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      in Environment

      Simpler models can outperform deep learning at climate prediction

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      Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better.The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models.Their analysis also reveals that a benchmarking technique commonly used to evaluate machine-learning techniques for climate predictions can be distorted by natural variations in the data, like fluctuations in weather patterns. This could lead someone to believe a deep-learning model makes more accurate predictions when that is not the case.The researchers developed a more robust way of evaluating these techniques, which shows that, while simple models are more accurate when estimating regional surface temperatures, deep-learning approaches can be the best choice for estimating local rainfall.They used these results to enhance a simulation tool known as a climate emulator, which can rapidly simulate the effect of human activities onto a future climate.The researchers see their work as a “cautionary tale” about the risk of deploying large AI models for climate science. While deep-learning models have shown incredible success in domains such as natural language, climate science contains a proven set of physical laws and approximations, and the challenge becomes how to incorporate those into AI models.“We are trying to develop models that are going to be useful and relevant for the kinds of things that decision-makers need going forward when making climate policy choices. While it might be attractive to use the latest, big-picture machine-learning model on a climate problem, what this study shows is that stepping back and really thinking about the problem fundamentals is important and useful,” says study senior author Noelle Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and the Department of Earth, Atmospheric and Planetary Sciences (EAPS).Selin’s co-authors are lead author Björn Lütjens, a former EAPS postdoc who is now a research scientist at IBM Research; senior author Raffaele Ferrari, the Cecil and Ida Green Professor of Oceanography in EAPS and co-director of the Lorenz Center; and Duncan Watson-Parris, assistant professor at the University of California at San Diego. Selin and Ferrari are also co-principal investigators of the Bringing Computation to the Climate Challenge project, out of which this research emerged. The paper appears today in the Journal of Advances in Modeling Earth Systems.Comparing emulatorsBecause the Earth’s climate is so complex, running a state-of-the-art climate model to predict how pollution levels will impact environmental factors like temperature can take weeks on the world’s most powerful supercomputers.Scientists often create climate emulators, simpler approximations of a state-of-the art climate model, which are faster and more accessible. A policymaker could use a climate emulator to see how alternative assumptions on greenhouse gas emissions would affect future temperatures, helping them develop regulations.But an emulator isn’t very useful if it makes inaccurate predictions about the local impacts of climate change. While deep learning has become increasingly popular for emulation, few studies have explored whether these models perform better than tried-and-true approaches.The MIT researchers performed such a study. They compared a traditional technique called linear pattern scaling (LPS) with a deep-learning model using a common benchmark dataset for evaluating climate emulators.Their results showed that LPS outperformed deep-learning models on predicting nearly all parameters they tested, including temperature and precipitation.“Large AI methods are very appealing to scientists, but they rarely solve a completely new problem, so implementing an existing solution first is necessary to find out whether the complex machine-learning approach actually improves upon it,” says Lütjens.Some initial results seemed to fly in the face of the researchers’ domain knowledge. The powerful deep-learning model should have been more accurate when making predictions about precipitation, since those data don’t follow a linear pattern.They found that the high amount of natural variability in climate model runs can cause the deep learning model to perform poorly on unpredictable long-term oscillations, like El Niño/La Niña. This skews the benchmarking scores in favor of LPS, which averages out those oscillations.Constructing a new evaluationFrom there, the researchers constructed a new evaluation with more data that address natural climate variability. With this new evaluation, the deep-learning model performed slightly better than LPS for local precipitation, but LPS was still more accurate for temperature predictions.“It is important to use the modeling tool that is right for the problem, but in order to do that you also have to set up the problem the right way in the first place,” Selin says.Based on these results, the researchers incorporated LPS into a climate emulation platform to predict local temperature changes in different emission scenarios.“We are not advocating that LPS should always be the goal. It still has limitations. For instance, LPS doesn’t predict variability or extreme weather events,” Ferrari adds.Rather, they hope their results emphasize the need to develop better benchmarking techniques, which could provide a fuller picture of which climate emulation technique is best suited for a particular situation.“With an improved climate emulation benchmark, we could use more complex machine-learning methods to explore problems that are currently very hard to address, like the impacts of aerosols or estimations of extreme precipitation,” Lütjens says.Ultimately, more accurate benchmarking techniques will help ensure policymakers are making decisions based on the best available information.The researchers hope others build on their analysis, perhaps by studying additional improvements to climate emulation methods and benchmarks. Such research could explore impact-oriented metrics like drought indicators and wildfire risks, or new variables like regional wind speeds.This research is funded, in part, by Schmidt Sciences, LLC, and is part of the MIT Climate Grand Challenges team for “Bringing Computation to the Climate Challenge.” More

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      Eco-driving measures could significantly reduce vehicle emissions

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      Any motorist who has ever waited through multiple cycles for a traffic light to turn green knows how annoying signalized intersections can be. But sitting at intersections isn’t just a drag on drivers’ patience — unproductive vehicle idling could contribute as much as 15 percent of the carbon dioxide emissions from U.S. land transportation.A large-scale modeling study led by MIT researchers reveals that eco-driving measures, which can involve dynamically adjusting vehicle speeds to reduce stopping and excessive acceleration, could significantly reduce those CO2 emissions.Using a powerful artificial intelligence method called deep reinforcement learning, the researchers conducted an in-depth impact assessment of the factors affecting vehicle emissions in three major U.S. cities.Their analysis indicates that fully adopting eco-driving measures could cut annual city-wide intersection carbon emissions by 11 to 22 percent, without slowing traffic throughput or affecting vehicle and traffic safety.Even if only 10 percent of vehicles on the road employ eco-driving, it would result in 25 to 50 percent of the total reduction in CO2 emissions, the researchers found.In addition, dynamically optimizing speed limits at about 20 percent of intersections provides 70 percent of the total emission benefits. This indicates that eco-driving measures could be implemented gradually while still having measurable, positive impacts on mitigating climate change and improving public health.

