Artificial intelligence is used across myriad disciplines to trawl through troves of data too complex for the human brain – and indeed the average computer – to process, as well as to solve seemingly unsolvable problems.
It’s posited that these technological super-brains could help us develop medicines and vaccines, solve economic problems, or engineer next-generation technology, among many other helpful applications.
But in one of science’s most difficult and often abstract fields, the power of the artificial mind is finally starting to prove itself. For the first time, scientists are using machine learning to come up with theories – rather than simply combing through the raw data – in some of the most confounding fields of mathematics.
As described in a new study in the journal Nature, researchers from the universities of Sydney and Oxford have been working with AI lab DeepMind, based in London, to apply machine learning to suggest new avenues for inquiry, and to attempt to prove mathematical theorems.