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      MIT in the media: 2023 in review

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      It was an eventful trip around the sun for MIT this year, from President Sally Kornbluth’s inauguration and Mark Rober’s Commencement address to Professor Moungi Bawendi winning the Nobel Prize in Chemistry. In 2023 MIT researchers made key advances, detecting a dying star swallowing a planet, exploring the frontiers of artificial intelligence, creating clean energy solutions, inventing tools aimed at earlier detection and diagnosis of cancer, and even exploring the science of spreading kindness. Below are highlights of some of the uplifting people, breakthroughs, and ideas from MIT that made headlines in 2023.

      The gift: Kindness goes viral with Steve HartmanSteve Hartman visited Professor Anette “Peko” Hosoi to explore the science behind whether a single act of kindness can change the world.Full story via CBS News

      Trio wins Nobel Prize in chemistry for work on quantum dots, used in electronics and medical imaging“The motivation really is the basic science. A basic understanding, the curiosity of ‘how does the world work?’” said Professor Moungi Bawendi of the inspiration for his research on quantum dots, for which he was co-awarded the 2023 Nobel Prize in Chemistry.Full story via the Associated Press

      How MIT’s all-women leadership team plans to change science for the betterPresident Sally Kornbluth, Provost Cynthia Barnhart, and Chancellor Melissa Nobles emphasized the importance of representation for women and underrepresented groups in STEM.Full story via Radio Boston

      MIT via community college? Transfer students find a new path to a degreeUndergraduate Subin Kim shared his experience transferring from community college to MIT through the Transfer Scholars Network, which is aimed at helping community college students find a path to four-year universities.Full story via the Christian Science Monitor

      MIT president Sally Kornbluth doesn’t think we can hit the pause button on AIPresident Kornbluth discussed the future of AI, ethics in science, and climate change with columnist Shirley Leung on her new “Say More” podcast. “I view [the climate crisis] as an existential issue to the extent that if we don’t take action there, all of the many, many other things that we’re working on, not that they’ll be irrelevant, but they’ll pale in comparison,” Kornbluth said.Full story via The Boston Globe 

      It’s the end of a world as we know itAstronomers from MIT, Harvard University, Caltech and elsewhere spotted a dying star swallowing a large planet. Postdoc Kishalay De explained that: “Finding an event like this really puts all of the theories that have been out there to the most stringent tests possible. It really opens up this entire new field of research.”Full story via The New York Times

      Frontiers of AI

      Hey, Alexa, what should students learn about AI?The Day of AI is a program developed by the MIT RAISE initiative aimed at introducing and teaching K-12 students about AI. “We want students to be informed, responsible users and informed, responsible designers of these technologies,” said Professor Cynthia Breazeal, dean of digital learning at MIT.Full story via The New York Times

      AI tipping pointFour faculty members from across MIT — Professors Song Han, Simon Johnson, Yoon Kim and Rosalind Picard — described the opportunities and risks posed by the rapid advancements in the field of AI.Full story via Curiosity Stream 

      A look into the future of AI at MIT’s robotics laboratoryProfessor Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory, discussed the future of artificial intelligence, robotics, and machine learning, emphasizing the importance of balancing the development of new technologies with the need to ensure they are deployed in a way that benefits humanity.Full story via Mashable

      Health care providers say artificial intelligence could transform medicineProfessor Regina Barzilay spoke about her work developing new AI systems that could be used to help diagnose breast and lung cancer before the cancers are detectable to the human eye.Full story via Chronicle

      Is AI coming for your job? Tech experts weigh in: “They don’t replace human labor”Professor David Autor discussed how the rise of artificial intelligence could change the quality of jobs available.Full story via CBS News

      Big tech is bad. Big AI will be worse.Institute Professor Daron Acemoglu and Professor Simon Johnson made the case that “rather than machine intelligence, what we need is ‘machine usefulness,’ which emphasizes the ability of computers to augment human capabilities.”Full story via The New York Times

      Engineering excitement

      MIT’s 3D-printed hearts could pump new life into customized treatments MIT engineers developed a technique for 3D printing a soft, flexible, custom-designed replica of a patient’s heart.Full story via WBUR

      Mystery of why Roman buildings have survived so long has been unraveled, scientists sayScientists from MIT and other institutions discovered that ancient Romans used lime clasts when manufacturing concrete, giving the material self-healing properties.Full story via CNN

      The most interesting startup in America is in Massachusetts. You’ve probably never heard of it.VulcanForms, an MIT startup, is at the “leading edge of a push to transform 3D printing from a niche technology — best known for new-product prototyping and art-class experimentation — into an industrial force.”Full story via The Boston Globe

      Catalyzing climate innovations

      Can Boston’s energy innovators save the world?Boston Magazine reporter Rowan Jacobsen spotlighted how MIT faculty, students, and alumni are leading the charge in clean energy startups. “When it comes to game-changing breakthroughs in energy, three letters keep surfacing again and again: MIT,” writes Jacobsen.Full story via Boston Magazine

      MIT research could be game changer in combating water shortagesMIT researchers discovered that a common hydrogel used in cosmetic creams, industrial coatings, and pharmaceutical capsules can absorb moisture from the atmosphere even as the temperature rises. “For a planet that’s getting hotter, this could be a game-changing discovery.”Full story via NBC Boston

      Energy-storing concrete could form foundations for solar-powered homesMIT engineers uncovered a new way of creating an energy supercapacitor by combining cement, carbon black, and water that could one day be used to power homes or electric vehicles.Full story via New Scientist

      MIT researchers tackle key question of EV adoption: When to charge?MIT scientists found that delayed charging and strategic placement of EV charging stations could help reduce additional energy demands caused by more widespread EV adoption.Full story via Fast Company

      Building better buildingsProfessor John Fernández examined how to reduce the climate footprints of homes and office buildings, recommending creating airtight structures, switching to cleaner heating sources, using more environmentally friendly building materials, and retrofitting existing homes and offices.Full story via The New York Times

      They’re building an “ice penetrator” on a hillside in WestfordResearchers from MIT’s Haystack Observatory built an “ice penetrator,” a device designed to monitor the changing conditions of sea ice.Full story via The Boston Globe

      Healing health solutions

      How Boston is beating cancerMIT researchers are developing drug-delivery nanoparticles aimed at targeting cancer cells without disturbing healthy cells. Essentially, the nanoparticles are “engineered for selectivity,” explained Professor Paula Hammond, head of MIT’s Department of Chemical Engineering.Full story via Boston Magazine

