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