Energy storage
Energy storage

Energy storage

Algorithms Alternative energy Artificial Intelligence Batteries Climate change Computer science and technology Electrical engineering and computer science (EECS) Energy Energy storage Faculty Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Pollution Research School of Engineering Sustainability Sustainable computing

3 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.

Artificial Intelligence Automobiles Batteries Cleaner industry Electric vehicles Energy Energy storage Industry MIT Energy Initiative Special events and guest speakers Supply chains Transportation

Driving American battery innovation forward

At MITEI’s Fall Colloquium, General Motors’ battery development expert emphasized how affordability, accessibility, and commercialization can position the US as a leader in battery tech.

Artificial Intelligence Chemical engineering Cleaner industry Climate Electric grid Electric vehicles Energy Energy efficiency Energy storage Infrastructure machine learning Mechanical engineering MIT Energy Initiative Renewable energy Research School of Engineering Sustainability Sustainable computing Weather modeling

How artificial intelligence can help achieve a clean energy future

AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.

Artificial Intelligence Batteries Carbon dioxide chemistry Cleaner industry Climate change Collaboration DMSE Electric grid Energy Energy storage Faculty Government Infrastructure Innovation and Entrepreneurship (I&E) Mechanical engineering MIT Energy Initiative Policy Renewable energy School of Engineering School of Science Special events and guest speakers Startups Students Sustainability The Engine Transportation

MIT Energy Initiative conference spotlights research priorities amidst a changing energy landscape

Industry leaders agree collaboration is key to advancing critical technologies.

Algorithms Artificial Intelligence Climate change Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Emissions Energy Energy storage Infrastructure Lincoln Laboratory machine learning MIT Energy Initiative MIT Schwarzman College of Computing MIT Sloan School of Management Research School of Engineering Supercomputing Sustainable computing

Responding to the climate impact of generative AI

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.

Artificial Intelligence Chemical engineering Cleaner industry Climate change Department of Energy (DoE) DMSE Energy Energy storage Faculty Fusion Government MIT Energy Initiative Nuclear power and reactors Policy Renewable energy School of Architecture and Planning School of Engineering Special events and guest speakers Startups Students Sustainability Urban studies and planning

Ensuring a durable transition

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