      A new antibiotic, discovered with artificial intelligence, may defeat a dangerous superbugUsing a machine-learning algorithm, researchers from MIT discovered a type of antibiotic that’s effective against a particular strain of drug-resistant bacteria.Full story via CNN

      To detect breast cancer sooner, an MIT professor designs an ultrasound braMIT researchers designed a wearable ultrasound device that attaches to a bra and could be used to detect early-stage breast tumors.Full story via STAT

      The quest for a switch to turn on hungerAn ingestible pill developed by MIT scientists can raise levels of hormones to help increase appetite and decrease nausea in patients with gastroparesis.Full story via Wired

      Here’s how to use dreams for creative inspirationMIT scientists found that the earlier stages of sleep are key to sparking creativity and that people can be guided to dream about specific topics, further boosting creativity.Full story via Scientific American

      Astounding art

      An AI opera from 1987 reboots for a new generationProfessor Tod Machover discussed the restaging of his opera “VALIS” at MIT, which featured an artificial intelligence-assisted musical instrument developed by Nina Masuelli ’23.Full story via The Boston Globe

      Surfacing the stories hidden in migration dataAssociate Professor Sarah Williams discussed the Civic Data Design Lab’s “Motivational Tapestry,” a large woven art piece that uses data from the United Nations World Food Program to visually represent the individual motivations of 1,624 Central Americans who have migrated to the U.S.Full story via Metropolis

      Augmented reality-infused production of Wagner’s “Parsifal” opens Bayreuth FestivalProfessor Jay Scheib’s augmented reality-infused production of Richard Wagner’s “Parsifal” brought “fantastical images” to audience members.Full story via the Associated Press

      Understanding our universe

      New image reveals violent events near a supermassive black holeScientists captured a new image of M87*, the black hole at the center of the Messier 87 galaxy, showing the “launching point of a colossal jet of high-energy particles shooting outward into space.”Full story via Reuters

      Gravitational waves: A new universeMIT researchers Lisa Barsotti, Deep Chatterjee, and Victoria Xu explored how advances in gravitational wave detection are enabling a better understanding of the universe.Full story via Curiosity Stream 

      Nergis Mavalvala helped detect the first gravitational wave. Her work doesn’t stop thereProfessor Nergis Mavalvala, dean of the School of Science, discussed her work searching for gravitational waves, the importance of skepticism in scientific research, and why she enjoys working with young people.Full story via Wired

      Hitting the books

      “The Transcendent Brain” review: Beyond ones and zeroesIn his book “The Transcendent Brain: Spirituality in the Age of Science,” Alan Lightman, a professor of the practice of humanities, displayed his gift for “distilling complex ideas and emotions to their bright essence.”Full story via The Wall Street Journal

      What happens when CEOs treat workers better? Companies (and workers) win.Professor of the practice Zeynep Ton published a book, “The Case for Good Jobs,” and is “on a mission to change how company leaders think, and how they treat their employees.”Full story via The Boston Globe

      How to wage war on conspiracy theoriesProfessor Adam Berinsky’s book, “Political Rumors: Why We Accept Misinformation and How to Fight it,” examined “attitudes toward both politics and health, both of which are undermined by distrust and misinformation in ways that cause harm to both individuals and society.”Full story via Politico

      What it takes for Mexican coders to cross the cultural border with Silicon ValleyAssistant Professor Héctor Beltrán discussed his new book, “Code Work: Hacking across the U.S./México Techno-Borderlands,” which explores the culture of hackathons and entrepreneurship in Mexico.Full story via Marketplace

      Cultivating community

      The Indigenous rocketeerNicole McGaa, a fourth-year student at MIT, discussed her work leading MIT’s all-Indigenous rocket team at the 2023 First Nations Launch National Rocket Competition.Full story via Nature

      “You totally got this,” YouTube star and former NASA engineer Mark Rober tells MIT graduatesDuring his Commencement address at MIT, Mark Rober urged graduates to embrace their accomplishments and boldly face any challenges they encounter.Full story via The Boston Globe

      MIT Juggling Club going strong after half centuryAfter almost 50 years, the MIT Juggling Club, which was founded in 1975 and then merged with a unicycle club, is the oldest drop-in juggling club in continuous operation and still welcomes any aspiring jugglers to come toss a ball (or three) into the air.Full story via Cambridge Day

      Volpe Transportation Center opens as part of $750 million deal between MIT and fedsThe John A. Volpe National Transportation Systems Center in Kendall Square was the first building to open in MIT’s redevelopment of the 14-acre Volpe site that will ultimately include “research labs, retail, affordable housing, and open space, with the goal of not only encouraging innovation, but also enhancing the surrounding community.”Full story via The Boston Globe

      Sparking conversation

      The future of AI innovation and the role of academics in shaping itProfessor Daniela Rus emphasized the central role universities play in fostering innovation and the importance of ensuring universities have the computing resources necessary to help tackle major global challenges.Full story via The Boston Globe

      Moving the needle on supply chain sustainabilityProfessor Yossi Sheffi examined several strategies companies could use to help improve supply chain sustainability, including redesigning last-mile deliveries, influencing consumer choices and incentivizing returnable containers.Full story via The Hill

      Expelled from the mountain top?Sylvester James Gates Jr. ’73, PhD ’77 made the case that “diverse learning environments expose students to a broader range of perspectives, enhance education, and inculcate creativity and innovative habits of mind.”Full story via Science

      Marketing magic of “Barbie” movie has lessons for women’s sportsMIT Sloan Lecturer Shira Springer explored how the success of the “Barbie” movie could be applied to women’s sports.Full story via Sports Business Journal

      We’re already paying for universal health care. Why don’t we have it?Professor Amy Finkelstein asserted that the solution to health insurance reform in the U.S. is “universal coverage that is automatic, free and basic.”Full story via The New York Times 

      The internet could be so good. Really.Professor Deb Roy described how “new kinds of social networks can be designed for constructive communication — for listening, dialogue, deliberation, and mediation — and they can actually work.”Full story via The Atlantic

