Transcript
Idnani: I'm sensing that my talk is going to be a little bit different in the sense that you all might be wondering, why are we having a talk focused on quantum computing, when the current big thing that's going around everywhere around us is the GenAI? My hope with today's talk is to introduce you all to quantum computing, which I think is way more cooler and more disruptive than AI. Given that quantum is a buzzword these days, I would like to show you a picture of where we stand in this space, what work is currently being done in technology, and if and when any of us should be worried about quantum computing breaking RSA. I'll also share my insights into how quantum computing can transform industries, unlock new possibilities, and reshape our future.
Outline
We'll start with, why are we talking about quantum computing? We'll dive into some core concepts about quantum computing. Then we'll take a look at some opportunities and threats that exist today because of quantum computing. After that, I'll take you all where we stand in quantum today. Then, how each one and every one of us can prepare for this quantum-powered future.
Why Quantum?
Before we dive into quantum computing, let's see, why are we talking about quantum computing today? For that, let's look at the current global challenges that surround us today. Let's talk about food security. In 2023, United Nations reported that nearly 735 million people faced hunger. Now with our growing population, global population expected to touch around 10 billion in 2050, how do we feed everyone sustainably? We need to come up with more smarter ways to distribute and produce food in order to support our growing population. Then coming to sustainable energy. Despite our best efforts, fossil fuels still account for almost 80% of our global energy consumption. We need to flip this number quick and on its head. That transition to clean energy, it requires balancing these complex optimizations that our current systems struggle with.
Then, climate change. We've all just lived through the hottest year on record, that's 2023. The complexities of our climate system are overwhelming our modeling capabilities. On similar lines, talking about economic equality, again, we need better models to address the nuances of this global economy. Coming to disease research. Remember how long it took for us to develop vaccines for COVID? Believe me, that was unprecedentedly fast compared to the average turnaround time for our vaccine development. From drug discovery to personal medicine, our healthcare currently faces computational bottlenecks. Then, water scarcity. In 2025, half of our global population is expected to be living in water scarce areas. I'm talking about 4 billion people potentially lacking access to clean water. Managing this vital resource requires us to balance these complex and interconnected systems.
Now your question would be, these problems are really huge. Why can't we have more powerful classical computers to solve these problems? You know things are tough when even the computers say, sorry, too complicated for me to handle. Why is it so? The first reason, complexity. These challenges are so complex and interconnected that we are hitting against the classical computation wall. We are dealing with problems that have millions, sometimes billions of variables. Our traditional computers can't just deal with this level of complexity within a reasonable timeframe. It's like asking a toddler to reorganize your taxes. Will they attempt? Yes, sure, why not? Good luck with your taxes then.
Then, as you gather more data and your problem grows in scale, we are pushing against the boundaries of this classical computation. This is especially true when we need to find optimal solutions among vast possibilities. A task that becomes exponentially more difficult as the complexity of the problem increases. If you all here have heard of Moore's law, the observation that the number of transistors on a microchip double every two years, and we are already approaching the physical limit of how small we can make these transistors. Here is the thing, these challenges don't mean that classical computers are completely useless for these challenges. No, what it means is that there are significant challenges in these classical computers being able to solve these problems completely or quickly enough to keep pace with these evolving global issues.
Qubits Over Bits
This is where quantum computers come into picture. These quantum computers aren't just faster computers. Don't misunderstand them as, we have another upgrade to your classical computers. No, it's a fundamentally different way of approaching computation and approaching problem solving. It's a way that allows us to tackle these global challenges that we are currently living in. Let's now talk about what is quantum computing. The way I like to understand quantum computing is that it is made up of two words, quantum and computing. Computing is something that we are all familiar with. We use it in our everyday life. We understand how it works. We use it to check our emails. We use it to watch cat videos.
Occasionally, we use it to do some work as well. Throw in the word quantum, and suddenly it becomes very weird. Why is that? Classical computers, they follow your normal laws of physics that, again, we are familiar with. For example, if I throw you a ball, you know where the ball will land depending on the speed and direction of the ball. However, when you're talking about quantum, when you're talking at the quantum level, we are dealing with atoms, electrons, and photons. These tiny particles, they follow different laws. The same ball analogy, at a quantum level, you will not know how it's going to behave.
