Subtitles section Play video Print subtitles Quantum computers use the natural world to produce machines with staggeringly powerful processing potential. I think it's gonna be the most important computing technology of this century, which we are really just about one fifth into. We could use quantum computers to simulate molecules, to build new drugs and new materials and to solve problems plaguing physicists for decades. Wall Street could use them to optimize portfolios, simulate economic forecasts and for complex risk analysis. Quantum computing could also help scientists speed up discoveries in adjacent fields like machine learning and artificial intelligence. Amazon, Google, IBM and Microsoft, plus a host of smaller companies such as Rigetti and D-Wave, are all betting big on Quantum. If you were a billionaire, how many of your billion would you give over for an extra 10 years of life? There are some simply astonishing financial opportunities in quantum computing. This is why there's so much interest. Even though it's so far down the road. But nothing is ever a sure thing. And dealing with the quirky nature of quantum physics creates some big hurdles for this nascent technology. From the very beginning, it was understood that building a useful quantum computer was going to be a staggeringly hard engineering problem if it was even possible at all. And there were even distinguished physicists in the 90s who said this will never work. Is Quantum truly the next big thing in computing, or is it destined to become something more like nuclear fusion? Destined to always be the technology of the future, never the present. In October 2019, Google made a big announcement. Google said it had achieved quantum supremacy. That's the moment when quantum computers can beat out the world's most powerful supercomputers for certain tasks. They have demonstrated with a quantum computer that it can perform a computation in seconds. What would take the world's fastest supercomputer? Years, thousands of years to do that same calculation. And in the field, this is known as quantum supremacy and it's a really important milestone. Google used a 53 qubit processor named Sycamore to complete the computation, a completely arbitrary mathematical problem with no real world application. The Google Quantum computer spit out an answer in about 200 seconds. It would have taken the world's fastest computer around 10000 years to come up with a solution, according to Google scientists. With that, Google claimed it had won the race to quantum supremacy. But IBM had an issue with the findings. Yes, IBM, the storied tech company that helped usher in giant mainframes and personal computing. It's a major player in quantum computing. IBM said one of its massive supercomputer networks, this one at the Oak Ridge National Laboratories in Tennessee, could simulate a quantum computer and theoretically solve the same problem in a matter of days, not the 10000 years that Google had claimed. Either way, it was a huge milestone for quantum computers, and Silicon Valley is taking notice. Venture capital investors are pouring hundreds of millions of dollars into quantum computing startups, even though practical applications are years or even decades away by 2019. Private investors have backed at least 52 quantum technology companies around the world since 2012, according to an analysis by nature. Many of them were spun out of research teams at universities in 2017 and 2018. Companies received at least $450 million in private funding more than four times the funding from the previous two years. That's nowhere near the amount of funding going into a field like artificial intelligence. About $9.3 billion with a venture capital money poured into AI firms in 2018. But the growth in quantum computing funding is happening quickly for an industry without a real application. Yet it is not easy to figure out how to actually use a quantum computer to do something useful. So nature gives you this very, very bizarre hammer in the form of these this interference effect among all of these amplitudes. Right. And it's up to us as quantum computer scientists to figure out what nails that hammer can hit. That's leading to some backlash against the hype and concern that quantum computing could soon become a bubble and then dry up just as fast if progress stalls. Quantum computers are also notoriously fickle. They need tightly controlled environments to operate in. Changes in nearby temperatures and electromagnetic waves can cause them to mess up. And then there's the temperature of the quantum chips themselves. They need to be kept at temperatures colder than interstellar space, close to absolute zero. One of the central tenets of quantum physics is called superposition. That means a subatomic particle like an electron can exist in two different states at the same time. It was and still is super hard for normal computers to simulate quantum mechanics because of superposition. No, it was only in the early eighties that a few physicists, such as Richard Feynman had the amazing suggestion that if nature is giving us that computational lemon, well, why not make it into lemonade? You've probably heard or read this explanation of how a quantum computer works. Regular or classical computers run on bits. Bits can either be a 1 or a zero. Quantum computers, on the other hand, run on quantum bits or cubits. Cubits can be either 1 or zero or both or a combination of the two at the same time. That's not wrong per say, but it only scratches the surface. According to Scott Aaronson, who teaches computer science and quantum computing at the University of Texas in Austin. We asked him to explain how quantum computing actually works. Well, let me start with this. You never hear your weather forecaster say we know there's a negative 30 percent chance of rain tomorrow. Right. That would just be non-sense, right? Did the chance of something happening, as always, between 0 percent and 100 percent. But now quantum mechanics is based on numbers called amplitudes. Amplitudes can be positive or negative. In fact, they can even be complex numbers involving the square root of negative