      Fostering educational excellence

      MIT students give legendary linear algebra professor standing ovation in last lectureAfter 63 years of teaching and over 10 million views of his online lectures, Professor Gilbert Strang received a standing ovation after his last lecture on linear algebra. “I am so grateful to everyone who likes linear algebra and sees its importance. So many universities (and even high schools) now appreciate how beautiful it is and how valuable it is,” said Strang.Full story via USA Today

      “Brave Behind Bars”: Reshaping the lives of inmates through coding classesGraduate students Martin Nisser and Marisa Gaetz co-founded Brave Behind Bars, a program designed to provide incarcerated individuals with coding and digital literacy skills to better prepare them for life after prison.Full story via MSNBC

      Melrose TikTok user “Ms. Nuclear Energy” teaching about nuclear power through social mediaGraduate student Kaylee Cunningham discussed her work using social media to help educate and inform the public about nuclear energy.Full story via CBS Boston  More

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      in Energy

      AI meets climate: MIT Energy and Climate Hack 2023

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      The MIT Energy and Climate Hack brought together participants from myriad fields and disciplines to develop rapid, innovative solutions to one of the most complex challenges facing society today: the global energy and climate crisis. Hundreds of students from MIT and colleges across the globe convened on MIT’s campus and virtually for this year’s event, which was held Nov. 10-12.

      Established in 2013, the MIT Energy and Climate Hack has been the launchpad for innovative and sustainable solutions for a decade; an annual reminder that exciting new ideas are always just around the corner.

      According to Claire Lorenzo, an MIT student organizer and communications director for this year’s Energy and Climate Hack, “There were a lot of people from a lot of places who showed up; both virtually and in person. It was encouraging to see how driven everyone was. How passionate they were about finding great solutions. You could see these ideas starting to form immediately.”

      On the first day, representatives from companies across numerous industries presented participants with their most pressing energy and climate-related challenges. Once the gathering broke into teams, participants had two days to “hack the challenge” they were assigned and present their solution to company representatives, fellow hackers, and judges.  

      The focus areas at this year’s event were energy markets, transportation, and farms and forests. Participating corporate sponsors included Google, Crusoe, Ironwood, Foothill Ventures, Koidra, Mitra Chem, Avangrid, Schneider Electric, First Solar, and Climate Ledger. 

      This year’s event also marked the first time that artificial intelligence emerged as a viable tool for developing creative climate solutions. Lorenzo observed, “I’m studying computer science, so exploring how AI could be harnessed to have a positive impact on the climate was particularly exciting for me. It can be applicable to virtually any domain. Like transportation, [with emissions] for example. In agriculture, too.”

      Energy and Climate Hack organizers identified the implementation of four core AI applications for special consideration: the acceleration of discovery (shortening the development process while simultaneously producing less waste), optimizing real-world solutions (utilizing automation to increase efficiency), prediction (using AI to improve prediction algorithms), and processing unstructured data (using AI to analyze and scale large amounts of data efficiently).

      “If there was a shared sentiment among the participants, it would probably be the idea that there isn’t a singular solution to climate change,” says Lorenzo, “and that requires cooperation from various industries, leveraging knowledge and experience from numerous fields, to make a lasting impact.”

      After the initial round of presentations concluded, one team from each challenge advanced from the preliminary presentation judging session to the final presentation round, where they pitched their solutions to a crowded room of attendees. Once the semi-finalists had pitched their solutions, the judges deliberated over the entries and selected team Fenergy, which worked in the energy markets sector, as the winners. The team, consisting of Alessandro Fumi, Amal Nammouchi, Amaury De Bock, Cyrine Chaabani, and Robbie Lee V, said, “Our solution, Unbiased Cathode, enables researchers to assess the supply chain implications of battery materials before development begins, hence reducing the lab-to-production timeline.”

      “They created a LLM [large language model]-powered tool that allows innovative new battery technologies to be iterated and developed much more efficiently,” Lorenzo added.

      When asked what she will remember most about her first experience at the MIT Energy and Climate Hack, Lorenzo replied, “Having hope for the future. Hope from seeing the passion that so many people have to find a solution. Hope from seeing all of these individuals come so far to tackle this challenge and make a difference. If we continue to develop and implement solutions like these on a global level, I am hopeful.”

      Students interested in learning more about the MIT Energy and Climate Hackathon, or participating in next year’s Hack, can find more information on the event website. More

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      Celebrating Kendall Square’s past and shaping its future

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      Kendall Square’s community took a deep dive into the history and future of the region at the Kendall Square Association’s 15th annual meeting on Oct. 19.

      It’s no secret that Kendall Square, located in Cambridge, Massachusetts, moves fast. The event, titled “Looking Back, Looking Ahead,” gave community members a chance to pause and reflect on how far the region has come and to discuss efforts to shape where it’s going next.

      “The impact of the last 15 years of working together with a purposeful commitment to make the world a better place was on display this evening,” KSA Executive Director Beth O’Neill Maloney told the audience toward the end of the evening. “It also shows how Kendall Square can continue contributing to the world.”

      The gathering took place at the Microsoft NERD Center on Memorial Drive, on a floor that also featured music from the Kendall Square Orchestra and, judging by the piles of empty trays at the end of the night, an exceedingly popular selection of food from Kendall Square restaurants. Attendees came from across Cambridge’s prolific innovation ecosystem — not just entrepreneurs and life science workers but also high school and college students, restaurant and retail shop owners, workers at local cleantech and robotics companies, and leaders of nonprofits.

      KSA itself is a nonprofit made up of over 150 organizations across Kendall Square, from major companies to universities like MIT to research organizations like the Broad Institute of MIT and Harvard and the independent shops and restaurants that give Kendall Square its distinct character.

      The night’s programming included talks about recent funding achievements in the region, a panel discussion on the implications of artificial intelligence, and a highly entertaining, whirlwind history lesson led by Daniel Berger-Jones of Cambridge Historical Tours.

      “Our vision for the state is to be the best, and Kendall really represents that,” said Yvonne Hao, Massachusetts secretary of economic development. “When I went to DC to talk to folks about why Massachusetts should win some of these grants, they said, ‘You already have Kendall, that’s what we’re trying to get the whole country to be like!’”

      Hao started her talk by noting her personal connection to Kendall Square. She moved to Cambridge with her family in 2010 and has watched the neighborhood transform, with her kids frequenting the old and new restaurants and shops around town.

