About Izhar Medalsy, CEO of Quantum Elements

Izhar Medalsy is the Co-Founder and CEO of Quantum Elements, a deep-technology company pioneering a unified, AI-enhanced software stack designed to make quantum computers practical, reliable, and production-ready.

Quantum Elements integrates every layer of the quantum workflow—from hardware bring-up and calibration to simulation, error suppression, and error correction—into a seamless platform powered by advanced modeling and intelligent automation. Izhar’s mission is to accelerate the industry’s path toward practical quantum advantage by connecting the dots across the quantum stack and enabling system operators, researchers, and developers to work with unprecedented speed and precision.

Izhar brings more than 15 years of experience in advanced engineering, emerging technologies, and organizational leadership. Before founding Quantum Elements, he held senior R&D and technology roles where he built and scaled multidisciplinary teams, drove complex product initiatives, and helped translate frontier science into tangible business outcomes. Izhar is a frequent speaker on quantum acceleration, simulation, and the role of AI in next-generation computing systems.

Izhar hold a PhD in Physical Chemistry from the Hebrew University of Jerusalem, Israel and did his post-dot at ETH Zurich.

Izhar’s Links

Izhar’s Company: https://quantumelements.ai

Izhar’s LinkedIn Profile: https://www.linkedin.com/in/izhar-medalsy-5b674546/

Summary:

David W. Schropfer and Izhar Medalsy discussed the evolving landscape of the quantum workforce, noting an increasing influx of talent from non-traditional physics backgrounds, which is essential for the industry’s growth. They emphasized that the quantum computing sector requires diverse roles beyond engineering, as the technology is not expected to produce consumer-grade products like laptops. Izhar highlighted the necessity for a skilled workforce that understands both quantum and classical technologies, advocating for cross-disciplinary opportunities, particularly in control electronics and mechanical engineering.

The conversation also covered the transition from research and development to practical applications in quantum technology, with Izhar expressing optimism about its imminent real-world uses in fields such as chemistry and optimization. They explored the role of agentic AI in enhancing productivity within quantum computing, allowing individuals without coding skills to participate effectively. Additionally, they discussed the advantages of Quantum Elements’ platform for investment banks and technical teams, which enables users to simulate quantum environments and explore algorithms without extensive coding knowledge. The discussion concluded with reflections on the transformative potential of quantum technology compared to AI, with Izhar inviting further engagement with Quantum Elements.

SHOW NOTES:

#89 – Is The Expanding Quantum Computing Workforce Your Next Career Move?

Welcome back to DIY Cyber Guy.
Hair on Fire: 1 out of 5
Effects: Future Quantum Professionals

In recent months, we’ve talked several times about the biggest technology shift on the horizon: Quantum computers.
• when they’ll break all of our encryption,
• if error correction will come under control,
• whether the quantum threat is three years away or thirty.
But lately, the entire quantum industry is beginning to pivot; the conversation is evolving from the actual machines and to the human beings required to run it.
Quantum computers can perform mind-bending calculations, but they are fragile, error-prone, and require a workforce that, frankly, doesn’t exist yet. The sheer gap in talent is now the biggest barrier to quantum adoption.
An MIT senior lecturer and research scientist named Jonathan Ruane said:
“We expect to see a proliferation of folks who are not researchers in quantum technology gain employment in the broader quantum market,”
SOURCE: https://mitsloan.mit.edu/ideas-made-to-matter/building-a-quantum-workforce

Today, we break down why the push to build a quantum workforce is the only thing standing between us and the coming age of Quantum computers.
Here with me to talk about all of this today is Izhar Medalsy, a serial tech entrepreneur and co-founder and CEO of Quantum Elements, which is a company dedicated to unlocking the power of quantum computing and making this new technology accessible to engineers and the workforce both inside and outside of the Quantum Industry.

Welcome Izhar!
Q: How would you characterize the Quantum Workforce today – is it starting to evolve beyond PhD engineers?

