Making climate models relevant for local decision-makers
A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.
A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.
DenseAV, developed at MIT, learns to parse and understand the meaning of language just by watching videos of people talking, with potential applications in multimedia search, language learning, and robotics.
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
The startup Augmental allows users to operate phones and other devices using their tongue, mouth, and head gestures.
With generative AI models, researchers combined robotics data from different sources to help robots learn better.
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
“Alchemist” system adjusts the material attributes of specific objects within images to potentially modify video game models to fit different environments, fine-tune VFX, and diversify robotic training.
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.