WE NOTE THAT THE FOLLOWING TRANSCRIPT WAS CREATED BY A ROBOT SO PLEASE FORGIVE ANY TYPOS.
[Tom] I'm Tom Zuber the managing partner of Zuber Lawler. Thank you all for joining. Zuber Lawler is a law firm with offices across the United States in seven different cities. We do a lot of work in traditional areas of technology. But also we're exceedingly excited about emerging areas of technology that we believe will drive the global economy come 10 to 20 years from now and quantum computing is certainly one of the biggest shiny objects on our horizon. And so we're quite focused on it as a law firm. And we started dead cat live cat. I sit on the editorial board of dead cat live cat along with the law firms BLG and Canada and Marx and Clark in Europe pursuant to facilitating a conversation about the quantum technology and also as lawyers and some of us being scientists, we are geeking out on that intersection. I'm still delighted here to be here with Bob Liscouski. And Bob is the CEO of QCI, one of the very exciting companies in this space. One of the reasons why I'm so excited is because it seems that Bob's company and Bob are focused on helping us to take this quantum computing technology and to bring it to everyday real world problems and helping us solve those through the integration of AI software, of these of this computing power into our daily lives. So I find that to be a very exciting part of the conversation, I think it's a critical component of the conversation we're having, which is how do we make use of this stuff? So on that note, why don't we start with some of the basics here, Bob, prior to QCI, you were chairman of convergent risk group, and then president in Plant Sciences Corporation and Assistant Secretary for infrastructure with the government at the Department of Homeland Security, that's obviously an impressive, and it's a varied background, how did you get into quantum computing?
[Robert] Yeah, well, thank you, Tom. And it's a pleasure to be here with you guys. I appreciate the conversation. So, you know, if you dig back further, in my background, you'll find out that I started as an undercover cop, way back when, right, and a homicide cop, and then, you know, kept my career going and law enforcement and security. But, you know, just to kind of go back to your question for a moment, when I was actually working the streets as a detective, I was going for a master's degree in computer science at the same time. And, and I was programming in COBOL, and Fortran. And you know, I kind of got the computer bug at that point to say, you know, there's actually a better way to do a lot of things, if you look at, and this may sound like it's coming completely orthogonal to this entire discussion. But when you look at detective work, it's about data, right? It's about collecting information and trying to make that make sense of information, in some cases, very straightforward. In some cases, it's extremely complex. And, you know, I knew intuitively then that computer technology, even this is back in the late 70s, was going to be impactful to that industry, to every industry. And I kept that curiosity with me all the way through my career. And in varying forms, like I kept getting involved in a lot of different types of technology projects. Although I didn't finish my master's in computer science, I was really bitten by it. And I can tell you that everywhere I went, I looked at ways that we could use technology to better further the mission requirements of the organizations I was working for. Right. So whether that was in the Department of Homeland Security, or within the context of the other jobs that I had, even in Plant Sciences and looking at that, that was ions, spectrometry, everywhere I went, you know, we were being touched by computer technology. And even within the government, I had consulted on something called the Intelligence Science Board, which was an advisory board to the Director of National Intelligence, and looking at really high tech projects and the efficacy of those projects being used in the intelligence community. So you know, technology has always been in my blood. But getting into quantum was not exactly something I had a, you know, a plan for, right. The way I got into it was, quite frankly, through the investment side of it. After I sold the implant sciences, we sold it, it wasn't my company was public company. But, I got approached by some of the investors in that technology to say, hey, we'd like to take another shot at the public markets, we think we're really interested in quantum technology. And they approached me about taking on the job. Frankly, I didn't know anything about quantum computing at the time, I'm like, I think he could probably do better. And but I got intrigued by it. And I saw that the, you know, clearly it's staying abreast of all the computer technology going on out there. So I was very intrigued by the opportunity and said, You know, I think we can actually do this. But here's the framework. We don't want to be a hardware company, we actually want to be an enabling company. And everything I've ever done is not being focused on just the technology in terms of hardware, it's always been about enabling users to exploit technology for their benefit. So that's kind of a longer answer than you probably wanted. But that's how I got to where I am.
