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.
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Energy
Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano
Startup accelerator program grows to over 30 companies, almost half of them with MIT pedigrees.
Read MoreWorking to advance the nuclear renaissance
Dean Price, assistant professor in the Department of Nuclear Science and Engineering, sees a bright future for nuclear power, and believes AI can help us realize that vision.
Read MoreHow Leaders Can Get Strategic About Energy Costs
Position your organization to withstand shocks—and even capitalize on them.
Read MoreAt MIT, former U.S. ambassador to China Nicholas Burns highlights climate change as an area for diplomatic engagement, while exploring areas including China’s emphasis on STEM education.
Read MoreNew method could increase LLM training efficiency
By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
Read More3 Questions: How AI could optimize the power grid
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.
Read MoreWorking to eliminate barriers to adopting nuclear energy
Nuclear waste continues to be a bottleneck in the widespread use of nuclear energy, so doctoral student Dauren Sarsenbayev is developing models to address the problem.
Read MoreNew materials could boost the energy efficiency of microelectronics
By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.
Read MoreHelping power-system planners prepare for an unknown future
Macro, 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.
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