Professor Andras Juhasz, of the Mathematical Institute at the University of Oxford and co-author on the paper, said: ‘Pure mathematicians work by formulating conjectures and proving these, resulting in theorems. But where do the conjectures come from?

‘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.’

Professor Marc Lackeby, of the Mathematical Institute at the University of Oxford and co-author, said: ‘It has been fascinating to use machine learning to discover new and unexpected connections between different areas of mathematics. I believe that the work that we have done in Oxford and in Sydney in collaboration with DeepMind demonstrates that machine learning can be a genuinely useful tool in mathematical research.’

Professor Geordie Williamson, Professor of Mathematics at the University of Sydney and director of the Sydney Mathematical Research Institute and co-author, 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.’