Quantum Computing To Accelerate Machine Learning

Google is the latest to enter the realm of quantum computing by establishing a laboratory to study this technology.

Their recent announcement of the Google “Quantum Artificial Intelligence Lab (QAIL)”  , which is powered by the new D-Wave Two quantum computer, establishes a venue for researchers around the world to experiment with this new technology.

It’s anticipated that Google engineers, along with NASA scientists  and independent researchers, will use the new laboratory to test out different theories on how computer systems and artificial intelligence model the real world. The facility will be operated by the non-profit group Universities Space Research Association (USRA).

Developed and manufactured by D-Wave , the second generation machine (“D-Wave Two”) is based on a 512 quantum bit (“qubit”) superconducting processor chip.  The unit is housed inside a cryogenics system within a 10 square meter shielded room.

For a truly fascinating and detailed explanation on how a quantum computer functions, please refer to the D-Wave Technology Deep Dive page for in-depth documents and videos. For a higher level view, they describe the quantum computers operation as:

The laws of quantum physics, which govern the microscopic world, allow bits of matter to be in two states simultaneously.

All modern-day computing relies on the ultra-fast manipulation of billions of bits of information.

Quantum computing combines these two ideas, allowing us to put bits of information into their 0 and 1 states at the same time. This process allows quantum computers to consider and manipulate all combinations of bits simultaneously, making quantum computation powerful and fast.

The Google team is particularly interested in using quantum computing to further developments in the area of machine learning. This deals with how computers can over time accumulate more data, determine how to process the data and apply this iterative process to developing more accurate models of what the data represents. All this is done by the computer itself, without software developers having to explicitly write all of the underlying programming code.

Some applications for machine learning are in the areas of curing diseases, modeling DNA sequences, increasing agricultural yields and tracking climate changes. For Google, machine learning can also be used to develop better search and results algorithms and improve speech recognition. It’s not too long until a computer will no longer need a physical interface such as a mouse or keyboard; it will just do what you tell it as well as create texts and documents from speech.

While the cost of the D-Wave Two quantum supercomputer was not disclosed, earlier reports on the D-Wave One put the price in excess of $10 Million.  To put this in perspective, the quantum computer can operate as much as 11,000 time faster than a standard Intel processor used in a typical desktop system selling for under $1,000. So at approximately 10,000 times the performance for 10,000 times the price, the cost isn’t so unreasonable.

(Image Credit – D-Wave)

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