At a Glance:
- Sarah Boen, director of Technology Strategy at Tektronix, explains her role as a futurist and forecasts quantum computing opportunities.
- From finance, materials science and healthcare supply chains to cryptography, the effects of scalable quantum computing systems will transform our lives.
- Do new technologies truly solve more problems than they create?
Far faster and infinitely more powerful, quantum computers can do calculations that are mind-bogglingly complex. No conventional computer can match up to their potential for cracking complex problems.
And even though the hardware needed to run quantum algorithms at scale have not yet been built, companies such as IBM, Dell, ColdQuanta, Google and Boeing are using simulators and emulators to make these potential workhorses a reality.
As quantum computing advances as a discipline, there is emerging recognition that scalable quantum computing systems—ones that can handle parallel runs of computation on increasingly complex problems—are on a course to being disruptive across all digitalization efforts.
Quantum computing is expected to have the most significant impact in such areas as optimization (e.g., more efficient parcel delivery systems), cryptography (espionage) and in industry-specific applications, such as finance, materials science and healthcare, said Sara Boen, director of Technology Strategy at Tektronix, a test and measurement manufacturer headquartered in Beaverton, Ore.
The Quantum Economic Development Consortium (QED-C), an industry-driven consortium overseen by the U.S. National Institute of Standards and Technology (NIST), foresees a major role for quantum computing in optimizing supply chains, too, pointed out Boen, who has submitted an application on behalf of Tektronix.
Her goal within QED-C is to cover those three aspects, in addition to participating in a workforce planning group to look at what skills the electronics industry will need as the technology matures. “I’m really looking at it from a very broad perspective and have a team of technologists that are working to assess the technology at a deeper level,” she said.
What follows is an edited transcript of Machine Design’s conversation with Boen.
Machine Design: What’s involved in defining what will shape the technology of the future?
Sarah Boen: That’s a great question. I started this role almost a year ago, and the first thing that I had to do was distance myself from the current technology and what was happening currently in the world, because it’s really easy to get bogged down into current state. I spent a lot of my time networking, talking to key industry thought leaders, understanding where technology is going from the perspective of test and measurement, and identifying those trends and identifying areas where we should focus. A part of that is really looking at the external trends that drive technology.
A couple things to touch on that I think are really fascinating are the areas of social issues and environmental issues, and thinking about how technology can enable solving some of these issues and where that is going to take technology. I take a very broad view; it’s not just about this is the next G, in terms of 5G or 6G, but really understanding what problems are in the world and how technology can enable those problems to be solved.
And from there, I map out what technology components we need to invest in internally to be prepared for these new technologies. Also, what opportunities we have with partnerships with industry or with research institutions to help move us forward on our path. That’s an overview of the kind of things that I think about as a futurist. It’s a very interesting role and sometimes takes me out of my comfort zone. But I really enjoy the role.
MD: Consider some of the technologies that will have real impact over the next five or 10 years. 6G, semiconductors, wireless versus wired…what should we keep an eye on?
SB: First and foremost, AI, which can be considered a loaded term. But there are three core drivers of technology that are driven by the needs of AI: high-performance computing, then you have other technologies, like your morphic computing, and quantum computing. All of those technologies are really driven to support the future of AI.
We hear a lot about quantum computing, for example, and I see that in the future there’s a lot of technical hurdles for that technology to be commercially viable, but it will coexist with current classical computing. It has a specific advantage for certain types of problems, and it will be used in conjunction with classical computing. On the high-performance compute side, there’s a couple of challenges with that industry, and that’s all-around power and latency. When you’re dealing with a lot of information, introducing latency within the system, of course this is not a good thing.
So I see a re-architecture of what you would have in the rack of a data center—for example, of how those systems are created—and a shift to using more optical technology to help with the power and latency concerns, as well as to increase the overall bandwidth of those systems. Over the next five years, there’s definitely a lot of innovation happening within the compute side.