[Tom] That was a great answer, Bob. And also, I find it compelling your comparison, by analogy of data collection in the investigative space with data collection in this technology space. So that that's interesting I hadn't heard that before and makes a lot of sense. QCI is one of the first public pure plays in the quantum computing space. Meaning of course that QCI focuses exclusively on quantum computing, does QCI make any hardware at all, or is it all software?
[Robert] No, we're all software. In fact, we're sort of the middle layer between end users and the hardware technology. So we're completely agnostic from the hardware.
[Robert] And our goal from the get go is to always be end user focus, look at problems and look at ways we can enable users to gain access to various types of platforms out there.
[Tom] It's interesting, I think of the comparisons between Apple and Microsoft, and I watched the conversation later and Steve Jobs life between him and Bill Gates and Bill Gates the moderator was asking Steve what did you admire about get Bill and that was a painful question. Of course, I'm sure he's personality, but what he finally said is the notion that Bill got that part of the conversation right, it was a software conversation in the beginning. And he nailed that part of it. And understanding that was really what people should aim at, or at least a big part of what they should aim at was genius on Bill's part. So your focus reminds me a little bit of that, right, which is that everybody's trying to get these this hardware up and running. But ultimately, what we're going to experience as commercial users is that interface that that software interface, so I think that's pretty cool.
[Robert] So 100%, so I thank you for that. And like, you know, we, you know, past this prologue, so we learned from those experiences, right? And if you to your point, if you go back and look at the industry, in terms of what industries, you know, what has survived the industry, hardware companies have come and gone, right, you name them, there's been dozens and dozens of them that have tried to enter into the marketplace, did it for a while but didn't survive. And I think you know, that, you know, what we learned here was, you know, we don't want to be, we don't want to be that hardware provider, we can't just provide a single interface, we have to be absolutely agnostic to the technology that QPU use. And it's on us to make sure that the end users can access the various QPUs and the value proposition there was really interesting, because, you know, we're kind of taking that middleman out, right? If you look at right now, the conventional ways of going for QPUs, you really need a lot of hardware programmers really talented, scarce resources to make that work. Whereas with our platform, you know, we go down to the end user level, because the platform does all the hard work of interfacing, if as long as the problems can be transformed into a way a quantum computer can calculate them. That that's where we focus our time. So again, our goal here is to be as agnostic to the QPU as possible.
[Tom] Makes good sense. And I may mispronounce this, so please feel free to correct me, Bob. Last year QCI officially launched this quantum computing software execution platform quadalest?
[Robert] Qatalyst actually.
[Tom] Oh, I was 50/50. On that.
[Robert] everything's got to be a “Q” in the quantum world, right? It can't, we can't make it easy.
[Tom] Qatalyst. So what's been the response to catalyst so far, Bob?
[Robert] t's been great. You know, we started off, the beta program was actually called Mukai. We set that off in summer 2020. And we had a really good response to that. Initially, I mean, it's a relative term, we didn't have 1000s users, we had like 10s of users of Mukai, maybe more than that. But the bottom line was we had people that were testing and giving us good feedback, and then we commercially launch catalyst. But we didn't do it with the intent of trying to sell catalyst, our intent was really gain users and get people using catalyst on various QPUs or on the CPUs for that matter, because that's the duality of catalyst. And, and benefit from the user community. So we've had users everywhere, everything from wind energy consulting firms trying to look at optimization of wind turbine placement, pharmaceuticals, supply chain, folks, things like this, plus, we've had a significant outreach to the academic community. One of the things we've, you know, we saw very early on, again, taking a page out of the apple playbook. They went for the education market very clearly, right, they were trying to get the early users, you know, young kids and kids, you know, going through school to become apple users. And that was very smart on their part, we kind of said, you know, what we need to be going down to the academic institutions, where they're teaching quantum computing. And instead of just saying, This is what a quantum computer is actually giving the hands on experience to start programming for quantum computing. So we launched off something called qubit u. And we partnered up with Purdue and a couple of other institutions first off last year, just to test it. And we didn't actually get into the academic programs, our intent was to go with a quantum computing clubs, right, small groups of users do the word of mouth thing. And now we're moving into the academic institutions directly to become part of their curriculum, to give students access to catalyst and ultimately to the QPUs through Amazon's bracket as part of their program to make QPUs more available. So our whole focus has been on getting an expanding user base. And now we're moving into the commercial side, we're actually selling access to it and providing services around that.
