Research
Research

Method prevents an AI model from being overconfident about wrong answers

More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.

Study: When allocating scarce resources with AI, randomization can improve fairness

Introducing structured randomization into decisions based on machine-learning model predictions can address inherent uncertainties while maintaining efficiency.

MIT researchers advance automated interpretability in AI models

MAIA is a multimodal agent that can iteratively design experiments to better understand various components of AI systems.

Proton-conducting materials could enable new green energy technologies

Analysis and materials identified by MIT engineers could lead to more energy-efficient fuel cells, electrolyzers, batteries, or computing devices.

Large language models don’t behave like people, even though we may expect them to

A new study shows someone’s beliefs about an LLM play a significant role in the model’s performance and are important for how it is deployed.

AI model identifies certain breast tumor stages likely to progress to invasive cancer

The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.

Machine learning unlocks secrets to advanced alloys

An MIT team uses computer models to measure atomic patterns in metals, essential for designing custom materials for use in aerospace, biomedicine, electronics, and more.

Creating and verifying stable AI-controlled systems in a rigorous and flexible way

Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.

AI method radically speeds predictions of materials’ thermal properties

The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.

How to assess a general-purpose AI model’s reliability before it’s deployed

A new technique enables users to compare several large models and choose the one that works best for their task.