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    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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      Study links rising temperatures and declining moods

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      Rising global temperatures affect human activity in many ways. Now, a new study illuminates an important dimension of the problem: Very hot days are associated with more negative moods, as shown by a large-scale look at social media postings.Overall, the study examines 1.2 billion social media posts from 157 countries over the span of a year. The research finds that when the temperature rises above 95 degrees Fahrenheit, or 35 degrees Celsius, expressed sentiments become about 25 percent more negative in lower-income countries and about 8 percent more negative in better-off countries. Extreme heat affects people emotionally, not just physically.“Our study reveals that rising temperatures don’t just threaten physical health or economic productivity — they also affect how people feel, every day, all over the world,” says Siqi Zheng, a professor in MIT’s Department of Urban Studies and Planning (DUSP) and Center for Real Estate (CRE), and co-author of a new paper detailing the results. “This work opens up a new frontier in understanding how climate stress is shaping human well-being at a planetary scale.”The paper, “Unequal Impacts of Rising Temperatures on Global Human Sentiment,” is published today in the journal One Earth. The authors are Jianghao Wang, of the Chinese Academy of Sciences; Nicolas Guetta-Jeanrenaud SM ’22, a graduate of MIT’s Technology and Policy Program (TPP) and Institute for Data, Systems, and Society; Juan Palacios, a visiting assistant professor at MIT’s Sustainable Urbanization Lab (SUL) and an assistant professor Maastricht University; Yichun Fan, of SUL and Duke University; Devika Kakkar, of Harvard University; Nick Obradovich, of SUL and the Laureate Institute for Brain Research in Tulsa; and Zheng, who is the STL Champion Professor of Urban and Real Estate Sustainability at CRE and DUSP. Zheng is also the faculty director of CRE and founded the Sustainable Urbanization Lab in 2019.Social media as a windowTo conduct the study, the researchers evaluated 1.2 billion posts from the social media platforms Twitter and Weibo, all of which appeared in 2019. They used a natural language processing technique called Bidirectional Encoder Representations from Transformers (BERT), to analyze 65 languages across the 157 countries in the study.Each social media post was given a sentiment rating from 0.0 (for very negative posts) to 1.0 (for very positive posts). The posts were then aggregated geographically to 2,988 locations and evaluated in correlation with area weather. From this method, the researchers could then deduce the connection between extreme temperatures and expressed sentiment.“Social media data provides us with an unprecedented window into human emotions across cultures and continents,” Wang says. “This approach allows us to measure emotional impacts of climate change at a scale that traditional surveys simply cannot achieve, giving us real-time insights into how temperature affects human sentiment worldwide.”To assess the effects of temperatures on sentiment in higher-income and middle-to-lower-income settings, the scholars also used a World Bank cutoff level of gross national income per-capita annual income of $13,845, finding that in places with incomes below that, the effects of heat on mood were triple those found in economically more robust settings.“Thanks to the global coverage of our data, we find that people in low- and middle-income countries experience sentiment declines from extreme heat that are three times greater than those in high-income countries,” Fan says. “This underscores the importance of incorporating adaptation into future climate impact projections.”In the long runUsing long-term global climate models, and expecting some adaptation to heat, the researchers also produced a long-range estimate of the effects of extreme temperatures on sentiment by the year 2100. Extending the current findings to that time frame, they project a 2.3 percent worsening of people’s emotional well-being based on high temperatures alone by then — although that is a far-range projection.“It’s clear now, with our present study adding to findings from prior studies, that weather alters sentiment on a global scale,” Obradovich says. “And as weather and climates change, helping individuals become more resilient to shocks to their emotional states will be an important component of overall societal adaptation.”The researchers note that there are many nuances to the subject, and room for continued research in this area. For one thing, social media users are not likely to be a perfectly representative portion of the population, with young children and the elderly almost certainly using social media less than other people. However, as the researchers observe in the paper, the very young and elderly are probably particularly vulnerable to heat shocks, making the response to hot weather possible even larger than their study can capture.The research is part of the Global Sentiment project led by the MIT Sustainable Urbanization Lab, and the study’s dataset is publicly available. Zheng and other co-authors have previously investigated these dynamics using social media, although never before at this scale.“We hope this resource helps researchers, policymakers, and communities better prepare for a warming world,” Zheng says.The research was supported, in part, by Zheng’s chaired professorship research fund, and grants Wang received from the National Natural Science Foundation of China and the Chinese Academy of Sciences.  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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      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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      Why animals are a critical part of forest carbon absorption