      The crux of Hao’s talk was to remind attendees they had more to celebrate than KSA’s anniversary. Massachusetts was recently named the recipient of two major federal grants that will fuel the state’s innovation work. One of those grants, from the Advanced Research Projects Agency for Health (ARPA-H), designated the state an “Investor Catalyst Hub” to accelerate innovation around health care. The other, which came through the federal CHIPS and Science Act, will allow the state to establish the Northeast Microelectronics Coalition Hub to advance microelectronics jobs, workforce training opportunities, and investment in the region’s advanced manufacturing.

      Hao recalled making the pitch for the grants, which could collectively amount to hundreds of millions of dollars in funding over time.

      “The pitch happened in Kendall Square because Kendall highlights everything magical about Massachusetts — we have our universities, MIT, we have our research institutions, nonprofits, small businesses, and great community members,” Hao said. “We were hoping for good weather because we wanted to walk with government officials, because when you walk around Kendall, you see the art, you see the coffee shops, you see the people bumping into each other and talking, and you see why it’s so important that this one square mile of geography become the hub they were looking for.”

      Hao is also part of work to put together the state’s newest economic development plan. She said the group’s tier one priorities are transportation and housing, but listed a number of other areas where she hopes Massachusetts can improve.

      “We can be an amazing, strong economy that’s mission-driven and innovation-driven with all kinds of jobs for all kinds of people, and at the same time an awesome community that loves each other and has great food and small businesses and looks out for each other, that looks diverse just like this room,” Hao said. “That’s the story we want to tell.”

      After the historical tour and the debut of a video explaining the origins of the KSA, attendees fast-forwarded into the future with a panel discussion on the impact and implications of generative AI.

      “I think the paradigm shift we’re seeing with generative AI is going to be as transformative as the internet, perhaps even more so because the pace of adoption is much faster now,” said Microsoft’s Soundar Srinivasan.

      The panel also featured Jennat Jounaidi, a student at Cambridge Rindge and Latin School and member of Innovators for Purpose, a nonprofit that seeks to empower young people from historically marginalized groups to become innovators.

      “I’m interested to see how generative AI shapes my upbringing as well as the lives of future generations, and I think it’s a pivotal moment to decide how we can best develop and incorporate AI into all of our lives,” Jounaidi said.

      Panelists noted that today’s concerns around AI are important, such as its potential to perpetuate inequality and amplify misinformation. But they also discussed the technology’s potential to drive advances in areas like sustainability and health care.

      “I came to Kendall Square to do my PhD in AI at MIT back when the internet was called the ARPA-Net… so a while ago,” said Jeremy Wertheimer SM ’89, PhD ’96. “One of the dreams I had back then was to create a program to read all biology papers. We’re not quite there yet, but I think we’re on the cusp, and it’s very exciting.

      Above all else, the panelists characterized AI as an opportunity. Despite all that’s been accomplished in Kendall Square to date, the prevailing feeling at the event was excitement for the future.

      “Generative AI is giving us chance to stop working in siloes,” Jounaidi said. “Many people in this room go back to their companies and think about corporate responsibility, and I want to expand that to creating shared value in companies by seeking out the community and the people here. I think that’s important, and I’m excited to see what comes next.” More

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      in Energy

      New tools are available to help reduce the energy that AI models devour

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      When searching for flights on Google, you may have noticed that each flight’s carbon-emission estimate is now presented next to its cost. It’s a way to inform customers about their environmental impact, and to let them factor this information into their decision-making.

      A similar kind of transparency doesn’t yet exist for the computing industry, despite its carbon emissions exceeding those of the entire airline industry. Escalating this energy demand are artificial intelligence models. Huge, popular models like ChatGPT signal a trend of large-scale artificial intelligence, boosting forecasts that predict data centers will draw up to 21 percent of the world’s electricity supply by 2030.

      The MIT Lincoln Laboratory Supercomputing Center (LLSC) is developing techniques to help data centers reel in energy use. Their techniques range from simple but effective changes, like power-capping hardware, to adopting novel tools that can stop AI training early on. Crucially, they have found that these techniques have a minimal impact on model performance.

      In the wider picture, their work is mobilizing green-computing research and promoting a culture of transparency. “Energy-aware computing is not really a research area, because everyone’s been holding on to their data,” says Vijay Gadepally, senior staff in the LLSC who leads energy-aware research efforts. “Somebody has to start, and we’re hoping others will follow.”

      Curbing power and cooling down

      Like many data centers, the LLSC has seen a significant uptick in the number of AI jobs running on its hardware. Noticing an increase in energy usage, computer scientists at the LLSC were curious about ways to run jobs more efficiently. Green computing is a principle of the center, which is powered entirely by carbon-free energy.

      Training an AI model — the process by which it learns patterns from huge datasets — requires using graphics processing units (GPUs), which are power-hungry hardware. As one example, the GPUs that trained GPT-3 (the precursor to ChatGPT) are estimated to have consumed 1,300 megawatt-hours of electricity, roughly equal to that used by 1,450 average U.S. households per month.

      While most people seek out GPUs because of their computational power, manufacturers offer ways to limit the amount of power a GPU is allowed to draw. “We studied the effects of capping power and found that we could reduce energy consumption by about 12 percent to 15 percent, depending on the model,” Siddharth Samsi, a researcher within the LLSC, says.

      The trade-off for capping power is increasing task time — GPUs will take about 3 percent longer to complete a task, an increase Gadepally says is “barely noticeable” considering that models are often trained over days or even months. In one of their experiments in which they trained the popular BERT language model, limiting GPU power to 150 watts saw a two-hour increase in training time (from 80 to 82 hours) but saved the equivalent of a U.S. household’s week of energy.

      The team then built software that plugs this power-capping capability into the widely used scheduler system, Slurm. The software lets data center owners set limits across their system or on a job-by-job basis.

      “We can deploy this intervention today, and we’ve done so across all our systems,” Gadepally says.

      Side benefits have arisen, too. Since putting power constraints in place, the GPUs on LLSC supercomputers have been running about 30 degrees Fahrenheit cooler and at a more consistent temperature, reducing stress on the cooling system. Running the hardware cooler can potentially also increase reliability and service lifetime. They can now consider delaying the purchase of new hardware — reducing the center’s “embodied carbon,” or the emissions created through the manufacturing of equipment — until the efficiencies gained by using new hardware offset this aspect of the carbon footprint. They’re also finding ways to cut down on cooling needs by strategically scheduling jobs to run at night and during the winter months.