[Tom] That's incredible. And to me, this is the whole ball of wax really, at least as far as the next major milestone, which is to bring quantum computing into helping us with practical, everyday problems. So as I understand it, then catalysts enables organizations to migrate their existing applications to quantum ready solutions, and to realize superior performance, even while running in the context of running solutions on traditional computers. So that to me, is a game changer, right? As far as teaching the world to apply quantum technology to contemporary real world problems. So that's a neat trick and how do you do it? How do you get a quantum computer to be more specific to help out a traditional computer with contemporary practical problem?
[Robert] Yeah, so to your point, it's exactly the intent here was trying to bring folks, you know, through the through the gates of more classical computing and into the quantum world. And so, you know, we focus on the more business focused users, those that have already identified that quantum computing is going to be competitively advantage to them. And I was I was having this conversation this morning with somebody in the supply chain world, trying to make a business case for why quantum computing is necessary. And quite candidly, I don't want to be sort of Darwinian about it. But you know, it's a choice. If you don't want to get on board now, you can wait until your downstream when quantum computing becomes a reality in terms of its true performance advantage. Yeah, or, you can prepare yourself now. We're using catalysts. And you know, there's other consultants out there, or firms doing this sort of thing. But, you know, obviously advocating catalyst here, you could use catalyst to start getting quantum ready and getting on that path, in quantum. So the way you can do that with our, our capability is the same techniques you would use to program a quantum computer and prepare a Qubot, for example, and a Qubot can either run and classically or quantumly. And so you know, we're helping formulate the problems in a way that can run either or on a QPU or CPU with the intent of providing the advantage of a QPU, one that actually provides a performance advantage without having to reprogram the entire problem. So you know, what's so there's a couple of different advantages here. Number one, you begin to gain the quantum expertise to understand how your problem needs to be formulated appropriately. But number two, we're not asking you to bet on a particular horse in which which QPU is going to actually give you the better performance, you can try anything that's available through bracket right now. Rigetti, the D wave the eye on cue, and try them on all those QPUs to see which one's going to give you the better performance. And then, so you're not having to bet on the horse. Right? So it's intended to your point and the word we use is democratization. So we are trying to hit the masses through this approach, and demystify the whole quantum sort of cloud in terms of, you know, what do you have to do to get to use a quantum computer, so business users can actually formulate their problems to run on it.
[Tom] Fascinating. So let's try and illustrate for the rest of us by example, to get our minds around how quantum computing can actually help people today are problem solving contexts. So to get to the point, can you provide an example of a problem and a solution that's comprised of both a quantum computing component as well as a traditional computing context?
