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Quantum computing, which can perform complex calculations exponentially faster than normal computers, has the potential to create great wealth by reimagining how problems are solved. But this huge computational power, if not managed responsibly, can have serious consequences, warns David Schatsky.
A commonly used encryption system actually could never be practically broken. It could take thousands, even millions of years, to crack some of the super-secure encryption systems used today. But a quantum computer could conceivably break this kind of encryption in maybe six months’ time. If quantum computing is realized, the encryption systems that are used globally will eventually become almost useless.
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TANYA OTT: This is something everyone should care about—whether you run a large business, or you just buy stuff or do your banking online, or send emails. There’s a big change coming to a computer near you.
I’m Tanya Ott and this is the Press Room, Deloitte University Press’s podcast on the issues and ideas that matter to your business. And today, right now, I’m going to try to convince you that you can understand something as complex as Quantum Computing.
To help me, I’ve got David Schatsky. He analyzes emerging technology and business trends for Deloitte, and he’s written an article that makes the case for why this sci-fi sounding development is going to—no hyperbole here—change the way the world works. Here we go!
I was telling a friend, a very smart friend I should say, that I was going to be talking to you today about quantum computing, and he said good luck making that make sense to people!
DAVID SCHATSKY: No kidding!
TANYA OTT: So your first task is to explain quantum computing in a way that average people can understand. Are you ready for it?
DAVID SCHATSKY: Sure, I can do that.
TANYA OTT: OK! Let's hear it. Hit me.
DAVID SCHATSKY: Quantum computing is a totally new design for computers that can perform really complicated calculations thousands of times faster than normal computers.
TANYA OTT: How is that possible? How do quantum computers differ from our traditional electronic computers?
DAVID SCHATSKY: Well, that's just it. Electronic computers use electronics. They use electrical signals to indicate true and false, or yes and no. And quantum computers use quantum mechanics, which is the bizarre behavior of subatomic particles, to perform their calculations. They use quantum mechanical behavior, which performs things that we don't fully understand, but we know that it works really, really fast.
TANYA OTT: OK. So basically these very, very, very small particles act in a bizarre way, a strange way. We don't exactly know why they do that, but we know that they do it, and it can speed things up dramatically?
DAVID SCHATSKY: Yeah. The subatomic particles behave in pretty wacky, but consistent, ways. And they're so wacky that traditional computers can't readily simulate this behavior. So the idea is to harness the particles themselves and their wacky behavior as a kind of computation and to use them then to perform calculations that are beyond the reach of traditional computers.
TANYA OTT: You say it's going to be a lot faster and there's an example that I read—it's the phone book problem. Maybe that's a good way of expressing how much faster this is than a traditional electronic computer.
DAVID SCHATSKY: Absolutely. The phone book problem is a good example because it's easy to understand what it is and how a traditional computer would solve it. The phone book problem is the name for the task of finding something in an unsorted list, like looking up someone in the phone book when you only have their phone number, because the phone book is sorted by name, not phone number.
In classical computing, the standard way to do this, and really there's no way that's better than this, is to simply go through every entry in the phone book until you find a matching phone number. And that, in theory, requires as many steps as there are entries in the phone book. A researcher at Bell Labs found an algorithm that, if it could be run on a quantum computer, could do that in a small fraction of the time. Take, for instance, a billion entries—it would only take a little over 31,000 steps to find the right answer versus potentially a billion steps using a conventional computer.
TANYA OTT: [You] use the word “theoretical” because scientists believe this is going to work, but we don't actually have quantum computers yet, right?
DAVID SCHATSKY: We have things that are quantum computeresque or special cases of quantum computers, but they're all—I don't want to denigrate them—they're kind of experimental or jerry-rigged, you might say. And this proof that the phone book problem could be solved in fewer steps was a theoretical proof focusing on the number of steps and not exactly how to execute the steps. Now researchers and even companies are building devices that exhibit some of these quantum behaviors and are able to start testing these algorithms in practice, at least in experimental situations.
TANYA OTT: Venture capital firms, governments, and other entities are investing hundreds of billions of dollars into this research and development that you're talking about. What's the allure?
