mathematics and computation

Taken from the March 2019 issue of Physics World where it appeared under the title “A learning revolution”. Members of the Institute of Physics can enjoy the full issue via the Physics World app.
The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers – harnessed to algorithms refined over the past decade – are driving an explosion of applications in everything from medical physics to materials, as Marric Stephens discovers

When your bank calls to ask about a suspiciously large purchase made on your credit card at a strange time, it’s unlikely that a kindly member of staff has personally been combing through your account. Instead, it’s more likely that a machine has learned what sort of behaviours to associate with criminal activity – and that it’s spotted something unexpected on your statement. Silently and efficiently, the bank’s computer has been using algorithms to watch over your account for signs of theft.

Monitoring credit cards in this way is an example of “machine learning” – the process by which a computer system, trained on a given set of examples, develops the ability to perform a task flexibly and autonomously. As a subset of the more general field of artificial intelligence (AI), machine-learning techniques can be applied wherever there are large and complex data sets that can be mined for associations between inputs and outputs. In the case of your bank, the algorithm will have analysed a vast pool of both legitimate and illegitimate transactions to produce an output (“suspected fraud”) from a given input (“high-value order placed at 3 a.m.”).

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