B (2:45)

So thanks for having me. We did indeed deploy a system with 36 qubit in July of last year. So about a month later than what we wanted. But in the big scheme of these things, where technology developments, this is complex technology development, that one month is hardly anything in the scheme of things. So anyway, so we were proud to deploy that system that did fairly well. And as a matter of fact, just yesterday we announced that we have deployed our 108 qubit system on the cloud, including making it available to anyone in the world on aws. So we are really proud to take it live and make it available for anyone. So we are tracking close to our roadmap again, a couple months here or there doesn't make a big difference in the long term development of such complex technologies. So anyway, we are tracking close to our overall plan right now.

C (3:43)

Let's talk about the way in which your investors can think about tracking the plan and tracking the kinds of metrics, metrics that make the most intuitive sense to them. I mean, are qubits the best indicator of Rigetti's progress or is there something else that investors who tend to be, you know, finance people, what should they be looking at?

B (4:01)

Yeah, it's a great question. And qubits is definitely one of the important metric to track. But there are many other metrics too that talk not just about the quantity of qubits, but the quality of qubits. Specifically, the metric that we in the technical world use is called fidelity, which is the accuracy of information transfer between qubits. So you want as many qubits as possible, you want them as high quality as possible, you want them to act extremely fast. And if something goes wrong and there is an error, you want some kind of error mitigation or error correction schemes. So there are four things we track at a very high level. There are probably dozens of more metrics we track, but four important ones that we use to monitor progress. One is the physical number of qubits. Second is the fidelity of the qubits. Third is the speed. And fourth is error mitigation or error correction. When Errors do happen. Overarching goal for all of us in quantum computing, not just trigger, but everyone, is to get to what we call a critical inflection in the overall quantum computing ecosystem, which is quantum advantage, which is when we can demonstrate superiority with quantum computing over classical computing for practical applications. So we can clearly demonstrate we are faster or better or cheaper than CPU or GPU technology that we all use today. And for that quantum advantage, we have quantified and said that the four important things that I mentioned, you need to be roughly at about 1,000 qubits, physical qubits, you need to be like high 99.9 or something like that. For two qubit gate fidelity, you need to be faster than 50 nanosecond gate speed, and you need to have some form of error mitigation or correction. So from a financial perspective, investor perspective, I would say overall investors should look at how we are making progress towards achieving quantum advantage. We have said we are roughly about three years from that milestone. But it's important obviously to keep track of how we are making progress on those four milestones. And as we just discussed, we announced our 108qubit system at what we call 99.1% 2qubit gate fidelity, or 99.9% 1qubit gate fidelity at 60 nanosecond gate speed yesterday. So you can see we are making progress towards that quantum advantage milestone. But we still, and we will go as fast as we can, but we are still about three years away, we think.

C (6:31)

Can we talk a little bit about the. Not only the time to achieve the capabilities of quantum you've just laid out, but there's also, there is a very influential voice out there, and that's Demis Hassabis, who has cast some doubt as to whether the leaps and bounds that quantum computing promises are necessary in order to make some of the big leaps in AI that folks are getting excited about. When you listen to that, what's your reaction? You know, his take is classical computing can do more than enough. We don't need to wait for quantum to push us ahead. And does that make you nervous for the kind of size of addressable market you think that investors might ultimately think you have?

B (7:15)