      An animated GIF compares what 20% eco-driving adoption looks like to 100% eco-driving adoption.Image: Courtesy of the researchers

      “Vehicle-based control strategies like eco-driving can move the needle on climate change reduction. We’ve shown here that modern machine-learning tools, like deep reinforcement learning, can accelerate the kinds of analysis that support sociotechnical decision making. This is just the tip of the iceberg,” says senior author Cathy Wu, the Class of 1954 Career Development Associate Professor in Civil and Environmental Engineering (CEE) and the Institute for Data, Systems, and Society (IDSS) at MIT, and a member of the Laboratory for Information and Decision Systems (LIDS).She is joined on the paper by lead author Vindula Jayawardana, an MIT graduate student; as well as MIT graduate students Ao Qu, Cameron Hickert, and Edgar Sanchez; MIT undergraduate Catherine Tang; Baptiste Freydt, a graduate student at ETH Zurich; and Mark Taylor and Blaine Leonard of the Utah Department of Transportation. The research appears in Transportation Research Part C: Emerging Technologies.A multi-part modeling studyTraffic control measures typically call to mind fixed infrastructure, like stop signs and traffic signals. But as vehicles become more technologically advanced, it presents an opportunity for eco-driving, which is a catch-all term for vehicle-based traffic control measures like the use of dynamic speeds to reduce energy consumption.In the near term, eco-driving could involve speed guidance in the form of vehicle dashboards or smartphone apps. In the longer term, eco-driving could involve intelligent speed commands that directly control the acceleration of semi-autonomous and fully autonomous vehicles through vehicle-to-infrastructure communication systems.“Most prior work has focused on how to implement eco-driving. We shifted the frame to consider the question of should we implement eco-driving. If we were to deploy this technology at scale, would it make a difference?” Wu says.To answer that question, the researchers embarked on a multifaceted modeling study that would take the better part of four years to complete.They began by identifying 33 factors that influence vehicle emissions, including temperature, road grade, intersection topology, age of the vehicle, traffic demand, vehicle types, driver behavior, traffic signal timing, road geometry, etc.“One of the biggest challenges was making sure we were diligent and didn’t leave out any major factors,” Wu says.Then they used data from OpenStreetMap, U.S. geological surveys, and other sources to create digital replicas of more than 6,000 signalized intersections in three cities — Atlanta, San Francisco, and Los Angeles — and simulated more than a million traffic scenarios.The researchers used deep reinforcement learning to optimize each scenario for eco-driving to achieve the maximum emissions benefits.Reinforcement learning optimizes the vehicles’ driving behavior through trial-and-error interactions with a high-fidelity traffic simulator, rewarding vehicle behaviors that are more energy-efficient while penalizing those that are not.The researchers cast the problem as a decentralized cooperative multi-agent control problem, where the vehicles cooperate to achieve overall energy efficiency, even among non-participating vehicles, and they act in a decentralized manner, avoiding the need for costly communication between vehicles.However, training vehicle behaviors that generalize across diverse intersection traffic scenarios was a major challenge. The researchers observed that some scenarios are more similar to one another than others, such as scenarios with the same number of lanes or the same number of traffic signal phases.As such, the researchers trained separate reinforcement learning models for different clusters of traffic scenarios, yielding better emission benefits overall.But even with the help of AI, analyzing citywide traffic at the network level would be so computationally intensive it could take another decade to unravel, Wu says.Instead, they broke the problem down and solved each eco-driving scenario at the individual intersection level.“We carefully constrained the impact of eco-driving control at each intersection on neighboring intersections. In this way, we dramatically simplified the problem, which enabled us to perform this analysis at scale, without introducing unknown network effects,” she says.Significant emissions benefitsWhen they analyzed the results, the researchers found that full adoption of eco-driving could result in intersection emissions reductions of between 11 and 22 percent.These benefits differ depending on the layout of a city’s streets. A denser city like San Francisco has less room to implement eco-driving between intersections, offering a possible explanation for reduced emission savings, while Atlanta could see greater benefits given its higher speed limits.Even if only 10 percent of vehicles employ eco-driving, a city could still realize 25 to 50 percent of the total emissions benefit because of car-following dynamics: Non-eco-driving vehicles would follow controlled eco-driving vehicles as they optimize speed to pass smoothly through intersections, reducing their carbon emissions as well.In some cases, eco-driving could also increase vehicle throughput by minimizing emissions. However, Wu cautions that increasing throughput could result in more drivers taking to the roads, reducing emissions benefits.And while their analysis of widely used safety metrics known as surrogate safety measures, such as time to collision, suggest that eco-driving is as safe as human driving, it could cause unexpected behavior in human drivers. More research is needed to fully understand potential safety impacts, Wu says.Their results also show that eco-driving could provide even greater benefits when combined with alternative transportation decarbonization solutions. For instance, 20 percent eco-driving adoption in San Francisco would cut emission levels by 7 percent, but when combined with the projected adoption of hybrid and electric vehicles, it would cut emissions by 17 percent.“This is a first attempt to systematically quantify network-wide environmental benefits of eco-driving. This is a great research effort that will serve as a key reference for others to build on in the assessment of eco-driving systems,” says Hesham Rakha, the Samuel L. Pritchard Professor of Engineering at Virginia Tech, who was not involved with this research.And while the researchers focus on carbon emissions, the benefits are highly correlated with improvements in fuel consumption, energy use, and air quality.“This is almost a free intervention. We already have smartphones in our cars, and we are rapidly adopting cars with more advanced automation features. For something to scale quickly in practice, it must be relatively simple to implement and shovel-ready. Eco-driving fits that bill,” Wu says.This work is funded, in part, by Amazon and the Utah Department of Transportation. More

