The University of Tennessee Institute of Agriculture (UTIA) AgResearch, in partnership with the Enterprise Sensor Systems LLC (EnSenSys) of Alamo, Tennessee, has been awarded a grant through the AI TechX Seed Fund to collaborate on “Rapid Identification of Cattle with Infectious Diseases Using AI and Hyperspectral Imaging.”

A QUT report published today into Australia’s bioeconomy has called for a national strategy and outlined the five key steps needed to grow a sustainable economic future. 

Researchers at VCU Massey Comprehensive Cancer Center have developed a novel algorithm that could provide a revolutionary tool for determining the best options for patients - both in the treatment of cancer and in the prescription of medicines. As recently published in Nature Communications, Jinze Liu, Ph.D., and Kevin Byrd, D.D.S., Ph.D., created Threshold-based Assignment of Cell Types from Multiplexed Imaging Data (TACIT), which assigns cell identities based on cell-marker expression profiles. TACIT cuts down cell identification time from over a month to just minutes—saving researchers valuable time and resources.

UC Riverside engineers highlight wafer-scale accelerators—massive computer chips the size of frisbees that span entire silicon wafers—as a breakthrough in AI computing. Published in Device, their review finds these chips outperform traditional GPUs in speed and energy efficiency, critical as AI models grow. Led by Professor Mihri Ozkan, the team cites Cerebras’ WSE-3 as using one-sixth the power of GPU systems. While costly and best suited for large-scale applications, wafer-scale chips reduce energy use by keeping data local. The paper also stresses sustainable manufacturing, noting most carbon emissions come from production. Efficiency, Ozkan argues, “starts at the factory” to ensure greener AI technologies.

Research builds on Emory’s research on influenza vaccines self-administered via Micron’s microarray technology. This trial represents first-ever CDC-sponsored clinical trial of vaccine delivered via “patch” technology and utilizes Micron’s first-in-class dissolvable microarray technology. 

 

MIT researchers built an ultrasmall, low-power receiver that is designed to block a certain type of interference. The chip could be utilized in 5G-enabled smart devices that would be smaller, have longer battery lives, and be more reliable in crowded radio environments.