My name is Rebel Brown. I am the VP of Strategy and marketing for quantum computing in INC we are a quantum hardware software vendor and our focus is on delivering systems with quantum that are highly accessible and affordable for non quantum experts rather than for quantum scientists.

So our whole are, as my CEO says, we want to democratize access to quantum because it is such a powerful technology. And today I'm gonna talk a little bit about quantum and then how it applies to Fe Ma. But that, but let me just tell you the Fe Ma application would be the same for any kind of supply chain logistics planning, et cetera. OK. So with that, I think you all can see my slides. I can't see you anymore, but I'm pretty sure you can see my slides. Can somebody let me know if you can't see my slides? I I don't know if I can hear anybody either for that matter. Um I'm assuming. Oh good. Thank you, Sarah. Thank you. You can see them good. All right. So I'm blind. I I have to go back and forth between screens to be able to see anything you guys say. So. Anyway, so first let's talk about it. I wanna give you a little introduction to quantum and then we'll go into the, into the application on F MA. All right. So I want you to imagine a world where all of our products were always available. And we all remember I put the toilet paper here just because we all remember the toilet paper shortage. Then we had no stocking and supplying because of the supply chain problems and the risk and COVID. Then we have formula.

I mean, we are constantly having problems with supply chains and logistics. Now imagine a world where we have efficient energy production and delivery and we don't have to worry about pipeline stability, et cetera. Imagine a world where you have accurate forecasts where you actually know when you can have a picnic and it's sure. Right. Um or a world where you can have a a autonomous vehicles that not only you drive you but deliver goods and services to your home, deliver your kids safely to school and speaking of safely and manage in a world where we have unbreakable security. Well, all of those are worlds that will come with the advent of quantum computing. Now quantum computing, I will give you a little bit of my background. I've been a consultant in high tech bleeding edge technologies for over 30 years. I've spent my career working with venture capitalists and investors as well as boards of directors, et cetera, helping build companies that were in emerging technology. All right. And this is my first full time job in 30 years. I found quantum so compelling and so exciting. And this company is so exciting that I actually took a full time gig to get into it. And I will tell you, I have worked with some of the most advanced technologies and some of the most amazing technologists on the planet.

And this technology is the biggest change we will ever see in our lifetimes when it comes to computing. OK? And there are many reasons for that. One of them is the fact that quite frankly um what whoops, sorry you guys, one of them quite frankly is that quantum is totally different from anything we've ever seen. It is not every technology advancement. When I started in technology, we were using punch cards as an example.

Within a few years, we were actually doing input on computers, then we were doing batch inputs. We've always done, I started on mainframes, then we went to distributed systems. I helped put UNIX in the market, then we went to P CS and all of that. Then now we're back to cloud which is a return and to many of us for time sharing when we had big systems with access, right? We do all these cycles repeat. This is not a repeated cycle, this is not an evolution, it is a revolution in what we do. All right. And that is why it is so different and so full of uh full of potentiality. OK. Now, um I wanna talk a, I'm gonna jump around on my slide deck a little bit. I wanna talk a little bit about. So, first of all, I wanna talk about Fe Ma and for those of you that don't know, F MA is a federal emergency and S and Management association, they are the folks that are just, that are, are um, signed that the, of the responsibility to reply and to respond when we have natural disasters like hurricanes, which we're all becoming accustomed to.

When we have techno, we have other disasters. Like let's say all the railway systems went down or all the phone systems went down. Anything that is a natural disaster and act of terrorism, et cetera, they literally have to get all of the resources, people supplies, you name it to that area in uh as quickly as possible. And it is a mass movement and a mass response from a variety of different areas. So if you look at what the f the criticality of F MA is, all right. It's around risk management, right? Which is, how do I take resources at the federal and local level and have them ready available in the right positions, all the different scenarios of what could happen to me and how do I make sure I have not too much and not too little just in time in the right place for people who need help in emergency reactions.

Ok. The second part is being able to forecast or model that especially when it comes to supply chain. Right? How do I make sure that I have the requirements I need for a variety of diverse scenarios. How do I make sure I have resources available both federally to move and in local municipality where things happen so that I can immediately be there on site with supplies, food resources, medical, whatever, right? How do I plan the logistics in advance for that? Because it's not simple to move all this. And my goal is what's the fastest, most effective response that I can make? OK. Now all of these are around what we call optimization and optimization is basically when you say OK, my optimization model and that's basically when you say OK, I have 500 trucks that I have to load with 10,000 orders and they have to all be delivered on, on trucks before six hours.