[Robert] Sure, so, so example, I just touched on briefly wind energy, and when windmill optimization. So as you can imagine, there are many parts of that problem, right? First, identifying the right location to put windmill farms, trying to understand how many farm how many windmills, you need to put in a plot of land optimize the power production, because that has an impact on the investment as an environmental impact may have a social impact in terms of the local population not going along with that because of the numbers of windmills, etc. So there's a lot of variations there that have to be considered. And we can help optimize that exact number of windmills to power production and investment requirement to get the most out of that plot of land. And we've actually demonstrated that with a consulting firm that's in the windmill space, that's actually shown where you can, you can achieve an optimal number of invest windmills for investment to produce the optimal or the maximum number of wattage or kilowatt out of a particular plot of land. Another area that's interesting for us completely separate from this is risk management. And using something we call community detection, which is an element of the of the catalyst software, to use it for actuarial analysis. So you can look at patient or potential ensured types of outcomes against your particular level of insurance. And you can identify those things which might be, you know, maybe higher risk categories of an insured versus a lower risk. And then you can understand the cost associated with that. We're just kicking a project off with that in the insurance industry, which we believe is going to be groundbreaking to apply this kind of technology to the risk management space. And the benefit for that, for me is that risk management has got such a broad application to it today. It's not just insurance space, right? It's supply chain risk, it's, you know, any types of risks, political risks, there's a lot of different types of risks out there that that the variabilities of the risk, and on the potential outcomes are too complex to really calculate with conventional computing. And, you know, it's our thesis that quantum computing has a meaningful role in the future of risk analysis, and we're going out and proving that and then we're doing some work in the supply chain space, looking at ways to optimize supply chains, you know, so after you collect all the data around the End to end connections between a supplier and a user, all the things that can potentially affect that supply chain and the outcomes affecting, you know, the ability to move products from point A to point B or if it's a chemical plant that might be in the production, you know, in the production business for plastics, certain chemicals are absolutely necessary for that if you have a supply chain disruption, you go down for a period of time, it's significant cost of money. Those are the types of problems we're working on today.
[Tom] Very exciting. And that makes a whole lot of sense here. So how would let's take that last example that the supply chain example, you've got a traditional computing context, it sounds like that is filling in most of the basic data points in the end to end analysis of a supply chain. And that makes perfect sense. And that's done today. Then you talked about a larger, more detailed analysis about where you're finding all of the additional smaller data points, the many of them that can contribute and effect that supply chain and those other primary data points. And that would be solved that sounds like by implication by the quantum computing component, conversation, you know?
[Robert] That's right.
[Tom] And so how do you look that in? How does that interface happen between the traditional computing context, that's got the end to end primary data points, and then that enhancement, by quantum computing components, as relates to all of the many, many data points that can affect those primary endpoint?
[Robert] Yeah, so that's a great question, because implied in that question is really the essence of you know, what the relationship between classical CPUs and QPUs are going to be, that's never going to go away? Right? I mean, quantum computing is never going to do away with classical computing, classical computers are going to be doing great things that they traditionally are good for, it's the more complex tasks where you have a high degree of variability, bigger matrices that have to be cut, you know, calculated different ways to calculate them. And, and speed with which that's required in terms of diversity of information that's always coming into a system. That's where quantum computing is going to come in, and then converging those answers together is what the art form is going to be right. So you have this ability. And that's precisely where we're working today. I'd like to tell you, we have a great answer for that. I don't think anybody does at this point. But I believe that we are working toward a really good answer. And so we're taking more of the traditional approach with, you know, the classical approach, we're partnering up with professional services, firms that know the end to end stuff at the at the client level, right. So we're not the subject matter expertise at the client level, right? So we're not going to be supply chain experts, we're going to partner up with supply chain experts. And we do partner up with supply chain experts that understand the subject matter understand the client space. And once they get that end to end, then we begin to figure out where can we optimize that, you know, points in that supply chain, and give them the data that they need to make the appropriate business decisions? So that's where that's going to come? And I think for the beginning, you know, it'd be perfectly honest, I think it's going to be a manual process, right? You know, you're going to have this darkness, this information, synthesize between those that are doing the work in the real detail work on the supply chain, those that are doing the work on the on the quantum space, having those answers come together in a more physical way, right, person to person, but eventually, that's going to happen, where it's going to be more of a hybrid approach.
