A 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.
This new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.
With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.
Whether they walk on two, four, or six legs, animals maintain stability by monitoring their body position and correcting errors with every step.
Macro, a modeling tool developed by the MIT Energy Initiative, enables energy-system planners to explore options for developing infrastructure to support decarbonized, reliable, and low-cost power grids.
MIT engineers show they can accurately measure blood glucose by shining near-infrared light on the skin.
Preliminary studies find derivatives of the compound, known as verticillin A, can kill some types of glioma cells.
The Institute will commit up to $1 million in new funding to increase supply of UROPs.
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.
Wedge-shaped vortex generators reduce drag in ship hulls, which could advance decarbonization for the shipping industry.
The new design from MIT engineers could pump up many biohybrid builds.
Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
X-ray observations reveal surprising features of the dying star’s most energetic environment.
MIT neuroscientists find a surprising parallel in the ways humans and new AI models solve complex problems.