Despite popular culture’s enduring tale of robotic takeover, fields like machine learning and high performance computing are reaching a tipping point where simple devices such as traffic lights, prostheses and cars are being replaced by intelligent counterparts which operate more efficiently and with autonomy.
While once a niche subset of artificial intelligence, machine learning is a process that allows software to predict and ‘learn’ based on data inputs. It is being used for a wide range of modern technologies and processes – ranging from satellite mapping and robotics, through to banking and law. Examples of emerging applications are as diverse as self-driving cars and intelligent traffic lights.
A difficult problem facing practitioners is that machine learning requires enormous computational grunt – with recent advances only becoming possible because of enormous leaps in high performance computing.
How industries can work together with academia and government to address these computational 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, which included leaders from a range of fields in engineering, science, computing 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 Centre of Microscopy and Microanalysis, Professor Julie Cairney, said there were many opportunities for machine learning projects that could benefit Australian industry.
“Advanced manufacturing, agriculture, supply chains, defence, data analysis, threat detection, transport, logistics, fuel and more – machine learning is having a transformative effect on almost every industry today,” she said.
Symposium host, machine learning engineer Professor Philip Leong from the School of Electrical and Information Engineering, said: “Ultimately, machine learning fosters human understanding and endeavour. These techniques are allowing us to understand the previously impossible, and develop capabilities that respond to some of society’s biggest challenges.”
Ultimately, machine learning fosters human understanding and endeavour. These techniques are allowing us to understand the previously impossible.
“The University of Sydney is deeply committed to working with UTS, the state government and companies like AMD in the this exciting new precinct of Tech Central. We hope that this event will foster stronger ties between all parties involved and that the symposium will become an annual event,” said Professor Leong.
Professor Michael Blumenstein, Deputy Dean (Research and Innovation) at the University of Technology Sydney (UTS)’s Faculty of Engineering and IT, said UTS was very pleased to collaborate on the initiative and work closely with the University of Sydney, the NSW government and industry to leverage complementary expertise and capabilities at Tech Central.
“UTS is committed to aligning with the state government’s vision to enhance R&D capability in partnership with universities as well as industry to drive job growth to support the NSW economy. Research-industry collaboration is essential in supporting innovation through research translation, and these types of collaborative activities will enable the acceleration of commercial success in the state,” said Professor Blumenstein.
“From the cloud and PCs, to communications and intelligent endpoints, AMD’s high-performance and adaptive computing solutions are playing an increasingly larger role in shaping the capabilities of nearly every service and product defining the future of computing today.
Dr Joe Peng, AMD’s Regional Sales Manager for Australia and New Zealand said: “AMD’s support shows its commitment to working with universities and customers to narrow the gap between academia and industry by leveraging our leading machine learning and high performance computing platform,."