That sounds simple. But think about it, you've got all the different products, you've got all the different trucks, you've got all the different routing. It's a very complex computation. And what F MA does is that on steroids? All right. It is huge movements of, of people, resources planning houses, you know everything from water to housing, temporary housing facilities. All right. Now let me give you a little example. About why these problems are so hard. All right, this is a scenario that shows you here's a logistic problem that has just 10 destinations. All right. And it results in over 3.6 million different options that have to be evaluated by a computer different combinations and approaches. All right. Now look at 400 destinations and you end up with, I don't even want to try to figure out what that number is. You get to th th or sorry, 40 destinations. Now take 300 destinations. And it's more atoms than the atoms and more options than atoms in the universe. And no, I do not know how they manage the atoms in the universe. But look at the size of these now instead of take destinations, take, OK, I have 40 different vehicles that are coming in with different supplies.

You are looking at computations that are so large compared to what we have seen in the past that literally our classical systems are running out of ways to do them. Now, the reason for that and I didn't put this slide in here, but I'll, I'll talk to you about it. The reason for the fact that there are so many different conversa or different computations. All right, they're so big is, or the classical systems having so much trouble classical systems process things in serial, they process rows of bits that are zeros or wants you get a 64 bit system, 64 bits means that, that is containing a piece of information. The next 64. So classical systems do this, they read this way, right? And then they go back and compare what they've learned with something else that's really not fast. If you think about a million variables with 30 constraints that have to be applied to them, which basically means you have a million variables that have 30 constraints. And when one of those constraints changes everything changes. And now I have to look at what happens when I change all 30 constraints in different ways, different combinations and what that does to my data, it's a huge combinatorial problem. All right now quantum computers are multidimensional.

So you'll hear people talk about Hilbert space and all this other thing think of a quantum computer as a multidimensional space. Like if you were on a Holodeck or you were in a hologram and you could have bits of data points all around you and 360 degrees of dimensionality, right? And then you could apply constraints to them and you could literally change one thing and everything would transform based on that and tell you what the result was. That's what quantum does. It does it in real time massively parallel multiple dimensions. All right. So what that means is I can very quickly look at a problem like a computation for optimization. And I can say, oh if I change these two things, that constraints this is what happens if I do this instead, this is what happens. Quantum computers do that immediately and give us the ability to respond more quickly. That's why they have so much promise. All right. So when you talk about what you can do with emergency response or supply chains or logistics, first of all, you can optimize so you can minimize the risk of not having the right supplies, not having the right people, not getting them to a destination on time.

And you can optimize that to such a fashion and so quickly that you can now have everything available and ready. You can also model for the future. So you can look at modeling and go ok, things like weather. So it's really difficult to model weather and have it be trustworthy to these days. You know, you can assume you're gonna have a dry operation, it turns out to be wet and that changes how much weight you can put on a dirt road, et cetera. So you can have that weather forecast, fill into your modeling. But you can also model to like I was talking about the optimizations of how do I move all these things, you can model them advance and you can throw in all different kinds of scenarios. Well, what happens if it rains? What happens if it snows? What happens if another hurricane hits? What happens if I don't have resources here or they can't move? What else can I do, you can do all of that modeling with quantum computers in a much faster, more scalable and more precise fashion. OK. So now if you look at the power of quantum, this is these are just to give you an idea, an idea. All right. So when you look at bits, all right, and that's the ones and zeros, we use an eight bit system is like three cubits.

When you get into something larger, look at a third, a 20 cubits system can process the equivalent of what a million bits are in 30 cubits. All right, or 20 cubits. That's how you start to get the scale. All right. Now, if you look at the time to solve 10 seconds will be a minute. Look, look what happens when they start to overlap on time. A problem that would take a classical of, of a computer or an algorithm 330 years quantum will solve in 10 minutes. That's where we're gonna get the power. Everybody. It's from being able to scale to large data sets and do it quickly. All right. Now, the other thing that is different from quantum is the precision. All right. In a typical classical environment, you will only get one answer.

You will get the best optimum answer because scientists and mathematicians will tell you there's only one best answer always. But there may be multiple other answers that are off by 0.01 from the optimum answer. Whichever one I picked, I think actually it's this one that are better scenarios for how you can respond. So getting more precision, you get more precision because you can run more data and more depth of data. But you also get more precision because you get what's known as a diversity of results that are all solve the problem the way you want it. And one that's off by 0.01 or 0.001 may be better in your situation than another. So that's what quantum brings to you. Now, let's talk a little bit about how you apply quantum to a a logistics problem. Yeah, Sarah, that's what I did the first time I saw those numbers too. Uh And, and it's hum it, they are, they are off scale. I cannot even comprehend the volume that a quantum computer is gonna be able to process. All right, I can't get my mind around it. We're not there yet. We're in stage one of quantum, but as we grow the systems and learn more about the systems, what these systems can do. Imagine imagine the most complex scheduling applications. Airlines, all right. Airlines take a day to reschedule to run their scheduling. If not more.

