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Scientists identify new pattern in mathematics using artificial intelligence, Science News


Scientists have identified patterns in mathematics that have never been seen before. 

The discovery, made by the use of artificial intelligence, can help to develop fundamentally new problem-solving techniques.

The study, conducted by the University of Sydney, has been published in Nature.

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According to its co-author, Geordie Williamson, ”Problems in mathematics are widely regarded as some of the most intellectually challenging problems out there.”

“While mathematicians have used machine learning to assist in the analysis of complex data sets, this is the first time we have used computers to help us formulate conjectures or suggest possible lines of attack for unproven ideas in mathematics.”

Going forward artificial intelligence will be more and more critical to reduce workload and save time.

It is also making a wide range of industrial processes more efficient, from cement production to cooling data centres.

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“Working to prove or disprove longstanding conjectures in my field involves the consideration of, at times, infinite space and hugely complex sets of equations across multiple dimensions,” Professor Williamson said.

While computers have long been used to generate data for experimental mathematics, the task of identifying interesting patterns has relied mainly on the intuition of the mathematicians themselves. But that has changed now.

“We have demonstrated that, when guided by mathematical intuition, machine learning provides a powerful framework that can uncover interesting and provable conjectures in areas where a large amount of data is available, or where the objects are too large to study with classical methods,” said co-author András Juhász, from the University of Oxford.

Williamson said: “AI is an extraordinary tool. This work is one of the first times it has demonstrated its usefulness for pure mathematicians, like me.”

“Intuition can take us a long way, but AI can help us find connections the human mind might not always easily spot.”

(With inputs from agencies)

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