional a champion for quantum computing in supply chain, who would it be and why? Oh my, a champion. Ooh. I've always been quite the fan of Richard Feinman. there's a couple of physicists out there in the world who over time have shown to have the knowledge to understand the intense mathematics and, and concepts going on, but the kind of broad overview of many industries and the capacity to tie these things together in new and interesting ways. I think everything, Richard Feinman was a physicist who was able to do that. He worked on the, the Manhattan Project and he was one of the first advocates and, and kind of proponents for quantum computing I think very famously, I'll say an abridged clean version of it.'cause I think he gets a little colorful in the quote too. He said you know what, the world behaves quantum mechanically, right? Nature behaves quantum mechanically. So if you wanna simulate nature. You need to use a quantum computer, right? It, it, it seemed almost, you know, simple for him, right? If you wanna simulate this thing that happens in a certain way, you need to simulate it in a certain way. And he always believed that this would be something that would be possible. It was an inevitability. And I would love to see his thoughts on this new technology and where it can apply and how it can apply. He had the mind to be able to see kind of logical consequences of these new technologies, of these new calculations. How it can apply and how it can apply to so many different industries and, and cross-disciplinary fields.'cause he, he was also a physicist who, got away from physics every once in a while and started publishing in chemistry and doing really interesting things in different fields but saw all the ties and how they really all do connect together at the end of the day, from its core principles. So, it would be really fun to have a chat with Richard Feynman and say, where do you see this going and how do you see this connecting to all these different industries and applications, the problems we have in the world? And, and given this technology and new compute resources, what would you do with it? I would love to hear his answer on that. Great. We're coming towards the end of the podcast now, Erik, is there any question I haven't asked that you wish I had or any aspect of this we haven't touched on that you think it's important for people to be aware of? Yeah. I think one of the biggest things we deal with as far as being individuals in the quantum computing industry is a notion that quantum computing is this herculean thing, right? This mountain of intimidation. You know, I talk to companies and, you know, as soon as I say the word quantum, it brings up notions of physics. Something about physics has a connotation being extremely difficult. If you're doing it, oh, you must be a smart person. You know, it, it almost has this, this concept of difficulty. So we, we get a, a, a not it situation where on the call everyone puts their fingers to the nose and says, Ooh, not it, you know, let, I'll let somebody else in my company handle the quantum side. But we're, we're getting to a place where quantum computing is becoming more intimidating than, than it should be seen as. It is more computer science than physics. You can do interesting problems and solve interesting challenges using this new technology. While it still has a stigma of being difficult, it's not as intimidating as you're probably imagining it to be. You can go online right now and program a problem that does a raffle for a contestant of, you know, at, at a convention or, you know, you put your, your business card in a fishbowl, and pick out who the winner is using a quantum computer. You can put together GUI applications with quantum computing. You can do interesting problems that at the end of the day will look the same as any other classical computing thing you've done right. You can put these kinds of interesting programs together using this new resource and have fun exploring it, right?, Quantum computing is no longer as intimidating as people might imagine it to be. It's a new resource that companies should be investigating because it will apply to almost every industry. It's just a matter of where will it apply for you and when will it apply for you? Are the questions that each company and corporation needs to find out the answers for themselves on. Erik, if people would like to know more about yourself or any of the things we discussed on the podcast today, where would you have me direct them? Absolutely, feel free to visit our website, Classiq.io. So cl A-S-S-I-Q, dot io. We have lots of resources there. If you're looking at quantum code, there's, you know, there's a link to our GitHub that you can have some fun and check out, different use cases and applications. And feel free to reach out to me directly also. I'm always happy to talk about quantum computing like this, Tom, I have a blast answering these questions and I love helping people figure out how quantum can apply, where it can apply and, and all the fun that you can have with it. So feel free to email me at Erik erik@Classiq.io. Super. Erik, that's been fascinating. Thanks a million for coming on the podcast today. Thank you for having me, Tom. Okay. Thank you all for tuning into this episode of the Sustainable Supply Chain Podcast with me, Tom Raftery. Each week, thousands of supply chain professionals listen to this show. If you or your organization want to connect with this dedicated audience, consider becoming a sponsor. 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