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.
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Cleaner industry
At the 2025 MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
Read MoreAgreement between MIT Microsystems Technology Laboratories and GlobalFoundries aims to deliver power efficiencies for data centers and ultra-low power consumption for intelligent devices at the edge.
Read MorePuzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
Read MoreA platform to expedite clean energy projects
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
Read MoreThe multifaceted challenge of powering AI
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
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 MoreEnsuring a durable transition
Progress on the energy transition depends on collective action benefiting all stakeholders, agreed participants in MITEI’s annual research conference.
Read MoreMIT ARCLab announces winners of inaugural Prize for AI Innovation in Space
The challenge asked teams to develop AI algorithms to track and predict satellites’ patterns of life in orbit using passively collected data
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