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.
Department
Electrical Engineering and Computer Science
New method enables fast, accurate estimates of cardiovascular state to inform blood pressure management
A mathematical method, validated with experimental data, provides a fast, reliable, and minimally invasive way of determining how to treat critical blood pressure changes during surgery or intensive care.
New transistor’s superlative properties could have broad electronics applications
Ultrathin material whose properties “already meet or exceed industry standards” enables superfast switching, extreme durability.
Study across multiple brain regions discerns Alzheimer’s vulnerability and resilience factors
Genomics and lab studies reveal numerous findings, including a key role for Reelin amid neuronal vulnerability, and for choline and antioxidants in sustaining cognition.
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.
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.
License plates of MIT
Custom plates display expressions of scholarship, creativity, and MIT pride among Institute affiliates.
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.
Collaborative effort supports an MIT resilient to the impacts of extreme heat
Increasing severity and duration of heat drives data collection and resiliency planning for the forthcoming Climate Resiliency and Adaptation Roadmap.
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.
Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building
Members of the MIT community, supporters, and guests commemorate the opening of the new college headquarters.
Machine learning and the microscope
PhD student Xinyi Zhang is developing computational tools for analyzing cells in the age of multimodal data.