When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
MIT researchers introduce generative AI for databases
This new tool offers an easier way for people to analyze complex tabular data.
Researchers leverage shadows to model 3D scenes, including objects blocked from view
This technique could lead to safer autonomous vehicles, more efficient AR/VR headsets, or faster warehouse robots.
A smarter way to streamline drug discovery
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
Technique improves the reasoning capabilities of large language models
Combining natural language and programming, the method enables LLMs to solve numerical, analytical, and language-based tasks transparently.
Researchers use large language models to help robots navigate
The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.
A technique for more effective multipurpose robots
With generative AI models, researchers combined robotics data from different sources to help robots learn better.
Looking for a specific action in a video? This AI-based method can find it for you
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
Scientists use generative AI to answer complex questions in physics
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
A better way to control shape-shifting soft robots
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.