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      A lot of attention has been paid to how climate change can drive biodiversity loss. Now, MIT researchers have shown the reverse is also true: Reductions in biodiversity can jeopardize one of Earth’s most powerful levers for mitigating climate change.In a paper published in PNAS, the researchers showed that following deforestation, naturally-regrowing tropical forests, with healthy populations of seed-dispersing animals, can absorb up to four times more carbon than similar forests with fewer seed-dispersing animals.Because tropical forests are currently Earth’s largest land-based carbon sink, the findings improve our understanding of a potent tool to fight climate change.“The results underscore the importance of animals in maintaining healthy, carbon-rich tropical forests,” says Evan Fricke, a research scientist in the MIT Department of Civil and Environmental Engineering and the lead author of the new study. “When seed-dispersing animals decline, we risk weakening the climate-mitigating power of tropical forests.”Fricke’s co-authors on the paper include César Terrer, the Tianfu Career Development Associate Professor at MIT; Charles Harvey, an MIT professor of civil and environmental engineering; and Susan Cook-Patton of The Nature Conservancy.The study combines a wide array of data on animal biodiversity, movement, and seed dispersal across thousands of animal species, along with carbon accumulation data from thousands of tropical forest sites.The researchers say the results are the clearest evidence yet that seed-dispersing animals play an important role in forests’ ability to absorb carbon, and that the findings underscore the need to address biodiversity loss and climate change as connected parts of a delicate ecosystem rather as separate problems in isolation.“It’s been clear that climate change threatens biodiversity, and now this study shows how biodiversity losses can exacerbate climate change,” Fricke says. “Understanding that two-way street helps us understand the connections between these challenges, and how we can address them. These are challenges we need to tackle in tandem, and the contribution of animals to tropical forest carbon shows that there are win-wins possible when supporting biodiversity and fighting climate change at the same time.”Putting the pieces togetherThe next time you see a video of a monkey or bird enjoying a piece of fruit, consider that the animals are actually playing an important role in their ecosystems. Research has shown that by digesting the seeds and defecating somewhere else, animals can help with the germination, growth, and long-term survival of the plant.Fricke has been studying animals that disperse seeds for nearly 15 years. His previous research has shown that without animal seed dispersal, trees have lower survival rates and a harder time keeping up with environmental changes.“We’re now thinking more about the roles that animals might play in affecting the climate through seed dispersal,” Fricke says. “We know that in tropical forests, where more than three-quarters of trees rely on animals for seed dispersal, the decline of seed dispersal could affect not just the biodiversity of forests, but how they bounce back from deforestation. We also know that all around the world, animal populations are declining.”Regrowing forests is an often-cited way to mitigate the effects of climate change, but the influence of biodiversity on forests’ ability to absorb carbon has not been fully quantified, especially at larger scales.For their study, the researchers combined data from thousands of separate studies and used new tools for quantifying disparate but interconnected ecological processes. After analyzing data from more than 17,000 vegetation plots, the researchers decided to focus on tropical regions, looking at data on where seed-dispersing animals live, how many seeds each animal disperses, and how they affect germination.The researchers then incorporated data showing how human activity impacts different seed-dispersing animals’ presence and movement. They found, for example, that animals move less when they consume seeds in areas with a bigger human footprint.Combining all that data, the researchers created an index of seed-dispersal disruption that revealed a link between human activities and declines in animal seed dispersal. They then analyzed the relationship between that index and records of carbon accumulation in naturally regrowing tropical forests over time, controlling for factors like drought conditions, the prevalence of fires, and the presence of grazing livestock.“It was a big task to bring data from thousands of field studies together into a map of the disruption of seed dispersal,” Fricke says. “But it lets us go beyond just asking what animals are there to actually quantifying the ecological roles those animals are playing and understanding how human pressures affect them.”The researchers acknowledged that the quality of animal biodiversity data could be improved and introduces uncertainty into their findings. They also note that other processes, such as pollination, seed predation, and competition influence seed dispersal and can constrain forest regrowth. Still, the findings were in line with recent estimates.“What’s particularly new about this study is we’re actually getting the numbers around these effects,” Fricke says. “Finding that seed dispersal disruption explains a fourfold difference in carbon absorption across the thousands of tropical regrowth sites included in the study points to seed dispersers as a major lever on tropical forest carbon.”Quantifying lost carbonIn forests identified as potential regrowth sites, the researchers found seed-dispersal declines were linked to reductions in carbon absorption each year averaging 1.8 metric tons per hectare, equal to a reduction in regrowth of 57 percent.The researchers say the results show natural regrowth projects will be more impactful in landscapes where seed-dispersing animals have been less disrupted, including areas that were recently deforested, are near high-integrity forests, or have higher tree cover.“In the discussion around planting trees versus allowing trees to regrow naturally, regrowth is basically free, whereas planting trees costs money, and it also leads to less diverse forests,” Terrer says. “With these results, now we can understand where natural regrowth can happen effectively because there are animals planting the seeds for free, and we also can identify areas where, because animals are affected, natural regrowth is not going to happen, and therefore planting trees actively is necessary.”To support seed-dispersing animals, the researchers encourage interventions that protect or improve their habitats and that reduce pressures on species, ranging from wildlife corridors to restrictions on wildlife trade. Restoring the ecological roles of seed dispersers is also possible by reintroducing seed-dispersing species where they’ve been lost or planting certain trees that attract those animals.The findings could also make modeling the climate impact of naturally regrowing forests more accurate.“Overlooking the impact of seed-dispersal disruption may overestimate natural regrowth potential in many areas and underestimate it in others,” the authors write.The researchers believe the findings open up new avenues of inquiry for the field.“Forests provide a huge climate subsidy by sequestering about a third of all human carbon emissions,” Terrer says. “Tropical forests are by far the most important carbon sink globally, but in the last few decades, their ability to sequester carbon has been declining. We will next explore how much of that decline is due to an increase in extreme droughts or fires versus declines in animal seed dispersal.”Overall, the researchers hope the study helps improves our understanding of the planet’s complex ecological processes.“When we lose our animals, we’re losing the ecological infrastructure that keeps our tropical forests healthy and resilient,” Fricke says.The research was supported by the MIT Climate and Sustainability Consortium, the Government of Portugal, and the Bezos Earth Fund. More

