Posts
Caroline Brogan, Reporter at Imperial College London explains, New research suggests combining educational topics and research disciplines to help researchers breathe life into lifelike intelligent robots.
3D rendering of a female robot looking like she is thinking about something using her artificial intelligence.
Photo: Imperial College London
The comment piece suggests that teaching materials science, mechanical engineering, computer science, biology and chemistry as a combined discipline could help students develop the skills they need to create lifelike artificially intelligent (AI) robots as researchers.
Known as Physical AI, these robots would be designed to look and behave like humans or other animals while possessing intellectual capabilities normally associated with biological organisms. These robots could in future help humans at work and in daily living, performing tasks that are dangerous for humans, and assisting in medicine, caregiving, security, building and industry.
Although machines and biological beings exist separately, the intelligence capabilities of the two have not yet been combined. There have so far been no autonomous robots that interact with the surrounding environment and with humans in a similar way to how current computer and smartphone-based AI does.
Co-lead author 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 said: “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.”
Co-lead author Dr Aslan Miriyev of Empa and the Department of Aeronautics at Imperial said: “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.
Source: Imperial College London