      “Data centers can use these easy-to-implement approaches today to increase efficiencies, without requiring modifications to code or infrastructure,” Gadepally says.

      Taking this holistic look at a data center’s operations to find opportunities to cut down can be time-intensive. To make this process easier for others, the team — in collaboration with Professor Devesh Tiwari and Baolin Li at Northeastern University — recently developed and published a comprehensive framework for analyzing the carbon footprint of high-performance computing systems. System practitioners can use this analysis framework to gain a better understanding of how sustainable their current system is and consider changes for next-generation systems.  

      Adjusting how models are trained and used

      On top of making adjustments to data center operations, the team is devising ways to make AI-model development more efficient.

      When training models, AI developers often focus on improving accuracy, and they build upon previous models as a starting point. To achieve the desired output, they have to figure out what parameters to use, and getting it right can take testing thousands of configurations. This process, called hyperparameter optimization, is one area LLSC researchers have found ripe for cutting down energy waste. 

      “We’ve developed a model that basically looks at the rate at which a given configuration is learning,” Gadepally says. Given that rate, their model predicts the likely performance. Underperforming models are stopped early. “We can give you a very accurate estimate early on that the best model will be in this top 10 of 100 models running,” he says.

      In their studies, this early stopping led to dramatic savings: an 80 percent reduction in the energy used for model training. They’ve applied this technique to models developed for computer vision, natural language processing, and material design applications.

      “In my opinion, this technique has the biggest potential for advancing the way AI models are trained,” Gadepally says.

      Training is just one part of an AI model’s emissions. The largest contributor to emissions over time is model inference, or the process of running the model live, like when a user chats with ChatGPT. To respond quickly, these models use redundant hardware, running all the time, waiting for a user to ask a question.

      One way to improve inference efficiency is to use the most appropriate hardware. Also with Northeastern University, the team created an optimizer that matches a model with the most carbon-efficient mix of hardware, such as high-power GPUs for the computationally intense parts of inference and low-power central processing units (CPUs) for the less-demanding aspects. This work recently won the best paper award at the International ACM Symposium on High-Performance Parallel and Distributed Computing.

      Using this optimizer can decrease energy use by 10-20 percent while still meeting the same “quality-of-service target” (how quickly the model can respond).

      This tool is especially helpful for cloud customers, who lease systems from data centers and must select hardware from among thousands of options. “Most customers overestimate what they need; they choose over-capable hardware just because they don’t know any better,” Gadepally says.

      Growing green-computing awareness

      The energy saved by implementing these interventions also reduces the associated costs of developing AI, often by a one-to-one ratio. In fact, cost is usually used as a proxy for energy consumption. Given these savings, why aren’t more data centers investing in green techniques?

      “I think it’s a bit of an incentive-misalignment problem,” Samsi says. “There’s been such a race to build bigger and better models that almost every secondary consideration has been put aside.”

      They point out that while some data centers buy renewable-energy credits, these renewables aren’t enough to cover the growing energy demands. The majority of electricity powering data centers comes from fossil fuels, and water used for cooling is contributing to stressed watersheds. 

      Hesitancy may also exist because systematic studies on energy-saving techniques haven’t been conducted. That’s why the team has been pushing their research in peer-reviewed venues in addition to open-source repositories. Some big industry players, like Google DeepMind, have applied machine learning to increase data center efficiency but have not made their work available for others to deploy or replicate. 

      Top AI conferences are now pushing for ethics statements that consider how AI could be misused. The team sees the climate aspect as an AI ethics topic that has not yet been given much attention, but this also appears to be slowly changing. Some researchers are now disclosing the carbon footprint of training the latest models, and industry is showing a shift in energy transparency too, as in this recent report from Meta AI.

      They also acknowledge that transparency is difficult without tools that can show AI developers their consumption. Reporting is on the LLSC roadmap for this year. They want to be able to show every LLSC user, for every job, how much energy they consume and how this amount compares to others, similar to home energy reports.

      Part of this effort requires working more closely with hardware manufacturers to make getting these data off hardware easier and more accurate. If manufacturers can standardize the way the data are read out, then energy-saving and reporting tools can be applied across different hardware platforms. A collaboration is underway between the LLSC researchers and Intel to work on this very problem.

      Even for AI developers who are aware of the intense energy needs of AI, they can’t do much on their own to curb this energy use. The LLSC team wants to help other data centers apply these interventions and provide users with energy-aware options. Their first partnership is with the U.S. Air Force, a sponsor of this research, which operates thousands of data centers. Applying these techniques can make a significant dent in their energy consumption and cost.

      “We’re putting control into the hands of AI developers who want to lessen their footprint,” Gadepally says. “Do I really need to gratuitously train unpromising models? Am I willing to run my GPUs slower to save energy? To our knowledge, no other supercomputing center is letting you consider these options. Using our tools, today, you get to decide.”

      Visit this webpage to see the group’s publications related to energy-aware computing and findings described in this article. More

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      in Environment

      AI pilot programs look to reduce energy use and emissions on MIT campus

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      Smart thermostats have changed the way many people heat and cool their homes by using machine learning to respond to occupancy patterns and preferences, resulting in a lower energy draw. This technology — which can collect and synthesize data — generally focuses on single-dwelling use, but what if this type of artificial intelligence could dynamically manage the heating and cooling of an entire campus? That’s the idea behind a cross-departmental effort working to reduce campus energy use through AI building controls that respond in real-time to internal and external factors. 

      Understanding the challenge

      Heating and cooling can be an energy challenge for campuses like MIT, where existing building management systems (BMS) can’t respond quickly to internal factors like occupancy fluctuations or external factors such as forecast weather or the carbon intensity of the grid. This results in using more energy than needed to heat and cool spaces, often to sub-optimal levels. By engaging AI, researchers have begun to establish a framework to understand and predict optimal temperature set points (the temperature at which a thermostat has been set to maintain) at the individual room level and take into consideration a host of factors, allowing the existing systems to heat and cool more efficiently, all without manual intervention. 

