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Could This Memory Tech Reduce AI’s Energy Demands?

Texas Engineers teamed up with the world’s largest semiconductor foundry to fabricate and test an emerging memory technology that could help deal with the increasing energy demand of artificial intelligence.

Together with Taiwan Semiconductor Manufacturing Company (TSMC), researchers tested SOT-MRAM, a type of memory that can retain information even when power is off. It uses magnetic properties, making it faster while also consuming less energy than other memory technologies.

Ian Anderson and Team Win Outstanding Poster Award at the 2026 Hilton Head Workshop

Texas ECE PhD student Ian Anderson led a team that won the Outstanding Poster Award at the 2026 Hilton Head Workshop (Solid-State Sensors, Actuators, and Microsystems Workshop), held May 31–June 4 on Hilton Head Island, South Carolina, for their paper on "Enabling Lithium Niobate Phononic Frequency Combs via Thermal Engineering and Design." Ian is part of Prof. Ruochen Lu's research group.

John Sheputis

John Sheputis is a prominent data center executive, entrepreneur, and real estate investor with over 20 years of experience in digital infrastructure. His commercial and technical contributions include helping establish several major U.S. data center markets, advancing sustainable construction and operations, and driving early adoption of renewable energy and environmental accountability.

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