Imagine being able to do it in a minute every time you have something that's a problem. Every time you have a down a plane that's out of service or whatever it's there immediately. That's just one of those, I mean, doing models of chemicals that are chemistry and pharma that would take days to do now that you can build a model and you can start to look at all the variations and do it instantaneously or within minutes. That's what these quantum computers are gonna do. You guys, it is, that's why I left my consulting business for 30 years to go to work for a company because this is the coolest stuff ever. And I've done a lot of cool stuff and this stuff. I just, I mean, I'm a geek, I'm a closet geek and I love it. All right. So now let me talk to you a little bit of, let's talk about a simple, uh, not a simple, but let's talk about logistics and emergency response. Ok. So a man have distributed resources, right? So you have resources like people, uh military response, helpers, medical response, fire, whatever, right? You have resources that are humans with different specialties and they're both staged in federal locations as well as local locations, right?

Because it's not like we're gonna ship everybody from the DC to go to California for a fire, right? Um, we have different kinds of, you know, trucks, right? And transportation that, that moves these things. But we also have trucks that have to get there right. Once you have to transport trucks and, and motor and motor pools, et cetera and a TV. S to those sites, we have supplies and I just put some simple things here, but you have to have beds, you have to have food, you have to have water, you have to have medical supplies, right? And then you have medical supplies down here in medical things. So these are the kinds of resources that you're trying to plan and to get to a site, right? So what you wanna do, no clue why that's in there guys. Sorry. So what you wanna do is you wanna get to an emergency site and you want to take all of these things from all of these locations and get them to the emergency site or sites. Take Katrina. Katrina wasn't just one site, it was multiple sites and it was bringing the resources in from across the south, the, the, the southern states from uh from all over the United States to here for this emergency response right now.

The other part that's important is you have to transport that right? Yeah. And I call it trains planes and automobiles, right? You have to use all of these different transport systems to get these things from here to there. Right now. Let's just look at, if you were just moving each little from one location by transport, look at all the options here. I could send by all these different I could send by rail, I could send by planes I could spend by, you know, people by buses and maybe food I can send by transports, right? By big big semis, right? But this is just assuming one site. Now imagine you're moving from 10 sites and this becomes 10 X of the computations. OK. Now, let's say, I don't know why it keeps doing that. Um So now let's say I add in. Now, I gotta get it off of these things and into the right places on this end. All right. So how do I do that? And how do I manage this? Look at all of these options. These are just options as if I was going from one site to one site. And I only had one railroad car, 12 different options for planes, one bus and one semi imagine the multiplication on this, right? And look how complex it gets.

And every one of these is a variable in a computation, every single asset, every single transport, every single where it's going, everything is a variable. And then you have the constraints of, well, I have to get this guy or a guy like this to this site by this time. And I can't send him on a bus or here because he won't get in time. And I, you know, it becomes astronomical. And what happens is the classical computers of today cannot process this in a timely fashion. They can, they can find an answer, but it may take hours and we don't have hours to figure out how to load up when a hurricane hits or when a fire strikes or when we have an emergency, that is so horrific that we have hundreds, if not thousands of people that need help. Now, right, we've got to figure this out. So now what I've told you about quantum, what you can see is what qua quantum does is it makes this a seamless computation. And all of a sudden I get results back, I can scale the results to run the whole thing to all of the problems at once. One of the techniques people use today is they break it down into subsets I can run the whole thing at once.

I can run it quickly and I can very precisely start to run this. So that now instead of looking like all of these runs, right, all of these runs times, however many, probably, probably realistically 100 X I can now look at it as a simple thing that I can then have it come back and tell me without a doubt, you put these things on this and you do it and you stage it in this way, this is the order you send it.

And the bottom line is I get resources and people where they need to be faster and I get them there more effectively and I get the right amount there. So that what you need is on board and they're on site immediately and then everything continues to flow. And I have a highly efficient responses to emergencies. And by the way, if you want to think about this, in another way, the same problem comes when you're trying to move military operations, move troops, when you're trying to move cargo ships, when you're trying to get cargo ships through a Suez canal, after there has been a backup when you're trying to unload dock ships at the port of Long Beach, because there's 50 set f transport ships waiting and it takes days to get them through.

