Laboratory for Information and Decision Systems (LIDS)

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 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 IntelligenceCybersecurityMachine Learning

MIT scientists investigate memorization risk in the age of clinical AI

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

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Artificial IntelligenceMachine Learning

The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.

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Artificial IntelligenceMachine Learning

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.

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Artificial IntelligenceMachine LearningRobotics

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.

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Artificial IntelligenceMachine LearningRobotics

New 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.

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Artificial IntelligenceMachine Learning

Researchers 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.

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Artificial IntelligenceMachine Learning

Charting the future of AI, from safer answers to faster thinking

MIT PhD students who interned with the MIT-IBM Watson AI Lab Summer Program are pushing AI tools to be more flexible, efficient, and grounded in truth.

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Artificial IntelligenceAutonomous VehiclesMachine LearningRobotics

Teaching robots to map large environments

A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

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