How quantum computing will change analytics [Q&A]

quantum computing

Google announced in October that after years of theorizing, it had finally achieved the milestone of quantum supremacy -- carrying out a calculation in just three minutes that would take up to 100,000 years for a conventional computer.

Ask any analytics expert what they're excited to see in the future, and you’re likely going to hear quantum computing. That's largely due to the sweeping ways it will transform analytics. We spoke with Prasad Kothari, vice president of analytics and client solutions at The Smart Cube, about what that looks like.

BN: What is quantum computing and why does it matter?

PK: Quantum computing signifies the next big change in IT. Today there are some challenges that are so complex there simply isn't enough computational power in the world to tackle them. Most of these challenges relate to complex networks, like social networks and protein-protein interaction networks (which, in healthcare, help doctors and scientists understand protein function and the biology of the cell). But with quantum, this is likely to change.

BN: And how does quantum computing differ from classical computing?

PK: It's a bit tricky to explain, but here it is in its simplest form: classical computing processes bits that are either in a 0 state or a 1 state, they cannot be both at the same time. Quantum computing uses something called quibits that can be in both a 0 state and a 1 state. (Schrodinger's bits, anyone?)

A lot of quantum machine learning algorithms, such as Grover’s search algorithm, are based on core concepts of quantum physics, and quantum computing provides the ideal environment to run them.

The upshot is that this ability to look at things not just in binary states, but using the principle of superposition, allows quantum computers to look at many variables at the same time. Which means much more data can be stored. Much, much more.

In short, this means we can process far more complex equations, and as the complexity and sheer size of our data sets continue to grow year after year, this ability could be vital in helping us put the world’s data to better use.

BN: Predictive analytics is used in all sorts of industries today to help inform business decisions. However, with our current capabilities, there are only so many variables you can calculate before simulations take too long to be useful. How does quantum change that?

PK: With quantum computing, an almost infinite number of variables can be added to simulations, providing far more specific insights than we’ve seen thus far. This is especially useful for solving complex optimization problems -- things like figuring out the best way to schedule flights or determining the most efficient delivery routes.

While we can do this already, with quantum capabilities we can make sure every possibility is accounted for.

BN: We've heard that quantum computing will help computers to 'see'. What does this mean?

PK: In 2017, a sciencemag.org article reported on a breakthrough in quantum technology that saw a computer recognize trees in a series of images. This may not sound like the most amazing achievement or even one that's all that useful. But as a proof of concept it shows that we’ll soon be able to use computer vision to look at more complex problems -- including those that require heavy data crunching.

BN: In addition to the many uses for computer vision powered by quantum computing, are there other ways it'll make machines smarter than they already are?

PK: We already have computers that can make themselves smarter, but now we’re see machine learning capabilities accelerate exponentially -- reducing problem-solving times from hundreds of thousands of years to mere seconds. To put this in context, when IBM's Deep Blue computer defeated chess champion Garry Kasparov in 1997, it was able to examine a possible 200 million moves a second. With quantum capabilities it will be possible to calculate a trillion moves per second. And that's a lot of chess.

BN: What industries do you think stand to benefit the most from quantum computing?

PK: Healthcare stands out as one. Quantum computing will increase the accuracy and speed of diagnosis, optimize the selection of clinical trial candidates and make the much talked about personalized healthcare industry a reality -- with treatments created to meet the needs of a patient's specific genetic makeup.

Quantum will be able to analyze troves of data (everything from a person’s metabolic rate, diet, personal habits, medical and prescription history) and recommend patient-specific treatment.

It's likely every area of healthcare -- from diagnosis to drug development and treatment -- will be much improved and require less human effort. It will take patient care and personalization to a new level of precision.

BN: Are there any others?

PK: E-commerce is another. The current means of analyzing a person's online shopping behavior, as well as pushing recommendations for products to buy, are in fact quite sophisticated. But not compared to how quantum computing will accelerate the experience. It will rapidly analyze every single click to understand complex relationships between data variables and increase accuracy so recommendations made to the buyer will be in near-real time. It will no longer be only when the person lands on a page or when they refresh that personalized suggestions will be made. Those will happen simply as a person scrolls through a retailer’s site.

BN: It seems like the possibilities are nearly limitless for how quantum computing will change the game across sectors when it comes to making machines smarter, faster and more precise. Any closing thoughts?

PK: As Google said in its blog post about its quantum computing milestone, the concept sounds futuristic because, until recently, it was. Now that it's real, we see a world of new opportunities for how technology can advance not only the analytics and scientific sectors, but society as a whole.

What are you most excited about when it comes to the possibilities ushered in by quantum computing?

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