Computer Science and Artificial Intelligence Laboratory (CSAIL)

Artificial IntelligenceMachine Learning

The philosophical puzzle of rational artificial intelligence

As AI technology advances, a new interdisciplinary course seeks to equip students with foundational critical thinking skills in computing.

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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 IntelligenceMachine Learning

Generative AI tool helps 3D print personal items that sustain daily use

“MechStyle” allows users to personalize 3D models, while ensuring they’re physically viable after fabrication, producing unique personal items and assistive technology.

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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

Guided learning lets “untrainable” neural networks realize their potential

CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.

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Artificial IntelligenceMachine Learning

A new way to increase the capabilities of large language models

MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.

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Artificial IntelligenceMachine Learning

Enabling small language models to solve complex reasoning tasks

The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.

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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 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

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.

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