Transcription
This is a story about God playing dice with the universe. Something Albert Einstein told us he didn't do back in 1926. Einstein was criticizing physicists' theory of quantum mechanics.
Yet a century after Einstein's denial, billions of dollars are being invested today in taking that theory and turning it into reality. With the prospect of a revolution in computing potentially larger even than generative A.I. Quantum computing is very high. Potential investors are increasingly asking us about the implications of quantum computing, quantum computing, quantum computing, political and state-level economic supports to develop quantum. And we want to be part of that.
IBM is one of the companies leading the charge in quantum computing. At IBM, we developed some of the very foundations of quantum information science starting as early as 1970. Jaime Garcia is the director of Quantum Partnerships at IBM, a Ph.D. chemist. She's working on quantum computers, transforming health care at places like the Cleveland Clinic.
Quantum computers are just a totally different paradigm to calculate solutions to problems. And so what most experts have done today that are studying quantum computing for different application spaces is to really sit down with the math and figure out like, are the algorithms here that I can use and that I can exploit using a quantum computer going to bring me any sort of advantage over what can be done today in classical sort of state-of-the-art techniques.
At the core of classical computing are bits, single pieces of information that can have the value of zero or one. But quantum technology relies on qubits, a unit that can have multiple values simultaneously. It's like holding a coin in your hand that is heads, tails, and everything in between until you open your hand to check.
Physicist Jerry Chow is IBM's director of Quantum Hardware System Development. Really, fundamentally, there's a different math, right? It's the mathematics of quantum mechanics that is governing how you actually manipulate these quantum bits, which then gives rise to a whole host of different opportunities for algorithms and types of problems that you could actually solve using quantum computers.
As we're studying things today, using a lot of something called error mitigation as our approach to deal with dealing with errors in ways in the system and in the quantum computer itself. This is going to continue to evolve. In fact, we think that next year we're going to see examples of what we call quantum advantage, which is where you're able to come up with a solution to a problem that is cheaper or faster or more accurate than with classical alone.
A turning point in IBM's efforts to make quantum computing a reality came when it made it available to the world on the cloud in 2016. The IBM Quantum Experience was really a pivotal moment for us in terms of getting quantum computers for the first time out onto the cloud and into the hands of. Anybody, really, people, right. What's interesting is that before that period, I'd say it was really much. More in the realm of physics, right. That we were doing experiments on small devices, qubit devices, that we were looking at, understanding how they worked. Trying to make them better. But we didn't had any kind of real thought about how is this going to be used for computation.
In the nine years since, you put Quantum Experience out there. What is what have you learned at IBM? I think what I learned from that experience really was that there was a whole lot of people out there who wanted to touch and learn about quantum. I think we were sitting there the first night after we launched it, watching these circuits coming in and people were actually running things and we were like, Oh wow, this is picking up some steam here. And then, you know, to this point, we've had tremendous uptake in terms of using the platform to actually generate new papers and research. Thousands of papers have been generated which have been would have been impossible for us to do, just as individual scientists or researchers studying these devices in our own lab and working with other scientists in collaborations and in success, that community could go places that classical computing, even using the large language models of AI, could never take us. So it's not just speed, it's actual accuracy.
When we're using classical, no matter how infinite we get, it's an approximation, right? Absolutely. It's absolutely not. Just not not not a question about speed. The whole point of the quantum computer and what it can do is that it can give us the ability to actually get potentially more accurate results, also get results that otherwise are unattainable using a classical computer alone.
Companies like Google, Microsoft, and Intel are all exploring the potential of quantum computing. But there's also a new group of contenders, startups that are betting it all on the hope that quantum tech will one day become profitable. One of those firms is Maryland-based IonQ. Its CEO is Niccolo Demasi, who believes he has the best horse in the race. We supply quantum computers to our both federal, state, and commercial customer partners. We also provide quantum key distribution, and we do that both on the ground and up in the heavens. Quantum key distribution is effectively quantum cybersecurity, and we're very focused on this not being just proof points in the lab, but doing useful quantum advantage examples for our customers and embedding ourselves into their workflows on an ongoing basis.