For example, that ball might be present in multiple places at the same time, or it might change direction unpredictably. Who can say that? Quantum computing is basically processing of information but using these laws of quantum physics. Again, to bring you a comparison of classical and quantum, in classical computing as well, you have some input, you have some output, and in between you do some processing, using transistors, your normal logic gates. In quantum computing as well, you have input, you have output, but the processing is done using these principles of quantum physics.
The next question comes, what makes quantum computing so powerful? We are talking about exponential speed-ups. How are quantum computers going to give us exponential speed-ups? For that, I'm going to explain with a simple analogy again. Imagine that we are in a maze with many intersections, and we are looking for the quickest way to exit. In a classical computer, you will be evaluating each intersection sequentially, identifying the next path until you reach the exit. Whereas, in quantum computing, you can explore multiple paths simultaneously, thus finding the quickest way to exit. Here is a disclaimer here. Quantum computing is not equal to parallel computing. It's much more than that. Why is that so? Classical computers, they do processing using bits, binary digits, 0 or 1.
Quantum computers, they do this processing using qubits, which are quantum bits. These qubits have quirky properties like superposition, entanglement, interference, which when combined into a quantum circuit, programmed into a quantum algorithm, give us that exponential speed-up. I'll not talk about all the concepts here, but I'll touch on the two of them which I think are really important, that's superposition and entanglement.
Coming to superposition, how do we explain superposition? Let's say I have a coin. This coin is either heads or tails. If I put it on the table here, I know it's a definite head or tail, and that is classical computer. It has a definite 0 or 1, no questions about it. What would happen if I start spinning this coin really fast? Will you be able to say if it's heads or tails? I'll probably say it's both until you stop spinning the coin and you take a look at which side are you looking at. That is superposition. A qubit is said to be in a state of superposition when it can be in a 0 or 1 or both at the same time. It is this property of qubits, that superposition, that allows a particle, a quantum entity, to be in multiple places at the same time and explore all the different paths very quickly. Coming to entanglement. This is a little bit trickier. Imagine you have two coins.
Somehow, these two coins are magically interconnected with each other in such a way that no matter how far apart you put them, and I'm not talking about one room to another room. No, I'm talking about galaxies far, so no matter how far you put them, they still stay interconnected. What that means is, if you spin one coin, the other coin spins as well. You stop one coin spinning, the other one stops as well. You look at one coin and you see what it is, whether it's heads or tails. Immediately, you know what the other coin would be, no matter where in the world or where in the universe or in the galaxy it is. That is weird.
In fact, Einstein called it spooky action at a distance. I think that's rightly so. This is entanglement. When two or more such qubits, they are entangled, then you are able to achieve the processing which nobody can comprehend. That's how. Then, of course, there are other properties as well, but then, because these quantum bits, these qubits, have these quirky properties, you achieve the exponential speed-up that we are talking about when you put them in a quantum circuit into a quantum algorithm. That's what really makes quantum computers so fast.
Now, you'll all be wondering, if quantum computing is so cool, then why are we not already using it? There are many reasons for it, but one main reason that I would like to call out is the very delicate quantum state of these qubits. These qubits are so sensitive to the environment that the minute there is an interaction with these qubits, it collapses, the quantum information is lost. The qubit, which can be in either 0 or 1 or both at the same time, which captures that quantum information, on any interaction with the environment, loses that information, collapses into a definite 0 or 1, which means we lose all the information that was packed in the qubit. This process is known as decoherence. The challenge is that the universe is always looking.
In our nature today, if you expose a qubit, it's not going to stay in the state of superposition. Because of decoherence, it's going to collapse. That's the challenge. The paradox is that because of this, you need to isolate these qubits in a very absolute zero temperature. You need to ensure that you're not interacting with it. Of course, you need to interact with it in order to manipulate them, in order to process information. This is a really hard, enormous technological or an experimental problem to solve. We are not there yet where we have a fault-tolerant quantum computer. One solution to this problem is that we build a fault-tolerant quantum computer, which means that it can correct its own errors. Because of the information that it is losing, it can correct itself, and thus give us reliable, scalable quantum computations.
