Connecting research to policy on Capitol Hill
MIT students and postdocs discussed science funding and research with policymakers in Washington during the MIT Science Policy Initiative’s annual Congressional Visit Days.
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Environment
A faster way to estimate AI power consumption
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
Read MoreAugmenting citizen science with computer vision for fish monitoring
MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.
Read MoreHow Joseph Paradiso’s sensing innovations bridge the arts, medicine, and ecology
From early motion-sensing platforms to environmental monitoring, the professor and head of the Program in Media Arts and Sciences has turned decades of cross-disciplinary research into real-world impact.
Read MoreFor Multinational Companies, Localization Matters More Than Ever
Three keys to success in a fractured global business environment.
Read MoreMIT Sea Grant students explore the intersection of technology and offshore aquaculture in Norway
AquaCulture Shock program, in collaboration with MIT-Scandinavia MISTI, offers international internships for AI and autonomy in aquaculture
Read More3 Questions: How AI is helping us monitor and support vulnerable ecosystems
MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.
Read MoreSchool of Architecture and Planning welcomes new faculty for 2025
Four new professors join the Department of Architecture and MIT Media Lab.
Read MoreMerging AI and underwater photography to reveal hidden ocean worlds
The LOBSTgER research initiative at MIT Sea Grant explores how generative AI can expand scientific storytelling by building on field-based photographic data.
Read MoreAI stirs up the recipe for concrete in MIT study
With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.
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