Not really. I mean, we. First of all, it's extremely difficult to project these kinds of things that far out. There are two camps, certainly. One camp that believes with classical computing, cpu, GPU technology, advances in AI will continue at a rapid rate and we will get to what's called as artificial general intelligence or AGI in a few years. The challenge for that camp, and we can see that firsthand is every successive iteration of LLMs, whether it's ChatGPT or Gemini or even Claude, the returns are getting marginal to some extent. We are not getting any closer to simulating, if you will, a human brain like condition. And that's evading us. And we are pouring a lot of computing power and lot of energy to do that. And despite that, that AGI goal remains elusive. There is a alternative camp and there are well known people like Yam Lacun who belong to that camp who are saying that there are better ways to get to AGI which do not involve just throwing more and more computing power and energy. And there have been some recent papers from companies like Google that also show that a quantum computer may play a very important role in simulating the randomness, if you will, of a human brain that classical computers seem to struggle with. So it's difficult to sit here and project exactly how things are going to work in the next five years. Whether Genai will continue to make rapid progress towards AGI, just with more cpu, GPU and energy, other whether quantum computing will be needed. But even if AGI can be accomplished with Gen, there are many, many applications that are just difficult for classical computing to do. A lot of probabilistic applications, whether it's like forecasting kind of applications, certainly the whole area of encryption, decryption, drug discovery and many other applications like that, where we already know that CPU GPU technologies have fundamental limitations. So quantum computing is a very different way of doing computing. We think it will open up a lot more avenues of the kinds of problems we can tackle and how we tackle them. So time will tell exactly how people use quantum computers and what kind of market size, the current projections, I mean, you mentioned market size, the current projections almost every independent report has made, whether It's BCG or McKinsey or IDC, they're all expecting the total market to approach roughly a trillion dollars about 15 to 20 years from now. The disparity comes in the early stages. If you say, what is a market size 5 years from now and 10 years from now, you see a big spread between numbers from McKinsey and BCG. For instance, BCG is a lot more conservative, talking about two to $3 billion a year five years from now, growing to about 15 to $20 billion ten years from now. McKinsey numbers, on the other hand, are roughly four to five times larger than PCG numbers. So there is a disparity. But overall, almost anyone who has taken a look at Quantum computing and the potential is projecting as much as like a trillion dollar market. And then why shouldn't it be, given that you are significantly better, we are talking a million or maybe even a billion times faster than CPU or GPU technology and also consuming a fractional amount of energy at the same time. So when I look at the overall metrics and where things are headed, it makes sense to me that a sizable part of the computing market will be available for quantum computing. And we are talking about roughly a trillion dollar market size. So I don't worry too much when somebody looks at the current situation and makes a prediction that the market is going to be much smaller than what independent reports are forecasting.

C (11:18)

Come, we'll come back to a moment on the commercial applications, but before we go there, can we talk about one application that you just alluded to, Subodh, which is when it comes to cryptology and when it comes to cyber security. Last week, Google's Quantum AI Research has published a white paper suggesting that quantum computing could break the security code of Bitcoin and that being able to do that might actually come about 20 times more quickly than had previously been anticipated. When you partner with governments, with academic institutions, how much is this idea of Bitcoin and cracking that code coming up as almost a warning to folks that they need to pay attention to quantum technologies?

B (12:03)

I mean, that statement itself tells you how quickly things can change in technology development. And we just don't know sitting here how things are going to evolve. That paper from Google and there are other studies that are reporting similar results too, suggests that indeed quantum computing's multidimensional capability, if you will, has tremendous impact on how people could use it to decrypt standard AES or RSA encryption right now. And it's not that people who devised RSA or AES encryptions were completely clueless about these kinds of things. It just they didn't know what quantum computers would be capable of doing back when they devised these encryption skins. If they knew about it, they would have devised it differently, which is what's going on right now. The whole area of what we call post quantum cryptography, where now that we know how quantum computers work, PQC is becoming an important field where people are coming up with new encryption schemes that will not be easily amenable for quantum computers to hack into. Anyway, having said that, most of the current world right now is still using standard RSA or AES type encryption. And unfortunately for all of us, that is very easily breakable with a quantum computer. And that's what the Google report showed initially about a year ago or even a few months ago I would say. But most of us were anticipating that we need close to hundreds of thousands of physical qubits at extremely high fidelity to be able to break AES or RSA encryption, even a 128bit encryption key. And that's where the timelines that most of us were talking about were. Eight years, ten years kind of timeline. What this current studies are suggesting is that there are significant number of software tricks effectively you can do and that allows you to break encryption a lot more easily than what we were forecasting with the so you need a lot less number of qubits, a lot lower fidelity and that suddenly brings a timeline much more closer to just a few years, couple years, three years maybe, as opposed to eight to 10 years VanEck's

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C (15:27)

So but I'd love to just talk about how you think about the path to broader commercial adoption might come about. You've got partnerships at the moment with NASA. You've got partnerships with with a number of government and academic organizations. But you are also partnering. And this comes from your latest investor relations report that came out just last month in March, you're actually in discussions with Standard Chartered and Moody's. Describe for us, if you don't mind, what those partnerships with those financial institutions entail.