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      in Energy

      MIT-Africa launches new collaboration with Angola

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      The MIT Center for International Studies announced the launch of a new pilot initiative with Angola, to be implemented through its MIT-Africa Program.The new initiative marks a significant collaboration between MIT-Africa, Sonangol (Angola’s national energy company), and the Instituto Superior Politécnico de Tecnologias e Ciências (ISPTEC). The collaboration was formalized at a signing ceremony on MIT’s campus in June with key stakeholders from all three institutions present, including Diamantino Pedro Azevedo, the Angolan minister of mineral resources, petroleum, and gas, and Sonangol CEO Gaspar Martins.“This partnership marks a pivotal step in the Angolan government’s commitment to leveraging knowledge as the cornerstone of the country’s economic transformation,” says Azevedo. “By connecting the oil and gas sector with science, innovation, and world-class training, we are equipping future generations to lead Angola into a more technological, sustainable, and globally competitive era.”The sentiment is shared by the MIT-Africa Program leaders. “This initiative reflects MIT’s deep commitment to fostering meaningful, long-term relationships across the African continent,” says Mai Hassan, faculty director of the MIT-Africa Program. “It supports our mission of advancing knowledge and educating students in ways that are globally informed, and it provides a platform for mutual learning. By working with Angolan partners, we gain new perspectives and opportunities for innovation that benefit both MIT and our collaborators.”In addition to its new collaboration with MIT-Africa, Sonangol has joined MIT’s Industrial Liaison Program (ILP), breaking new ground as its first corporate member based in sub-Saharan Africa. ILP enables companies worldwide to harness MIT resources to address current challenges and to anticipate future needs. As an ILP member, Sonangol seeks to facilitate collaboration in key sectors such as natural resources and mining, energy, construction, and infrastructure.The MIT-Africa Program manages a portfolio of research, teaching, and learning initiatives that emphasize two-way value — offering impactful experiences to MIT students and faculty while collaborating closely with institutions and communities across Africa. The new Angola collaboration is aligned with this ethos, and will launch with two core activities during the upcoming academic year:Global Classroom: An MIT course on geo-spatial technologies for environmental monitoring, taught by an MIT faculty member, will be brought directly to the ISPTEC campus, offering Angolan students and MIT participants a collaborative, in-country learning experience.Global Teaching Labs: MIT students will travel to ISPTEC to teach science, technology, engineering, arts, and mathematics subjects on renewable energy technologies, engaging Angolan students through hands-on instruction.“This is not a traditional development project,” says Ari Jacobovits, managing director of MIT-Africa. “This is about building genuine partnerships rooted in academic rigor, innovation, and shared curiosity. The collaboration has been designed from the ground up with our partners at ISPTEC and Sonangol. We’re coming in with a readiness to learn as much as we teach.”The pilot marks an important first step in establishing a long-term collaboration with Angola. By investing in collaborative education and innovation, the new initiative aims to spark novel approaches to global challenges and strengthen academic institutions on both sides.These agreements with MIT-Africa and ILP “not only enhance our innovation and technological capabilities, but also create opportunities for sustainable development and operational excellence,” says Gaspar. “They advance our mission to be a leading force in the African energy sector.”“The vision behind this initiative is bold,” says Hassan. “It’s about co-creating knowledge and building capacity that lasts.” More

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      in Environment

      School of Architecture and Planning welcomes new faculty for 2025

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      Four new faculty members join the School of Architecture and Planning (SA+P) this fall, offering the MIT community creativity, knowledge, and scholarship in multidisciplinary roles.“These individuals add considerable strength and depth to our faculty,” says Hashim Sarkis, dean of the School of Architecture and Planning. “We are excited for the academic vigor they bring to research and teaching.”Karrie G. Karahalios ’94, MEng ’95, SM ’97, PhD ’04 joins the MIT Media Lab as a full professor of media arts and sciences. Karahalios is a pioneer in the exploration of social media and of how people communicate in environments that are increasingly mediated by algorithms that, as she has written, “shape the world around us.” Her work combines computing, systems, artificial intelligence, anthropology, sociology, psychology, game theory, design, and infrastructure studies. Karahalios’ work has received numerous honors including the National Science Foundation CAREER Award, Alfred P. Sloan Research Fellowship, SIGMOD Best Paper Award, and recognition as an ACM Distinguished Member.Pat Pataranutaporn SM ’18, PhD ’20 joins the MIT Media Lab as an assistant professor of media arts and sciences. A visionary technologist, scientist, and designer, Pataranutaporn explores the frontier of human-AI interaction, inventing and investigating AI systems that support human thriving. His research focuses on how personalized AI systems can amplify human cognition, from learning and decision-making to self-development, reflection, and well-being. Pataranutaporn will co-direct the Advancing Humans with AI Program.Mariana Popescu joins the Department of Architecture as an assistant professor. Popescu is a computational architect and structural designer with a strong interest and experience in innovative ways of approaching the fabrication process and use of materials in construction. Her area of expertise is computational and parametric design, with a focus on digital fabrication and sustainable design. Her extensive involvement in projects related to promoting sustainability has led to a multilateral development of skills, which combine the fields of architecture, engineering, computational design, and digital fabrication. Popescu earned her doctorate at ETH Zurich. She was named a “Pioneer” on the MIT Technology Review global list of “35 innovators under 35” in 2019.Holly Samuelson joins the Department of Architecture as an associate professor in the Building Technology Program at MIT, teaching architectural technology courses. Her teaching and research focus on issues of building design that impact human and environmental health. Her current projects harness advanced building simulation to investigate issues of greenhouse gas emissions, heat vulnerability, and indoor environmental quality while considering the future of buildings in a changing electricity grid. Samuelson has co-authored over 40 peer-reviewed papers, winning a best paper award from the journal Energy and Building. As a recognized expert in architectural technology, she has been featured in news outlets including The Washington Post, The Boston Globe, the BBC, and The Wall Street Journal. Samuelson earned her doctor of design from Harvard University Graduate School of Design. More

