TSMC and Analog Devices, hardware development lab NTT Research, supplier of EUV machines ASML, and tech behemoth Amazon have signed up for the programme so far as part of a cunning plan to create next-generation, energy-efficient hardware for AI and quantum computing in the coming decade.
The research involves developing new architectures and software at the heart of a range of technologies, from analogue neural networks and neuromorphic computing, to hybrid-cloud computing and HPC.
The MIT AI Hardware Programme will be co-led by Jesús del Alamo, professor of electrical engineering, and Aude Oliva, director of strategic industry engagement and the MIT-IBM Watson AI Lab. It will be chaired by Anantha Chandrakasan, dean of the School of Engineering and a professor of electrical engineering and computer science at the university.
In a statement the team said that it is one thing to build more powerful chips and systems to handle ever-growing neural networks. It's another to do it in an energy-efficient manner that is sustainable for our planet/
"More optimised hardware has been proposed but significant new research is needed to realize these concepts," Alamo said. "Energy efficiency is the greatest need. As data sets get bigger, the hardware needs to expand accordingly and the energy consumption just explodes. It does not scale. We need new hardware."