As traditional computer chips reach their physical limits and artificial intelligence demands more energy than ever, University of Missouri researchers are rethinking how computers work by taking cues from the human brain. The timing is critical. Energy use from AI data centers is projected to double by the end of the decade, raising urgent questions about sustainability.
The solution may lie in neuromorphic computing, an approach that reimagines computer hardware to process information more like biological neural networks rather than conventional chips.
"One of the brain's greatest advantages is its efficiency," Suchi Guha, a professor of physics in Mizzou's College of Arts and Science, said. "It performs incredibly complex tasks using about 20 watts of power—roughly the same as an old light bulb. By comparison, today's computer architecture is extremely energy-intensive."
Making neuromorphic computing a reality starts at the hardware level. Guha and her team are developing electronic components designed to function like the connections between neurons that allow the brain to learn, adapt and store information—laying the groundwork for computers that are not only more powerful, but dramatically more efficient. Their recent research is published in the journal ACS Applied Electronic Materials.
To read more, click here.