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      in Environment

      Study shows how a common fertilizer ingredient benefits plants

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      Lanthanides are a class of rare earth elements that in many countries are added to fertilizer as micronutrients to stimulate plant growth. But little is known about how they are absorbed by plants or influence photosynthesis, potentially leaving their benefits untapped.Now, researchers from MIT have shed light on how lanthanides move through and operate within plants. These insights could help farmers optimize their use to grow some of the world’s most popular crops.Published today in the Journal of the American Chemical Society, the study shows that a single nanoscale dose of lanthanides applied to seeds can make some of the world’s most common crops more resilient to UV stress. The researchers also uncovered the chemical processes by which lanthanides interact with the chlorophyll pigments that drive photosynthesis, showing that different lanthanide elements strengthen chlorophyll by replacing the magnesium at its center.“This is a first step to better understand how these elements work in plants, and to provide an example of how they could be better delivered to plants, compared to simply applying them in the soil,” says Associate Professor Benedetto Marelli, who conducted the research with postdoc Giorgio Rizzo. “This is the first example of a thorough study showing the effects of lanthanides on chlorophyll, and their beneficial effects to protect plants from UV stress.”Inside plant connectionsCertain lanthanides are used as contrast agents in MRI and for applications including light-emitting diodes, solar cells, and lasers. Over the last 50 years, lanthanides have become increasingly used in agriculture to enhance crop yields, with China alone applying lanthanide-based fertilizers to nearly 4 million hectares of land each year.“Lanthanides have been considered for a long time to be biologically irrelevant, but that’s changed in agriculture, especially in China,” says Rizzo, the paper’s first author. “But we largely don’t know how lanthanides work to benefit plants — nor do we understand their uptake mechanisms from plant tissues.”Recent studies have shown that low concentrations of lanthanides can promote plant growth, root elongation, hormone synthesis, and stress tolerance, but higher doses can cause harm to plants. Striking the right balance has been hard because of our lack of understanding around how lanthanides are absorbed by plants or how they interact with root soil.For the study, the researchers leveraged seed coating and treatment technologies they previously developed to investigate the way the plant pigment chlorophyll interacts with lanthanides, both inside and outside of plants. Up until now, researchers haven’t been sure whether chlorophyll interacts with lanthanide ions at all.Chlorophyll drives photosynthesis, but the pigments lose their ability to efficiently absorb light when the magnesium ion at their core is removed. The researchers discovered that lanthanides can fill that void, helping chlorophyll pigments partially recover some of their optical properties in a process known as re-greening.“We found that lanthanides can boost several parameters of plant health,” Marelli says. “They mostly accumulate in the roots, but a small amount also makes its way to the leaves, and some of the new chlorophyll molecules made in leaves have lanthanides incorporated in their structure.”This study also offers the first experimental evidence that lanthanides can increase plant resilience to UV stress, something the researchers say was completely unexpected.“Chlorophylls are very sensitive pigments,” Rizzo says. “They can convert light to energy in plants, but when they are isolated from the cell structure, they rapidly hydrolyze and degrade. However, in the form with lanthanides at their center, they are pretty stable, even after extracting them from plant cells.”The researchers, using different spectroscopic techniques, found the benefits held across a range of staple crops, including chickpea, barley, corn, and soybeans.The findings could be used to boost crop yield and increase the resilience of some of the world’s most popular crops to extreme weather.“As we move into an environment where extreme heat and extreme climate events are more common, and particularly where we can have prolonged periods of sun in the field, we want to provide new ways to protect our plants,” Marelli says. “There are existing agrochemicals that can be applied to leaves for protecting plants from stressors such as UV, but they can be toxic, increase microplastics, and can require multiple applications. This could be a complementary way to protect plants from UV stress.”Identifying new applicationsThe researchers also found that larger lanthanide elements like lanthanum were more effective at strengthening chlorophyll pigments than smaller ones. Lanthanum is considered a low-value byproduct of rare earths mining, and can become a burden to the rare earth element (REE) supply chain due to the need to separate it from more desirable rare earths. Increasing the demand for lanthanum could diversify the economics of REEs and improve the stability of their supply chain, the scientists suggest.“This study shows what we could do with these lower-value metals,” Marelli says. “We know lanthanides are extremely useful in electronics, magnets, and energy. In the U.S., there’s a big push to recycle them. That’s why for the plant studies, we focused on lanthanum, being the most abundant, cheapest lanthanide ion.”Moving forward, the team plans to explore how lanthanides work with other biological molecules, including proteins in the human body.In agriculture, the team hopes to scale up its research to include field and greenhouse studies to continue testing the results of UV resilience on different crop types and in experimental farm conditions.“Lanthanides are already widely used in agriculture,” Rizzo says. “We hope this study provides evidence that allows more conscious use of them and also a new way to apply them through seed treatments.”The research was supported by the MIT Climate Grand Challenge and the Office for Naval Research. More