TRANSCRIPT

0:00 – David W. Schropfer
Welcome back, everybody, to DIY Cyber Guide. This is episode 89. Is the expanding quantum computing workforce your next career move? Now, this is a hair on fire one out of five. This is really for future quantum professionals. If you’re working in another industry, whether it’s in marketing or even accounting, or other types of areas where you’re not a PhD quantum physicist, but you’re thinking about this new industry that we’ve been talking about so much, then this is for you, especially if you think it’s an industry that is going to take over most of computing, which is one of the theories about where this technology is going. So in recent months, we’ve talked several times on this podcast about what we think is the biggest technology shift on the horizon, which is quantum computing. Computing? When will they break encryption keys? Is the error correction issue going to become under control sooner than later? Is the proliferation of quantum computing three years away or is it 30 years away? These are all types of topics that we’ve wrestled with and talked about many times in this podcast. But lately, the entire quantum industry is beginning to pivot, the conversations evolving from the actual machines to the human beings that are required to run it and run the businesses around the industry. Quantum computers, as we’ve talked about, can perform mind-bending calculations, but they’re fragile. They’re error-prone. They require a workforce that, frankly, is still evolving, not only to make the machines operate, but to make the businesses work to their greatest capacity. Mapping talent is now one of the bigger barriers to quantum adoption. Came out with a report recently written by a senior lecturer and research scientist named Jonathan Ruane. And I’m quoting the article now. We expect to see a proliferation of folks who are not researchers in quantum technology gain employment in the broader quantum market. And I do have the source of that quote and that article on DOI Cyber I just searched for episode 89. So today we’re going to break down the push to build a quantum workforce and make quantum computing the industry that it’s evolving to be, which again, can’t just run on PhDs and quantum physicists and highly skilled engineers. There’s a whole field of resources that have to be available to these companies as we go So here with me to talk about this today is Isar Medalsy, a serial tech entrepreneur and co-founder and CEO of Quantum Elements, which is a company dedicated to unlocking the power of quantum computing and making this new technology accessible to engineers and the workforce both inside and outside of the quantum industry. Welcome Isar.

4:12 – Izhar Medalsy
Thank you for having me David.

4:14 – David W. Schropfer
Thanks for being here. So my first question to you is how would you characterize the quantum workforce today? Is it starting to evolve beyond PhD engineers?

4:25 – Izhar Medalsy
I would say we’re starting to see this shift or this addition of talent coming from disciplines that are not as hard and exact as, you know, PhD in physics and quantum physics, etc. And to be honest, we need that because the industry is growing very fast. And in order to catch up with this growth, we need to be able to translate some of the know-how that we have now in quantum to the other fields that can be highly adopted by those talents that are coming in.

5:06 – David W. Schropfer
Okay, good. So we’ve talked about how quantum computers are different computers. The industry is going to be different. There’s never going to be a quantum laptop, or I’m sorry, I should never say never, but there’s probably not going to be a quantum laptop in our future. These are going to be industrial grade machines that are available through large networks and large enterprise systems or shared resources. So the industry is going to be different. We’re not going to need salespeople in a CompuServe retail location necessarily. So what are the kinds of positions that are starting to be required by the industry today beyond the engineers?

5:53 – Izhar Medalsy
I agree that conceptually and practically, quantum is very different. It uses a different set of physical rules. It solves problems in a completely different way. It means that everything that we know from how to fabricate those components all the way to operate them works differently than classical devices. But the key principles are still the same. You need to fabricate. You need to connect. You need to measure. You need to deal with errors. You need to start building circuits and algorithms. You need to deploy those algorithms. You need to connect them to the real world and to the cloud. So in order to do that, you need a workforce that is already kind of dealing with all of those problems on the classical realm of things, right? If you look at fabrication facilities for semiconducting industry, in some respect, these are the same facilities that are making the GPUs that today will make the QPUs of the future.

7:01 – Izhar Medalsy
If you’re looking at writing algorithms, then conceptually, yeah, they’re very different than classical computers. But once you abstract them enough, now you’re able to use a lot of the disciplines that have been developing and evolving in the last 50 years within the quantum realm. So there is a lot of kind of cross-disciplinary opportunities here, electrical engineering, and then we take it up and obviously marketing and sales and I think it’s definitely the time to think about how do we bring more people on board?

7:44 – David W. Schropfer
What an interesting way to think about it. I don’t think we’ve framed it that way ever before in this show that, you know, semiconductors as a great example of, you know, a highly technical manufacturing process requiring, you know, extremely small components to the individual chips, right? You know, clean rooms, and clean environments and extremely high technology just to manufacture. All those things are complete. I mean, it’s a different process to build a silicon bit versus a qubit in a processor. But still, that’s a very interesting corollary.

