Despite popular culture’s lingering story of robot takeover, fields like machine learning and high-performance computing are reaching a tipping point where simple devices such as traffic lights, prosthetics and cars are replaced by intelligent counterparts that operate more efficiently and with greater autonomy.
While machine learning was once a niche subset of artificial intelligence, it is a process that allows software to predict and “learn” based on data input. It is used for a wide variety of modern technologies and processes – ranging from satellite mapping and robotics to banking and law. Examples of emerging applications are as diverse as self-driving cars and intelligent traffic lights.
A difficult problem practitioners face is that machine learning requires tremendous computing power – with recent advances made possible only by giant leaps in high-performance computing.
How industries can collaborate with academia and government to tackle these computing challenges was recently discussed at a symposium co-hosted by the University of Sydney, UTS and semiconductor manufacturer AMD at Tech Central’s Quantum Terminal.
The symposium, attended by leaders from various fields in engineering, science, computer science and manufacturing, identified opportunities for collaboration between government, industry and academia to create world-class technologies based on real-time machine learning.
Pro-Vice Chancellor for Research (Enterprise and Engagement) and Director of the Center for Microscopy and Microanalysis, Professor Julie Cairneysaid there were many opportunities for machine learning projects that could benefit the Australian industry.
“Advanced manufacturing, agriculture, supply chains, defense, data analytics, threat detection, transportation, logistics, fuel and more — machine learning is transforming nearly every industry today,” she said.
Host of the symposium, professor computer technology from the University of Sydney, Philip Leonsaid: “Ultimately, machine learning fosters human learning and endeavor. These techniques enable us to understand the previously impossible and develop capabilities that address some of society’s greatest challenges.”