Merging 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.
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Environment
AI 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.
Read MoreStreamlining data collection for improved salmon population management
Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.
Read MoreExplained: Generative AI’s environmental impact
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
Read MoreMIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16
First organized MIT delegation highlights the Institute’s growing commitment to addressing climate change by showcasing research on biodiversity conservation, AI, and the role of local communities.
Read MoreNew AI tool generates realistic satellite images of future flooding
The method could help communities visualize and prepare for approaching storms.
Read MoreAdvancing urban tree monitoring with AI-powered digital twins
The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.
Read More“They can see themselves shaping the world they live in”
Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.
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