Prof Simon Lucy from the Australian Institute for Machine Learning on his experiences of creating new technologies across business and academia
In Australia we’re used to seeing academic and business activities kept relatively separate. But I’ve seen the clear benefits that come from linking science with business. Indeed, if you look at the top computer science universities in the USA, you’d struggle to find any senior academic who does not have a concurrent dual role with a commercial operator.
I recently became Co-Director (with Anton van den Hengel) at the Australian Institute for Machine Learning in Adelaide, South Australia. Immediately prior, I was Associate Professor at Carnegie Mellon University’s Robotics Institute, USA, and also Principal Scientist at Argo AI – a company that builds technology for self-driving cars – plus managing engagements with Samsung, and Apple, and a couple of other big companies.
All of this took place in Pittsburgh, Pennsylvania where an innovation district brings together Carnegie Mellon University, University of Pittsburgh and its Medical Center plus numerous established and start-up tech organisations. Recent data shows the area supports over 50,000 jobs, with the population of Pittsburgh being around 2.3 million.
Working in industry and academia
My dual roles in Pittsburgh worked together well. Yes, I had to be considered in navigating through the intellectual property implications. And yes, I was careful to disclose all my activities when it was appropriate.
But even with all that, we had some fantastic outcomes. The mix of my activities created positive results for both the university, and the technology companies.
After all, in the end we were all working towards similar kinds of scientific goals: to develop and apply machine learning to solve human problems. For example, we created Argoverse, a whole environment in which anyone who wants to work in autonomous vehicles can go and evaluate their algorithms and benchmark their activities.
Also through Carnegie Mellon University, I did some consulting work to develop artificial intelligence improve basketball shot taking, now incorporated into a product called Noah.
Creating value for industry
Many tech businesses see a value proposition in working with universities. Argo AI invested US$15 million in a research centre at Carnegie Mellon University, where all the technology developed was open source. The university benefitted by having a new research facility and working closely with the company, and the company benefited by having access to a pool of talented researchers, building capability in one geographical location and having a good look at innovation as it developed.
Ownership of intellectual property is not the only way that tech companies see value – they’re keen to find ways to incorporate thinking about blue sky problems into their activities. Working from quarter to quarter with strict commercial goals doesn’t always give businesses the freedom to be creative, and so having access to academics is one way to achieve this. I saw it work extremely well in Pennsylvania.
Moving to the Australian Institute for Machine Learning
Now that I’m here in Adelaide, I can see it has a lot in common with Pittsburgh. They’re both highly liveable cities, great places for families. But Adelaide also has the capacity to create real momentum when it comes to computer science, in the same way that Pittsburgh has done over recent decades.
We’ve got a concentration of world-class machine perception and learning expertise at the Australian Institute for Machine Learning and the AU$20 million Centre for Augmented Reasoning opening in early 2021, plus the innovation and entrepreneurship hub including Australia’s Space Agency next door at Lot Fourteen. I’m excited about the technology and growth in expertise that will undoubtedly emerge from South Australia’s co-located university, business and start-up communities.
Professor Simon Lucey
Co-Director Australian Institute for Machine Learning
University of Adelaide
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