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      in Energy

      Confronting the AI/energy conundrum

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      The explosive growth of AI-powered computing centers is creating an unprecedented surge in electricity demand that threatens to overwhelm power grids and derail climate goals. At the same time, artificial intelligence technologies could revolutionize energy systems, accelerating the transition to clean power.“We’re at a cusp of potentially gigantic change throughout the economy,” said William H. Green, director of the MIT Energy Initiative (MITEI) and Hoyt C. Hottel Professor in the MIT Department of Chemical Engineering, at MITEI’s Spring Symposium, “AI and energy: Peril and promise,” held on May 13. The event brought together experts from industry, academia, and government to explore solutions to what Green described as both “local problems with electric supply and meeting our clean energy targets” while seeking to “reap the benefits of AI without some of the harms.” The challenge of data center energy demand and potential benefits of AI to the energy transition is a research priority for MITEI.AI’s startling energy demandsFrom the start, the symposium highlighted sobering statistics about AI’s appetite for electricity. After decades of flat electricity demand in the United States, computing centers now consume approximately 4 percent of the nation’s electricity. Although there is great uncertainty, some projections suggest this demand could rise to 12-15 percent by 2030, largely driven by artificial intelligence applications.Vijay Gadepally, senior scientist at MIT’s Lincoln Laboratory, emphasized the scale of AI’s consumption. “The power required for sustaining some of these large models is doubling almost every three months,” he noted. “A single ChatGPT conversation uses as much electricity as charging your phone, and generating an image consumes about a bottle of water for cooling.”Facilities requiring 50 to 100 megawatts of power are emerging rapidly across the United States and globally, driven both by casual and institutional research needs relying on large language programs such as ChatGPT and Gemini. Gadepally cited congressional testimony by Sam Altman, CEO of OpenAI, highlighting how fundamental this relationship has become: “The cost of intelligence, the cost of AI, will converge to the cost of energy.”“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. Department of Energy.Wang also noted that innovations developed for AI and data centers — such as efficiency, cooling technologies, and clean-power solutions — could have broad applications beyond computing facilities themselves.Strategies for clean energy solutionsThe symposium explored multiple pathways to address the AI-energy challenge. Some panelists presented models suggesting that while artificial intelligence may increase emissions in the short term, its optimization capabilities could enable substantial emissions reductions after 2030 through more efficient power systems and accelerated clean technology development.Research shows regional variations in the cost of powering computing centers with clean electricity, according to Emre Gençer, co-founder and CEO of Sesame Sustainability and former MITEI principal research scientist. Gençer’s analysis revealed that the central United States offers considerably lower costs due to complementary solar and wind resources. However, achieving zero-emission power would require massive battery deployments — five to 10 times more than moderate carbon scenarios — driving costs two to three times higher.“If we want to do zero emissions with reliable power, we need technologies other than renewables and batteries, which will be too expensive,” Gençer said. He pointed to “long-duration storage technologies, small modular reactors, geothermal, or hybrid approaches” as necessary complements.Because of data center energy demand, there is renewed interest in nuclear power, noted Kathryn Biegel, manager of R&D and corporate strategy at Constellation Energy, adding that her company is restarting the reactor at the former Three Mile Island site, now called the “Crane Clean Energy Center,” to meet this demand. “The data center space has become a major, major priority for Constellation,” she said, emphasizing how their needs for both reliability and carbon-free electricity are reshaping the power industry.Can AI accelerate the energy transition?Artificial intelligence could dramatically improve power systems, according to Priya Donti, assistant professor and the Silverman Family Career Development Professor in MIT’s Department of Electrical Engineering and Computer Science and the Laboratory for Information and Decision Systems. She showcased how AI can accelerate power grid optimization by embedding physics-based constraints into neural networks, potentially solving complex power flow problems at “10 times, or even greater, speed compared to your traditional models.”AI is already reducing carbon emissions, according to examples shared by Antonia Gawel, global director of sustainability and partnerships at Google. Google Maps’ fuel-efficient routing feature has “helped to prevent more than 2.9 million metric tons of GHG [greenhouse gas] emissions reductions since launch, which is the equivalent of taking 650,000 fuel-based cars off the road for a year,” she said. Another Google research project uses artificial intelligence to help pilots avoid creating contrails, which represent about 1 percent of global warming impact.AI’s potential to speed materials discovery for power applications was highlighted by Rafael Gómez-Bombarelli, the Paul M. Cook Career Development Associate Professor in the MIT Department of Materials Science and Engineering. “AI-supervised models can be trained to go from structure to property,” he noted, enabling the development of materials crucial for both computing and efficiency.Securing growth with sustainabilityThroughout the symposium, participants grappled with balancing rapid AI deployment against environmental impacts. While AI training receives most attention, Dustin Demetriou, senior technical staff member in sustainability and data center innovation at IBM, quoted a World Economic Forum article that suggested that “80 percent of the environmental footprint is estimated to be due to inferencing.” Demetriou emphasized the need for efficiency across all artificial intelligence applications.Jevons’ paradox, where “efficiency gains tend to increase overall resource consumption rather than decrease it” is another factor to consider, cautioned Emma Strubell, the Raj Reddy Assistant Professor in the Language Technologies Institute in the School of Computer Science at Carnegie Mellon University. Strubell advocated for viewing computing center electricity as a limited resource requiring thoughtful allocation across different applications.Several presenters discussed novel approaches for integrating renewable sources with existing grid infrastructure, including potential hybrid solutions that combine clean installations with existing natural gas plants that have valuable grid connections already in place. These approaches could provide substantial clean capacity across the United States at reasonable costs while minimizing reliability impacts.Navigating the AI-energy paradoxThe symposium highlighted MIT’s central role in developing solutions to the AI-electricity challenge.Green spoke of a new MITEI program on computing centers, power, and computation that will operate alongside the comprehensive spread of MIT Climate Project research. “We’re going to try to tackle a very complicated problem all the way from the power sources through the actual algorithms that deliver value to the customers — in a way that’s going to be acceptable to all the stakeholders and really meet all the needs,” Green said.Participants in the symposium were polled about priorities for MIT’s research by Randall Field, MITEI director of research. The real-time results ranked “data center and grid integration issues” as the top priority, followed by “AI for accelerated discovery of advanced materials for energy.”In addition, attendees revealed that most view AI’s potential regarding power as a “promise,” rather than a “peril,” although a considerable portion remain uncertain about the ultimate impact. When asked about priorities in power supply for computing facilities, half of the respondents selected carbon intensity as their top concern, with reliability and cost following. More

