Sustainability
Sustainability

Sustainability

Algorithms Artificial Intelligence Climate Computer modeling IDSS machine learning Mechanical engineering MIT Schwarzman College of Computing Natural disasters Research School of Engineering Sustainability Weather

Generating scenarios for extreme events, without extreme data

A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.

Agriculture Artificial Intelligence chemistry Cleaner industry Computer modeling DMSE Emissions Food Industry machine learning Materials science and engineering Nuclear science and engineering Pollution Research School of Engineering School of Science Sustainability

Paving the way for greener ammonia production

New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Electronics machine learning MIT Schwarzman College of Computing Research School of Engineering Software Sustainability

Improving the speed and energy-efficiency of AI agents

A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.

Artificial Intelligence Computer science and technology Energy Energy efficiency Energy storage Innovation and Entrepreneurship (I&E) Nuclear science and engineering School of Engineering Startups Sustainability Sustainable computing Technology and society Water

Startup’s nuclear-inspired cooling system could make data centers more sustainable

Founded by two researchers from MIT, Ferveret reduces the amount of energy and water required to cool the chips that power AI.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Energy Environment machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering Sustainability Sustainable computing Technology and society

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.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Electronics machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability

Helping data centers deliver higher performance with less hardware

Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.

Artificial Intelligence Computer modeling Energy Faculty machine learning Nuclear power and reactors Nuclear science and engineering Profile Renewable energy School of Engineering Sustainability

Working 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.

3-D printing Additive manufacturing Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) machine learning Maker movement Mechanical engineering MIT Schwarzman College of Computing Research School of Engineering Sustainability

Preview tool helps makers visualize 3D-printed objects

By quickly generating aesthetically accurate previews of fabricated objects, the VisiPrint system could make prototyping faster and less wasteful.

Algorithms Artificial Intelligence Cities Civil and environmental engineering Climate change Computer modeling Computer science and technology Electrical engineering and computer science (EECS) Emissions IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Energy Initiative MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability Transportation

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.

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.