Quantum Algorithm Will Push AI 'Thinking' to New Heights

Quantum computing could help bring the age of super intelligent artificial intelligence. This linear system algorithm could help AI think faster.
Donovan Alexander

Quantum computing will revolutionize the world, reshaping our everyday lives. Companies like the Google, Microsoft, and IBM are making large investments in quantum computing. There is no doubt that quantum computing will not only disrupt every industry but will also tackle problems that are intractable for the classic computers now. 

Built on the principles of quantum mechanics, quantum computing would be able to harness those natural laws to process tremendous amounts of information using new types of the algorithms. As described by Seth Lloyd, the author of Programming the Universe: A Quantum Computer Scientist takes on the Universe, states, "A classical computation is like a solo voice—one line of pure tones succeeding each other. A quantum computation is like a symphony—many lines of tones interfering with one another."

One area that is sure to move beyond its current limits is the emerging area of artificial intelligence.

Quantum AI

As stated before traditional computer's think by analyzing large sets of data. A group of researchers from Singapore, Switzerland and the UK have recently published a study in the Physical Review Letters discussing the power of quantum computing and how it can apply to the machine learning processes of AI. In the published report the team highlighted that a quantum linear system algorithm could help process data and solve problems related to various industries including commodities pricing, social networks, and chemical structures. 

Using the power of a large data matrix, a linear system algorithm can process large sets of data to extrapolate into the future, or make predictions. The matrix combines larges sets of historical data, the factors that may influence that data, as well as how closely correlated this information is related to each other. By doing this on a large scale the, a linear system algorithm could draw relatively accurate conclusions about the future. 


To fully understand, a 10,000 square matrix would take a classical algorithm around a trillion computational steps while the new quantum algorithm, using a technique called singular value estimation, would be able to process the same matrix in just a few hundred steps. 

As explained by PhD student Zhikuan Zhao of Singapore University, "There is a lot of computation involved in analysing the matrix. When it gets beyond say 10,000 by 10,000 entries, it becomes hard for classical computers" 

Via: Eureka Alert 

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