[Tom] Wonderful. And so that actually was a specific question I had here, which was, will quantum computers ever really replace classical computers? And it sounds like the answer is no, we're not even talking about a relationship where movies have essentially replaced theater and we still have theater. That's cute, but we really, it's about movies for us. Now, we're not even going to be that they're going to sit side by side. And they're going to work together to solve the problems of tomorrow. So that that's, that's wonderfully susaint So thank you for that. So one of the things that's not so fun to think about in this space are our security risks. Right? And your you have a security background. So I think you've got a good vantage point to answer this question. As a recognized security leader, what types of new security risk do you anticipate as a function of quantum computing capacity?
[Robert] Yeah, so the first one everybody talks about is the risk to data based upon the ability to crack codes using quantum computing. And that's really a big risk, right? It's not a today risk. I mean, arguably, we can't crack the best 256 bit, you know, architecture. However, if and this is where, you know, it takes a little bit of a leap of faith, but you have to believe that this is going to happen, when quantum computing becomes completely advantageous in terms of performance, that will be a non issue, right? You know, cracking that code will no longer be a problem. And it just accept that going forward, as most security practitioners do. You always expect the adversary is going to have the ability to do something, if you're sitting back thinking that they never will. You're the only way you'll find out is when you're surprised and defeated. So we know from the national security standpoint, the government and even private sector are very concerned about protecting those secrets. That's why some of our adversaries who are, you know, on the same path for quantum supremacy, have been scooping up as much data as they can from us irrespective of whether they can possibly break the code or not. Because they know eventually they will, right? And they know that these secrets that are today are going to be valuable in 20 years when quantum computing is going to be absolutely a real thing. Right? So we're very worried about that. So that's the that's on the on the offensive side. On the defensive side, of course, that same technology can use can be used to protect networks, data arrest all the all the other typical things. And I think that's where the security implications really become more paramount is the fact you're going to be able to do these things in a secure environment today that previously, you would never really sure if you're compromised. I mean, let's face it, we all know that with information technology today, the likelihood of compromise is pretty much at 100%. Right? You have to you have to believe that somebody somewhere along with chain is compromised you either with an internal threat or an external threat. We want to get to a point in our in our lifecycle with security and you know, an enterprise work that we can absolutely protect it. And I firmly believe quantum computing technology is going to be a big player there. So then there's other things, what can we do with quantum technologies in the future that have more national security implications? Without a doubt, you know, quantum technology is going to have far more reaching capability to be able to do things such as the risk analysis that we talked about the predictability, you know, working with AI in the future, and you talked about, you know, what the future looks like, you know, from your own work, where AI was 40 years ago, and where it is today are orders of magnitude, right? It took that long before we finally had functioning AI capabilities. And the implementation of AI across this big data is really providing interesting insights. you extrapolate that and compare that into what quantum computing is going to do. It's going to have very, very significant insight into data today that I don't think we really can even begin to think about and doing, you know, predictive analytics and things like that. So there's are really a wide variety of areas that I believe are going to have national security implications for, for quantum computing.
[Tom] Yeah. And it's interesting to see the race that's going to develop on the offensive side of things in from the defensive side of things, you just have that and it's going to go on for quite some time. I think we can infer the answer to my next question from our conversation so far. But I don't want to infer I want to just ask this question succinctly, what is your vision for QCI? And what's your ultimate goal with the company and I'm talking on a timeframe now of, of years, or even decades?