B (15:58)

Yeah, so we continue to partner with several organizations. Our fundamental business model is to partner to grow the quantum ecosystem. So if you look at our entire stack, both the hardware and software, you will see several names that we partner with, including AWS that we deployed the system with, Nvidia for the NVQ link, Quanta computer in Taiwan for hardware and so on. Regarding, on the application side, we definitely encourage our customers to use our systems. We open up our code, source code, if you will, so that they fully understand how to take advantage of quantum computing. And a few names you mentioned, Moody's, hsbc, Standard Chartered are part of that effort that we are doing. Typically what we do with a customer or a partner like Moody's. Moody's main business model is obviously to predict economic recessions for central government, federal banks, those kinds of institutions. And typically with standard computers and algorithms that they have developed over the last century, the best accuracy that they can predict for economic recession is about 68%, which is not quite that good. So the effort is, could quantum computers do a better job? So we are basically taking their existing data, remapping, if you will, the data with a quantum computer and feeding it back to their current classical computer algorithms. And we are seeing a sizable bump in the predictability of recession and we take the number from 68 to like 77%. So pretty impressive when you think about how basically primitive quantum computers still are with few qubits and stuff like that. So we continue to work with them and we will see how, as we improve quantum computers, whether we can increase the predictability to 90s or even high 90s percent, which will be significant accomplishment. Along that line, we work with Standard Chartered HSBC to detect things like fraudulent transactions. You may remember about a decade ago, HSBC was fined more than 2 billion pounds for one fraudulent transaction that happened. I mean, it's like trying to pick a needle in a haystack when you have millions of transactions that are going through every day and one fraudulent transaction causes a steep penalty. But standard computers miss that transaction. But there were some unique signatures on that transaction. So we are working with them to see whether those unique signatures could have been picked up by a quantum computer. And that's the kind of stuff we are doing with those kinds of banks. But we are also dealing with other kinds of potential customer applications, whether it's pharmaceutical or other areas as well.

C (18:37)

Let's talk about the money because what you've just described there is so tangible. Sibode. Right. The idea that you could work with a bank to help it prevent the kind of security breach and fines of that magnitude. I mean, a billion pounds, this is a lot of value that could be delivered. Let's talk about the share price reaction to Retti's performance recently. And I want to talk about how much cash you've got available right now, what your cash burn rate is and how investors should think about that. So as of your most recent earnings, again, that was just, you know, just four weeks or so ago, you had cash and equivalents available to you of about $590 million. So you've got a decent amount of liquidity available. Help us understand what your cash burn rate is expected to be for 20, 26, how long that 590 is expected to last and where you think the milestone sits, where investors can say revenue is now going to start coming in at scale.

B (19:38)

Sure. So as you correctly pointed out, we are at the end of last quarter, we had about $590 million cash and cash equivalents and no debt. Our burn rate right now is roughly in the 75 to 80 million dollars a year. But we are hiring people. We are increasing our investments in capital expenditure so that burn rate will increase, but it is also offset by growing revenues. We are picking very nice orders from government, national labs and even some commercial customers. So there is going to be an offset of higher OPEX and higher capex, but also higher sales and margins that come with it. But overall, we feel very good that we have enough cash to take us through easily to that quantum advantage milestone that I talked about three years from now. And even beyond that, our view is that sales will continue to rapidly increase as we approach quantum advantage point because that's where commercial customers will kick in. Right now most of the demand, we see, if you will, is for on premise quantum computers with national labs and universities. You may have seen some press releases from us. Recently we announced an order from University of Saskatchewan in Canada. We recently announced an order from a Japanese research organization. Before that we announced an order from the government of India. So we are beginning to see good sizable business orders from national labs universities for on premise quantum computers. And we expect that to continue, but it's still relatively small. As we get closer to that quantum advantage milestone, roughly three years from now, we see a significant increase in commercial activity where commercial customers will start using quantum computers, whether it's on premise in their data center or through cloud like AWS or Microsoft Azure. So we expect that to increase significantly. Overall, we believe that in the next five years or so we should get close to cash flow breakeven kind of a situation given the projections of sales growth and, and our OPEX and everything. And certainly beyond that, we expect sizable profitability. I mean there's a lot of margins in these kinds of businesses because of the IP involved and we definitely expect to get to positive OI in the 5 to 10 year time period.

C (21:57)

So let's talk about, given that profile, let's talk about your share price because I'm very eager to know what it is like to be in a frontier technology like Quantum and to have to live through the rollercoaster of the following. So when I look at the share price of Rigetti last spring it was about 10 bucks a share, shot up nearly six fold towards the later part of last year. $60 and full disclosure.

B (22:22)

Right.

C (22:22)

I am a shareholder. I was excited, I was ecstatic. But we've now seen the stock swing back to about $13 this week. It truly has been, you know, as much as tech has been, there's been a lot of volatility, but more so in quantum, just given that it is to the eyes of the markets, a more nascent technology. Though, to your point, five years actually is not that long when you think about the patience that the market has shown for companies like Amazon, for example, when that business was trying to prove its way. So as a CEO, what do you make of this? What do you think the market is not understanding when it shows levels of swings like the ones I've just described?