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      Designing across cultural and geographic divides

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      In addition to the typical rigors of MIT classes, Terrascope Subject 2.00C/1.016/EC.746 (Design for Complex Environmental Issues) poses some unusual hurdles for students to navigate: collaborating across time zones, bridging different cultural and institutional experiences, and trying to do hands-on work over Zoom. That’s because the class includes students from not only MIT, but also Diné College in Tsaile, Arizona, within the Navajo Nation, and the University of Puerto Rico-Ponce (UPRP).Despite being thousands of miles apart, students work in teams to tackle a real-world problem for a client, based on the Terrascope theme for the year. “Understanding how to collaborate over long distances with people who are not like themselves will be an important item in many of these students’ toolbelts going forward, in some cases just as much as — or more than — any particular design technique,” says Ari Epstein, Terrascope associate director and senior lecturer. Over the past several years, Epstein has taught the class along with Joel Grimm of MIT Beaver Works and Libby Hsu of MIT D-Lab, as well instructors from the two collaborating institutions. Undergraduate teaching fellows from all three schools are also key members of the instructional staff.Since the partnership began three years ago (initially with Diné College, with the addition of UPRP two years ago), the class themes have included food security and sustainable agriculture in Navajo Nation; access to reliable electrical power in Puerto Rico; and this year, increasing museum visitors’ engagement with artworks depicting mining and landscape alteration in Nevada.Each team — which includes students from all three colleges — meets with clients online early in the term to understand their needs; then, through an iterative process, teams work on designing prototypes. During MIT’s spring break, teams travel to meet with the clients onsite to get feedback and continue to refine their prototypes. At the end of the term, students present their final products to the clients, an expert panel, and their communities at a hybrid showcase event held simultaneously on all three campuses.Free-range design engineering“I really loved the class,” says Graciela Leon, a second-year mechanical engineering major who took the subject in 2024. “It was not at all what I was expecting,” she adds. While the learning objectives on the syllabus are fairly traditional — using an iterative engineering design process, developing teamwork skills, and deepening communication skills, to name a few — the approach is not. “Terrascope is just kind of like throwing you into a real-world problem … it feels a lot more like you are being trusted with this actual challenge,” Leon says.The 2024 challenge was to find a way to help the clients, Puerto Rican senior citizens, turn on gasoline-powered generators when the electrical power grid fails; some of them struggle with the pull cords necessary to start the generators. The students were tasked with designing solutions to make starting the generators easier.Terrascope instructors teach fundamental skills such as iterative design spirals and scrum workflow frameworks, but they also give students ample freedom to follow their ideas. Leon admits she was a bit frustrated at first, because she wasn’t sure what she was supposed to be doing. “I wanted to be building things and thought, ‘Wow, I have to do all these other things, I have to write some kind of client profile and understand my client’s needs.’ I was just like, ‘Hand me a drill! I want to design something!’”When he took the class last year, Uziel Rodriguez-Andujar was also thrown off initially by the independence teams had. Now a second-year UPRP student in mechanical engineering, he’s accustomed to lecture-based classes. “What I found so interesting is the way [they] teach the class, which is, ‘You make your own project, and we need you to find a solution to this. How it will look, and when you have it — that’s up to you,’” he says.Clearing hurdlesTeaching the course on three different campuses introduces a number of challenges for students and instructors to overcome — among them, operating in three different time zones, overcoming language barriers, navigating different cultural and institutional norms, communicating effectively, and designing and building prototypes over Zoom.