MIT launches cross-disciplinary program to boost AI hardware innovation

Ryan Daws is a senior editor at TechForge Media with over a decade of experience in crafting compelling narratives and making complex topics accessible. His articles and interviews with industry leaders have earned him recognition as a key influencer by organisations like Onalytica. Under his leadership, publications have been praised by analyst firms such as Forrester for their excellence and performance. Connect with him on X (@gadget_ry) or Mastodon (

MIT has launched a new academia and industry partnership called the AI Hardware Program that aims to boost research and development.

“A sharp focus on AI hardware manufacturing, research, and design is critical to meet the demands of the world’s evolving devices, architectures, and systems,” says Anantha Chandrakasan, dean of the MIT School of Engineering, and Vannevar Bush Professor of Electrical Engineering and Computer Science. 

“Knowledge-sharing between industry and academia is imperative to the future of high-performance computing.”

There are five inaugural members of the program:

  • Amazon
  • Analog Devices
  • ASML
  • NTT Research
  • TSMC

As the diversity of the inaugural members shows, the program is intended to be a cross-disciplinary effort.

“As AI systems become more sophisticated, new solutions are sorely needed to enable more advanced applications and deliver greater performance,” commented Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Ellis Warren Professor of Electrical Engineering and Computer Science

 “Our aim is to devise real-world technological solutions and lead the development of technologies for AI in hardware and software.”

A key goal of the program is to help create more energy-efficient systems.

“We are all in awe at the seemingly superhuman capabilities of today’s AI systems. But this comes at a rapidly increasing and unsustainable energy cost,” explained Jesús del Alamo, the Donner Professor in MIT’s Department of Electrical Engineering and Computer Science.

“Continued progress in AI will require new and vastly more energy-efficient systems. This, in turn, will demand innovations across the entire abstraction stack, from materials and devices to systems and software. The program is in a unique position to contribute to this quest.”

Other key areas of exploration include:

  • Analog neural networks
  • New CMOS designs
  • Heterogeneous integration for AI systems
  • Monolithic-3D AI systems
  • Analog nonvolatile memory devices
  • Software-hardware co-design
  • Intelligence at the edge
  • Intelligent sensors
  • Energy-efficient AI
  • Intelligent Internet of Things (IIoT)
  • Neuromorphic computing
  • AI edge security
  • Quantum AI
  • Wireless technologies
  • Hybrid-cloud computing
  • High-performance computation

It’s an exhaustive list and an ambitious project. However, the AI Hardware Program is off to a great start with the inaugural members bringing significant talent and expertise in their respective fields to the table.

“We live in an era where paradigm-shifting discoveries in hardware, systems communications, and computing have become mandatory to find sustainable solutions—solutions that we are proud to give to the world and generations to come,” says Aude Oliva, Senior Research Scientist in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Director of Strategic Industry Engagement at the MIT Schwarzman College of Computing.

The program is being co-led by Jesús del Alamo and Aude Oliva. Anantha Chandrakasan will serve as its chair.

More information about the AI Hardware Program can be found here.

(Photo by Nejc Soklič on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo. The next events in the series will be held in Santa Clara on 11-12 May 2022, Amsterdam on 20-21 September 2022, and London on 1-2 December 2022.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: , , , , , , , , , ,

View Comments
Leave a comment

Leave a Reply