B (23:04)

Well, if you want to emphasize the swing, it was less than a dollar three years ago when I joined the company. It's been a roller coaster ride, if you will. It's not for the faint of heart to be involved in these kinds of companies. So we try not to look at the share price every day or even every week if possible. It's hard not to do that. But we try our best not to look at share price and make any decisions on the basis of that. This is a long term play as an investor. If you believe in quantum computing and your time horizon is five to 10 years, it's definitely a very, very exciting area to get into. But if you're just trading and because there is a lot of liquidity in quantum computing stocks, I mean any day it can move up or down 10% as you have seen. So you really, it becomes meme kind of a situation. But fundamentally we believe that as long as we keep executing our technology and get closer to commercialization, that quantum advantage and really see take off, this is going to be a phenomenal return for investors. You just don't try. You try your best not to look at the stock price and make any decisions on the basis of that. It is hard for investors to understand the various different modalities of quantum computing, how they are the pros and cons, the market potential. I mean, you can take a look at our analyst reports, the analysts that cover our companies as well as analysts that cover other quantum companies. And these people have done their homework, they have talked to us multiple times. And despite that, it is confusing to dissect the different technologies and the pros and cons. We belong to this camp that's called superconducting gate technology. We fundamentally believe of all the different modalities that modality has the most likely chances of winning because of scalability and gate speed. But there are other companies that are talking about Trapped Ion and Pureatom and there's legitimate pros and cons for different technologies. So it's not like one is just going to dominate and going to win. But fundamentally we believe in superconducting gate technology and we think there's a very high chance it will win. Within that. We believe in open partnership model and things like chiplets, which is really where we differentiate ourselves from other large companies like IBM, Google and so on.

C (25:23)

Let me ask you a cheeky question for my last question, Sibode, which is more about how cutting edge technologies like yours are getting funded. With the benefit of hindsight, when you look at how long OpenAI has stayed private, Anthropic has been private through a core building period. SpaceX stayed private for a long time and I personally put Quantum in the same bucket of those kinds of technologies. In terms of truly being cutting edge, do you wish that you'd stayed private for longer? Do you think there was a benefit to not having gone, had those companies have chosen not to go public for a long time?

B (26:04)

That's a really good question. And again, there are pros and cons of private versus public and the debate is raging on going on right now, as you can see. As an investor, I wish I had opportunities to invest in companies like OpenAI and SpaceX and they were not private in the hands of venture capitalist PE firms and only select few who have access to those investments. So as an investor, I think companies should as long as the company's game business plans looks reasonably solid and long term and good Chances of success. Companies should try to go public so average people can invest in the companies. On the flip side though, I'll be the first one to admit that when you are in the technology development mode and and sales are not that important and bottom line certainly doesn't make any sense in the early stages and unfortunately analysts have models that they have to write reports on and so they focus on the most tangible things which are financial metrics. It creates a problem for public companies when you are talking technologies because we are talking fundamental technical metrics, patterns know how, how we are going to close the gap and unfortunately it's very hard to determine valuations of those kinds of things and that creates a problem. And you see that problem firsthand in companies like ours and other quantum computing companies. How exactly do you value Rigeti or someone else and look at pros and cons of different technologies and market potentials and so on. So I can see the attraction for many entrepreneurs to try to keep the companies private as long as possible until the metrics start making sense to average investor. At the same time, I see the value of being public sooner. If it were completely up to me, to be honest, I would have tried to keep Rigetti private for a little longer before going public. We went public in March of 2022. I think that was a tad bit premature. We should have been closer to this 100 qubit, which is where we are right now. So this would have been a good time to go public because we are within three years of commercial launch and takeoff of sales. I think the investor world understands two to three year type timelines. When you start talking five and ten year timelines, it's very hard for investors to understand all that stuff.

C (28:30)

That's great perspective. Well, Dr. Subod Kulkarni, CEO of Rigetti, thank you very much for joining. Congratulations on the progress that you've made since we did speak about a year ago and please do come back. As you said, this is moving so quickly, unpredictably in some respects, but when the motion happens, it really does happen quickly. So we'd love to stay on top of it and to hear your updates. So thank you, thank you for having

B (28:51)

me and look forward to coming back again.

C (28:53)

Well, huge thanks to Rigetti CEO Dr. Kulkarni for today's conversation on quantum computing, something we're going to keep on watching closely. That's it for today's Brew Markets Daily.

A (29:03)

Brew Markets Daily is hosted by Anne Berry and produced by John Cartel Talk Abdullatif Aveni leroya and Emily Milian. Our technical director is Uchenawa Ogu. Brittany Dotako is our audio engineer. And the president of Morning Brew Inc. Is Devin Emery.