“The culture span is huge,” explains Epstein. “There are different ways of speaking, different ways of listening, and each organization has different resources.”First-year MIT student EJ Rodriguez found that one of the biggest obstacles was trying to convey ideas to teammates clearly. He took the class this year, when the theme revolved around the environmental impacts of lithium mining. The client, the Nevada Museum of Art, wanted to find ways to engage visitors with its artwork collection related to mining-related landscape changes.Rodriguez and his team designed a pendulum with a light affixed to it that illuminates a painting by a Native American artist. When the pendulum swings, it changes how the visitor experiences the artwork. The team built parts for the pendulum on different campuses, and they reached a point where they realized their pieces were incompatible. “We had different visions of what we wanted for the project, and different vocabulary we were using to describe our ideas. Sometimes there would be a misunderstanding … It required a lot of honesty from each campus to be like, ‘OK, I thought we were doing exactly this,’ and obviously in a really respectful way.”It’s not uncommon for students at Diné College and UPRP to experience an initial hurdle that their MIT peers do not. Epstein notes, “There’s a tendency for some folks outside MIT to see MIT students as these brilliant people that they don’t belong in the same room with.” But the other students soon realize not only that they can hold their own intellectually, but also that their backgrounds and experiences are incredibly valuable. “Their life experiences actually put them way ahead of many MIT students in some ways, when you think about design and fabrication, like repairing farm equipment or rebuilding transmissions,” he adds.That’s how Cauy Bia felt when he took the class in 2024. Currently a first-year graduate student in biology at Diné College, Bia questioned whether he’d be on par with the MIT students. “I’ve grown up on a farm, and we do a lot of building, a lot of calculations, a lot of hands-on stuff. But going into this, I was sweating it so hard [wondering], ‘Am I smart enough to work with these students?’ And then, at the end of the day, that was never an issue,” he says.The value of reflectionEvery two weeks, Terrascope students write personal reflections about their experiences in the class, which helps them appreciate their academic and personal development. “I really felt that I had undergone a process that made me grow as an engineer,” says Leon. “I understood the importance of people and engineering more, including teamwork, working with clients, and de-centering the project away from what I wanted to build and design.”When Bia began the semester, he says, he was more of a “make-or-break-type person” and tended to see things in black and white. “But working with all three campuses, it kind of opened up my thought process so I can assess more ideas, more voices and opinions. And I can get broader perspectives and get bigger ideas from that point,” he says. It was also a powerful experience culturally for him, particularly “drawing parallels between Navajo history, Navajo culture, and seeing the similarities between that and Puerto Rican culture, seeing how close we are as two nations.”Rodriguez-Andujar gained an appreciation for the “constant struggle between simplicity and complexity” in engineering. “You have all these engineers trying to over-engineer everything,” he says. “And after you get your client feedback [halfway through the semester], it turns out, ‘Oh, that doesn’t work for me. I’m sorry — you have to scale it down like a hundred times and make it a lot simpler.’”For instructors, the students’ reflections are invaluable as they strive to make improvements every year. In many ways, you might say the class is an iterative design spiral, too. “The past three years have themselves been prototypes,” Epstein says, “and all of the instructional staff are looking forward to continuing these exciting partnerships.” 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 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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      in Environment