DAVID SCHATSKY: The allure is very simply that if these quantum computers can be built, they have the potential to create great wealth by making it possible to solve some of the most difficult problems. There are problems in financial services—in managing risk and identifying optimal investments. There are problems in research around simulating the behavior of atoms and molecules that would enable researchers to design entirely new forms of matter. One example that's pretty concrete, that I like, that some researchers have looked at is the chemical processes used to produce fertilizer. There's a process that was invented over a hundred years ago that produces fertilizer using hydrogen, and fertilizer production is crucial to feeding the world. But the process that we have consumes, some people say, as much as 5 percent of the global annual output of natural gas. And so people are saying, if we can understand how to simulate the behavior of molecules, we could use that to devise a new process for producing fertilizer that could be significantly more efficient, save billions of cubic feet of gas, and the natural resource and the money associated with it.
TANYA OTT: We've got this idea that we can build a quantum computer. The beginning processes of that [are] happening, at least at the experimental level. But there are some pretty serious engineering challenges that they're facing. Can you sort of walk us through the big engineering challenges in terms of making this actually happen?
DAVID SCHATSKY: Yeah. So these devices are pretty exotic. For instance, one of the commercial quantum computers on the market has to operate in an enclosure that's carefully isolated from the outside environment at a super, super cold temperature that they say is far colder than interstellar space (which I'll have to take their word for).
TANYA OTT: I can't even imagine what that is!
DAVID SCHATSKY: It's very cold, is the point. And the other thing is that the fundamental computing unit, which is known as a quantum bit as opposed to a regular bit from a conventional computer, is perishable. So it can only maintain its state for a tiny, literally a fraction of a second or 50 microseconds, before [it starts] kind of decaying and errors creep in. Even reading the value of [a quantum bit], whether it's a zero or a one, is a very exacting process. It requires incredibly precise measurements. So the engineering—go past the physics to the engineering of these devices—is super, super complicated. And that's why they're not rolling off assembly lines right now. There's a lot of fundamental science and engineering going into devising these devices, making them more stable, [and] reducing the errors that accumulate in operating them. And then down the line, there'll be exploration of how to make them economical.
TANYA OTT: What do we think the timeline is going to be before we see this technology becoming more widely available?
DAVID SCHATSKY: The interesting thing about it is that there are already real companies doing real things relating to quantum computing now. IBM has made available its version of a quantum computer that you can access over the cloud and do experiments on it. There’s a company called D-Wave Systems that's actually selling them for $15 million a pop.
TANYA OTT: Oh, just that.
DAVID SCHATSKY: Just that! I would start lower, maybe an iPad or something, and then scale up. [laughter] So there's already work going on. What the long-term future looks like: Does every big financial services and life sciences company, does NASA and the Navy and the Air Force all have to have these operating on their premises sometime in the future? Maybe, but that's probably easily 10 years away, and some people would say more.
But the fact is that there's real interesting, potentially valuable, work going on now that is helping organizations understand what could be possible when these things do become available. In some cases, companies are reporting that just by thinking through the implications of how to solve problems on a quantum computer, they're coming up with better solutions to problems that they can put into play even today on conventional computers.
TANYA OTT: That's really interesting. One of the biggest hurdles that new technologies have to overcome is standards. And I'm going to boil it down with a really, really simplistic example that many people should understand and that's that this is like the VHS versus Beta moment in the evolution of most technologies—and the fact that I just said VHS, Beta, and quantum computing in the same sentence is crazy.
DAVID SCHATSKY: First time ever done!
TANYA OTT: I am a pioneer! What can I say? What are the big questions on the quantum computing front when it comes to these standards and how it's done?
DAVID SCHATSKY: You know, it's an interesting question because standards matter most when there are lots of people doing things with lots of equipment and they need to pool their resources or they need interoperability. We're at a very early stage now where you can measure the research groups looking at this probably in the dozens. There's probably fewer than a dozen principal ways, principal kind of architectures for these quantum computers. So, I think we're still a ways off before standardization or the lack thereof becomes an inhibitor here. You could think of standardization and innovation as really diametrically opposed. Maybe that's a little bit overly strong, but we're in an innovation phase. There's a kind of discovery, experimentation, and iteration. Once you start imposing standards, you kind of put the brakes on that. So we're a ways away, I think, from the standardization of this.
TANYA OTT: We've talked a lot about the exciting potential of quantum computing, but there are some concerns about some less-than-desired outcomes. For instance, this could have serious implications for encryption systems—those things that keep our online transactions safe—because with quantum computing, people are able to attack that encryption much faster.