[Robert] So listen, you got to crawl to walk and run this space. And the vision that we have right now is executing and developing a capability and a platform that satisfies the customers provides access to any number of QPUs, and does that effectively. And we can do that, like I said, in a broad way, and provide that value. I think, as we begin to move along on the spectrum of quantum computing, I think we're going to be driven at that point, then by what the hardware capabilities are. So I'm going to answer your question, but let me just go back to the beginning, what I think is really interesting, you hit on as well, the more users you have with quantum technology, much like with personal computers, and more practical applications and software coming into the marketplace, it is going to drive the implementation of hardware over time, right. I mean, we know that just based upon the phone technology we have today, the same phone that we have today is, again, orders of magnitude more powerful than any computer existed 30 years ago, and I don't care what it was. And I you know, I eventually think quantum computing is going to be the same ilk. And the reason that it did is because users demanded that technology, right? Just like they're going to demand it today, you know, in QPUs in the future. And, you know, I think that's what the hardware vendors have to be very sensitive to is, as more and more users come online, and companies like ours provide access to, to users, they're going to shape with hardware looks like, you know, I used to say and you know, it's kind of even just six months ago, you know, it's you're not going to see a quantum computer on a on a desktop in my lifetime. Well, I think that's a wrong statement. I frankly, and I actually think that you likely will see a quantum computer on our desktop in our lifetime. It may not be the IBM chandelier with all the infrastructure that it necessarily requires. But it may be a different form of quantum computer that allows you to scale and operate at room temperature. And there's some really interesting, interesting things that are going on there. And from my point of view, asked me about the vision, we want to be open to ensuring we can adapt appropriately. Right now my near term focus is growing through I want to do some acquisitions of professional services that can bring us closer to problems, look at software that we can continue to augment. You know, visualization is a very powerful thing. And we're looking at ways that we can display the data that we're able to analyze through a quantum computer. It's for a better output for the for the end user, but we're really end user focused. So I'd say for the next 235 years, our focus is going to continue to build that AR platform focused on end users. And then we're going to wait and see for potentially to see how the hardware industry shakes out because like I said earlier, there's no winners yet. It's, it's too far too far out there to even call a winner. I don't care what anybody says, from my point of view, I wouldn't want to make a bet. So
[Tom] pardon me from being a nerdy lawyer, but I am. So I'm going to ask a nerdy lawyer question. And just one, though, I promise, what types of legal issues is QCI facing now that, in particular, I'm talking about legal issues that are informed by the quantum subject matter, right. So some legal work is just legal work. And it's our list of subject matter. But there are obviously going to increasingly be legal issues that really are particular to quantum computing as a subject matter. So are you facing any of those issues now? And what are they?
[Robert] Well, we're not. knock on wood, at least I don't know that we are right now. But, you know, I think as the industry matures, much like I, you know, you're asking me in a hypothetical sense, where I think, you know, this is going to become more nettlesome in terms of legal issues. And I think it's going to be on the privacy side. And looking at the ethics of quantum computing, and particularly the AI areas, which I, I should probably just turn that around to you and say, Where do you think they're going to be? Because I'd be interested in your perspective, I think, I think the ethical considerations that are going on out in discussions today that haven't I don't think they really lead to any legal challenges yet, but I think they're going to in the future, as computer technology becomes more capable of, of acting like humans, right, or at least making decisions such as humans. And then being more invasive in our lives. I think that's where the, I believe anywhere, this was some of the legal issues are going to be coming from I don't know, I don't want to completely turn this around. But I'm curious to see what you think.
[Tom] Fair enough. And we do think a lot about that. I think that things that we're seeing today, they're mostly IP and privacy related issues. Right. And that's to be expected. So on the privacy front, I think the implications are clear enough, which is that privacy in in some respects, we're going to lose a lot of what we currently cherish. And that's I think, inevitable. Quantum computing is going to accelerate that so many of these issues have to deal with how do you put restraints first at the regulatory level, but then also at the level of execution, navigating that privacy terrain with dexterity, where the privacy laws vary so much by jurisdiction, the laws here in California are different than the laws in New Mexico, there are different federal laws in Canada and different from the laws in Europe. And we deal a lot with those sorts of issues. So becoming dexterous and navigating that terrain, I think is the stakes are going to be higher in the quantum computing realm because the power is greater right. Also, on the IP front, it's a question not just an understanding technology, which of course isn't so neat trick, and not many, not many executives, or lawyers really understand the technology as much as those scientists that are actually cooking it up. So we try and really get our minds around that we really want to be well versed in the technology, not just so we can describe it, which I think is simple enough. But so we can also advise our clients on how to protect it, not just where the ball is today. But where's the ball going to be in three years? Where's it going to be in five years? Where's it going to be in 10 years, and where are the competitive advantages, because those aren't always obvious when you're drafting an application, even when you're familiar with the technology. But when the technology is so new, I think those challenges are all the more enhanced. So the goal isn't to get a patent application, the goal is to file the goal is to get a patent that is actually going to give you the strongest competitive advantage in five years, and in 10 years. In that sense, um, the quantum computing subject matter really does have to be front and Central. First, you really need to understand what it is today and where it's going tomorrow. And then you start doing the legal work. So I'd say those are the two biggest issues, the privacy issues, and then the IP issues, then, of course, we're going to have other things, there's going to be security regulations that are focused strictly on quantum computing, there are going to antitrust concerns, how does that play out is this deal really going to have antitrust implications five years from now as the industry plays out, those sorts of things are going to be coming down the pike, we're going to have government regulations that are strictly for this in terms of what quantum computing can get into and what it can't get into, including as relates to privacy rights, but also his other concerns. But I think those things are further down the pipe, not by decades, but by years, that the IP and privacy issues are here today.
