Creating a common language
New faculty member Kaiming He discusses AI’s role in lowering barriers between scientific fields and fostering collaboration across scientific disciplines.
Validation technique could help scientists make more accurate forecasts
MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.
Streamlining data collection for improved salmon population management
Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.
User-friendly system can help developers build more efficient simulations and AI models
By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.
MIT engineers help multirobot systems stay in the safety zone
New research could improve the safety of drone shows, warehouse robots, and self-driving cars.
3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
MIT students' works redefine human-AI collaboration
Projects from MIT course 4.043/4.044 (Interaction Intelligence) were presented at NeurIPS, showing how AI transforms creativity, education, and interaction in unexpected ways.
New training approach could help AI agents perform better in uncertain conditions
Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.
A platform to expedite clean energy projects
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
Toward video generative models of the molecular world
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.
Explained: Generative AI’s environmental impact
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
Algorithms and AI for a better world
Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.
Making the art world more accessible
The startup NALA, which began as an MIT class project, directly matches art buyers with artists.
New computational chemistry techniques accelerate the prediction of molecules and materials
With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.
For healthy hearing, timing matters
Machine-learning models let neuroscientists study the impact of auditory processing on real-world hearing.