8:25 – Unidentified Speaker
Would you recommend that for people who are thinking about quantum, would you recommend that they come from the semiconductor industry or they come from I don’t know, maybe the Azures and the AWSs of the world.

8:41 – David W. Schropfer
Is there a particular part of computing or is there an industry outside of computing altogether where people should be thinking about, hey, maybe quantum is an area where I could thrive personally in my career move?

8:56 – Izhar Medalsy
I would open the scope even more. If you’re someone who is dealing with control electronics, you have you’re in high demanding quantum, right? If you ever dealt with lasers, then by all means, even if you’re a mechanical engineer, you know, you’re, you’re familiar with building racks and infrastructures. And these are all components that we need, and we need in scale. And the only way that we can catch up is if we are able to articulate in the right way, why we need this workforce and why it’s so attractive for those talents to come in and look at what we’re doing. From the outside, quantum might look scary. But when you break it down to its basic components, they’re more or less the same than what we’re familiar, but the setting is different. Obviously, when you go to the science level, there are big differences, but it doesn’t mean that you cannot participate in this in the workforce.

10:03 – Izhar Medalsy
Okay.

10:04 – David W. Schropfer
And what about a good old-fashioned business development? I mean, at the end of the day, somebody has to buy your product, whether it’s software or hardware, or it’s being offered as a service. Is Quantum really just big companies selling to big companies, or is there a more traditional business development aspect to it as well?

10:27 – Izhar Medalsy
Absolutely business development. I just said last week for dinner at UCLA with, you know, a gentleman that did this move from traditional, let’s say, SaaS platforms into quantum. And now he’s the general manager of one of the companies that are leading the quantum control electronics efforts. And, you know, the process is the same, you need to find the right application for your technology, you need to convince the person on the other side that that’s the right solution for him. Obviously, we’re still building the application space and finding the right places that quantum can be helpful. It’s still a future-looking industry.

11:10 – David W. Schropfer
We’re still in kind of the shift from R&D to real-world application.

11:15 – Izhar Medalsy
But as we’re very optimistic and very bullish on this technology, I think that we’ll see this technology manifest itself in those verticals sooner than than we thought before.

11:27 – David W. Schropfer
Well, let’s talk about that. So the shift from R&D to let’s just say a practical application that can be consumed and relied upon to give a correct answer to the question that’s being asked or the problem that’s being asked to solve, how would you characterize where the industry is today? How far away is that threshold between R&D and production? And is it confined to certain types of problems today? Or are there really still test problems that are about to be production problems and production functionality in the near future?

12:10 – Izhar Medalsy
It’s definitely one of the questions that the experts in the industry are dealing with on a daily basis.

12:17 – Unidentified Speaker
Yeah.

12:19 – Izhar Medalsy
You know, my thought is that when you kind of look at the progress so far and you start trying to project to the future, you actually understand that the curve is steeper than we thought before. There will still be some hurdles. Until now, we were more in the theoretical realm of what can be done. We were starting to see problems that can show quantum advantage, but are still they’re confined to a more scientific setting. So they’re solving kind of problems that don’t have real world applications. But if we look deeper, we are starting to see hints to the fact that those real world application will come sooner rather than later, because we have a way to look into the problems that are hindering us from getting Meaning, if so far it was more of a discovery, can we do it or can we not? Will quantum or qubits are able to get to a working condition? And now we’re at the position where it seems more like an engineering effort and a scaling effort. It means that we can look at this trajectory and say, okay, we think that within three years, maybe five, that will be this measure. Massive shift and inflection point where this technology is being able to move from more of the scientific environment to the real application environment. And to your point, where will be the first real world benefit? I would assume it will be in the areas that are more native for quantum, meaning chemistry, optimization problems, those kinds of things, because it’s easier to describe them in the context of quantum.

14:20 – Unidentified Speaker
Right.

14:20 – David W. Schropfer
And we’ve talked about pharmaceutical development, which is really a chemical equation problem, dealing with lots of possible and crunching those numbers in a way that a classical computer can’t. So listening to this podcast right now are probably a decent slice of the future quantum workforce. And the reason I asked the last question about, frankly, the crystal ball of when do you think the step out of more of an R&D mode into a production mode, is the question of when should people get excited about this industry? From an employment standpoint, when should somebody who’s working in SAS, who’s working in semiconductors, who’s working in cybersecurity, but is fascinated by the quantum industry and what quantum computers can do. When should they get excited about it? What steps should they take? Maybe today? Is it applying for a job today? Or is it taking a course today? Or is it just staying tuned to DIY cyber guy every single week?

