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- Explained: Generative AI’s environmental impact - MIT News
Plus, generative AI models have an especially short shelf-life, driven by rising demand for new AI applications Companies release new models every few weeks, so the energy used to train prior versions goes to waste, Bashir adds New models often consume more energy for training, since they usually have more parameters than their predecessors
- Using liquid air for grid-scale energy storage - MIT News
The model then draws on state-of-the-art pricing data that’s released every year by the National Renewable Energy Laboratory (NREL) and is widely used by energy modelers worldwide The NREL dataset forecasts prices, construction and retirement of specific types of electricity generation and storage facilities, and more, assuming eight
- A new approach could fractionate crude oil using much less energy
“Roughly 1 percent of global energy use goes into separating crude oil into gasoline, diesel, and heating oil,” writes Aamir Khollam for Interesting Engineering This new membrane “excelled in lab tests…[and] effectively separated real industrial oil samples containing naphtha, kerosene, and diesel ”
- Energy | MIT News | Massachusetts Institute of Technology
A new approach could fractionate crude oil using much less energy MIT researchers’ new membrane separates different types of fuel based on their molecular size, eliminating the need for energy-intensive crude oil distillation May 22, 2025 Read full story →
- A nonflammable battery to power a safer, decarbonized future
Now Alsym Energy has developed a nonflammable, nontoxic alternative to lithium-ion batteries to help renewables like wind and solar bridge the gap in a broader range of sectors The company’s electrodes use relatively stable, abundant materials, and its electrolyte is primarily water with some nontoxic add-ons
- Photonic processor could enable ultrafast AI computations with extreme . . .
Researchers developed a fully integrated photonic processor that can perform all the key computations of a deep neural network on a photonic chip, using light This advance could improve the speed and energy-efficiency of running intensive deep learning models for applications like lidar, astronomical research, and navigation
- Engineers develop an efficient process to make fuel from carbon dioxide
“The MIT process gets closer to an ambitious dream: turning captured CO2 into a feedstock for clean fuel that replaces conventional batteries and stores electricity for months or years,” writes Fialka “That could fill gaps in the nation's power grids as they transition from fossil fuels to intermittent solar and wind energy ”
- Confronting the AI energy conundrum - MIT News
“The energy demands of AI are a significant challenge, but we also have an opportunity to harness these vast computational capabilities to contribute to climate change solutions,” said Evelyn Wang, MIT vice president for energy and climate and the former director at the Advanced Research Projects Agency-Energy (ARPA-E) at the U S
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