Quantum AI – Fact, Fiction, or Future?

We recently had the pleasure of seeing the newly opened Microsoft Quantum Materials Lab in Kgs. Lyngby Denmark.  Considering that quantum computing has been popping up in the media for almost 25 years, what is it that is causing it all of a sudden to create such hype?   One reason is that big companies like IBM, Intel, Microsoft and Google have started investing in it at an unprecedented scale.  The reason for them to do so is obvious, quantum computing promises almost infinite amounts of computing power.  Like nuclear fusion, it can truly change how the world works.   A Microsoft representative mentioned that they needed several data-centers just to simulate a machine with only, say, 50 qubits.   Qubits being the equivalent of bits in the quantum computing world.  Amongst other things even such a small machine promises instant brute-force decryption of even the toughest cryptographic codes.

To truly understand how this can impact AI you just need to scroll back a few years.  What really kicked off the modern AI revolution was that during the naughties (2000’s) really good software was built to train AI’s on GPU’s.  This made it all of a sudden feasible to train on large datasets.  If we now have a quantum AI computer then we would likely be able to instantly train on datasets which today take days or even weeks.  This means we can also start training on much tougher problems and get much better solutions for existing datasets.

So are we still 25 years away from a quantum AI computer we can start using?  The answer is No!   Quantum computing research is actually not just one thing.  A lot of the research is for a general purpose quantum computer.  However hybrid systems with many qubits already exist today that can solve more specific problems.  For example, the company D-wave have created a quantum annealing machine with staggering 2000 qubits that you can buy today if your pockets are deep enough.  Quantum annealing helps solve optimization problems via a popular method called Simulated Annealing.  Most people working with machine learning will have run into this method during their studies, without going into the details, it is a good algorithm for solving a number of machine learning problems.    This is also where it starts getting interesting for AI usage.  Today the interfaces are non-existent, but people at Google AI and other big co’s are working on bridging the gap between such machines and everyday AI tools such as tensorflow.  Within a few years expect that it will be possible to upload your tensorflow code to a quantum cloud service and have it train almost instantly.  In the start it will only be for specific types of AI problems but in the future it will solve a whole range of tasks today performed by GPU’s.   IBM already has a simple quantum computing  cloud service, since it works so fast, it is not rented by the hour but instead by the minute!

 

 

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