AI’s revolutionary potential in the research and development space is already being manifested across engineering disciplines such as aviation, materials science and quantum computing.
Artificial intelligence (AI) is the great disruptor of the 21st century. Its standard-bearers, such as ChatGPT, have become everyday tools, attracting equal parts celebration and consternation. Not only is AI challenging and changing the way the world learns and works, it’s also radically overhauling the research and development (R&D) space.
Gary Walsh of BNNT Technology is among the leaders in R&D welcoming the power of AI to supercharge their investigations, and accelerate the pace of innovation and product development.
The science entrepreneur is currently involved in an AI company focused on interpreting data. He believes machine learning, used correctly, removes errors from and puts a rocket under traditional R&D processes, which are time-consuming and resource-intensive.
“If you’re confident in the AI being accurate, then it definitely has a place,” he told create. “In fact, you really can’t do without it. In 10 years’ time, you won’t be able to compete without AI, just for the speed of the process.”
Pushing boundaries
AI has become a significant part of the always-evolving engineering landscape. At the point where conventional and emerging technologies meet, generative AI has ushered in a paradigm shift by enabling the easy creation of innovative designs based on predefined constraints and objectives.
Engineers Australia’s Group Executive for Policy and Public Affairs, Damian Ogden CompIEAust, noted that “AI has the potential for significant transformation in the future of engineering in ways we are just starting to understand.”
“It can optimise design processes, improve modelling and help extract more meaningful insights from data,” he said. “This will lead to greater productivity, freeing up engineers to be more innovative.”
Read more: 9 useful AI tools for engineers
AI’s revolutionary potential in the R&D space is already being manifested across engineering disciplines where its tools are proving their efficacy in driving innovation and pushing boundaries in the pursuit of IP that can result in the commercialisation of new products.
Some of those areas include:
Aerospace and automotive. Engineers can use generative AI to explore innovative designs optimising weight, strength and aerodynamics, thereby reducing the material cost while improving performance. In the automotive industry, AI is essential to the development of self-driving vehicles and associated safety technology.
Robotics and manufacturing. Automating and optimising production systems is a key ability of generative AI. AI-driven robotics are increasingly capable of performing complex tasks and autonomously identifying defects and predicting failures.
Medical. Robots performing delicate surgical operations is just one headline-grabbing result of AI being applied to the health field. Using generative AI with highly specific information data can remove the risk of human error from analysing test results while speeding up results.
Materials science. AI has accelerated the discovery of new materials by bypassing the need for trial-and-error experiments and offering the rapid analysis of how different combinations of materials might behave together. AI can recommend new alloys that are lightweight, heat-resistant or durable, for application in batteries and energy storage.
Quantum computing. Australia is already a leader in the burgeoning field that promises to redefine what is possible. A new era of high-speed computing power promises the solving of problems considered impossible on current machines.
Will Australia lead?
So where does Australia rank among its competitor nations in the fourth Industrial Revolution? The National Artificial Intelligence Agency, which is part of the Department of Industry, Science and Resources, explored the landscape of Australia’s AI companies and research institutes in its 2023 AI ecosystem report.
It concluded that we boast a nimble and growing AI ecosystem, on par with some of the globe’s AI leaders.
Iven Mareels, Pro Vice-Chancellor Innovation and the Executive Dean of the Institute for Innovation, Science and Sustainability at Federation University, has witnessed first-hand the power of AI as a tool.
“Its powerful computing is amazing in the hands of specialists,” he told create. “I have already seen people accelerating their own research by a factor of three.”
But context understanding is key if we are to rely on the accuracy of AI tools for decision-making according to Ambarish Natu FIEAust CPEng, IT architect at the Australian Taxation Office.
“Context interpretation is quite important in terms of interpreting the legal side of it and the regulatory language” he said, stressing the need to balance the productivity opportunities against the need for human oversight.
AI promises to play an important part in the R&D underpinning the renewable energy transition, he said, as well as the rapid transformation of the agriculture sector, which by necessity has always been an innovation powerhouse.
“IT, data management and communications technology – a sector less traditionally risk averse – will make opportunities for us. There’s plenty I expect waiting to be done in that space.”
However, Mareels sounded a note of caution on Australia’s lack of investment in its data infrastructure as an impediment to harnessing the AI revolution for our R&D benefit.
“CSIRO is batting very strongly on it with Data61, its data and digital specialist arm. The technology itself is amazing – they’re looking at how generative AI can help do new science and new engineering. Whether we lead in this space depends on how well we can harness our data.”
Keen to explore AI in more depth? This webinar in March will explore the critical ethical concerns related to AI and the essential skills engineers must develop.