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      in Environment

      VAMO proposes an alternative to architectural permanence

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      The International Architecture Exhibition of La Biennale di Venezia holds up a mirror to the industry — not only reflecting current priorities and preoccupations, but also projecting an agenda for what might be possible. Curated by Carlo Ratti, MIT professor of practice of urban technologies and planning, this year’s exhibition (“Intelligens. Natural. Artificial. Collective”) proposes a “Circular Economy Manifesto” with the goal to support the “development and production of projects that utilize natural, artificial, and collective intelligence to combat the climate crisis.” Designers and architects will quickly recognize the paradox of this year’s theme. Global architecture festivals have historically had a high carbon footprint, using vast amounts of energy, resources, and materials to build and transport temporary structures that are later discarded. This year’s unprecedented emphasis on waste elimination and carbon neutrality challenges participants to reframe apparent limitations into creative constraints. In this way, the Biennale acts as a microcosm of current planetary conditions — a staging ground to envision and practice adaptive strategies.VAMO (Vegetal, Animal, Mineral, Other)When Ratti approached John Ochsendorf, MIT professor and founding director of MIT Morningside Academy of Design (MAD), with the invitation to interpret the theme of circularity, the project became the premise for a convergence of ideas, tools, and know-how from multiple teams at MIT and the wider MIT community. The Digital Structures research group, directed by Professor Caitlin Mueller, applied expertise in designing efficient structures of tension and compression. The Circular Engineering for Architecture research group, led by MIT alumna Catherine De Wolf at ETH Zurich, explored how digital technologies and traditional woodworking techniques could make optimal use of reclaimed timber. Early-stage startups — including companies launched by the venture accelerator MITdesignX — contributed innovative materials harnessing natural byproducts from vegetal, animal, mineral, and other sources. The result is VAMO (Vegetal, Animal, Mineral, Other), an ultra-lightweight, biodegradable, and transportable canopy designed to circle around a brick column in the Corderie of the Venice Arsenale — a historic space originally used to manufacture ropes for the city’s naval fleet. “This year’s Biennale marks a new radicalism in approaches to architecture,” says Ochsendorf. “It’s no longer sufficient to propose an exciting idea or present a stylish installation. The conversation on material reuse must have relevance beyond the exhibition space, and we’re seeing a hunger among students and emerging practices to have a tangible impact. VAMO isn’t just a temporary shelter for new thinking. It’s a material and structural prototype that will evolve into multiple different forms after the Biennale.”Tension and compressionThe choice to build the support structure from reclaimed timber and hemp rope called for a highly efficient design to maximize the inherent potential of comparatively humble materials. Working purely in tension (the spliced cable net) or compression (the oblique timber rings), the structure appears to float — yet is capable of supporting substantial loads across large distances. The canopy weighs less than 200 kilograms and covers over 6 meters in diameter, highlighting the incredible lightness that equilibrium forms can achieve. VAMO simultaneously showcases a series of sustainable claddings and finishes made from surprising upcycled materials — from coconut husks, spent coffee grounds, and pineapple peel to wool, glass, and scraps of leather. The Digital Structures research group led the design of structural geometries conditioned by materiality and gravity. “We knew we wanted to make a very large canopy,” says Mueller. “We wanted it to have anticlastic curvature suggestive of naturalistic forms. We wanted it to tilt up to one side to welcome people walking from the central corridor into the space. However, these effects are almost impossible to achieve with today’s computational tools that are mostly focused on drawing rigid materials.”In response, the team applied two custom digital tools, Ariadne and Theseus, developed in-house to enable a process of inverse form-finding: a way of discovering forms that achieve the experiential qualities of an architectural project based on the mechanical properties of the materials. These tools allowed the team to model three-dimensional design concepts and automatically adjust geometries to ensure that all elements were held in pure tension or compression.“Using digital tools enhances our creativity by allowing us to choose between multiple different options and short-circuit a process that would have otherwise taken months,” says Mueller. “However, our process is also generative of conceptual thinking that extends beyond the tool — we’re constantly thinking about the natural and historic precedents that demonstrate the potential of these equilibrium structures.”Digital efficiency and human creativity Lightweight enough to be carried as standard luggage, the hemp rope structure was spliced by hand and transported from Massachusetts to Venice. Meanwhile, the heavier timber structure was constructed in Zurich, where it could be transported by train — thereby significantly reducing the project’s overall carbon footprint. The wooden rings were fabricated using salvaged beams and boards from two temporary buildings in Switzerland — the Huber and Music Pavilions — following a pedagogical approach that De Wolf has developed for the Digital Creativity for Circular Construction course