MIT researchers develop AI tool to improve flu vaccine strain selection
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
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.
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.
MIT engineers used a machine-learning model to design nanoparticles that can deliver RNA to cells more efficiently.
The team used two different AI approaches to design novel antibiotics, including one that showed promise against MRSA.
As large language models increasingly dominate our everyday lives, new systems for checking their reliability are more important than ever.
The Initiative for New Manufacturing is convening experts across the Institute to drive a transformation of production across the U.S. and the world.
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Four new professors join the Department of Architecture and MIT Media Lab.
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
This new approach could lead to enhanced AI models for drug and materials discovery.