At this point, I would like to call out that while quantum computing seems very promising, there are still a lot of unknowns in this space. What we are doing here today is we are leveraging and focusing on what we know about quantum, acknowledging the fact that there is still a lot to learn, to come. As Richard Feynman rightly said, if you think you understand quantum mechanics, then you don't understand quantum mechanics. Congratulations if all of you are utterly confused about quantum computing because that means that you're on the right track.
On a serious note, I think this is really apt. I think quantum computing is really very confusing because we cannot visualize quantum computing. We can't see these principles. We can't see these quirky properties. We can't see superposition happening in the nature around us. We can't see entanglement. What we can see is these outcomes, which seem really weird. We are being asked to accept things that we can't see. I think it's pretty obvious that it will make it confusing for us. That's completely fine if you think you don't understand quantum mechanics.
Opportunities and Threats from Quantum Computing
Let's move to opportunities and threats from quantum computing. First, we'll go to the exciting part first, how quantum computing is going to transform industries. Quantum computing can solve multiple problems across industries, ranging from simulation to optimization to machine learning. I'm going to talk about top four industries that I think are making great progress or great strides in quantum computing. However, I believe there are use cases in every industry which can benefit from quantum computing. Talking about pharmaceuticals first. Quantum computing can dramatically accelerate drug discovery. How is that so? What happens when a drug interacts with a human body?
Today, scientists have to run a lot of these tests in labs to find answers to these problems. With the help of quantum computing, you will not have to go to a lab to find the right medication for a right pathogen. You will be able to simulate it on a quantum computer itself. In fact, there are some companies like Biogen, which are already partnering with quantum computing firms to accelerate drug discovery for neurological diseases. Then, coming to logistics, quantum computing will be able to solve these persistent logistics and supply chain problems. In fact, you have Airbus, which has partnered with IonQ to look for use cases in aerospace around optimization.
Then, coming to finance industry. This is my wheelhouse. You'll be thinking, how quantum computing can benefit the finance world. Currently, the traditional computers, they are able to run very limited simulations for a portfolio, coming up with these optimizations. With the help of quantum computing, you'll be able to run a lot of these simulations in parallel, having millions of variables, very quickly, and come up with these optimization options for our customers. In fact, JPMorganChase is one of the first world's financial institutions to start investing in quantum computing and build an internal team of research scientists to look into the impact of quantum computing in the finance field, like cryptography, or their use cases, your business use cases around optimization, options analysis.
Then, coming to automotive industry, quantum computing is set to disrupt this automotive industry, from battery chemistry to traffic flow optimization. In fact, Volkswagen has already demonstrated the use of quantum computing in optimizing the bus routes in Lisbon for traffic congestion. These are the very exciting use cases where quantum computing can help. The true potential of quantum computing is in imagining use cases that we don't even think exist yet.
As exciting as quantum computing can be, there are also significant challenges that we need to be aware of, which is the current threat to our cybersecurity infrastructure. Take RSA encryption, for example, the foundation for our secure communications online today. It is considered to be unbreakable because of the extreme difficulty of factoring these large numbers into their prime factors. In 1994, Peter Shor came along and discovered this quantum algorithm that demonstrates that a quantum computer can be used to effectively factorize these large numbers, thus breaking these widely known encryption methods. What this means is that once fault-tolerant quantum computers become a reality, they'll be able to break the RSA encryption in a few hours as compared to a regular computer, which would take billions of years to crack.
If any one of you is using 123456 as your password, remember that a quantum computer will be able to break it in no time, though as a matter of fact, even your 6-year-old niece would. The good point is that you need a sufficiently large quantum computer. By that, I mean a quantum computer which is fault-tolerant, and uses a high number of qubits, which doesn't exist yet. We have time. We don't need to panic. We already have our cybersecurity community working on something known as post-cryptography standards encryption methods, which will make our classical as well as quantum computers secure.
Current Landscape
With that, let's change gears and come to where are we in quantum computing? What is the work being done in quantum computing today? Would you all be interested to know the story of quantum computing, how quantum computing has evolved over the years? Let me take you through a timeline which talks about these developments in the quantum space, from theoretical concepts to practical demonstrations to the most recent advancements in quantum computing. It all started with Planck's quantum hypothesis in 1900, which laid the foundation for quantum mechanics.
