The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
machine learning
Robots that spare warehouse workers the heavy lifting
Founded by MIT alumni, the Pickle Robot Company has developed machines that can autonomously load and unload trucks inside warehouses and logistic centers.
Read MoreA smarter way for large language models to think about hard problems
This new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.
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MIT engineers design an aerial microrobot that can fly as fast as a bumblebee
With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.
Read MoreNew control system teaches soft robots the art of staying safe
MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.
Read MoreMIT Sea Grant students explore the intersection of technology and offshore aquaculture in Norway
AquaCulture Shock program, in collaboration with MIT-Scandinavia MISTI, offers international internships for AI and autonomy in aquaculture
Read MoreResearchers discover a shortcoming that makes LLMs less reliable
Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.
Read MoreMIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
Read MoreHow artificial intelligence can help achieve a clean energy future
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
Read MoreThe cost of thinking
MIT neuroscientists find a surprising parallel in the ways humans and new AI models solve complex problems.
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