On the wireless/wired side, the biggest innovation that I see is—for example, in a factory—is the shift from wired Ethernet to wireless communication enabled by 5G. But I see the more interesting technology shift coming with 6G. Though, some experts in that field debate that this will be the last “G.”
I see a convergence of the terrestrial and non-terrestrial network. Your satellite network with your ground network and a movement of the data center into those networks. A couple things that are interesting with that is, one, that really helps to provide conductivity access to areas where maybe they don’t have access to a communication network. So that’s when we talk about the digital divide and providing an equal opportunity for everyone to have access to information.
"We hear a lot about quantum computing, for example, and I see that in the future there’s a lot of technical hurdles for that technology to be commercially viable, but it will coexist with current classical computing."
The other is, what is that ecosystem going to look like in 10 years? If you think about the traditional telecom data, those are different ecosystems of players. And that’s all coming together, and you can see that with companies like Amazon offering services within a Verizon network, for example. And so, in 10 years, where will we be getting our service from? Is it Verizon, is it Amazon? I think these are really interesting dynamics that will be playing out over the next 10 years.
MD: So, here’s a tongue-in-cheek follow-up related to these technological advances: Do you see them as truly solving problems, or are they creating more problems for us?
SB: Oh, that’s a great, great question. Of course, at Tektronix we’d like them to create more problems so we can solve the hump. I think the problems may even come down to psychological in terms of how people interface with each other and how they interface with the world.
I think a lot of your social responsibility and how the technology is going to shift the way that people live their everyday life needs to be considered and addressed as we advance the technology, because we’re going to be in this world where we’re used to interacting with objects through our communication in our face. As more and more machines start communicating with each other, what does that mean for the world and what types of problems are going to be introduced?
I do think that the psychology part is very important. My son, for example, is four-and-a-half. I saw him watching YouTube video of cars driving around. They were virtual but looked real, to where I really had a look at what he was watching. I was like, “Wow, that’s pretty amazing.” I think that more and more things like that are going to start to emerge to where the physical and that virtual world are really going to blend together. I am definitely excited to see what the future brings us.
"As more and more machines start communicating with each other, what does that mean for the world and what types of problems are going to be introduced?"
MD: In 10 years’ time your son will be 14 and looking to his future. What kind of advice will you be giving him in terms of in-demand skills?
SB: Well, definitely computer science. But that’s my background and my husband is also a computer scientist. So, from a technology perspective, physicists. Interestingly enough, in the field of quantum, the QEDC just published a report on the workforce needs for the future.
But I also think, for application-specific knowledge of how verticals work. For example, how does the financial industry take advantage of the quantum technology? That’s really the domain of experts working with algorithm developers to realize some of these use cases. I see a combination of general-purpose skills, but then those domain-specific skills to really revolutionize some of these industries.
MD: You’ve talked a little bit about how various verticals, such as financial, might try to draw in some of those capabilities. Can you expand on how QED-C is helping to propel quantum into the mainstream?
SB: There’s a couple things. One is the readiness of the technology. As the technology matures, more and more use cases can be supported. But in any consortium, it’s bringing together a network, an ecosystem of providers that can enable the commercialization of that technology. And that ranges from controlling the systems to writing algorithms that bring these use cases to life.
QED-C is really bringing that whole ecosystem together by working on the technology readiness. A part of that is on testing and standardization and making sure that all of the components that are required to build the systems are interoperable, and are working in an environment where it doesn’t take a Ph.D. physicist to run these systems—because obviously that’s not scalable.
MD: Is it fair to assume that there will ultimately be a trickle-down effect through supply chains? Why would the supply chain be a big focal point, and what role will quantum computing play?
SB: So that’s a good question. I’ll give an example. Just last week Dell announced an initiative looking at how to combine the value of high-performance compute with quantum. Those systems will work together, which involves the whole hardware and the whole software stack. You can imagine all of the work that goes into making sure that the systems operate.
