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Speaker 1: Let's say good morning now to ABC's Mike Debuski and

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Speaker 1: Mike I've been telling a wake up call listeners that

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Speaker 1: we're going to have to try to wrap our hands

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Speaker 1: our heads around this one because we're not only talking

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Speaker 1: about computers, but we're talking about quantum computing. What is it?

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Speaker 2: Yes, that's right. So quantum computing really requires us to

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Speaker 2: understand how normal computing works. But it does have potentially,

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Speaker 2: I know, it does have potentially very big implications though,

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Speaker 2: so it is important to talk about. So have you

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Speaker 2: ever seen the matrix? You know, the beginning of the

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Speaker 2: matrix when the numbers come cascading down off the top

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Speaker 2: of the screen and they're ones or zeros and they're green.

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Speaker 2: Those are bits, and those are basically, to make a

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Speaker 2: very complex story very short, the building blocks of modern computing. Right,

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Speaker 2: you arrange enough ones and zeros, you arrange enough bits

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Speaker 2: next to each other, and that creates a photograph on

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Speaker 2: your phone or a video game on your desktop. Right,

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Speaker 2: that is the building block upon which we build our

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Speaker 2: modern computing infrastructure. Quantum computing uses different building blocks, a

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Speaker 2: completely different thing. They use what are known as quantum

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Speaker 2: bits or cubits, as they are colloquially known instead of

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Speaker 2: being a one or a zero. This is where it

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Speaker 2: gets a little complicated. They are kind of both one

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Speaker 2: and zero and also some percentage of the two right

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Speaker 2: until you run a program. They can exist in this

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Speaker 2: quantum state where they are sort of both but also neither,

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Speaker 2: and maybe kind of more of one and maybe kind

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Speaker 2: of more of zero. It's very complicated, but the bottom

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Speaker 2: line is that creates an extra level of variability for

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Speaker 2: these computers, and that means that the big takeaway from

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Speaker 2: quantum computers is that they are able to solve problems

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Speaker 2: that are way more complex than normal computers can handle,

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Speaker 2: which opens up a lot of opportunity if these things

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Speaker 2: eventually mature and become part of the mainstream.

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Speaker 1: Okay, so when you say it can solve a lot

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Speaker 1: of things that regular computers can't, what kinds of things

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Speaker 1: are you talking about.

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Speaker 2: It's a great question, because up until recently this was

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Speaker 2: pretty theoretical. For example, last year, Google announced that they

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Speaker 2: got their quantum can computer to solve a problem that

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Speaker 2: would have taken a classical computer ten septillion years, right,

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Speaker 2: so they were condensing the large longer than the known

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Speaker 2: history of the universe down to basically an instant. But

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Speaker 2: it was a pretty theoretical math problem, right. It was

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Speaker 2: this really complex, really niche thing that everyday people wouldn't

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Speaker 2: normally encounter. Well, last month HSBC the Bank announced that

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Speaker 2: they used IBM's quantum computer to reduce the variability and

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Speaker 2: unpredictability of the bond trading market. They were able to

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Speaker 2: predict bond trading and the price that bonds were able

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Speaker 2: to go for at thirty four percent more accuracy. And

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Speaker 2: this was a test. It was in the European bond market.

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Speaker 2: But if IBM is to be believed, that is eventually

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Speaker 2: going to be your money that is being moved around

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Speaker 2: with these quantum computers and the algorithms that go along

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Speaker 2: with them. And then you consider the applications in things

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Speaker 2: like drug development or artificial intelligence. Taking again a ten

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Speaker 2: septillion year long problem and condensing it down to the

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Speaker 2: flip of a switch or the snap of a finger,

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Speaker 2: what could that do to something like developing a cancer

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Speaker 2: drug or developing an artificial intelligence model. Shrinking that progress

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Speaker 2: down dramatically, it has really big implications.

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Speaker 1: Okay, and then here's here's my out of this world question.

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Speaker 1: So remember the show Quantum Leap. I mean they are

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Speaker 1: they thinking about things like that too.

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Speaker 2: I don't think we're quite at the quantum leap level yet. Unfortunately,

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Speaker 2: you know, as much as we would like to leap

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Speaker 2: around time and space, you know that future, I think

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Speaker 2: is pretty far off, sir, no teleporting. And it's also

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Speaker 2: worth mentioning that as much of this sort of blue

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Speaker 2: sky thinking about like AI and drugs and financial trading

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Speaker 2: and whatnot, is great, these computers are still in sort

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Speaker 2: of an early stage. They still throw errors at a

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Speaker 2: point one percent rate, meaning one out of every one

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Speaker 2: thousand problems we give them, it returns an error. And

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Speaker 2: that sounds like okay, but it's way higher than what

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Speaker 2: you would expect a computer. And IBM says, I was

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Speaker 2: able to talk to some of the experts at IBM

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Speaker 2: earlier this week. They told me that by twenty twenty

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Speaker 2: nine they plan to get that down to a tolerance level,

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Speaker 2: a fault level that is equitable with existing computers, bringing

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Speaker 2: that down to make it throw errors less and be

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Speaker 2: a little bit more reliable as a computer. Interestingly enough,

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Speaker 2: these things, as complex as they are and as good

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Speaker 2: as they are at like solving really complex problems. They

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Speaker 2: still make mistakes, so we have to account for that

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Speaker 2: going forward.

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Speaker 1: It sounds like AI like it's gonna get better, but

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Speaker 1: right now it still makes a lot of mistakes.

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Speaker 2: I think it's also it's very comparable to AI in

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Speaker 2: the sense that, yeah, it's gonna get better, but a

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Speaker 2: lot of things need to happen for it to get better,

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Speaker 2: and there's increasing doubt that it will. Right this idea

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Speaker 2: that there's you know, traditional computer advocates out there who say,

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Speaker 2: we actually shouldn't be investing all our time and efforts

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Speaker 2: and energy into quantum computing. Our traditional computers are able

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Speaker 2: to do, buy and large a lot of these things,

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Speaker 2: and if we were to develop them more, they would

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Speaker 2: be able to do it more quickly. So there's this

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Speaker 2: tension in the high end computing world that kind of

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Speaker 2: mimics what we're seeing with AI, where it's just like, Okay,

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Speaker 2: we're spending a lot of money on this stuff and

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Speaker 2: it's taken up a lot of energy and we're not

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Speaker 2: seeing a ton of practical applications that we can monetize

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Speaker 2: just yet. So will that portend a bad future for

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Speaker 2: either of these industries. I think we're just gonna have

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Speaker 2: to wait and see.

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Speaker 1: All right, ABC's Mike Debuski, thanks for almost making that understandable.

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Speaker 2: Of course I do my best. No, you did great.

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Speaker 1: It's my brain that can't grasp it. Thanks so much, Mike.

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Speaker 2: Take care,