AI Hardware Reimagined for Lower Energy Use
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By Grace Stanley
A new innovation from Cornell researchers lowers the energy use needed to power artificial intelligence – a step toward shrinking the carbon footprints of data centers and AI infrastructure.
As AI systems become increasingly powerful, they also become more power-hungry – raising urgent questions about sustainability. The research team, from Cornell Tech and Cornell Engineering, is tackling that challenge by rethinking the hardware that powers AI, aiming to make it faster, more efficient and less energy-intensive.
The researchers received a Best Paper Award for their findings, presented at the 2025 International Conference on Field-Programmable Logic and Applications, held from Sept. 1 to 5 in Leiden, Netherlands.
Their work focuses on a type of computer chip called a Field-Programmable Gate Array (FPGA). These chips are prized for their flexibility: Unlike traditional chips, they can be reprogrammed for different tasks after manufacturing. This makes them especially useful in rapidly evolving fields such as AI, cloud computing and wireless communication.
