When #AI operates in the physical world, “pretty close” may not cut it. LIDS researchers developed HardFlow, a method that helps pretrained generative AI satisfy hard constraints while improving solution quality — without retraining. bit.ly/4xydxBN
🗳️ What is AI telling voters about elections?
MIT’s new LLM Election Observatory, from LIDS PI @charapod and collaborators, is tracking how major AI models answer questions about candidates and issues — and how those answers evolve throughout the midterms.
bit.ly/4dwYpx7
When it comes to AI-assisted medical diagnosis, one size may not fit all.
A new study from @MarzyehGhassemi and team found that AI explanations affect clinicians and non-experts differently—highlighting the need to design AI support around user expertise.
bit.ly/4gv0jR7
Congratulations to LIDS PI Sasha Rakhlin, named director of MIT’s Statistics and Data Science Center! @rakhlin aims to strengthen connections across MIT and advance the rigorous foundations of data science and #AI. MIT News: bit.ly/4gcm08m
Inspired by pinecones, tree bark, and seedpods, MIT researchers developed a mathematical framework for designing manufacturable, adaptive materials that mimic complex behaviors found in nature — with applications from robotics to aerospace. bit.ly/4zr0VOK