at ETH Zurich. Each year, her students are tasked with disassembling a building due for demolition and using the materials to design a new structure. In the case of VAMO, the goal was to upcycle the wood while avoiding the use of chemicals, high-energy methods, or non-biodegradable components (such as metal screws or plastics). “Our process embraces all three types of intelligence celebrated by the exhibition,” says De Wolf. “The natural intelligence of the materials selected for the structure and cladding; the artificial intelligence of digital tools empowering us to upcycle, design, and fabricate with these natural materials; and the crucial collective intelligence that unlocks possibilities of newly developed reused materials, made possible by the contributions of many hands and minds.”For De Wolf, true creativity in digital design and construction requires a context-sensitive approach to identifying when and how such tools are best applied in relation to hands-on craftsmanship. Through a process of collective evaluation, it was decided that the 20-foot lower ring would be assembled with eight scarf joints using wedges and wooden pegs, thereby removing the need for metal screws. The scarf joints were crafted through five-axis CNC milling; the smaller, dual-jointed upper ring was shaped and assembled by hand by Nicolas Petit-Barreau, founder of the Swiss woodwork company Anku, who applied his expertise in designing and building yurts, domes, and furniture to the VAMO project. “While digital tools suited the repetitive joints of the lower ring, the upper ring’s two unique joints were more efficiently crafted by hand,” says Petit-Barreau. “When it comes to designing for circularity, we can learn a lot from time-honored building traditions. These methods were refined long before we had access to energy-intensive technologies — they also allow for the level of subtlety and responsiveness necessary when adapting to the irregularities of reused wood.”A material palette for circularityThe structural system of a building is often the most energy-intensive; an impact dramatically mitigated by the collaborative design and fabrication process developed by MIT Digital Structures and ETH Circular Engineering for Architecture. The structure also serves to showcase panels made of biodegradable and low-energy materials — many of which were advanced through ventures supported by MITdesignX, a program dedicated to design innovation and entrepreneurship at MAD. “In recent years, several MITdesignX teams have proposed ideas for new sustainable materials that might at first seem far-fetched,” says Gilad Rosenzweig, executive director of MITdesignX. “For instance, using spent coffee grounds to create a leather-like material (Cortado), or creating compostable acoustic panels from coconut husks and reclaimed wool (Kokus). This reflects a major cultural shift in the architecture profession toward rethinking the way we build, but it’s not enough just to have an inventive idea. To achieve impact — to convert invention into innovation — teams have to prove that their concept is cost-effective, viable as a business, and scalable.”Aligned with the ethos of MAD, MITdesignX assesses profit and productivity in terms of environmental and social sustainability. In addition to presenting the work of R&D teams involved in MITdesignX, VAMO also exhibits materials produced by collaborating teams at University of Pennsylvania’s Stuart Weitzman School of Design, Politecnico di Milano, and other partners, such as Manteco. The result is a composite structure that encapsulates multiple life spans within a diverse material palette of waste materials from vegetal, animal, and mineral forms. Panels of Ananasse, a material made from pineapple peels developed by Vérabuccia, preserve the fruit’s natural texture as a surface pattern, while rehub repurposes fragments of multicolored Murano glass into a flexible terrazzo-like material; COBI creates breathable shingles from coarse wool and beeswax, and DumoLab produces fuel-free 3D-printable wood panels. A purpose beyond permanence Adriana Giorgis, a designer and teaching fellow in architecture at MIT, played a crucial role in bringing the parts of the project together. Her research explores the diverse network of factors that influence whether a building stands the test of time, and her insights helped to shape the collective understanding of long-term design thinking.“As a point of connection between all the teams, helping to guide the design as well as serving as a project manager, I had the chance to see how my research applied at each level of the project,” Giorgis reflects. “Braiding these different strands of thinking and ultimately helping to install the canopy on site brought forth a stronger idea about what it really means for a structure to have longevity. VAMO isn’t limited to its current form — it’s a way of carrying forward a powerful idea into contemporary and future practice.”What’s next for VAMO? Neither the attempt at architectural permanence associated with built projects, nor the relegation to waste common to temporary installations. After the Biennale, VAMO will be disassembled, possibly reused for further exhibitions, and finally relocated to a natural reserve in Switzerland, where the parts will be researched as they biodegrade. In this way, the lifespan of the project is extended beyond its initial purpose for human habitation and architectural experimentation, revealing the gradual material transformations constantly taking place in our built environment.To quote Carlo Ratti’s Circular Economy Manifesto, the “lasting legacy” of VAMO is to “harness nature’s intelligence, where nothing is wasted.” Through a regenerative symbiosis of natural, artificial, and collective intelligence, could architectural thinking and practice expand to planetary proportions? More

