Research

Artificial Intelligence

“This is science!” – MIT president talks about the importance of America’s research enterprise on GBH’s Boston Public Radio

MIT faculty join The Curiosity Desk to discuss football, math, Olympic figure skating, AI and the quest to cure ovarian cancer.

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Artificial IntelligenceMachine Learning

Helping AI agents search to get the best results out of large language models

EnCompass executes AI agent programs by backtracking and making multiple attempts, finding the best set of outputs generated by an LLM. It could help coders work with AI agents more efficiently.

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Artificial Intelligence

SMART launches new Wearable Imaging for Transforming Elderly Care research group

WITEC is working to develop the first wearable ultrasound imaging system to monitor chronic conditions in real-time, with the goal of enabling earlier detection and timely intervention.

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Artificial IntelligenceMachine Learning

How generative AI can help scientists synthesize complex materials

MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.

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Artificial IntelligenceMachine Learning

Why it’s critical to move beyond overly aggregated machine-learning metrics

New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.

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Artificial Intelligence

At MIT, a continued commitment to understanding intelligence

With support from the Siegel Family Endowment, the newly renamed MIT Siegel Family Quest for Intelligence investigates how brains produce intelligence and how it can be replicated to solve problems.

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Artificial IntelligenceEnergyMachine Learning

3 Questions: How AI could optimize the power grid

While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.

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Artificial IntelligenceMachine Learning

Decoding the Arctic to predict winter weather

With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.

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