New research from Imperial College London suggests combining multiple educational fields such as materials science, mechanical engineering, computer science, biology, and chemistry to help further artificial intelligence (AI). According to the research, this combined discipline would provide students with the skills needed to develop lifelike AI robots.
The robots the research refers to is Physical AI, which would act and exhibit behaviors similar to humans and other animals. These robots could also have the intellect capabilities of biological organisms. Physical AI could assist humans at work and home, undertaking dangerous or difficult tasks, including medicine, caregiving, manufacturing, and security.
The research was published on Nov. 10 in Nature Machine Intelligence.
Current AI Capabilities
Modern AI has yet to combine the intelligence capabilities of machines and biological beings, but ongoing work is bringing us closer to that prospect. Currently, the closest connection between humans and AI comes from smartphone technology, but eventually, that same connection will be found between autonomous robots, the environment, and humans.
The co-lead author of the research was Professor Mirko Kovac of Imperial’s Department of Aeronautics and the Swiss Federal Laboratories for Materials Science and Technology (Empa) ‘s Materials and Technology Centre of Robotics.
“The development of robot ‘bodies’ has significantly lagged behind the development of robot ‘brains’. Unlike digital AI, which has been intensively explored in the last few decades, breathing physical intelligence into them has remained comparatively unexplored,” Kovac said.
According to the researchers, this can be partly attributed to the lack of a systematic educational approach to AI. More specifically, an approach that would teach students and researchers how to develop an entire unit consisting of robot bodies and brains.
In the paper, the researchers define Physical AI and demonstrate how an approach can be developed by combining scientific disciplines. This would lead to the development of robots with capabilities similar to intelligent organisms, including bodily control, autonomy, and sensing.
The research lists five main disciplines that should be integrated for Physical AI: materials science, mechanical engineering, computer science, biology, and chemistry.
“The notion of AI is often confined to computers, smartphones and data intensive computation,” Prof. Kovac said. “We are proposing to think of AI in broader sense and co-develop physical morphologies, learning systems, embedded sensors, fluid logic and integrated actuation. This Physical AI is the new frontier in robotics research and will have major impact in the decades to come, and co-evolving students’ skills in an integrative and multidisciplinary way could unlock some key ideas for students and researchers alike.”
For Physical AI to become its own discipline and develop robots to a point in which they have intelligence capabilities, the researchers say conventional robotics and AI needs to be combined with other disciplines.
“We envision Physical AI robots being evolved and grown in the lab by using a variety of unconventional materials and research methods,” Prof. Kovac continued. “Researchers will need a much broader stock of skills for building lifelike robots. Cross-Disciplinary collaborations and partnerships will be very important.”
The researchers also say that support from faculty members is key to integrating these disciplines.
Dr. Aslan Miriyev of Empa and the Department of Aeronautics at Imperial was co-lead author of the research.
“Such backing is especially needed as working in the multidisciplinary playground requires daring to leave the comfort zones of narrow disciplinary knowledge for the sake of a high-risk research and career uncertainty.,” Miriyev said.
“Creating lifelike robots has thus far been an impossible task, but it could be made possible by including Physical AI in the higher education system. Developing skills and research in Physical AI could bring us closer than ever to redefining human-robot and robot-environment interaction.”
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