Think small

Think small

It’s my sister’s fault that I ended up working in the area of AI and robotics. She is the managing director of Silicon Valley Robotics in California and for more than a decade has been telling our family that robotics is the way of the future and we should get on board. I’m the younger sister, so my natural inclination is not to listen to what she says, but when an opportunity came up in 2014 to help set up the world’s first research centre combining robotics and computer vision, she was the first person I called. The Australian Centre for Robotic Vision, an ARC-funded Centre of Excellence, gave me the opportunity to apply my research management and commercial skills – and also opened my eyes to the enormous potential of robotics and robotics-related technologies.

My early science career was looking at something completely different. My training is in earth sciences, specifically the application of isotopic dating techniques to understand the timing of geological processes. I started my career looking at the development of the Alpine-Himalayan mountain chain and trying to unpick whether it formed via continuous or episodic geological activity, or a combination of both. After my post-doc I left the field and have forged a non-linear career path. I honed my skills in research communication and management in the materials science area and then developed my research commercialisation skills working in the social sciences and later in water recycling, before finding myself in AI and robotics.

Countries need to invest in AI to drive growth and remain globally competitive.

I’m now the CEO of the Queensland AI Hub. We are currently seeing countries around the world investing billions of dollars into the use and development of artificial intelligence (AI). The purpose is clear: countries need to invest in AI to drive growth and remain globally competitive. AI also opens the door to new approaches to solve complex, large-scale problems that humans cannot tackle alone. Global poverty, hunger, war, access to healthcare, ageing populations, protecting and remediating the environment … These are all areas where AI may be the force multiplier required for us to implement significant positive change.

The need to drive this positive action and make sure Australians benefit has led me to my current role. My previous experience in robotics and cyber-physical systems, developing Australia’s first Robotics Roadmap, has made me acutely aware that this country produces fantastic talent and technologies but is at risk of losing this advantage. We stand on the precipice of the new AI era, poised to either harness and support our strengths in this area or see them dissipate and benefit other nations, with irreversible consequences.

I am optimistic that we will choose to support our sovereign capability in AI, but to truly flourish we need to harness the capability Australia also has in another transformational field – quantum technology. To exploit the full potential of AI we need access to more computation resources at a cheaper price in a way that is environmentally sustainable. Mining, storing and analysing data is computationally intensive – costing time, money and energy. Training an AI model can generate carbon emissions from data centres equivalent to running five cars for 15 years. Quantum computing will revolutionise the training of AI models and the optimisation of algorithms and potentially require 100 to 1,000 times less power.

Quantum sensors will allow us to deploy robotics and AI at scales that have been previously unimagined.

Quantum computing harnesses the power of quantum bits (qubits), which have a theoretically infinite number of states, compared with binary digits (bits), allowing exponentially more simultaneous calculations. Quantum AI algorithms have the potential to identify patterns that are invisible to classical computers. The area I’m most excited about is the development of quantum sensors.

Quantum sensors exploit quantum effects to measure time, dynamics (forces, acceleration and rotation), and fields (gravitational, electromagnetic and mechanical) with unprecedented precision, stability and sensitivity. Such sensors have the potential to revolutionise navigation in self-driving cars, replacing lidar (light detection and ranging) for mapping the environment. Conventional lidar measures the distance to an object by illuminating it with pulsed laser light and measuring the reflection, while quantum “lidar” measures the arrival time of single photons in a trillionth of a second and can be used to position a car on the Earth’s surface, build maps and navigate, and even to allow vehicles to sense around corners.

The University of Queensland is building these sensors from both nano-engineered mechanical devices fabricated on a silicon chip, and atomic gases cooled until they behave as matter waves. While I’m not part of these developments, we should all be paying attention to the influence this important field will have on the future of many emerging technologies.

Quantum sensors will become ubiquitous. These powerful, tiny devices will give us accurate, real-time information on a number of physical attributes necessary to inform our understanding of the world. Importantly, quantum sensors will allow us to deploy robotics and AI at scales that have been previously unimagined and give us some hope that we can solve some of the world’s intractable problems. I look forward to seeing this technology meet its potential in my lifetime.

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