Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
Tools build on years of research at Lincoln Laboratory to develop a rapid brain health screening capability and may also be applicable to civilian settings such as sporting events and medical offices.
New test could help determine if AI systems that make accurate predictions in one area can understand it well enough to apply that ability to a different area.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.