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Research team makes breakthrough that could revolutionize the future of AI: 'We can see with our own eyes the impact'

"This material solves a lot of existing challenges and is ready to be used today."

"This material solves a lot of existing challenges and is ready to be used today."

Photo Credit: Carnegie Mellon University College of Engineering

Artificial intelligence technology is moving fast and being adopted by more consumers and corporations every day. But these quick developments are causing massive energy problems that need effective solutions.

The spread of AI is taking a significant toll on the environment by using huge amounts of energy to power data centers and water to cool them down.

The energy consumed by these data centers could triple by 2028, and some estimates even say they could account for 8% of U.S. energy use by 2030.

A group of researchers from Carnegie Mellon University has developed a new thermal interface material that can cool AI data centers faster and with less power than the current standards.

The material achieves ultra-low thermal resistance while improving heat dissipation, which increases cooling efficiency. The team has also proved it to be highly reliable after testing it at extreme temperatures.

"The material is like a bridge between the nano- and macroscopic worlds," said Zexiao Wang, a Ph.D. candidate at the university. "Because the nanoscale material can be created using macroscale approaches, we can see with our own eyes the impact of the material on the world."

The authors said this breakthrough will benefit the AI industry, ultimately making AI development more affordable, renewable, and reliable.

"This material solves a lot of existing challenges and is ready to be used today. While an immediate need is focused on cooling data centers, the application for this innovation is extensive," said Sheng Shen, a professor at the university.

"It can break through in industries that have been stuck using outdated thermal interface materials. It can be used for pre-packaging, reworked when using non-adhesives, and enables thermal bonding of two substrates at room temperature."

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This innovation from Carnegie Mellon University is adding to the growing list of research devoted to improving the operation of AI, including Lenovo's new cooling system and other liquid cooling initiatives.

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