      Merging AI and underwater photography to reveal hidden ocean worlds

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      In the Northeastern United States, the Gulf of Maine represents one of the most biologically diverse marine ecosystems on the planet — home to whales, sharks, jellyfish, herring, plankton, and hundreds of other species. But even as this ecosystem supports rich biodiversity, it is undergoing rapid environmental change. The Gulf of Maine is warming faster than 99 percent of the world’s oceans, with consequences that are still unfolding.A new research initiative developing at MIT Sea Grant, called LOBSTgER — short for Learning Oceanic Bioecological Systems Through Generative Representations — brings together artificial intelligence and underwater photography to document the ocean life left vulnerable to these changes and share them with the public in new visual ways. Co-led by underwater photographer and visiting artist at MIT Sea Grant Keith Ellenbogen and MIT mechanical engineering PhD student Andreas Mentzelopoulos, the project explores how generative AI can expand scientific storytelling by building on field-based photographic data.Just as the 19th-century camera transformed our ability to document and reveal the natural world — capturing life with unprecedented detail and bringing distant or hidden environments into view — generative AI marks a new frontier in visual storytelling. Like early photography, AI opens a creative and conceptual space, challenging how we define authenticity and how we communicate scientific and artistic perspectives. In the LOBSTgER project, generative models are trained exclusively on a curated library of Ellenbogen’s original underwater photographs — each image crafted with artistic intent, technical precision, accurate species identification, and clear geographic context. By building a high-quality dataset grounded in real-world observations, the project ensures that the resulting imagery maintains both visual integrity and ecological relevance. In addition, LOBSTgER’s models are built using custom code developed by Mentzelopoulos to protect the process and outputs from any potential biases from external data or models. LOBSTgER’s generative AI builds upon real photography, expanding the researchers’ visual vocabulary to deepen the public’s connection to the natural world.

      This ocean sunfish (Mola mola) image was generated by LOBSTgER’s unconditional models.

      AI-generated image: Keith Ellenbogen, Andreas Mentzelopoulos, and LOBSTgER.

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      At its heart, LOBSTgER operates at the intersection of art, science, and technology. The project draws from the visual language of photography, the observational rigor of marine science, and the computational power of generative AI. By uniting these disciplines, the team is not only developing new ways to visualize ocean life — they are also reimagining how environmental stories can be told. This integrative approach makes LOBSTgER both a research tool and a creative experiment — one that reflects MIT’s long-standing tradition of interdisciplinary innovation.Underwater photography in New England’s coastal waters is notoriously difficult. Limited visibility, swirling sediment, bubbles, and the unpredictable movement of marine life all pose constant challenges. For the past several years, Ellenbogen has navigated these challenges and is building a comprehensive record of the region’s biodiversity through the project, Space to Sea: Visualizing New England’s Ocean Wilderness. This large dataset of underwater images provides the foundation for training LOBSTgER’s generative AI models. The images span diverse angles, lighting conditions, and animal behaviors, resulting in a visual archive that is both artistically striking and biologically accurate.

