Studying tumors’ surroundings
The advance of any cancer is determined by the molecular characteristics of the tumor itself as well as by its interaction with the surrounding cells. But understanding how these interactions influence the course of the disease has been difficult. A new study published in Cell analyzes the molecular interactions that occurred in response to a variety of cancer treatments in more than 2,500 lab-produced models of tumors and their microenvironments, derived from the cells of patients with colon cancer. “This study helps us understand where tumors start and if treatment drives them towards chemo-resistance and chemo-sensitivity,” said Smita Krishnaswamy, associate professor of genetics and computer science at Yale School of Medicine and co–senior author of the study.
Alliance to set AI standards
Yale Engineering became a founding member of the AI Alliance, an international community of leading researchers, technology developers, and organizational leaders. Launched by IBM and Meta, the alliance aims to advance open, safe, responsible AI that benefits society. “We are excited to join the AI Alliance as a founding partner,” said Jeffrey Brock ’92, dean of the Yale School of Engineering & Applied Science. “Its commitment to innovative and open AI development aligns with our vision at Yale Engineering. This partnership enables us to work with a broad range of university and industry leadership to pursue collaborative research, while formulating policy and standards for safe, explainable, and trustworthy AI.”
Sustainable computing
With a $1.3 million grant jointly funded by the United Kingdom’s Engineering and Physical Sciences Research Council and the United States’s National Science Foundation, Prof. Robert Soulé aims to reduce the energy consumption of computing. Specifically, his project focuses on computer networks, which consume an estimated one-and-a-half times the energy of all data centers, according to some reports. In contrast to other large-scale computer infrastructures, accounting for the carbon emissions of the network is extremely difficult. The project is designed to collect information about the power consumption of network devices, and potentially allow users to make informed decisions that minimize overall power consumption.