one. So so a qubit is a bit that has an amplitude for being zero and another amplitude for being one. The goal for quantum computers is to make sure the amplitudes leading to wrong answers cancel each other out. And it scientists reading the output of the quantum computers are left with amplitudes leading to the right answer of whatever problem they're trying to solve. So what does a quantum computer look like in the real world? The quantum computers developed by companies such as Google, IBM and Rigetti were all made using a process called superconducting And this is where you have a chip the size of an ordinary computer chip and you have little coils of wire in the chip, you know, which are actually quite enormous by the standards of cubits. There are, you know, nearly big enough to see with the naked eye. But you can have two different quantum states of current that are flowing through these coils that correspond to a zero or a one. And of course, you can also have super positions of the two. Now the coil can interact with each other via something called Josef's injunctions. So they're laid out in roughly a rectangular array and the nearby ones can talk to each other and thereby generate these very complicated states, what we call entangled states, which is one of the essentials of quantum computing and the way that the cubists interact with each other is fully programmable. OK. So you can send electrical signals to the chip to say which cube it should interact with each other ones at which time. Now the order for this to work, the whole chip is placed in that evolution refrigerator. That's the size of a closet roughly. And the calls it do about one hundredth of a degree above absolute zero. That's where you get the superconductivity that allows these bits to briefly behave as cubits. And IBM's research lab in Yorktown Heights, New York, the big tech company, houses several quantum computers already hooked up to the cloud. Corporate clients such as Goldman Sachs and JP Morgan are part of IBM's Q Network, where they can experiment with the quantum machines and their programming language. So far, it's a way for companies to get used to quantum computing rather than make money from it. Quantum computers need exponentially more cubits before they start doing anything useful. IBM recently unveiled a fifty three cubic computer the same size as Google's sycamore processor. We think we're actually going to need tens of thousands, hundreds of thousands of qubits to get to real business problems. So you can see quite a lot of advances and doubling every year or perhaps even a little faster is what we need to get us there. That's why it's 10 years out, at least. Quantum computing would need to see some big advances between then and now, bigger advances than what occurred during the timeline of classical computing and Moore's Law. Oh, we need better than Moore's Law. Moore's Law is doubling every two years. We're talking doubling every year. And occasionally some really big jumps. So what's quantum computers become useful? What can they do? Scientists first came up with the idea for quantum computers as a way to better simulate quantum mechanics. That's still the main purpose for them. And it also holds the most moneymaking potential. So one example is the caffeine molecule. Now, if you're like me, you've probably ingested billions or trillions of. Caffeine molecules so far today. Now, if computers are really that good, really that powerful. We have these these tremendous supercomputers that are out there. We should be able to really take a molecule and represented exactly in a computer. And this would be great for many fields, health care, pharmaceuticals, creating new materials, creating new flavorings anywhere where molecules are in play. So if we just start with this basic idea of caffeine, it turns out it's absolutely impossible to represent one simple little caffeine molecule in a classical computer because the amount of information you would need to represent it, the number of zeros and ones you would need is around ten to forty eight. Now, that's a big number. That's one with forty eight zeros following it. The number of atoms in the earth are about 10 to 100 times that number. So in the worst case, one caffeine molecule could use 10 percent of all the atoms in the earth just for storage. That's never going to happen. However, if we have a quantum computer with one hundred and sixty cubits and this is a model of a 50 kubert machine behind me, you can kind of figure, well, if we make good progress, eventually we'll get up to 160 good cubits. It looks like we'll be able to do something with caffeine, a quantum computer, and it's never going to be possible. Classical computer and other potential use comes from Wall Street. Complex risk analysis and economic forecasting. Quantum computing also has big potential for portfolio optimization. Perhaps the biggest business opportunity out of quantum computing in the short term is simply preparing for the widespread use of them. Companies and governments are already attempting to quantum proof their most sensitive data and secrets. In 1994, a scientist at Bell Labs named Peter Shaw came up with an algorithm that proved quantum computers could factor huge numbers much more quickly than their classical counterparts. That also means quantum computers is powerful and efficient enough could theoretically break RSA encryption. RSA is the type of encryption that underpins the entire internet. Quantum computers, the way they're built now, would need millions of cubits to crack RSA cryptography. But that milestone could be 20 or 30 years away and governments and companies are beginning to get ready for it. For a lot of people, that doesn't matter. But for example, for health records, if health records to be opened up that could compromise all kinds of things. Government communications. Banking records. Sometimes even banking records from decades ago contain important information that you don't want exposed. But the problem we've got is we don't really know when we'll be able to do this or even if we'll ever build one big enough to do this. But what we do now, is that