Chakrabartty works to make AI more energy efficient

A grant from NSF will allow Chakrabartty's team to curb unsustainable amounts of energy use

Brandie Jefferson 
Shantanu Chakrabartty
Chakrabartty

In 2019, the energy required to train a top-of-the-line artificial intelligence system was more than the energy required to operate five U.S. cars over their entire lifetimes. The situation has only gotten worse. 

To curb this unsustainable amount of energy use, Shantanu Chakrabartty, the Clifford W. Murphy Professor in electrical engineering at Washington University in St. Louis’ McKelvey School of Engineering, will lead a project funded by a three-year $1.14 million grant from the National Science Foundation.

Working with Gert Cauwenberghs at the University of California, San Diego, Chakrabartty plans to develop new hardware to be used in machine learning. The algorithms that will be developed as part of the research will be made available to the research community.

The new algorithms are being developed to be able to work with an openly shared computing platform currently available from the Neuroscience Gateway Portal at the San Diego Supercomputing Center.

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