A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.
MIT students and postdocs discussed science funding and research with policymakers in Washington during the MIT Science Policy Initiative’s annual Congressional Visit Days.
Read MoreStrahinja Janjusevic brings an international perspective and US Naval Academy education to his graduate research in the MIT Technology and Policy Program.
Read MoreProject AI Evidence will connect governments, tech companies, and nonprofits with world-class economists at MIT and across J-PAL’s global network to evaluate and improve AI solutions.
Read MoreHe joins Nikos Trichakis in guiding the cross-cutting initiative of the MIT Schwarzman College of Computing.
Read MoreMacro, a modeling tool developed by the MIT Energy Initiative, enables energy-system planners to explore options for developing infrastructure to support decarbonized, reliable, and low-cost power grids.
Read MoreMIT faculty and MITEI member company experts address power demand from data centers.
Read MoreAssistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.
Read MoreThe Initiative for New Manufacturing is convening experts across the Institute to drive a transformation of production across the U.S. and the world.
Read MoreMIT Advanced Vehicle Technology Consortium marks a decade of developing data that improve understanding of how drivers use and respond to increasingly sophisticated automotive features.
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