And that’s taking off-the-shelf components that were designed for classical technology—not necessarily designed specifically for quantum—and ensuring that they can operate within that environment and operate reliably. Over time, maybe that that will shift to purpose-built components, but right now there’s this convergence of hardware and software from both of these worlds coming together to realize the potential of the technology.
MD: Can you talk a bit about the opportunities for sensors, communication and computation? For instance, how will quantum accelerate technologies associated with sensors?
SB: The sensing field is very focused on aerospace and defense, so more accurate positioning systems, for example, to detect a submarine underwater. You can imagine that the military and the suppliers of solutions to the military are actively involved in sensing technology.
One other interesting application for sensing is in the area of healthcare and wearables, and being able to wear a sensor on your body and to understand what’s actually going on inside. For example, in the future, could a wearable predict that you are going to have a heart attack? I think that’s a very interesting application of the technology.
On the communication side, which is focused on secure communication being able to detect a security breach, for example. There’s a really big push today to get ready for quantum, but also to be able to detect those security breaches. If someone is sniffing or stealing that data that’s being transmitted, you don’t want to find out there was a breach after the fact. A lot of work is going on in that field.
With computing, a focus on a very diverse set of industries, from the financial industry being able to predict prices for securities, being able to predict whether I should give you a loan or not based on information, to supply chain and logistics optimization of a logistics system. I think it was BMW that put out a request for ideas on how they could use quantum technology.
"One other interesting application for sensing is in the area of healthcare and wearables, and being able to wear a sensor on your body and to understand what’s actually going on inside. For example, in the future, could a wearable predict that you are going to have a heart attack?"
There’s a lot of experimentation; there are companies like Cambridge Quantum Computing in the UK that offer services to help companies with their research on solving some of these business problems and seeing how well a quantum computer can solve problems. It’s a really interesting field right now, a lot of discovery and research. We are kind of in this commercialization research phase.
MD: Describe some of the approaches that enabled computation beyond traditional capabilities of classical machines? Why do we still need both?
SB: They will coexist. There are certain classes of problems that are well suited for a quantum computer and most of that focuses on problems where a classical computer just could not solve the problem in a reasonable amount of time. But there’s also a cost and complexity associated with that. The high-performance computing industry is driven by AI and is also going through a lot of innovation.
High-performance computing is not going to look the same in five years that it does today. I talked a little earlier about some of the innovation that go into memory-based architectures, the shift to optical interfaces. That’s really to keep up with the speed of innovation that’s required for that industry. And, yet, we have quantum on the other side. The industry is planning on the architecture for those two systems to coexist.
You start thinking about how do you design a solution, such that, if I have a problem, how can I optimally map that to the compute resources that I have? If you look back in history, it is the same thing as a CPU and then a GPU, for example, and so I see that a quantum processor will just follow that evolution.
MD: How will data and information systems be protected from cyberattacks?
SB: There’s a lot of work being done within the quantum communications field with a technology called QKD (quantum key distribution). The idea there is that within quantum we’re dealing with qubits as opposed to bits, and if an attack happens on that system, the state of that qubit is disrupted to where you know that that attack happened. That doesn’t prevent the attack from happening. It provides you with the knowledge that it did happen.
The reason why the industry is maybe moving faster with that technology, even before quantum computing is mature, is because of all the sensitive information that’s being communicated today. By rolling out this technology, independent of the maturity of quantum computers, you can at least know what data has been compromised. Of course, the financial industry, for example, is one industry that is motivated to look at that technology.
MD: Let’s get back to you, Sarah. What’s next for your career path? Where do you see yourself in 10 years?
SB: Oh, that’s a great question. Well, I’m currently enrolled in an executive education program at UC Berkeley, focused on CTOs [chief technology officers]. So, I see myself as a CTO for a technology company in 10 years.
Editor’s Note: Machine Design's Women in Science and Engineering (WISE) hub compiles our coverage of gender representation issues affecting the engineering field, in addition to contributions from equity seeking groups and subject matter experts within various subdisciplines.