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.
Research
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.
Reasoning skills of large language models are often overestimated
New CSAIL research highlights how LLMs excel in familiar scenarios but struggle in novel ones, questioning their true reasoning abilities versus reliance on memorization.
When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
MIT researchers introduce generative AI for databases
This new tool offers an easier way for people to analyze complex tabular data.
Researchers leverage shadows to model 3D scenes, including objects blocked from view
This technique could lead to safer autonomous vehicles, more efficient AR/VR headsets, or faster warehouse robots.
Understanding the visual knowledge of language models
LLMs trained primarily on text can generate complex visual concepts through code with self-correction. Researchers used these illustrations to train an image-free computer vision system to recognize real photos.