Energy

Artificial IntelligenceEnergyMachine Learning

Puzzling out climate change

Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.

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Artificial IntelligenceEnergy

The 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.

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Artificial IntelligenceEnergyMachine Learning

Explained: 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.

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Artificial IntelligenceEnergyMachine Learning

Q&A: The climate impact of generative AI

As the use of generative AI continues to grow, Lincoln Laboratory’s Vijay Gadepally describes what researchers and consumers do to help mitigate its environmental impact.

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Artificial IntelligenceEnergyMachine Learning

Unlocking the hidden power of boiling — for energy, space, and beyond

Associate Professor Matteo Bucci’s research sheds new light on an ancient process, to improve the efficiency of heat transfer in many industrial systems.

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Artificial IntelligenceEnergy

Ensuring a durable transition

Progress on the energy transition depends on collective action benefiting all stakeholders, agreed participants in MITEI’s annual research conference.

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Artificial IntelligenceEnergyMachine Learning

Nanoscale transistors could enable more efficient electronics

Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.

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CultureEconomyEnergy

How 2024 Elections Will Shape Tech Investment

The 2024 presidential election’s economic battle between Trump and Harris highlights divergent approaches to America’s business future. Trump’s focus on tax cuts and deregulation benefits large corporations but risks talent shortages, while Harris emphasizes progressive taxation, workforce development, and innovation in clean energy, potentially fostering sustainable growth and supporting startups.

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Artificial IntelligenceEnergyMachine Learning

Proton-conducting materials could enable new green energy technologies

Analysis and materials identified by MIT engineers could lead to more energy-efficient fuel cells, electrolyzers, batteries, or computing devices.

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Artificial IntelligenceEnergyMachine Learning

AI method radically speeds predictions of materials’ thermal properties

The approach could help engineers design more efficient energy-conversion systems and faster microelectronic devices, reducing waste heat.

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