15:24 – Izhar Medalsy
I would say it’s a combination of your personality type and how you Read the tea leaves. I would say if you if it was up to me apply yesterday. But you know, you might be a bit more risk averse. So maybe apply But in fairness, we are at the point where the market has high demand for talent. If you are dealing with components that are now relevant to classical compute, I don’t see why not starting to look into quantum.

16:05 – Izhar Medalsy
You know, in any company that is growing and coming from the R&D phase to the product phase, and then obviously to scale, you have this transition or this evolution. You have the core tech development teams that are really focused on the fundamentals, the discovery. Then you have the R&D team that takes that and shape it into something that can become more of a product. Then you have the marketing and sales team that are now telling the world about the great things that you’ve done. Assuming that there is still a lot of effort on the technology development and discovery part, but even for the, you know, the most successful companies, there is still a strong need to take those components and tell what problems they’re going to solve. And in order to do that, they need the teams that already have done that a few times in other verticals, in other industries. So I really cannot think of many jobs that are now outside of quantum that cannot be ported over today, because those companies are growing very fast, especially the public companies. And the demand is there.

17:36 – David W. Schropfer
It’s thrilling to hear you say the word today, in the context of the question that I asked, because the shift is happening now. And I think that’s the message that I certainly want to bring to my listeners, and it sounds like you do too, which is, it’s today. It’s not three years, five years, 10 years. I don’t think so.

17:57 – Unidentified Speaker
I think it’s definitely today.

18:00 – David W. Schropfer
Now, let’s talk about, frankly, getting people excited about the quantum industry. Now, Quantum Elements, the company where you’re CEO and co-founder, oops, I apologize. Are you founder or co-founder? You’re co-founder. I didn’t want to get that wrong. So thinking about Quantum Elements where you’re CEO and co-founder, the business model of your company is to make it more accessible, mostly to developers and engineers, if I understand correctly. Is that correct, roughly?

18:35 – Izhar Medalsy
That’s absolutely correct. And what we are doing is using AI, agentic AI and simulation tools to make quantum more accessible, not only to external talent, but even to internal talent, because, you know, currently, the software stack or every component is sliced in a way that requires a lot of deep know-how in what you’re doing, and it’s very hard to migrate between those layers. Because Quantum needs us to build from the ground up a lot of components that are already salt or classical, it requires specific tools to be able to deal with calibration. Or to deal with errors, or to deal with applications and algorithms. And what we’re seeing is that if you are using best in breed AI and agentic capabilities, you’re now able to not only increase the productivity, but also allow people to articulate their problem in a more, in a software way, meaning, can you tell me how to deal with noise in this specific algorithm? Can you run a simulation of this algorithm on a specific modality, whether it’s superconducting, quantum computers, or ionics, and show me the differences? If you’re able to articulate this question that is pivotal to what you’re doing, but maybe you don’t have the know-how of how to write the code in order to do that, you will get to your end goal faster. And you will be more empowered, you’ll have much more freedom to explore different layers of the stack that is needed in order to build a quantum computer. And that’s what we’re focusing on in quantum elements.

20:43 – David W. Schropfer
Okay, so when you said AI, half the listeners said, oh, I can use AI, I use JATCPT every day, and I use Gemini, use some of the other AI products, but agentic AI is different. And AI for the use of governing the activity of a quantum computer is different too. So help my listeners understand a little bit more about the difference between… I don’t want to say between chat GPT and what you’re doing there, that’s too far afield. But like agentic AI is a term that I think most of my listeners are comfortable with. Like if you hire a real real estate agent, that real estate agent goes out there in the world, finds what you’re looking for, and comes back to you with the result. Agentic AI is effectively doing something similar. It’s going out in the world and trying to come back with the answer that you asked it to do on a continuous basis. So in the example that you just gave, what quantum elements is doing is using agentic AI to help tell quantum what it is that it should be doing and what results it’s looking for, again, from 30 or 50,000 feet. Is that about right?

