Quantum Supremacy Is Here—Allegedly
“Quantum supremacy” has arrived, according to Google. Google’s quantum computer has completed a calculation in 200 seconds that would take a “classical” supercomputer 10,000 years to complete. But IBM is pushing back, saying their supercomputer could perform the task in just a few days “with far greater fidelity.” If they’re right, Google’s computer has a big “quantum advantage,” but not “quantum supremacy.”
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Sophie Bushwick is technology editor at Scientific American in New York, New York. Previously, she was a senior editor at Popular Science.
IRA FLATOW: This is Science Friday. I’m Ira Flatow. Oh, in case you missed it, the quantum supremacy has arrived. Yeah, at least according to Google. What does that mean? Well, Google says its quantum computer solved a problem in just 200 seconds that would have taken the best supercomputer 10,000 years to complete. But the pushback has already started. Here to fill us in is Sophie Bushwick, technology editor at Scientific American. Pushback starting.
SOPHIE BUSHWICK: Oh, yeah, absolutely. I mean, this goes back. This is a big, big breakthrough. This is Google’s– Google’s compared this to the first airplane flight in terms of the significance of this finding.
IRA FLATOW: No kidding.
SOPHIE BUSHWICK: Yeah. So this is a big deal which means there’s a really high standard of proof that Google has to meet to say that we have achieved quantum supremacy. So there’s already been pushback against that claim.
IRA FLATOW: Start at the beginning. What is the quantum supremacy, and how does that start?
SOPHIE BUSHWICK: So the whole appeal of a quantum computer is that it can solve certain types of problems exponentially faster than classical computers. And the problem is, it’s really hard to build a working quantum computer. So a lot of different tech companies have been struggling with this conundrum, and none of them have managed to get a quantum computer that could really fulfill the promise of solving these problems super fast. So that’s what Google claims they’ve done. They say this is a problem your regular computer would take thousands and thousands of years. We’ve done it in seconds.
Almost immediately, IBM started working on– they said, well, could this type of problem that you’ve solved be actually solved much faster by a regular old computer, not a quantum one? And they have released what they say is an algorithm that could solve it in just 2 and 1/2 days, instead of 10,000 years. So they’re saying, Google’s achievement isn’t quite as big as they’re making it out to be.
IRA FLATOW: And there’s no quantum computer around the corner for everybody to buy it.
SOPHIE BUSHWICK: No, I mean, even Google’s quantum computer, it solved this one problem. It’s not about to break down all of these barriers that quantum computers could eventually maybe do. Because one of the exciting things– one of the types of problems that quantum computers could be very good at solving is factoring big numbers, which is a key component of most modern encryption methods. So the idea is that if a quantum computer could solve these problems much better than a classical computer, they could crack most modern encryption.
IRA FLATOW: And that’s the theory. If Google is right, then the encryptions are not that secure anymore.
SOPHIE BUSHWICK: Well, down the road–
IRA FLATOW: Down the road.
SOPHIE BUSHWICK: –I’d say encryptions are not– that’s right. They haven’t actually– the type of problem that Google’s quantum computer solved is not the encryption problem. But the idea is that this is the first step on a path toward that. And in fact, even if they do reach that point, which could be years in the future, researchers are working on new methods of encryption that you couldn’t crack with a quantum computer. So it’s not definite that encryption will be destroyed forever.
IRA FLATOW: Spy versus spy continues.
SOPHIE BUSHWICK: Very much so. Yeah.
IRA FLATOW: Let’s talk about another continuing story that the researchers have discovered that algorithms can be biased. Whoa.
SOPHIE BUSHWICK: Right, this is just another example of the ways that you can inadvertently put bias in an algorithm. And this is actually a health care algorithm that’s used to determine, is this person at high risk of being ill? And so hospitals or insurance companies can make sure that these high risk patients are eligible for extra care to kind of stave off some of these more expensive complications. And researchers were looking at the algorithm, and they realized that for black patients to be classified as high risk, they ended up being much sicker than the white patients who had similar risk scores.
And the reason this– what this comes down to is the algorithm was using health care spending as a proxy for health care needs. And the fact is that a lot of black patients are from a lower income bracket and so thus would have less money to spend on health care. And the other issue is that a lot of black patients face implicit bias from doctors, which makes them less likely to trust their doctors and less likely to go to the doctor and say, hey, I have this problem. Can you help me? And can I pay for treatment for this?
IRA FLATOW: Can they fix the algorithm?
SOPHIE BUSHWICK: That’s what the researchers are hoping to do. They’ve said that they weren’t doing this as sort of a gotcha attempt to sort of break down the algorithm. What they want to do is make it fairer. So the issue with all these algorithms is you put data in, you get a result out, but you don’t know how the algorithm reached the conclusion it did. So it’s really important that companies that are relying on these algorithms test them thoroughly and make sure that you can eliminate bias as much as possible before you actually start using it.
IRA FLATOW: Also, I’ve got to go to what I said in the introduction. Researchers taught rats how to drive. This is a great video of it. It’s up on the web.
SOPHIE BUSHWICK: Yes, this is an amazing study. I encourage everyone to look up this video. They basically took– it looks like a big plastic box that they put on wheels, and they put the rat in it. And there’s these copper wires that the rats can grab, and grabbing different wires steers the car in different directions. And so you can watch these rats driving their car around, like chasing down food rewards. And apparently, they were also saying, hey, how does this affect the rat’s mood? So they looked at stress hormones and anti-stress hormones in the rats’ droppings. And they found that a rat that got to drive itself around had much lower stress than a rat that was sitting in a remote control car.
IRA FLATOW: So the rats– what that says– enjoys driving. It wants to drive.
SOPHIE BUSHWICK: Yes, so it’s possible maybe rats just love the freedom of the open road. Or what the researchers have suggested is actually happening is that learning a new skill is satisfying, and it’s that satisfaction that is making the rats less stressed and happier.
IRA FLATOW: Let’s see if I can squeeze in one last story about CRISPR to fight viruses. What did the researchers do there?
SOPHIE BUSHWICK: So we know that you can use the CRISPR technique to kind of slice and dice DNA to do genetic modifications, but what these researchers said was what if we could use it to attack RNA viruses? So they programmed an enzyme related to the enzyme used in CRISPR to attack RNA in cells outside the body. And what they found was that they targeted three different viruses, and for all three of them, this technique was able to reduce the transmissibility of the virus.
IRA FLATOW: Oh, wow.
SOPHIE BUSHWICK: It was less likely to spread outside the cell.
IRA FLATOW: Wow, so there’s some future about that, so now we’re–
SOPHIE BUSHWICK: You could absolutely use– this is really exciting, but it’s still in the very early stages. So it’ll be interesting to see them test this in animals next.
IRA FLATOW: Isn’t that always the last words of a report? More research is needed.
SOPHIE BUSHWICK: More research is always a good idea, I would say. Yes.
IRA FLATOW: Thank you, Sophie. Sophie Bushwick, technology editor at Scientific American. Thank you.