A team of students in the UK has created a way to turn handwritten equations into computer code, which could help maths experts solve their most complex problems.
Dominik Henjes, Paul Popa and Aleksandr Jermakov came up with their algorithm during a hackathon that challenged people to use artificial intelligence and machine learning to improve lives.
Their system recognises equations and coverts them into code, even if they were written by hand on paper. It could be used by experts to develop their own programs to solve difficult maths problems and eliminate mistakes when manually typing equations into a computer.
“Dominik, Paul and Aleksandr were worthy winners,” said Tom Gray, Chief Technology Officer for Kainos. “All the 20 undergraduates who took part showed a genuine passion for AI, which was inspirational to see.”
All the entries ran on Microsoft’s cloud platform, Azure, while Naveed Hussain, a Big Data and AI Architect at the company, was one of the judges. Other solutions included using AI to detect bias in articles, accurately predict flight times and delays, estimate the amount of rubbish produced in the UK and predict streets where crime will occur.
Jermakov hailed the hackathon as “the perfect stepping stone from academic knowledge towards real-life applications of artificial intelligence”.
Hussain agreed. “I was amazed by Dominik, Paul and Aleksandr’s brilliant entry and delighted that they won first prize in the hackathon,” he said. “AI is helping people across the world solve problems and achieve more at work and at home. As we increasingly turn to digital solutions to help us in our daily lives, we will need more young people like these students to create the next wave of technology.”
The bootcamp is run by Kainos – Microsoft’s Partner of the Year 2018 – and forms part of a free, two-week summer camp featuring learning, workshops and practical sessions focused on AI and its uses. It is held every year and is open to undergraduates who have an interest in machine learning and are studying a degree in Computer Science, Software Engineering, Mathematics, Physics, Statistics or Data Science.