IEEE Talks Big Data: Whurley
William Hurley (Whurley) is Chair of the IEEE Quantum Computing Working Group. In this interview, Whurley explores some of the ways quantum computing will change the world, including by analyzing large, often disparate datasets that traditional computers struggle to process. He’s also involved in a new IEEE project that aims to eliminate arguably the biggest barrier to quantum computing going mainstream: the lack of industry-standard definitions about its most fundamental concepts. Whurley has been announced as a keynote speaker at the annual SXSW Conference, March 9-18, 2018, in Austin. This session will be included as a part of the IEEE Tech for Humanity Series at SXSW.
Question: Quantum computing has been in development for decades but some vendors are starting to offer commercial products. How long before quantum computers become something that's common in at least large enterprises and government agencies? And what are the barriers to adoption? Cost? The learning curve of quantum computing?
Whurley: Most people probably see that adoption happening in the next 5 to 10 years; I believe 3 to 5 years is realistically possible. Ultimately that timing depends on us breaking down the current barriers. In addition to the technical hurdles, understanding how this technology will apply to current businesses is a barrier. CEOs and entrepreneurs need to be able to say with confidence: “Okay, I know what we’re going to use this for. I know why we’re going to allocate millions of dollars to this technology.”
There’s a great Microsoft Lab video series—three presentations, about one hour each—asking the question, “What would we do with a quantum computer?” If the people building them are asking that, how are potential buyers going to get excited about concrete applications?
Educating the non-technical community about 1) what quantum computing is, 2) how it works (without getting too deep into the physics), and most importantly, 3) how it applies to their business is a big step. If I can tell you how this new thing will help you do what you do better or faster, you’re going to at least listen to what I have to say.
Question: What are some examples of how businesses are already using quantum computers to do things that were impossible or impractical with traditional computers?
Whurley: The point at which a quantum computer demonstrates the ability to execute an operation that a traditional computer can’t is commonly called “quantum supremacy.” We haven’t hit that point yet. Google has plans to produce a 49-qubit chip by the end of the year, which theoretically would have achieved the point of supremacy, but IBM just simulated a 56-qubit quantum computer on a traditional system. That pushed the goal posts back a bit, but we’ll get there soon.
In the meantime, several organizations are using quantum computers right now. NASA flew a D-Wave quantum computer for a robotics mission in space. Google used a D-Wave machine for search, image labeling, and voice recognition. Lockheed Martin has been using D-Wave’s quantum technology in partnership with the University of Southern California since 2011. Their primary goal was to use the D-Wave One to create and test aircraft, radar and other systems more efficiently. They were also supporting research in hopes of using the system in the future to support advanced modeling and simulation.
Question: How does quantum computing fit in with some other emerging trends and technologies? For example, could a smart city use it to analyze and act on all of the Big Data produced by Internet of Things (IoT) sensors in infrastructure and connected vehicles?
Whurley: IoT is a prime example of how we’re generating more data than we ever have. With just two cameras and a radar system, MLB’s Statcast system generates 7 terabytes of data per baseball game. That’s roughly 1.7 exabytes of data per regular season, in just this one narrow example. Doing anything comprehensive with that data requires huge, huge amounts of processing power. Traditional computers just can’t handle that volume efficiently. Medical researchers pay thousands of dollars an hour for supercomputing time to analyze data sets. Some of their operations take several days for a supercomputer to complete. Without quantum computing, there’s no practical way to mine all that data.
With a quantum computer, we can take advantage of much faster algorithms (e.g., Grover’s algorithm for searching an unstructured database, Shor’s algorithm for factoring). If you have a database with 1 million items, a traditional computer would have to look at 500,000 items to find a search item. Using Grover’s algorithm, a quantum computer would only have to look at 1,000 items. The average quantum search is the square root of the number of items being searched, which is a quadratic increase in speed. The bigger the dataset, the bigger the time savings.
