Dance and Engineering Team Up to Build AI Model That Can Read Movement

Dance carries knowledge about how people live — information about the dancer’s landscapes, communities and histories. However, AI systems that analyze human movement are trained almost entirely on everyday actions like walking, sports and gestures, recorded in Western labs with no information about the geographic or cultural origins of the movement.

From Texas ECE to the Cutting Edge of Photonic Computing: Alum Geo Tu and Lightmatter

Geo Tu earned his B.S. in electrical engineering from Texas ECE in 2008. He went on to earn an M.S. in electrical engineering from the University of Southern California in 2010. Now an architect at Lightmatter, Tu is helping develop technology designed to address one of computing’s most pressing challenges: moving enormous volumes of data quickly and efficiently.

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.

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