[Robert] Yeah, you know, Tom, you bring up an interesting point, too, you know, you know, at an intellectual level, running a company like this, I don't have the benefit of really kind of looking over the horizon too much, right? Because I'm just focused on the day to day execution. But the at some point, I would love to get engaged with a conversation around some of those far reaching out issues. Because to your point, this is a time when you have the ability to affect what they look like at least
[Robert] at least if you can gain some insight into them, you have maybe not a lot of a ton of influence, but you have that ability to kind of make a little bit of a nudge here and there in terms of how things are going. So I think you're absolutely right on track with that, by the way.
[Tom] Yeah. So I'd love to have that conversation and probably longer than you want to have it . So we're agreed there and that's also very exciting, but I think also We need to recognize that the law in general does a terrible job of keeping up with technology. That can be a challenge. But it's also a gift because you can use that to your advantage as a company. If you're if you're focusing on our obligating that terrain with dexterity. There was a the BMW quantum computing challenge. QCI recently competed, how did it go?
[Robert] So we did well, actually, there were about there were four different problems. And I believe out of those four, those four problems are well over 100. I don't know the I forget the exact number maybe 150 or so respondents to the question to those four problems. And we were selected to be one of three respondents the follow up to the problem about the spatial orientation, or the distribution for quantum sensors, or for sensors on a car for autonomous driving. We came runner up, we didn't get we didn't get the final but we demonstrated a very efficacious approach a very valid approach toward the problem. The winner they legitimately outperformed us on that. But we showed really good demonstration on that. And we got, you know, really good feedback from the folks at BMW and Amazon. So we're able to show demonstrably where the capabilities are, in terms of how to position sensors around autonomous vehicles or autonomous driving vehicles. And we're pursuing that as a consequence, right. And, you know, sometimes the benefit of I liken that to Shark Tank, you know, sometimes, you know, the folks who get the investment from Shark Tank are not the only winners, the folks that didn't get the investment from Shark Tank are frequently the winners because they've learned from the experience, and they're able to kind of leverage that into a success. And I put us in the same category. You know, I think the success we're going to have as a result of the experience we had with BMW, and the feedback was really beneficial to us. And we were actually going out, and I don't want to suggest we've gotten any opportunities yet. But we're working with that's in the process of working through opportunities with other manufacturers, to look at ways that we can help optimize their autonomous driving vehicles. So it was a very, very beneficial for us.
[Tom] I think that's tremendous outcome. So congratulations, Bob and congratulations for the whole company. So I see, this is not a fair question. I'm going to ask anyway.
[Tom] I see you once at the Harvard Kennedy School. Great to speak to a fellow alum always. And so my question is, are you making any use of your policy degree in your capacity as the CEO of a quantum computing company from full disclosure, I really don't use my degree that much, but I had fun going to school there.
