The $5 Million Quantum Question

Google Quantum AI has unveiled a new competition under the umbrella of XPRIZE. The goal is to find novel algorithms and apply them to solving problems which current computers can't do.

Despite the hundreds of  millions of dollars spent on this new technology, we are still at the starting blocks of taking advantage of the quantum computers in the production environment.

We can start with what we don't have. We don't have quantum computers with chips large enough to solve any real-life problem. The size of these chips are measured in qubits (the equivalent of bits in classical computers). Even if you get large numbers of them, you still have to solve the problem of 'noise' which can render the system completely unusable. The noise can come  from many sources, including among neighboring qubits. The more of them you have, the bigger the problem is.

The next challenge is the lack of available algorithms which perform better on quantum computers. In the previous issues of Recurrent Patterns, we discussed the effort involved in protecting encrypted information from the algorithms that are taking advantage of quantum computers. But that's about future threats. What about future promises?

Reading the XPRIZE page you can see the potential targets for quantum computing capabilities. One area with a lot of potential is new drug discoveries. Quantum computers could enable more accurate predictions of how drug candidates interact with proteins in the human body. Beyond the realm of human biology, quantum computers could conduct simulations of electrical grid loads. They could model new materials and molecules to be used in batteries or fusion reactors.

To get an idea of what has been achieved so far, you can visit web pages of all the quantum computer vendors to read the case studies. IBM case studiesregarding quantum computing are mostly about new materials, but also about supply chain optimization done in partnership with Exxon Mobil. While D-Waveis focused on logistic operation optimization, they’ve also worked on things like employee scheduling and financial services to build better portfolios.

Interestingly enough, from the initial secrecy where very few selected people could come even close to a quantum computer, all the vendors now provide quantum computing as a service. You can get access to quantum computing through IBM, D-Wave, Google, Microsoft or try Rigetti, OQC, QuEra and IONQ  through AWS. You can get all that either for free for a limited compute time or for a very affordable price.

That said, the quantum computing industry is coming to the realization that despite hiring the best and the brightest, they can't hire all of them. They need help.

There are many examples from the past where this XPRIZE model has worked and is still working nicely. One of them is Kaggle, where since 2010 anyone can compete for money to develop new models to solve data science challenges. Notable examples from Kaggle are improving gesture recognition for Microsoft Kinect, making a football AI for Manchester City, coding a trading algorithm for Two Sigma Investments, and improving the search for the Higgs boson at CERN. It also became a recruitment place for companies to find their next hires.

The recurrent pattern in all this? Sometimes we associate progress with various companies, but the truth is that no company in existence has all the resources to do it on its own. The quantum computer industry needs you and is willing to pay you for your smarts. Smart people will always be in demand.