This is one of the biggest problem promises of quantum. And one of the things that people believe in the industry is that optimization will be one of the first applications for quantum. The reason for that is a, we need it as you can, I mean this was a F MA but you can, you guys can all see how this applies to supply chains for everything from cars to consumer products, to medical and pharma to you know emergency responses to troop movements, to scheduling airplanes, scheduling buses, trains, you name it.

This is what quantum is gonna do for us. We're gonna solve it like that. And, and better yet when we have something that has a problem, a plane goes, a plane can't fly an airport is closed, we can reroute and re optimize immediately instead of taking so long to re to put people in different planes to reschedule et cetera. That's what quantum is going to do for us. You guys, that's one aspect of quantum, there are many but that's the optimization side. So for F MA if you look at what it does, what it will do is it will reduce the risk and it will improve the re readiness. So you have less risk of out of of resources not being where they need to be or not enough resources, which is one of the problems we had with Katrina, we didn't get there fast enough and we didn't get the right things on board quantum helps to solve the risk of the not having enough there and the right things there.

All right, it also improves the speed of the initial response because I can quick, I will be able to quickly uh define what is the optimal logistic? What's the optimal supply co content? What's the fastest way to get it there? And how do I get it on site? Right. It will also give you the ability to improve the ongoing responses because you can now model all of these scenarios. You can throw in different weather scenarios, throw and different. What if this happens? What if I can't get people through a muddy road? What if I can't get them down this road? What if I can't get a plane there? What if I lose these resources, all of those scenarios? What if another hurricane hits? What if the fire spreads by double, you can model all of that ahead of time very effectively and then you can plan for it. So that's what quantum is gonna do to us. Right. Right. The army and the government are part of the disaster response but F MA organizes it. All right. So you don't have the arm army and the, and the other agencies managing the response F MA plans and manages the response and then they call in those resources, Mary. So they're the, they are the oversight for that.

All right, and then they bring everything in and by the way, your point brought up something that, that for me, when you talk about risk and not having resources, what happens if you've model that you have resources from a local military base, but there's someplace else doing some kind of a of a training and you don't have them when the, when the disaster hits, you have to be able to model for that again.

Right. F MA is Fe Ma does not have the resources, they have the management responsibility, the planning and the modeling responsibility. All right, I'm not gonna talk about funding or lack of funding. That's not what I'm here to talk to. I'm talking about what quantum can do for these environments. OK. Um So the same thing could be said if you want to talk about something negative there, our our withdrawal from Afghanistan could have been if we'd had quantum computers could have been done more effectively from a computational standpoint, not necessarily logistics of what actually happens but from the computation.

So I'm talking about no worries Mary. I'm no, not sorry, but I'm just not talking about, I'm talking about what quantum can do for us. So I'm out of time. But if you guys have questions, let me know and I'll try to answer them. The other thing I want to tell you is I had a group earlier this morning of a group of women who I was talking about stem and careers in quantum and they wanted me to um to meet, they wanted me oh God, nobody text me and tell me doing this. They wanted me to start a group on linkedin for women in quantum to just have conversations. So I'm gonna do that right? So if you're interested in getting involved in that, go find me on linkedin. It's Rebel Brown and I'm gonna start a group that's just for women in tech in quantum that just want to talk about quantum. Not, you know, just, you know, because I, you know, I can, I, I love teaching, I do a lot of work with women. I actually also have a degree in neuroscience and I do a lot of work with abused women and kids and help reprogram minds to release all that. Um But I do a lot of work with women and I'd love to start a group and we're gonna do it so you guys can just come in. All right. So um any questions, come ask me, come find the group and we'll have more conversations. OK?

Because I think we all need to do this. All right. Thank you mckenzie. Great to see you again. Mackenzie was on my earlier session, right? OK. And Mary, uh you're right. I saw your note before it fled through. It is about uh communications, et cetera. But that's, that's not a quantum problem. That's a management problem. All right, thanks Jennifer. Great to see you guys come find me on linkedin and we'll go have fun. We'll build a group. All right, bye. And if you do have questions too, just about this, feel free to find me on linkedin. You can also find me here. Let me give you my email rebel at quantum computing inc.com. I think I typed that. No, I didn't know. OK. And my personal email is Rebel at Rebel brown.com if you'd rather go there. All right. All right. Great to meet you guys. Thank you so much for coming along. I appreciate it. Have a great rest of your sessions. OK? Bye.