21:56 – Izhar Medalsy
I’ll give you maybe an example from a different field. When we look at autonomous vehicles, we take the vehicle part of this, those two words for granted, because it’s already there, you know, everyone has a car. And then we’re only focusing on autonomous part of it, which uses AI and tools that we are more or less familiar with. When we look at quantum, until now, we were really dealing with building the quantum, making sure that this device can work, move it from the lab to real world, and be able to now make it work at scale. Meaning that when we did this we’re now able to take the autonomous angle of quantum if you’re able to add the sensors and add the augmentation that is needed in order to automate and use AI to do that. So in quantum elements, what we’re doing is we have the way of generating almost like a digital twin of any quantum device out there. Using that, we are now able to train AI models and agentic AI in order to accelerate the development of this technology on the software stack. And it allows individuals and professionals that maybe are not super proficient with how to write the quantum code to be able to contribute they understand how to solve the problems, they just don’t understand the specific tools that are needed. But if we’re able to abstract it and give them ways to use maybe LLMs or other AI tools that they’re already familiar with, then this transition and this adoption is much, much easier and their participation in the workforce is smoother and more meaningful.

24:11 – David W. Schropfer
See, I’d like to get an example of that. So let’s say one of our listeners works at an investment bank, which is certainly one of the industries that it was consistently looking for any advantage it can get, whether it’s coming from a type of computer or coming from industry knowledge or anything else. And let’s say you work in the technical team of that type of group, why would that person go to Quantum Element’s website and what can they expect to find there that will give the IT department of that company, or perhaps the investment bank itself, an advantage, a leg up, a start in quantum computing, where they haven’t had one before?

24:57 – Izhar Medalsy
Imagine that you had at your disposal, when you’re thinking about what to use and how to use, a menu of of all the different hardwares that are out there, but in a digital version that is running on the cloud. Obviously, we’re not saying we’re here to replace or that’s better than a quantum device. We’re saying we’re giving you the same experience and the same performance of a certain scale of a quantum computer running on your laptop. And now you’re at a position where you can plain English, or you can use some sort of a canvas in order to run different algorithms, explore different applications on every different system that is out there. You want to use ion traps or superconducting qubits. You want to explore different chemical simulations or others. You can develop and try and run and compare on this environment, and then you have much higher confidence when you’re going to the real hardware and spend the effort and the money there because you already understood all the governing conditions that will make this algorithm or your application successful. In other words, we’re not saying that our flight simulator is going to replace the pilots. We’re saying we’re making you a more successful pilot when you go and fly your airplane.

26:30 – David W. Schropfer
Absolutely fascinating. I think it’s important that a company like yours exists today because it really sounds like you are part of the effort to shepherd companies and users of quantum technologies from, hey, this is an interesting R&D project. Let’s wait for it to become something to, hey, I could be using this in the immediate future and I should be getting good at it now and understanding how it affects my business. Business in my industry now, whatever that industry might be.

27:00 – Izhar Medalsy
Yeah, yeah. So you can think about the ability to look at current state and future state of the industry, and be able to articulate and extrapolate how your efforts are gonna evolve over time, because this digital twin, this flight simulator, allows you to control all conditions that are governing this kind of of system in an environment that is yours and that in control. And it’s also cost effective because you’re able to roam and change the different platforms or different conditions that you’re working on. And also, in some cases, you can use plain English to articulate the problem that you’re dealing with. And the system will help you.

27:53 – David W. Schropfer
And that’s very good to hear. I mean, personally, I can code very, very little. So there’s no part of my resume that describes me as a developer, although I understand it. Plain English is a much better way to get a technologist like myself able to use a new technology without having to actually learn the computer language itself. So hopefully that example widens the population of people that could use a product like that to start getting acquainted with quantum as a practical application without coming from the developer community per se?

28:33 – Izhar Medalsy
We do think so, yeah. And that was the reason we insisted on making this system, our platform, agentic or AI native. I shouldn’t say maybe agentic, AI native from the get-go.

28:47 – Unidentified Speaker
and we’re using agents, but we’re also using AI and ML tools that every software developer is using.

28:57 – Izhar Medalsy
And the uniqueness of using this platform is that if you think about what is fundamentally different in a quantum computer, what’s fundamentally different in a quantum computer versus a classical computer is that you cannot stop the computational process a quantum device midway without measurement, because once you’ve measured, you’ve changed the state of your quantum system, right? But when you have a continuous time simulation of your hardware at scale, and one of the things that makes us unique is that we can simulate large quantum devices, you’re able to stop at any point and ask yourself, what happened so far? What are the reasons that things are maybe not working as expected? Pinpoint to that, go correct them, and have a much tighter feedback loop on the things that you’re doing. So when you’re now porting it to the real world system, your success rate goes up, your time spent on those development cycles goes down. And obviously the time to market is short.

