A “scientific sandbox” lets researchers explore the evolution of vision systems
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.
The speech-to-reality system combines 3D generative AI and robotic assembly to create objects on demand.
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.
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.