Can we build neural networks whose structure and computational abilities match a real brain? We are not quite there yet, but our new work shows a strategy for getting closer to this goal.

Bedartha Goswami’s goal is to build a bridge between machine learning and climate science. It’s not easy: when new methods in machine learning are developed, the ways that they can be applied in the climate sector is often not considered. Goswami is a team player, so his solution has been to put together a group with the interdisciplinary expertise needed for real breakthroughs in climate science.

When children develop into adults, how they learn changes a lot. While children show a lot of random behaviour, adults perform more goal-directed actions. An influential theory describes these changes as being similar to the behaviour of an optimisation algorithm commonly used in machine learning. This empirical test shows that there are striking similarities but also important differences between human development and machine learning algorithms.

Research in machine learning and data science in and from Africa has the potential to play a more significant global role and faces unique challenges. The pan-African network of AIMS (African Institute for Mathematical Sciences) and its postgraduate programmes prepare young Africans to contribute towards this goal.

Deep learning algorithms are very good at recognizing specific objects (e.g. a dog, a car) within an image ​(known as image classifiers)​. But how do they actually do that? Most often the mechanisms underlying an algorithm’s decision remain opaque. What if we could explain any ​such ​black-box algorithm intuitively and, by doing so, even learn from it?​

Understanding the 3D nature of our world is key to many applications in augmented and virtual reality and simulation. But 3D training data is difficult to obtain. Hence, we develop an algorithm to create 3D graphics that can be trained with 2D images alone. By designing our algorithm such that it can represent 3D data efficiently, we keep the computational cost manageable while moving from 2D images to 3D graphics.