      Image synthesis via reverse diffusion: This short video shows the de-noising trajectory from Gaussian latent noise to photorealistic output using LOBSTgER’s unconditional models. Iterative de-noising requires 1,000 forward passes through the trained neural network.Video: Keith Ellenbogen and Andreas Mentzelopoulos / MIT Sea Grant

      LOBSTgER’s custom diffusion models are trained to replicate not only the biodiversity Ellenbogen documents, but also the artistic style he uses to capture it. By learning from thousands of real underwater images, the models internalize fine-grained details such as natural lighting gradients, species-specific coloration, and even the atmospheric texture created by suspended particles and refracted sunlight. The result is imagery that not only appears visually accurate, but also feels immersive and moving.The models can both generate new, synthetic, but scientifically accurate images unconditionally (i.e., requiring no user input/guidance), and enhance real photographs conditionally (i.e., image-to-image generation). By integrating AI into the photographic workflow, Ellenbogen will be able to use these tools to recover detail in turbid water, adjust lighting to emphasize key subjects, or even simulate scenes that would be nearly impossible to capture in the field. The team also believes this approach may benefit other underwater photographers and image editors facing similar challenges. This hybrid method is designed to accelerate the curation process and enable storytellers to construct a more complete and coherent visual narrative of life beneath the surface.

      Left: Enhanced image of an American lobster using LOBSTgER’s image-to-image models. Right: Original image.

      Left: AI genertated image by Keith Ellenbogen, Andreas Mentzelopoulos, and LOBSTgER. Right: Keith Ellenbogen

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      In one key series, Ellenbogen captured high-resolution images of lion’s mane jellyfish, blue sharks, American lobsters, and ocean sunfish (Mola mola) while free diving in coastal waters. “Getting a high-quality dataset is not easy,” Ellenbogen says. “It requires multiple dives, missed opportunities, and unpredictable conditions. But these challenges are part of what makes underwater documentation both difficult and rewarding.”Mentzelopoulos has developed original code to train a family of latent diffusion models for LOBSTgER grounded on Ellenbogen’s images. Developing such models requires a high level of technical expertise, and training models from scratch is a complex process demanding hundreds of hours of computation and meticulous hyperparameter tuning.The project reflects a parallel process: field documentation through photography and model development through iterative training. Ellenbogen works in the field, capturing rare and fleeting encounters with marine animals; Mentzelopoulos works in the lab, translating those moments into machine-learning contexts that can extend and reinterpret the visual language of the ocean.“The goal isn’t to replace photography,” Mentzelopoulos says. “It’s to build on and complement it — making the invisible visible, and helping people see environmental complexity in a way that resonates both emotionally and intellectually. Our models aim to capture not just biological realism, but the emotional charge that can drive real-world engagement and action.”LOBSTgER points to a hybrid future that merges direct observation with technological interpretation. The team’s long-term goal is to develop a comprehensive model that can visualize a wide range of species found in the Gulf of Maine and, eventually, apply similar methods to marine ecosystems around the world.The researchers suggest that photography and generative AI form a continuum, rather than a conflict. Photography captures what is — the texture, light, and animal behavior during actual encounters — while AI extends that vision beyond what is seen, toward what could be understood, inferred, or imagined based on scientific data and artistic vision. Together, they offer a powerful framework for communicating science through image-making.In a region where ecosystems are changing rapidly, the act of visualizing becomes more than just documentation. It becomes a tool for awareness, engagement, and, ultimately, conservation. LOBSTgER is still in its infancy, and the team looks forward to sharing more discoveries, images, and insights as the project evolves.Answer from the lead image: The left image was generated using using LOBSTgER’s unconditional models and the right image is real.For more information, contact Keith Ellenbogen and Andreas Mentzelopoulos. More