In fact, when Planck talked about quantum mechanics, all the classical physicists, they got together and collectively said, this doesn't make sense. Who knew what this physicist spoke at that time will become an unofficial motto for quantum physics now. Then, this was followed by some theoretical developments done in 1927, which is Heisenberg's Uncertainty Principle, and EPR Paradox in 1935. Then you will see a little bit slow movement in quantum computing for four decades. Then 1980s saw some pivotal ideas emerge, like Feynman's proposal for quantum simulation, and BB84's Quantum Key Distribution. Then, the 1990s, they saw these algorithms develop, like quantum algorithms develop. 1994, we just talked about Shor's algorithm. 1996, Grover's search algorithm for optimizations. These were developed.
Then, the late 1990s, that marked the beginning of practical implementation of quantum computers. 1998, we saw the first 2-qubit NMR quantum computer being released. 2001, we had a 7-qubit demonstration of the Shor's algorithm. Then, 2000s saw some crucial advancements in quantum. 2004, we had our first quantum error correction. Then, 2007 and 2011, we had D-Wave releasing their first commercial quantum computer and then scaling it to 127 qubits.
Now, coming to the next two, I think they are important and they mark a significant milestone in their time. 2016, IBM released a 5-qubit quantum computer and made it available to the public, like us, via the cloud. People like us, who were only able to study about quantum computing in theory, were now able to access quantum computing via the cloud and go run our algorithms directly on a quantum hardware and a simulator. This was a real significant milestone. Now, we have almost all cloud providers providing their quantum computing-as-a-service offering, but it started with IBM in 2016. Then, 2019, Google claims to have achieved quantum supremacy with its 53-qubit Sycamore processor. This was not a real-life problem that they solved. No, it wasn't, but they demonstrated that a programmable quantum computer can solve a problem which a classical cannot in no matter how much time you give it, in no given timeframe. I say it's impressive, but with some caveats.
Then, coming to our most recent advancements. There have been a lot of advancements in the last few years. I've just hand-picked a few of them. 2021, we had IBM releasing their 127-qubit quantum processor, and in two years' time, that's 2023, they were able to scale it to 1121-qubit quantum processor, codenamed as Condor. In mid-August, we had these finalized NIST PQC standards, post-quantum cryptography standards released to withstand the attack of quantum computers. This whole thing looks so impressive and amazing, and the advancements that we are doing in the world of quantum computing seems amazing.
Let me take you to this market map of quantum computing. With this, I want to show you all the key players who are involved in quantum computing. I'll just go through the top five layers on the top first. Users are the firms and the companies which are using quantum computing. Then you have applications. These are quantum solutions for customer-centric problems. Then you have software that we all know, the program that makes these computers work. You have QPUs. They are the brain of quantum computer. Then the actual hardware, which is used to build a quantum computer.
Below that, you see a lot of these logos and the company names appearing. What is cool about it is that this list is really diverse. You will see some big tech giant names. You will see some small startups. You will see some research labs. You will also see some big companies from different industries combining their hands, joining forces together and working on this quantum computing field. Another interesting point is, you will notice that some names appear in more than one category, which means that there are some companies who are contributing in more than one space within quantum computing. Isn't it exciting?
Let me talk a little bit about what are the innovations which are being done in the quantum hardware space. You all don't need to understand this in detail. My main idea of having this slide here is to show you that there are multiple companies which are trying to build quantum computers the way their research points them to. There's no one single way of building a quantum computer. Different companies are trying different options. For example, you have companies like IBM, Google, Rigetti, who are using superconducting qubits to create their quantum computer.
Basically, they are passing electrical currents through these superconducting materials and using it to make these quantum computers. Then you have neutral atoms. You have companies like ColdQuanta, which are using laser to convert atoms into qubits. Then you have silicon spin. Intel is using their chip-making experience to build qubits on silicon chips. Then you have companies like Quantum Brilliance, they are leveraging defects in diamonds to create qubits. What's the surprising thing here? These qubits can actually work at room temperature. Then you have IonQ and Honeywell, which are trapping ions to convert into qubits. You have PsiQuantum, which is using a different way to create qubits using light. Then you have Microsoft, which is also trying to create their quantum computer using something known as topological qubits, which they expect is going to be much faster, much smaller. They'll be able to scale this to a large quantum-scale quantum computer, if this is developed.