      “It’s not that different from what folks are doing in houses,” explains Les Norford, a professor of architecture at MIT, whose work in energy studies, controls, and ventilation connected him with the effort. “Except we have to think about things like how long a classroom may be used in a day, weather predictions, time needed to heat and cool a room, the effect of the heat from the sun coming in the window, and how the classroom next door might impact all of this.” These factors are at the crux of the research and pilots that Norford and a team are focused on. That team includes Jeremy Gregory, executive director of the MIT Climate and Sustainability Consortium; Audun Botterud, principal research scientist for the Laboratory for Information and Decision Systems; Steve Lanou, project manager in the MIT Office of Sustainability (MITOS); Fran Selvaggio, Department of Facilities Senior Building Management Systems engineer; and Daisy Green and You Lin, both postdocs.

      The group is organized around the call to action to “explore possibilities to employ artificial intelligence to reduce on-campus energy consumption” outlined in Fast Forward: MIT’s Climate Action Plan for the Decade, but efforts extend back to 2019. “As we work to decarbonize our campus, we’re exploring all avenues,” says Vice President for Campus Services and Stewardship Joe Higgins, who originally pitched the idea to students at the 2019 MIT Energy Hack. “To me, it was a great opportunity to utilize MIT expertise and see how we can apply it to our campus and share what we learn with the building industry.” Research into the concept kicked off at the event and continued with undergraduate and graduate student researchers running differential equations and managing pilots to test the bounds of the idea. Soon, Gregory, who is also a MITOS faculty fellow, joined the project and helped identify other individuals to join the team. “My role as a faculty fellow is to find opportunities to connect the research community at MIT with challenges MIT itself is facing — so this was a perfect fit for that,” Gregory says. 

      Early pilots of the project focused on testing thermostat set points in NW23, home to the Department of Facilities and Office of Campus Planning, but Norford quickly realized that classrooms provide many more variables to test, and the pilot was expanded to Building 66, a mixed-use building that is home to classrooms, offices, and lab spaces. “We shifted our attention to study classrooms in part because of their complexity, but also the sheer scale — there are hundreds of them on campus, so [they offer] more opportunities to gather data and determine parameters of what we are testing,” says Norford. 

      Developing the technology

      The work to develop smarter building controls starts with a physics-based model using differential equations to understand how objects can heat up or cool down, store heat, and how the heat may flow across a building façade. External data like weather, carbon intensity of the power grid, and classroom schedules are also inputs, with the AI responding to these conditions to deliver an optimal thermostat set point each hour — one that provides the best trade-off between the two objectives of thermal comfort of occupants and energy use. That set point then tells the existing BMS how much to heat up or cool down a space. Real-life testing follows, surveying building occupants about their comfort. Botterud, whose research focuses on the interactions between engineering, economics, and policy in electricity markets, works to ensure that the AI algorithms can then translate this learning into energy and carbon emission savings. 

      Currently the pilots are focused on six classrooms within Building 66, with the intent to move onto lab spaces before expanding to the entire building. “The goal here is energy savings, but that’s not something we can fully assess until we complete a whole building,” explains Norford. “We have to work classroom by classroom to gather the data, but are looking at a much bigger picture.” The research team used its data-driven simulations to estimate significant energy savings while maintaining thermal comfort in the six classrooms over two days, but further work is needed to implement the controls and measure savings across an entire year. 

      With significant savings estimated across individual classrooms, the energy savings derived from an entire building could be substantial, and AI can help meet that goal, explains Botterud: “This whole concept of scalability is really at the heart of what we are doing. We’re spending a lot of time in Building 66 to figure out how it works and hoping that these algorithms can be scaled up with much less effort to other rooms and buildings so solutions we are developing can make a big impact at MIT,” he says.

      Part of that big impact involves operational staff, like Selvaggio, who are essential in connecting the research to current operations and putting them into practice across campus. “Much of the BMS team’s work is done in the pilot stage for a project like this,” he says. “We were able to get these AI systems up and running with our existing BMS within a matter of weeks, allowing the pilots to get off the ground quickly.” Selvaggio says in preparation for the completion of the pilots, the BMS team has identified an additional 50 buildings on campus where the technology can easily be installed in the future to start energy savings. The BMS team also collaborates with the building automation company, Schneider Electric, that has implemented the new control algorithms in Building 66 classrooms and is ready to expand to new pilot locations. 

      Expanding impact

      The successful completion of these programs will also open the possibility for even greater energy savings — bringing MIT closer to its decarbonization goals. “Beyond just energy savings, we can eventually turn our campus buildings into a virtual energy network, where thousands of thermostats are aggregated and coordinated to function as a unified virtual entity,” explains Higgins. These types of energy networks can accelerate power sector decarbonization by decreasing the need for carbon-intensive power plants at peak times and allowing for more efficient power grid energy use.

      As pilots continue, they fulfill another call to action in Fast Forward — for campus to be a “test bed for change.” Says Gregory: “This project is a great example of using our campus as a test bed — it brings in cutting-edge research to apply to decarbonizing our own campus. It’s a great project for its specific focus, but also for serving as a model for how to utilize the campus as a living lab.” More

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      Jackson Jewett wants to design buildings that use less concrete

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      After three years leading biking tours through U.S. National Parks, Jackson Jewett decided it was time for a change.

      “It was a lot of fun, but I realized I missed buildings,” says Jewett. “I really wanted to be a part of that industry, learn more about it, and reconnect with my roots in the built environment.”

      Jewett grew up in California in what he describes as a “very creative household.”

      “I remember making very elaborate Halloween costumes with my parents, making fun dioramas for school projects, and building forts in the backyard, that kind of thing,” Jewett explains.

      Both of his parents have backgrounds in design; his mother studied art in college and his father is a practicing architect. From a young age, Jewett was interested in following in his father’s footsteps. But when he arrived at the University of California at Berkeley in the midst of the 2009 housing crash, it didn’t seem like the right time. Jewett graduated with a degree in cognitive science and a minor in history of architecture. And even as he led tours through Yellowstone, the Grand Canyon, and other parks, buildings were in the back of his mind.

      It wasn’t just the built environment that Jewett was missing. He also longed for the rigor and structure of an academic environment.

      Jewett arrived at MIT in 2017, initially only planning on completing the master’s program in civil and environmental engineering. It was then that he first met Josephine Carstensen, a newly hired lecturer in the department. Jewett was interested in Carstensen’s work on “topology optimization,” which uses algorithms to design structures that can achieve their performance requirements while using only a limited amount of material. He was particularly interested in applying this approach to concrete design, and he collaborated with Carstensen to help demonstrate its viability.

