MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.
The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
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.
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.
