MIT scientists developed a training method to generate models that simulate the effects of human activities on climate much more quickly than other approaches.
With up to $53 million from ARPA-H, the researchers will use AI to generate safer herbicides that reduce dependence on imports and improve the security of the U.S. food supply.
Read MoreBy learning how matter moves, the WorldParticle system could assist with developing soft robots, medicines, and more.
Read MoreThe new approach, known as FLEX, could lead to more intuitive, interactive household and assistive robots.
Read MoreA machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Read MoreA new system identifies and corrects unreliable object descriptions stored in a robot’s memory, improving the robot’s ability to interact with its environment.
Read MoreFrom a nuclear revival to qubits, the MIT Energy Initiative’s annual research conference tracked deployment of today’s technologies to discovery of tomorrow’s breakthroughs.
Read MoreMIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
Read MoreAssistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Read More“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
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