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.
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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.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.
A new technique enables users to compare several large models and choose the one that works best for their task.
Members of the MIT community, supporters, and guests commemorate the opening of the new college headquarters.
New CSAIL research highlights how LLMs excel in familiar scenarios but struggle in novel ones, questioning their true reasoning abilities versus reliance on memorization.
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
The challenge asked teams to develop AI algorithms to track and predict satellites’ patterns of life in orbit using passively collected data
This new tool offers an easier way for people to analyze complex tabular data.
MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient. Its acquisition by Databricks broadened that mission.