Because you can account for more variables, quantum computing has the potential to help us identify connections between different datasets. For example, you could analyze historical weather data alongside population migration and disease outbreak data to try and identify leading indicators for epidemics, and to what degree weather and food supply are factors in the spread of infectious diseases. The conclusions you were able to draw might help governments plan more effectively for the next disaster. Traditional computers are capable of this kind of analysis given time, but quantum computers have the potential to do it much, much faster. That speed can mean the difference between an analysis that’s doable and one that would take too long to be practical.
Today there are so many scientists making some assumptions out of the Big data they’ve gathered. Those assumptions often are based on what they think is happening or will happen or did happen. We hope quantum computing will usher in an age of knowing rather than assuming.
Take urban traffic, for example. Volkswagen Group is using quantum computing to analyze Beijing’s traffic congestion based on the actual data collected from 10,000 taxis. This analysis can be used to more accurately predict when and where problems will occur, allowing Beijing and other municipalities to optimize their roads, bridges, and other infrastructure to minimize congestion.
Only a robust, reliable quantum computer can handle this Herculean task. “If there are too many factors in a given space, such as a large number of moving cars that you have to distribute to countless alternative points, this quickly leads to a combinatorial explosion, which overwhelms traditional computers, even with the cloud behind them,” says Florian Neukart, Volkswagen of America Principal Data Scientist.
Question: How does quantum computing affect cybersecurity? For example, it has the potential to undermine today's cryptography, but doesn't it also have the potential to enable new, stronger security mechanisms?
Whurley: What effect quantum computing will have on cybersecurity and encryption is a hotly debated topic. There is absolutely an opportunity to use a robust quantum computer to break some current encryption schemes. China is investing heavily in quantum cryptography for that reason. But we know that quantum computers are coming for our encrypted data and communications, so we can plan for that. In some cases, simply doubling the length of your encryption key will prevent quantum hacking. In others, we’ll need new forms of quantum-enabled encryption or other methods already in development. The International Conference on Post-Quantum Cryptography was held for the eighth time this year, so my personal opinion is that this is something that we will address in time. As we get further into the quantum age, I’m confident that we’ll turn things that are currently viewed as negatives—like threatening current encryption schemes—into much larger positives.
Question: You're part of the IEEE P7130™ Standard for Quantum Computing Definitions project, which launched in August. What are its goals, and how will it help make quantum computing a viable option for more businesses, researchers and others?
Whurley: Quantum computing doesn’t have an industry-standard set of definitions for fundamental terms and concepts, such as a qubit. If you shop for a quantum processor today, or look to invest in a company that makes them, you’ll find big differences in specs. Some vendors offer 2,048-qubit models, and others have 5-qubit models. Which one is better? It’s tough to make those kinds of fundamental comparisons when the industry hasn’t agreed on a definition for qubit.
When buyers and investors can’t make apples-to-apples comparisons, they often base their decision on brand or marketing hype. That gives incumbents and big companies a competitive edge over startups. Hence the adage “no one ever got fired for buying IBM.” Without an industry-standard nomenclature, we can’t develop performance benchmarks or standards.
A nomenclature is also critical for training the next generation of people who will design and use quantum computers. Colleges and universities can’t teach students terms and concepts when there are multiple definitions for each one.
Those are a few examples of why the IEEE P7130—Standard for Quantum Computing Definitions project was created. It will help eliminate the language barrier that is holding quantum computing back from changing the world. To learn more about IEEE P7130 and how to get involved, please visit the Quantum Computing Working Group landing page.
|William Hurley (Whurley) is Chair of the IEEE Quantum Computing Working Group. In this interview, Whurley explores some of the ways quantum computing will change the world, including by analyzing large, often disparate datasets that traditional computers struggle to process. He’s also involved in a new IEEE project that aims to eliminate arguably the biggest barrier to quantum computing going mainstream: the lack of industry-standard definitions about its most fundamental concepts. Whurley has been announced as a keynote speaker at the annual SXSW Conference, March 9-18, 2018, in Austin. This session will be included as a part of the IEEE Tech for Humanity Series at SXSW.|