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      Evelyn Wang: A new energy source at MIT

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      Evelyn Wang ’00 knows a few things about engineering solutions to hard problems. After all, she invented a way to pull water out of thin air.Now, Wang is applying that problem-solving experience — and a deep, enduring sense of optimism — toward the critical issue of climate change, to strengthen the American energy economy and ensure resilience for all.Wang, a mechanical engineering professor by trade, began work this spring as MIT’s first vice president for energy and climate, overseeing the Institute’s expanding work on climate change. That means broadening the Institute’s already-wide research portfolio, scaling up existing innovations, seeking new breakthroughs, and channeling campus community input to drive work forward.“MIT has the potential to do so much, when we know that climate, energy, and resilience are paramount to events happening around us every day,” says Wang, who is also the Ford Professor of Engineering at MIT. “There’s no better place than MIT to come up with the transformational solutions that can help shape our world.”That also means developing partnerships with corporate allies, startups, government, communities, and other organizations. Tackling climate change, Wang says, “requires a lot of partnerships. It’s not an MIT-only endeavor. We’re going to have to collaborate with other institutions and think about where industry can help us deploy and scale so the impact can be greater.”She adds: “The more partnerships we have, the more understanding we have of the best pathways to make progress in difficult areas.”From MIT to ARPA-EAn MIT faculty member since 2007, Wang leads the Device Research Lab. Along with collaborators, she identifies new materials and optimizations based on heat and mass transport processes that unlock the creation of leading-edge innovations. Her development of the device that extracts water from even very dry air led Foreign Policy Magazine to name her its 2017 Global ReThinker, and she won the 2018 Eighth Prince Sultan bin Abdulaziz International Prize for Water.Her research also extends to other areas such as energy and desalination research. In 2016, Wang and several colleagues announced a device based on nanophotonic crystals with the potential to double the amount of power produced by a given area of solar panels, which led to one of her graduate researchers on the project to co-found the startup Antora Energy. More recently, Wang and colleagues developed an aerogel that improves window insulation, now being commercialized through her former graduate students in a startup, AeroShield.Wang also spent two years recently as director of the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E), which supports early-stage R&D on energy generation, storage, and use.  Returning to MIT, she began her work as vice president for energy and climate in April, engaging with researchers, holding community workshops, and planning to build partnerships.“I’ve been energized coming back to the Institute, given the talented students, the faculty, the staff. It’s invigorating to be back in this community,” Wang says. “People are passionate, excited, and mission-driven, and that’s the energy we need to make a big impact in the world.”Wang is also working to help align the Institute’s many existing climate efforts. This includes the Climate Project at MIT, an Institute-wide presidential initiative announced in 2024, which aims to accelerate and scale up climate solutions while generating new tools and policy proposals. All told, about 300 MIT faculty conduct research related to climate issues in one form or another.“The fact that there are so many faculty working on climate is astounding,” Wang says. “Everyone’s doing exciting work, but how can we leverage our unique strengths to create something bigger than the sum of its parts? That’s what I’m working toward. We’ve spun out so many technologies. How do we do more of that? How do we do that faster, and in a way so the world will feel the impact?”A deep connection to campus — and strong sense of optimismUnderstanding MIT is one of Wang’s strengths, given that she has spent over two decades at the Institute.Wang earned her undergraduate degree from MIT in mechanical engineering, and her MS and PhD in mechanical engineering from Stanford University. She has held several chaired faculty positions at MIT. In 2008, Wang was named the Esther and Harold E. Edgerton Assistant Professor; in 2015, she was named the Gail E. Kendall Professor; and in 2021, she became the Ford Professor of Engineering. Wang served as head of the Department of Mechanical Engineering from 2018 through 2022.As it happens, Wang’s parents, Kang and Edith, met as graduate students at the Institute. Her father, an electrical engineer, became a professor at the University of California at Los Angeles. Wang also met her husband at MIT, and both of her brothers graduated from the Institute.Along with her deep institutional knowledge, administrative experience, and track record as an innovator, Wang is bringing several other things to her new role as vice president for climate: a sense of urgency about the issue, coupled with a continual sense of optimism that innovators can meet society’s needs.“I think optimism can make a difference, and is great to have in the midst of collective challenge,” Wang says. “We’re such a mission-driven university, and people come here to solve real-world problems.”That hopeful approach is why Wang describes the work as not only as a challenge but also a generational opportunity. “We have the chance to design the world we want,” she says, “one that’s cleaner, more sustainable and more resilient. This future is ours to shape and build together.”Wang thinks MIT contains many examples of world-shaping progress, She cites MIT’s announcement this month of the creation of the Schmidt Laboratory for Materials in Nuclear Technologies, at the MIT Plasma Science and Fusion center, to conduct research on next-generation materials that could help enable the construction of fusion power plants. Another example Wang references is MIT research earlier this year on developing clean ammonia, a way to make the world’s most widely-produced chemical with drastically-reduced greenhouse gas emissions.“Those solutions could be breakthroughs,” Wang says. “Those are the kinds of things that give us optimism. There’s still a lot of research to be done, but it suggests the potential of what our world can be.”Optimism: There’s that word again.“Optimism is the only way to go,” Wang says. “Yes, the world is challenged. But this is where MIT’s strengths — in research, innovation, and education — can bring optimism to the table.” More