The information age is built on mathematics. From finding the best route between two points, over predicting the future load on a national power grid or tomorrow's weather, to identifying ideal treatment options for diseases, algorithms share a common structure: they take input data, process it through a series of calculations, and deliver an output. Powering the ongoing AI revolution are increasingly sophisticated algorithms, often composed of millions of lines of code. And the more steps a model goes through before presenting a solution, the costlier it is in the number of physical computing units, time, and energy required.
Optimizing these mathematical models is at the heart of the work of the Machine Learning and Data Science Unit (MLDS) at the Okinawa Institute of Science and Technology (OIST). Led by Professor Makoto Yamada, the unit strives to unlock the full potential of machine learning (ML) and improve efficiency, optimizing not just data science but also education and the scholarly output within the unit through a distributed hierarchy.