[Robert] Well, it was great to go there. What I don't know what year you went, I graduated in 88. So it was a while back, but I had a actually there was a fair amount of work. The coursework I did on information technology was the strategic uses of Information Technology, particular guy named Jerry Macklin was the professor. And it really, it was actually for me a tremendous experience, because it allowed me to look at the public policy aspects of a business operations in general, obviously, was a public policy oriented degree, but the you know, operations, whether they be commercial businesses, or covering government operations, you know, are all looking at the time to implement computer technology. So I took away from that significant amount of benefit. And the policy experience is very beneficial to me, because I spent a fair amount of time up on The Hill talking to, you know, congressmen, senators, congressmen, you know, representatives and senators, on this topic, as you might know, there's been significant interest in in the legislature from the Endless Frontier Act that's being proposed, and other quantum initiatives, and then trying to connect the dots for a policymaker to understand what that means in the industry. I have found that experience at Kennedy School has helped me really kind of fashion those arguments. So it's meaningful for them to understand how something commercial level actually has a policy implication, because it's very much about the things you just talked about. Its privacy, its security, it's about the big policy issues that they have to consider. And it's also about workforce, right? You know, workforce development, competitive advantages, national security, competitiveness, all those types of big national security's issues, and all those other types of social issues are all embedded in what we're doing today. And to get a public, you know, to get a legislator, talk about that, and get them to understand that or their staff, more importantly, is really meaningful. So it was tremendously helpful to me.
[Tom] That's great to hear. And it was a wonderful experience.
[Robert] I'm with you. I had a great time.
[Tom] So I've got I like to end with one off topic question, I guess that makes it two just for fun again. If you were to invite three persons of history to dinner party to discuss quantum computing and what QCI is doing in space, who would it be and why?
[Robert] Yeah, so I'll tell you a tongue in cheek it'd be Sheldon Cooper because I'm a Big Bang Theory fan. And, and I get most of my quantum knowledge from I shouldn't say this because it's not true. But I like to get around my team. I'm the least quantum guy on my team. Right? So I actually posed this question to my team to kind of see what they said. And of course, you know, the Schrodinger, it's Einstein. You know, it's Heisenberg, right? It's all the all the big names out there and, and kind of get their feedback about what is the day envision where we are today. And they're thinking about where quantum computing is, you know, because this was an evolution for us to get to this point. For them. It was revolutionary to think about this. You know, it'd be it'd be wonderful to talk to Einstein about what was your what's your vision for the commercial space? And if you thought about commercializing quantum computing, does it even resemble what we're talking about today? Are we too constrained? Right? Are we thinking about quantum computing in the context of a bit or a byte, you know, where a one a zero? And the same time they could be the one? Or were you thinking much bigger than that? Are we just constraining ourselves? As you know, you think about quantum computing, and I'm not suggesting I could possibly think or understand what they were suggesting. But just a layman's level, quantum computing happens around us every single moment of every single day, right? molecules interact, atoms direct, there's all this stuff going on all the time. It's a quantum level, right? And it's happened naturally. Right? That's what those guys were experiment, experiment, you know, thinking about, and then we put it into a framework today where IBM is trying to make a game on a computer, is that the right answer? You know, what's the right answer for this? And what were they thinking? It'd be wonderful to have that conversation.
[Tom] I agree. And if you ever have that dinner party, I'd want an invitation.
[Robert] Well, Maybe with Sheldon but I don’t think that’s going to happen. But you never know.
[Tom] Bob, that was a sensational conversation, from my perspective. I really enjoyed having it. I want to thank you very much for your time. I also want to congratulate you, you're having a visionary success over there at QCI. So it's great just to witness from the sidelines. So thank you very much for taking the time.
[Robert] Thank you for what you're doing. And like I said, I'd very much enjoy the engagement with you downstream because I'd like to get your thinking on what we're doing.
[Tom] That sounds great, Bob, I'll reach out. Thank you so much.
[Robert] Alright, have a good one
[Tom] Thanks. Goodbye, everyone.