Again, just to highlight, lot of innovations are being done in quantum computing hardware. We don't know which of these technologies will work out. Maybe something new comes up. Maybe it's a mix of technologies. You never know. Maybe you have more than one company which succeeds in making these fault-tolerant quantum computers. Only time will tell. All of these are really working very hard to get us to that phase.
Now that we have looked at the hardware, let's also zoom in on the software aspect. What you see on this slide is a layered approach to the quantum programming languages. This will be interesting to some of you. You all can go and start exploring these QDKs and these quantum programming languages in your free time. I think this is really cool. On the top, you have quantum universal languages, which are high-level and can work across systems. Then you have full-stack libraries. Companies have released their comprehensive toolset to be able to program these quantum computers.
For example, IBM has Qiskit, Rigetti has Forest. Then you have quantum algorithms. These are specific instructions which are given to a quantum computer that can solve problems. Again, different companies have their own. Then you have quantum circuits. These are nothing but blueprints to these quantum operations. You have pyQuil from Rigetti, you have Cirq from Google. Assembly language, now this is the closest a quantum computer can understand. Again, each company has their own. The last layer that you see is hardware, which is the physical device. One thing that I do want to call out here is that though this chart is from 2018, but still, even today, this chart is highly relevant as a foundation.
Definitely there have been changes, but there have been changes, like these programming languages that we are talking about have matured considerably. Languages like Q#, Qiskit, Cirq, they are all adding new capabilities as the hardware is evolving. Then, you will also see some new entrants like Silq, which is focusing on intuitive quantum programming. You have PennyLane, which is talking about targeting quantum machine learning. There's an overall trend in the software field for more accessible high-level languages.
I'll also talk about QCaaS Pioneers. I touched a little bit about this in the previous slides where I talked about IBM releasing a 5-qubit quantum processor, made it to public via the cloud. You also have a lot of these cloud providers who have made quantum hardware accessible to companies and individuals via these cloud providers. You have IBM in Q2 2016, followed by Alibaba in Q1 2018. This was followed by Rigetti and AWS in 2019, launching their quantum computing-as-a-service offering. Then, 2020, you had Microsoft and Xanadu as well, who were launching their quantum computing-as-a-service offerings. If you all are also interested, please go check these out. You will find interfaces. These cloud computing firms act as brokers, allowing you to connect to these quantum hardwares via their services.
Quantum Computing Roadmap
Then with that, I would like to wrap up this section with a summary of where we are in quantum computing. If you look at today and the next one to five years, we are in this stage called as NISC. This is Noisy Intermediate-Scale Quantum era. No, this is not, now I'm seriously questioning my career choices era. No, this is Noisy Intermediate-Scale era, which means that we have quantum computers today, but they are small and they are error-prone. It's like your personal computers of 1970s, like limited but showing great potential. Then, next 5 to 10 years, we expect to enter this FTQC era, which is Fault-Tolerant Quantum Computing era. This will be a crucial milestone for us. What this will mean is that we have quantum computers that are fault-tolerant, means they can correct their own errors, thus making them reliable to solve actual world problems. Then, 10-plus years, we are talking about large-scale quantum computers, which will have the potential to revolutionize our industries and solve these global challenges.
Preparing for a Quantum Future
With that, it's very natural to wonder, what can we do today to prepare us for this quantum-powered future? That brings us to our last section, what can each one of us do to prepare ourselves? I'll take a minute to let this sink in, that quantum is not a matter of if, but when. What I mean by this is, there's no doubt that quantum computing is coming. Quantum computers are coming. They are already there. We are waiting for fault-tolerant quantum computers to arrive, but again, there's not a question if they'll come. No, the question is, are we prepared? Are we ready? Do we understand the impact of quantum computing in our technology, in our everyday lives? This is a call to action for each and every one of you, because quantum computing is going to impact every industry, no matter what.
These are the questions that you have to ask yourself. Do we have a quantum workforce ready that understands quantum computing? Are we reimagining our business processes to see how would we do them in the era of quantum computing? Are we having these ethical frameworks ready to make use of this powerful quantum computing technology ethically? What we all need to collectively do is, first and foremost, embrace the quantum shift. Recognize that this is not just a technological revolution. No, it's a paradigm shift in the way we approach problem solving. Individuals and companies, we all need to understand what quantum computing can do, from its implications on cybersecurity to the potential applications in our industries.