DAVID SCHATSKY: Absolutely. One of my favorite themes about technology is that it can be a force for good or evil—it can have amazing outcomes and unintended consequences. In fact, one of the first things that was posited about quantum computing is that it could be really good at doing the calculations necessary to crack encryption systems that are widely used everywhere. By one estimate, a commonly used encryption system actually could never be practically broken. It could take thousands, even millions of years, to crack some of the super-secure encryption systems used today. But a quantum computer could conceivably break this kind of encryption in maybe six months’ time. What that means is that at some point in the future if quantum computing is realized, the encryption systems that are used globally will eventually become almost useless. The consequence is that that companies and agencies and governments are already starting to think about how to prepare for a new era of stronger encryption so that they can withstand attempts to crack their encryption in the quantum era.
TANYA OTT: What do companies do right now to prepare for this, particularly if they're not directly involved in R&D or in the computer industry? That encryption issue is huge.
DAVID SCHATSKY: It is huge and a lot of people don't realize, regarding encryption and hacking of data, that it's not just about stealing data and using it today. There are hackers who are stealing data that's encrypted, that they can't access today, but they are saving it for the day when they will be able to crack it. So organizations that are concerned with security need to start taking this seriously. Some standards agencies have already made the recommendation that organizations need to adopt a more agile approach to encryption, and prepare their systems to be able to upgrade and update the encryption methods that they use when new ones are available. In terms of security and encryption, that is something they can start doing today. Even if the data is not vulnerable to quantum cracking today, it's reasonably safe to assume that it could be, and so companies need to start planning for upgrading to more secure encryption.
TANYA OTT: What other actions do companies need to do to prepare for this age of quantum computing?
DAVID SCHATSKY: I don't think we fully understand all of the potential implications and applications of quantum computing, but it makes sense for companies, especially those that are trying to make long-range plans, to start to play with the idea and to start to think about how their business might operate differently, and what the strategic implications might be of being able to do some of the analysis that now takes them minutes, hours or weeks. If they could do it almost instantly, what would they do differently? Not just faster, but what would they do differently? How would it affect their ability to manage risk? How would it affect their ability to deliver better services or operate more efficiently? Just playing those scenarios out, I think, is appropriate at this time even if they can't necessarily act on them. It could yield new insights about how to operate better and to help an organization get prepared for the quantum future.
One thing to keep in mind is—and you can probably hear in the tone of my voice [that] I'm pretty excited about this—but I don't want to set expectations—that in FY18, chief information officers are going to be putting in line items for quantum computing in their budgets. This is not, by and large, a commercial phenomenon today; it's an R&D phenomenon. But companies that have an interest in R&D, that have an R&D budget, should seriously consider allocating some slice of it to quantum, because it's going to be really influential down the line and it would make sense to start informing themselves today.
TANYA OTT: OK. So look at that! Fifteen minutes and 47 seconds, and I actually feel like I might be one microstep closer to understanding what quantum computing is.
DAVID SCHATSKY: That is fabulous. In the future, it'll be a nanostep, so we'll really show the progress there.
TANYA OTT: And that shows my lack of knowledge. I can't even come up with the incremental step! Thanks, David.
DAVID SCHATSKY: Thank you so much. I hope I write something else that's interesting to you so we can do another one soon.
I don’t want to brag of anything, but there is so much awesome information packed into that site. Here’s a sample of just some of the topics we’ve covered recently:
CHRIS COCHRAN: I can't tell you how much time I personally missed from work just trying to help my daughter survive. And I'm not the only one. It's more than lost productivity. It's lost income, it's taxes, it's money that could be spent in other areas that are being spent on treatment and sometimes wasted on treatment.
AJIT KAMBIL: Most senior executives, when they come into a very large company, will spend 12-hour days during the workweek. Some of them spend time, when they get home every day, doing emails and so forth. That adds, you know, to a 14-hour day sometimes, and then there's at least 5 to 10 hours potentially on the weekend. And that's not sustainable in the long run.
MICHAEL RAYNOR: Your car, your house, your sneakers, your tennis racket…
BRENNA SNIDERMAN: Customers know that their data is being gathered and analyzed, but they don’t want to feel watched. And they don’t want to know that they don’t have a say in the matter.
MICHAEL RAYNOR: Those disclaimers that some people tend to just walk past as a necessary check box before they can get on to what they really want to do—I think it will be increasingly important for people to understand precisely what it is that they are agreeing to.
JIM GUSZCZA: We’re leaving digital breadcrumbs behind as we go about our day-to-day activities because we're all carrying these little smartphones with us. They capture our locations or the buses we're riding in, or the cars we're driving are connected [to] the sensors. Now it is much more possible to gather information about people's day-to-day activities and use this behavioral data to actually figure out: What do people want?
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