In this episode of Today I Learned (about data), we discuss the status of quantum computing, its current challenges and when businesses can expect to use it in their day-to-day operations.
There is a lot of hype around quantum computing these days as it's expected to be one of the most revolutionary technologies we've ever seen, but the question remains: When can IT leaders expect to use quantum computers in their day-to-day business operations?
In this podcast episode of Today I Learned (about data), we discuss the status of quantum computing for business and the current challenges that are holding it back. We speak with Brian Hopkins, an analyst at Forrester, who breaks down the engineering challenges and explains why quantum computing is still mostly considered theoretical.
EB: Hello and welcome to this episode of Today I Learned (about data), where TechTarget's editors give you a behind-the-scenes look at some of the work they've been doing on all things data-related. I'm Ed Burns, executive editor of SearchCIO and SearchEnterpriseAI, and today I'm talking with Gabriella Frick, site editor of SearchCIO. Hi, Gabriella. What did you learn about today?
GF: Hi, Ed. Today I learned about quantum computing and how close businesses might be to being able to get their hands on it.
EB: This is a great topic. Quantum computing is very exciting and we've been seeing a lot of reporting on it lately. One thing about it is that it seems like every time we hear about it it's always people saying it's going to be just over the horizon -- maybe next year, maybe five years from now we'll start getting quantum computers that businesses can actually use. But we still seem to be a little ways off from that.
At the same time we're seeing some huge investments from major companies like IBM and Google, and there's a lot of other startups who are working specifically on the problem of quantum computing. It definitely seems like there is some real traction there. So, Gabriella, what are you hearing?
GF: It's true, this is a really active area right now. And I know our listeners have probably heard that before over the years, but we're seeing a lot of companies developing hardware, doing research and conducting demonstration projects. And some have even made announcements suggesting that they're close to having some kind of broadly usable quantum computers, which I think is some pretty big news.
But I spoke with Brian Hopkins, an analyst at Forrester, and he said we'll likely have a lot further to go before businesses start using quantum computers as part of their regular operations.
BH: We're trying to seek this thing called quantum advantage and quantum advantage is a very pragmatic thing. [It] means there's a business case -- a return on investment -- for solving particular kinds of supercomputing-like scientific, modeling and simulation problems on a quantum computer, cheaper than on a supercomputer. We haven't reached that.
EB: So, I've been hearing in the news about advances in quantum computing and it's a hot topic right now, but it's a little hard to follow. There's always this back and forth going on it seems like right now. I'm thinking specifically of this past year. Google said that they actually achieved quantum supremacy, which Hopkins was talking about in that quote but then IBM came back and said no, actually they didn't really. So, I'm confused. Where are we?
GF: So, this is the problem and the fact that this is more theoretical at this point. Hopkins said what Google accomplished was more theoretical. And it sounds like they may have rigged the game a bit. But either way, what they did is so detached from any kind of real-world problem that there isn't really a reason to get excited, yet. And it probably gives you a good idea of where quantum computers are today when one of the biggest advancements is something purely theoretical.
But anyway, Hopkins said part of the reason why quantum computers seem so distant still, despite all these investments and all of the progress we're seeing, is the scale of the engineering challenges. So, basically, quantum computers operate completely different than classical computers and a lot of the challenges lie in the realm of physics more so than computation.
BH: The way that we measure the power of a digital computer today is with the number of bits. How many bits? It's 32 bits; it's 64 bits. How much information can it process in one clock cycle? And then how fast is the clock cycle? It's 3 gigahertz, 3.2 gigahertz. It's a 64 bit, 3.2 gigahertz four CPU chip. So, number of processors, speed of the clock cycle and how big a data set it can process. Those are the standard measurements. None of that stuff applies to quantum computing. One of the engineering problems to solve is 'How do I make qubits that actually stay useful, longer?' It's not only the number of qubits that I have but the quality of those qubits that creates the number of circuits that you can run, which is then the complexity of the algorithms and the data sets you can solve it from.
GF: Still, Hopkins said he does think it's worth keeping an eye on quantum computing. He said it's going to be one the most revolutionary technologies the world has seen and that, once it becomes fully realized, it will change the world. The only question is when will we get to that point? Will it be five, 10, 15 years? We really don't know that yet.
EB: Right, that's always the question when you're talking about these emerging technologies, is when will it actually make an impact? Certainly, it sounds like quantum computing does have the potential to be hugely impactful and eventually be one of the most exciting technologies that we've seen, like Hopkins was saying, but it is a little frustrating not knowing when we'll actually see that.
Thank you, Gabriella, for taking us through some of your reporting on this topic -- it was really interesting. And to our listeners, we have a lot more coverage about the emergence of quantum computing and its potential applications for businesses on our site, SearchCIO.com, so head over there to learn more. And thank you for joining us on this episode of Today I Learned (about data).