Staying ahead, being proactive in this space will keep us ahead of the curve. This mindset is really important. Then, know that the true potential of quantum computing is truly limitless, offering us new hope to solve the global challenges that I talked about earlier. Of course, as we envision this quantum-powered future, we need to be committed to make use of this technology ethically.
Then, coming to how can we collectively prepare for Q-Day, the quantum day, when the fault-tolerant quantum computers will arrive, we need to have a workforce ready. We need to invest in building awareness, in building training programs that will make our quantum force ready. There is a lot of education gap in quantum computing. A very small number of universities today are offering courses on quantum computing. This is a gap that we need to address. Not just the education gap, we also need to ensure that we are scaling our infrastructure.
If we want companies to use quantum computing, we should have enough infrastructure for them to be able to run their processes on quantum computers. Just these two are not enough. We need to do a lot of research in this field. My hope with quantum computing is that just like we all don't need to understand how classical computing works underneath, same way, we won't have to know how quantum computing works. What probably we'll do is, when we are programming solutions, we'll go into a quantum library, we'll import some quantum algorithm. We'll use it in our problem statement and run it on a quantum computer. That requires a lot of research, collaboration between industries, between academia, between firms, everyone. That's required. Of course, we all need to ensure that we are committed to building ethical frameworks for responsible quantum tech use.
When I started my journey into quantum computing, I had to learn a lot of quantum computing. Of course, I'm still learning. Very recently, now people come and ask me, "Teena, we want to get into quantum computing. What can we do now to get started into quantum computing?" I've just put across a slide to help all of you interested folks who want to give quantum computing a try, who want to understand what is it that a quantum computer can do. These are the things that you can do. First and foremost, learning. Understand the fundamentals of quantum computing. Maybe read books if you're interested, otherwise internet is a great source of information these days. There are a lot of online courses, there are video courses, just make use of these courses. Do workshops, invite guest speakers. There's a lot you can do in this space. Then, networking. Conferences, meetups. Understand what the quantum industry leaders think about quantum computing. This will give you an idea of what are the trends to look out for.
Then, coming to building a quantum workforce. Like it's said, alone you go slow, together you go fast. We all need to build that quantum workforce with us. Find those like-minded people. It could be in your organization. It could be personally as well. As you start engaging into quantum computing, you will find those other fellow people who are also like you, interested in trying to understand the potential of quantum computing. Do that.
Then, use cases. Your learning is incomplete until you apply to a use case. I'll encourage each one and every one of you to think in your industry, one use case where you think quantum computing can be useful. It can be any computationally intensive problem. It can be anywhere where your classical algorithms struggle. Or maybe a very data intensive processing that you are doing, which can benefit from quantum computing. Then try to reimagine if you were to solve that problem using quantum computer, how would that be? Build those things. Quantum computing-as-a-service.
Like I said before, minimize your entry to quantum world using quantum computing-as-a-service. Almost all cloud providers have exposed their quantum service as an offering for you to be able to connect to different hardware providers. What this means is that organizations don't need to invest upfront into quantum. No, they can do agile investments, and start experimenting on quantum. Lastly, show not tell. Demonstrate the art of possible. Build POCs, build small pilot projects, see what can you do in this quantum computing world.
Conclusion
I really wanted to show you this snippet because I think it truly captures the essence of working in a quantum computing world. I saw this online the other day and I was laughing because this was surprisingly funny, but also very accurate in terms of quantum computing. My hope is that if you all can understand this now, my mission is accomplished. It's like you've got the sense of how working in quantum computing is like. What's happening here basically is that the project is in a superposition of states right now of being completely successful and not even started at that level. The weird thing is that it's really tricky because the minute you'll try to observe it, you don't know what the outcome is going to be.
I think quantum computing is like Schrodinger's Cat. It's very scary, but also very exciting at the same time. We will not know until we open that box. Definitely there are threats, but the opportunities are far greater. I want you all to take that quantum mindset with you. Embrace the uncertainty. Explore all the possibilities. Don't be afraid to be in superposition of ideas. I think the future of quantum computing is really very exciting. Let's welcome this new era of quantum computing and see how fantastically awesome it is and how it's going to reshape our future.
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