So what will it look like as we go beyond showing so-called quantum advantage in the lab and embedding it into real-world workflows? One place people look to first is in the life sciences work like Dr. Garcia is doing at the Cleveland Clinic. An example of something that we've done is we've taken some of the algorithms that we've worked on for chemistry, and alongside Cleveland Clinic, we've started looking at different chemical processes that they really care about. So you can think about this in the larger context of, you know, therapeutics, design, drug discovery, that kind of thing. And really what we're doing with the Cleveland Clinic is pushing the boundaries of algorithm development methodology of using quantum computers again in concert with classical computers to come up with solutions to problems that they care about. Protein folding is definitely one area, mRNA secondary structure. Understanding how things come together and how they look in sort of 3D is a very interesting area, as you can imagine, as you're trying to understand how these things fit together in a biological system.
It isn't just life sciences that could be revolutionized by the addition of quantum computing. Financial markets are another target of opportunity. IBM scored an early advantage this year when HSBC said it used the tech company's Heron Quantum processor to make a 34% improvement in predicting how likely a bond will trade at a given price. There's a lot of excitement in the market space as well, right? Especially because optimization is certainly in another area, which we know is a classically difficult problem. And from the point of view of actually using a quantum computer to address optimization, there are many threads there in terms of leveraging this kind of large exponentially computational space to handle problems such as portfolio optimization, right, or risk management, right. So there's a lot of interesting ideas there that are being looked at by various financial institutions. What I can say at this stage is portfolio theory, options, pricing. These are very much now accessible from a quantum advantage perspective using our new Tempo system. Quantum key distribution and cybersecurity. That is, of course, front and center for financial services on a global basis. And so security and integrity of. The data flow is, of course, vital. I always like to jokingly say that you can spot our quantum security customers because they are not in the news for data breaches.
Even agriculture could benefit from quantum computing in ways we haven't yet imagined. Understanding processes such as nitrogen fixation to make things like better fertilizer help us grow better crops. Understanding things that are critical in impacting climate change, right. And in terms of how how carbon is handled, right, other things, including in better better batteries in terms of materials discovery.
The potential may be great, as are the investments being made. But when can we expect to see these potentially dramatic results? It turns out that that depends on whom you ask. IBM has made getting to quantum advantage in the real world a strategic priority and has a timeline of getting there in a big way by 2029. Our roadmap really shows the detail in terms of how we want to get from today to 2029. In between, we have this real important milestone also that we believe that with the community will be hitting quantum advantage, right where there will be some problems and claims of advantage where we will see quantum really surpassing any classical methods of solving certain types of problems, right. And we are looking at various ways of showing that academically, scientifically, and also empirically from the ground up in terms of compared with various kinds of classical methods today. And then we're building a lot of that. In the end, it's like architecting a large skyscraper. We're building a lot of the foundational elements so that when we hit Stirling and 2029, all the applications that people have been developing, all the software stack, all the eventual software libraries, they're still going to work, that they're going to work on a machine that's even more capable, something that can run hundreds of millions of gate operations compared to several thousands of gate operations on the on the advantage-level machines that we're building today.
IBM says it's on track to have quantum computing payoff in a big way by 2029. But IonQ's Demasi says they're already there. So our machines, we announced on September 12th at our Analyst Day are 36 quadrillion times more powerful than anyone else's machine. And that gap is increasing. Not only do we believe we are five years ahead of anybody else in the quantum computing business, whether it's government programs, adversaries, or commercial companies, but we also have the lowest unit economics. So we're able to build a fully fault-tolerant 2 million qubit system and keep our cost of goods sold under $30 million. Taking that together, it means that we are a fully fledged quantum internet solution. We can provide our customers a platform of computing, cybersecurity, networking, communications, and sensing. And there is no other company in the history of the world that's ever able to supply a complete quantum internet.
Everyone in the quantum business seems to agree that Einstein was wrong, that it's either coming soon or is already here, and that it will be big. But figuring out who's ahead in this race sometimes feels like predicting those days. IBM says it's ahead because it has more total qubits in its machines. IonQ says it's not the number of qubits, but the number of algorithmic qubits. Putting it in front, and quantum company Continuum has yet a third measure of quantum volume. Maybe we shouldn't be surprised that there isn't a single measurement. It's like those qubits that are both ones and zeros at the same time until they're observed, and it looks likely that we will all be able to observe what quantum computing can do for us in the very near future.