MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

The consortium will bring researchers and industry together to focus on impact.

By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.

Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.

Inspired by the mechanics of the human vocal tract, a new AI model can produce and understand vocal imitations of everyday sounds. The method could help build new sonic interfaces for entertainment and education.

The Thermochromorph printmaking technique developed by CSAIL researchers allows images to transition into each other through changes in temperature.

Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.

Biodiversity researchers tested vision systems on how well they could retrieve relevant nature images. More advanced models performed well on simple queries but struggled with more research-specific prompts.

With models like AlphaFold3 limited to academic research, the team built an equivalent alternative, to encourage innovation more broadly.

Researchers at MIT, NYU, and UCLA develop an approach to help evaluate whether large language models like GPT-4 are equitable enough to be clinically viable for mental health support.