30:19 – David W. Schropfer
Excellent. And for the benefit of my listeners, Quantum Elements is not a sponsor. We don’t charge people to be on this podcast, but I’m so fascinated with how to bring quantum to not only other developers, but to other industries and really help shepherd it down the road to production. Quantum Elements is really doing some interesting things that I think everybody should know about.

30:46 – David W. Schropfer
Thank you for giving that description because that’s exactly part of the gap that I think that exists that you’re filling right now, which is tremendous. Isar, imagine you are the head of recruiting for the entire quantum industry. What would you say to people to get them excited, to get the whole workforce at large, everybody listening to this podcast, what example, nevermind the time it takes to get this accomplished, but can you give an example of what quantum computing can do in the fullness of time when it goes into production? What kind of jaw-dropping production example can you give about a type of problem that quantum can solve or something it can do?

31:33 – Izhar Medalsy
background is in physics and chemistry, kind of the intersection between them. And so I really tend to gravitate towards those kind of areas because I feel a bit more comfortable there.

31:50 – Izhar Medalsy
I think that maybe from my perspective, the piece that is the most fascinating is the ability to significantly reduce the amount of we need to do in the lab and bring them to the virtual realm. Today, we take it for granted that you need to spend months in the lab to mix components and go through different processes in order to maybe come up with a new material or come up with a new drug, et cetera. We saw the evidences from companies like DeepMind that you’re able to use AI in order to predict how proteins fold and then, of course, accelerate the time it takes us to develop new drugs. But think about this capability, but just three orders or four orders of magnitude increased in speed. All of a sudden, you’re able to take large scale problems and deal with them very quickly to a point that rather than mixing and pipetting and using all sorts of chemical processes, you can go to the computer and run those kind of calculations. And rather than today, on classical devices, it will take hundreds of millions of years, you would be able to do it instantly. That’s a paradigm shift in how we’re thinking about development, development of drugs, development of new components, and development of other aspects of things that we still didn’t think about. And the reason being is very fundamental. When we use classical devices, we take the reality around us, and we chop it into bits and pieces, we make the analog world around us digital. And we came to accept this reality as a reality because it serves us very well. But if we’re able to use analog devices to describe the analog environment around us and use the power of nature to solve those kind of problems, we’re in a different position to ask very unique questions that we weren’t in the position to ask previously. And I think that’s what’s the most exciting aspect of quantum is for me.

34:23 – Unidentified Speaker
Excellent.

34:24 – David W. Schropfer
And I often tell my listeners, quantum computer is not a faster classical computer. It’s different. It’s more akin to how nature works because it’s based on quantum physics as opposed to classical computers, which are simply based on a one or zero. Everything boils down to just that. So it is very exciting. And I appreciate your conservatism by not saying we’ll be able to solve many more diseases or get drugs to market for pandemics much faster than before. Those things may be true, but what you said very clearly is it will be exponentially faster to test different combinations, using pharmaceuticals as an example, to perhaps bring a new drug to market, as opposed to lab testing, which is actually physically mixing different chemicals or components together to try to get those results, or even using a classical computer And because they’re not equipped for that, it would take, as you said, millions of years of classical computing, even if we tethered them all together on the planet to work on the same problem, it would still take millions of years to solve some of these problems. So it is exciting. It might move the needle in disease, and it might move the needle in pharmaceuticals, and it might cure and prevent death and pain, which is an exciting kind of field. That’s just one industry example. That’s just pharmaceuticals.

35:47 – David W. Schropfer
Izhar, it’s been wonderful to have you on the podcast today. Thank you for your perspective. And my last question is, how can people find out more about what you do?

36:00 – Izhar Medalsy
Go to quantumelements.ai. Check it out. Shoot us an email. We’d be delighted to talk with you and explain to you why you should get excited about quantum as we are.

36:15 – David W. Schropfer
Wonderful. And if anybody missed that, just go to Look for episode 89, that’s eight, nine, and you’ll find all the links to ISAR’s website, to Quantum Elements, and some of the links we talked about here today. Thanks again for being on the show.

36:32 – Unidentified Speaker
Thank you, David. Really a pleasure to talk to you.