Energy-saving hardware could reduce the carbon footprint of AI-driven drug development
Maryam Mahdi | | Quick Read
From aiding in the development of new drugs to enhancing the efficiency of manufacturing practices, AI is changing the way pharma works. But AI’s impact on the environment has not yet been fully addressed – it’s estimated that the energy consumed by computers when training an AI platform results in a carbon footprint that is five times greater than the entire lifespan of a car (1).
Now, researchers at Purdue University have developed a hardware device made of quantum material that could inject extra intelligence, reducing reliance on energy-draining software platforms (2). According to Shriram Ramanathan, a professor at the university, the hardware’s design was inspired by the way the human brain stores and recalls information.
“Human beings store elementary information in a hierarchical way in their brains. And this allows us to categorize complex information so that it can be recalled and reconstructed when needed,” he explains. “Similarly our device relies on neural trees whose ‘branches’ hold information about different categories of data.”
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