We have come a long way since the times when all artificial intelligence could do was beat humans at chess. These days it can help solve important challenges, such as tackling climate change and improving human health.

The INTEGRAL project is a great example of this. It involves mathematicians developing revolutionary machine learning techniques in order to support the conservation of forests and improve traffic in large cities to protect people's health. The name, INTEGRAL, is based on the phrase "India remote imagery analysis". And although the new techniques are being developed for forests and cities in India, they will eventually provide tools that are useful all over the world.

INTEGRAL comprises scientists at the University of Cambridge, as well as a range of organisations in India and beyond. The articles and podcast below explore this fascinating inter-disciplinary and multi-national project, as well as some of the maths involved.

New ways of seeing with the INTEGRAL project — In this podcast we ask the INTEGRAL team about their innovative machine learning approaches to understanding remotely gathered images, and the significant impact these technologies can have on the world.

Seeing traffic through new eyes — Don't like traffic cameras? Then think again. This article explores how these devices can help us make better, and healthier, planning decisions for our cities.

Understanding the diversity of forests using AI — This article explores how the techniques developed by the INTEGRAL team will help us understand India's forests.

Maths in a minute: Machine learning and neural networks — Here's a quick introduction to the type of artificial intelligence used by the INTEGRAL team: machine learning.

Maths in a minute: Semi-supervised machine learning — With ordinary machine learning, algorithms still need a lot of human help to complete their tasks. The techniques being developed by the INTEGRAL team, involving semi-supervised learning, revolutionise this approach.