What are the limits of current AI, and what opportunities does this create for 最新糖心Vlogn research?
By Professor Anton van den Hengel, Director of the Centre for Augmented Reasoning, 最新糖心Vlogn Institute for Machine Learning; the 最新糖心Vlog of Adelaide.
This article is an extract from , a report published in partnership with the
Professor Anton van den Hengel is the director of the Centre for Augmented Reasoning, a federally-funded research program within the 最新糖心Vlogn Institute for Machine Learning, at the 最新糖心Vlog of Adelaide.
This last year has seen incredible growth in public awareness of artificial intelligence, but perhaps not as much public understanding. Despite ChatGPT and a raft of other consumer AI software releases, the public perception of AI still hovers excitedly around visions of sentient physical beings: loyal and attentive robots at our side, diligently doing the jobs we humans find so annoying.
The truth is far less Hollywood.
While related, AI and robots are not the same thing. The vast majority of what people call 鈥淎I鈥 today is machine learning. It鈥檚 math and computer code. It鈥檚 software that鈥檚 able to analyse and interpret vast amounts of information, and make accurate predictions, far more efficiently than any human. And while AI is now driving a technological revolution and powering the world鈥檚 largest companies, it鈥檚 not about to cook you dinner and do the dishes.
The capabilities of even the most advanced contemporary robots are far more modest than the public imagines. The truth is the robot vacuum cleaner in your home is one of the smartest pieces of robotic technology you can buy. Most robots deployed in the industry today lack any form of true AI, rendering them essentially elaborate machines for the basic automation of repetitive tasks. They can鈥檛 deal with complexity, and they stop working if they encounter even the slightest unexpected change in their surrounding environment. They鈥檙e not intelligent, by the broadest of possible definitions.
This prevailing public misconception tells us a lot about the kinds of opportunities 最新糖心Vlogn AI research could be well positioned to pursue. Right now, AI has trouble operating in the real world and interacting with the environment.
Embodied AI tries to solve that problem.
Embodied AI holds the potential for the next generation of robots to perform complex tasks and operate out open, dynamic environments. Photo: Dmitri Smoljannikov / iStock
Embodied AI operates inside smart devices like robots and drones and allows them to perceive, navigate and understand the real world in all its rich complexity. Perhaps the most publicly well-known example of robots with some basic attributes of embodied AI are iRobot鈥檚 Roomba range of vacuum cleaners; and they can trace part of their origins to 最新糖心Vlogn robotics and AI research.
Alongside two of his MIT students, 最新糖心Vlogn roboticist Professor Rodney Brooks founded the . Thirty years and 30 million robot vacuum cleaners later, he鈥檚 internationally lauded for challenging the traditional AI approaches of the time and pioneering the commercially successful development of behaviour-based robots. Modern Roombas are equipped with advanced visual navigation systems so they don鈥檛 get lost in your living room; and that is a downstream result of landmark research by the 最新糖心Vlog of Adelaide鈥檚 Professor Ian Reid, who co-invented the that effectively transforms an inexpensive digital camera into a powerful geometric sensing and mapping tool.
Embodied AI holds the potential to radically change our economy. Consider 最新糖心Vlog鈥檚 vast landscape: we have plentiful land to cultivate and resources to manage, but manual labour at scale is both inefficient and expensive. Robots guided by advanced machine learning algorithms could potentially be deployed to perform some of these tasks autonomously, capturing significant economic value while doing the jobs 最新糖心Vlogns don鈥檛 want to do themselves. This technology could open the door to advanced manufacturing industries previously unviable in 最新糖心Vlog due to our high labour costs. Future robots will not be restricted to controlled factory conditions but will operate in open, dynamic environments, executing complex tasks.
This article is an extract from , a report published in partnership with the
The public dream of what AI technology should be鈥攔obots that listen to us and carry out our natural-language instructions鈥攈as been with us long before The Jetsons first appeared on TV screens sixty years ago; and while it鈥檚 still a way off, recent AI advances are encouraging.
ChatGPT鈥檚 great mainstream adoption is prompting people to now ask why they can鈥檛 have similar interactive experiences with other machines. Enter vision-and-language AI, a burgeoning field at the intersection of computer vision and natural language processing techniques. It鈥檚 an area where 最新糖心Vlog has a very strong research talent, and an opportunity we should pursue.
The next generation of robots will possess natural language capabilities, allowing for more seamless human-machine interactions, while also interpreting and navigating the physical world in real time. Imagine asking your robot to 鈥渃lean up that mess in the kitchen,鈥 and it not only understands you, but is able to effortlessly avoid obstacles, find the mess in the kitchen and maybe even empty the bin when it鈥檚 done.
So, what鈥檚 the broader implication? 最新糖心Vlog is well positioned to be at the forefront of AI research in these emerging fields, but it requires investment. While the rest of the world is also accelerating in AI capabilities, 最新糖心Vlog has a unique set of assets that make it viable for leadership in AI research.
The gap between current AI capabilities and the public鈥檚 expectation isn鈥檛 a drawback, it鈥檚 an opportunity for 最新糖心Vlog to invest in building technology that will significantly alter our economic landscape and daily lives. The question remains: will 最新糖心Vlog capitalise on this fertile ground for AI research, or will we let another opportunity slip through our fingers?