      After earning his master’s, Jewett spent a year and a half as a structural engineer in New York City. But when Carstensen was hired as a professor, she reached out to Jewett about joining her lab as a PhD student. He was ready for another change.

      Now in the third year of his PhD program, Jewett’s dissertation work builds upon his master’s thesis to further refine algorithms that can design building-scale concrete structures that use less material, which would help lower carbon emissions from the construction industry. It is estimated that the concrete industry alone is responsible for 8 percent of global carbon emissions, so any efforts to reduce that number could help in the fight against climate change.

      Implementing new ideas

      Topology optimization is a small field, with the bulk of the prior work being computational without any experimental verification. The work Jewett completed for his master’s thesis was just the start of a long learning process.

      “I do feel like I’m just getting to the part where I can start implementing my own ideas without as much support as I’ve needed in the past,” says Jewett. “In the last couple of months, I’ve been working on a reinforced concrete optimization algorithm that I hope will be the cornerstone of my thesis.”

      The process of fine-tuning a generative algorithm is slow going, particularly when tackling a multifaceted problem.

      “It can take days or usually weeks to take a step toward making it work as an entire integrated system,” says Jewett. “The days when that breakthrough happens and I can see the algorithm converging on a solution that makes sense — those are really exciting moments.”

      By harnessing computational power, Jewett is searching for materially efficient components that can be used to make up structures such as bridges or buildings. These are other constraints to consider as well, particularly ensuring that the cost of manufacturing isn’t too high. Having worked in the industry before starting the PhD program, Jewett has an eye toward doing work that can be feasibly implemented.

      Inspiring others

      When Jewett first visited MIT campus, he was drawn in by the collaborative environment of the institute and the students’ drive to learn. Now, he’s a part of that process as a teaching assistant and a supervisor in the Undergraduate Research Opportunities Program.  

      Working as a teaching assistant isn’t a requirement for Jewett’s program, but it’s been one of his favorite parts of his time at MIT.

      “The MIT undergrads are so gifted and just constantly impress me,” says Jewett. “Being able to teach, especially in the context of what MIT values is a lot of fun. And I learn, too. My coding practices have gotten so much better since working with undergrads here.”

      Jewett’s experiences have inspired him to pursue a career in academia after the completion of his program, which he expects to complete in the spring of 2025. But he’s making sure to take care of himself along the way. He still finds time to plan cycling trips with his friends and has gotten into running ever since moving to Boston. So far, he’s completed two marathons.

      “It’s so inspiring to be in a place where so many good ideas are just bouncing back and forth all over campus,” says Jewett. “And on most days, I remember that and it inspires me. But it’s also the case that academics is hard, PhD programs are hard, and MIT — there’s pressure being here, and sometimes that pressure can feel like it’s working against you.”

      Jewett is grateful for the mental health resources that MIT provides students. While he says it can be imperfect, it’s been a crucial part of his journey.

      “My PhD thesis will be done in 2025, but the work won’t be done. The time horizon of when these things need to be implemented is relatively short if we want to make an impact before global temperatures have already risen too high. My PhD research will be developing a framework for how that could be done with concrete construction, but I’d like to keep thinking about other materials and construction methods even after this project is finished.” More

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      Fast-tracking fusion energy’s arrival with AI and accessibility

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      As the impacts of climate change continue to grow, so does interest in fusion’s potential as a clean energy source. While fusion reactions have been studied in laboratories since the 1930s, there are still many critical questions scientists must answer to make fusion power a reality, and time is of the essence. As part of their strategy to accelerate fusion energy’s arrival and reach carbon neutrality by 2050, the U.S. Department of Energy (DoE) has announced new funding for a project led by researchers at MIT’s Plasma Science and Fusion Center (PSFC) and four collaborating institutions.

      Cristina Rea, a research scientist and group leader at the PSFC, will serve as the primary investigator for the newly funded three-year collaboration to pilot the integration of fusion data into a system that can be read by AI-powered tools. The PSFC, together with scientists from the College of William and Mary, the University of Wisconsin at Madison, Auburn University, and the nonprofit HDF Group, plan to create a holistic fusion data platform, the elements of which could offer unprecedented access for researchers, especially underrepresented students. The project aims to encourage diverse participation in fusion and data science, both in academia and the workforce, through outreach programs led by the group’s co-investigators, of whom four out of five are women. 

      The DoE’s award, part of a $29 million funding package for seven projects across 19 institutions, will support the group’s efforts to distribute data produced by fusion devices like the PSFC’s Alcator C-Mod, a donut-shaped “tokamak” that utilized powerful magnets to control and confine fusion reactions. Alcator C-Mod operated from 1991 to 2016 and its data are still being studied, thanks in part to the PSFC’s commitment to the free exchange of knowledge.

      Currently, there are nearly 50 public experimental magnetic confinement-type fusion devices; however, both historical and current data from these devices can be difficult to access. Some fusion databases require signing user agreements, and not all data are catalogued and organized the same way. Moreover, it can be difficult to leverage machine learning, a class of AI tools, for data analysis and to enable scientific discovery without time-consuming data reorganization. The result is fewer scientists working on fusion, greater barriers to discovery, and a bottleneck in harnessing AI to accelerate progress.

      The project’s proposed data platform addresses technical barriers by being FAIR — Findable, Interoperable, Accessible, Reusable — and by adhering to UNESCO’s Open Science (OS) recommendations to improve the transparency and inclusivity of science; all of the researchers’ deliverables will adhere to FAIR and OS principles, as required by the DoE. The platform’s databases will be built using MDSplusML, an upgraded version of the MDSplus open-source software developed by PSFC researchers in the 1980s to catalogue the results of Alcator C-Mod’s experiments. Today, nearly 40 fusion research institutes use MDSplus to store and provide external access to their fusion data. The release of MDSplusML aims to continue that legacy of open collaboration.

      The researchers intend to address barriers to participation for women and disadvantaged groups not only by improving general access to fusion data, but also through a subsidized summer school that will focus on topics at the intersection of fusion and machine learning, which will be held at William and Mary for the next three years.

      Of the importance of their research, Rea says, “This project is about responding to the fusion community’s needs and setting ourselves up for success. Scientific advancements in fusion are enabled via multidisciplinary collaboration and cross-pollination, so accessibility is absolutely essential. I think we all understand now that diverse communities have more diverse ideas, and they allow faster problem-solving.”

      The collaboration’s work also aligns with vital areas of research identified in the International Atomic Energy Agency’s “AI for Fusion” Coordinated Research Project (CRP). Rea was selected as the technical coordinator for the IAEA’s CRP emphasizing community engagement and knowledge access to accelerate fusion research and development. In a letter of support written for the group’s proposed project, the IAEA stated that, “the work [the researchers] will carry out […] will be beneficial not only to our CRP but also to the international fusion community in large.”

      PSFC Director and Hitachi America Professor of Engineering Dennis Whyte adds, “I am thrilled to see PSFC and our collaborators be at the forefront of applying new AI tools while simultaneously encouraging and enabling extraction of critical data from our experiments.”

      “Having the opportunity to lead such an important project is extremely meaningful, and I feel a responsibility to show that women are leaders in STEM,” says Rea. “We have an incredible team, strongly motivated to improve our fusion ecosystem and to contribute to making fusion energy a reality.” More

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      Supporting sustainability, digital health, and the future of work

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      The MIT and Accenture Convergence Initiative for Industry and Technology has selected three new research projects that will receive support from the initiative. The research projects aim to accelerate progress in meeting complex societal needs through new business convergence insights in technology and innovation.

      Established in MIT’s School of Engineering and now in its third year, the MIT and Accenture Convergence Initiative is furthering its mission to bring together technological experts from across business and academia to share insights and learn from one another. Recently, Thomas W. Malone, the Patrick J. McGovern (1959) Professor of Management, joined the initiative as its first-ever faculty lead. The research projects relate to three of the initiative’s key focus areas: sustainability, digital health, and the future of work.

      “The solutions these research teams are developing have the potential to have tremendous impact,” says Anantha Chandrakasan, dean of the School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “They embody the initiative’s focus on advancing data-driven research that addresses technology and industry convergence.”

      “The convergence of science and technology driven by advancements in generative AI, digital twins, quantum computing, and other technologies makes this an especially exciting time for Accenture and MIT to be undertaking this joint research,” says Kenneth Munie, senior managing director at Accenture Strategy, Life Sciences. “Our three new research projects focusing on sustainability, digital health, and the future of work have the potential to help guide and shape future innovations that will benefit the way we work and live.”

      The MIT and Accenture Convergence Initiative charter project researchers are described below.

      Accelerating the journey to net zero with industrial clusters

      Jessika Trancik is a professor at the Institute for Data, Systems, and Society (IDSS). Trancik’s research examines the dynamic costs, performance, and environmental impacts of energy systems to inform climate policy and accelerate beneficial and equitable technology innovation. Trancik’s project aims to identify how industrial clusters can enable companies to derive greater value from decarbonization, potentially making companies more willing to invest in the clean energy transition.

      To meet the ambitious climate goals that have been set by countries around the world, rising greenhouse gas emissions trends must be rapidly reversed. Industrial clusters — geographically co-located or otherwise-aligned groups of companies representing one or more industries — account for a significant portion of greenhouse gas emissions globally. With major energy consumers “clustered” in proximity, industrial clusters provide a potential platform to scale low-carbon solutions by enabling the aggregation of demand and the coordinated investment in physical energy supply infrastructure.

      In addition to Trancik, the research team working on this project will include Aliza Khurram, a postdoc in IDSS; Micah Ziegler, an IDSS research scientist; Melissa Stark, global energy transition services lead at Accenture; Laura Sanderfer, strategy consulting manager at Accenture; and Maria De Miguel, strategy senior analyst at Accenture.

      Eliminating childhood obesity

      Anette “Peko” Hosoi is the Neil and Jane Pappalardo Professor of Mechanical Engineering. A common theme in her work is the fundamental study of shape, kinematic, and rheological optimization of biological systems with applications to the emergent field of soft robotics. Her project will use both data from existing studies and synthetic data to create a return-on-investment (ROI) calculator for childhood obesity interventions so that companies can identify earlier returns on their investment beyond reduced health-care costs.

      Childhood obesity is too prevalent to be solved by a single company, industry, drug, application, or program. In addition to the physical and emotional impact on children, society bears a cost through excess health care spending, lost workforce productivity, poor school performance, and increased family trauma. Meaningful solutions require multiple organizations, representing different parts of society, working together with a common understanding of the problem, the economic benefits, and the return on investment. ROI is particularly difficult to defend for any single organization because investment and return can be separated by many years and involve asymmetric investments, returns, and allocation of risk. Hosoi’s project will consider the incentives for a particular entity to invest in programs in order to reduce childhood obesity.

      Hosoi will be joined by graduate students Pragya Neupane and Rachael Kha, both of IDSS, as well a team from Accenture that includes Kenneth Munie, senior managing director at Accenture Strategy, Life Sciences; Kaveh Safavi, senior managing director in Accenture Health Industry; and Elizabeth Naik, global health and public service research lead.

      Generating innovative organizational configurations and algorithms for dealing with the problem of post-pandemic employment

      Thomas Malone is the Patrick J. McGovern (1959) Professor of Management at the MIT Sloan School of Management and the founding director of the MIT Center for Collective Intelligence. His research focuses on how new organizations can be designed to take advantage of the possibilities provided by information technology. Malone will be joined in this project by John Horton, the Richard S. Leghorn (1939) Career Development Professor at the MIT Sloan School of Management, whose research focuses on the intersection of labor economics, market design, and information systems. Malone and Horton’s project will look to reshape the future of work with the help of lessons learned in the wake of the pandemic.

      The Covid-19 pandemic has been a major disrupter of work and employment, and it is not at all obvious how governments, businesses, and other organizations should manage the transition to a desirable state of employment as the pandemic recedes. Using natural language processing algorithms such as GPT-4, this project will look to identify new ways that companies can use AI to better match applicants to necessary jobs, create new types of jobs, assess skill training needed, and identify interventions to help include women and other groups whose employment was disproportionately affected by the pandemic.

      In addition to Malone and Horton, the research team will include Rob Laubacher, associate director and research scientist at the MIT Center for Collective Intelligence, and Kathleen Kennedy, executive director at the MIT Center for Collective Intelligence and senior director at MIT Horizon. The team will also include Nitu Nivedita, managing director of artificial intelligence at Accenture, and Thomas Hancock, data science senior manager at Accenture. More