Nature Climate Change, Published online: 07 August 2025; doi:10.1038/s41558-025-02373-3

The decarbonization of energy systems requires access to minerals that are critical for manufacturing low-carbon technologies. Here researchers show that meeting climate targets could be impeded by material shortages, revealing the importance of diverse solutions that balance mitigation, equity and resource constraints.

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.

“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 Thomas D. and Virginia W. Cabot 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 study

Traffic 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 open street maps, 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.

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 benefits

When 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.

Nature Climate Change, Published online: 07 August 2025; doi:10.1038/s41558-025-02394-y

The implementation gap between national climate targets and actual policies has been seen as a main barrier for decarbonization. Here researchers show it is rooted in the structural limitation of states and discuss future research directions to promote the emergence of transformative states.

The MIT Center for International Studies announced the launch of a new pilot initiative with Angola, to be implemented through its MIT-Africa Program.

The new initiative marks a significant collaboration between MIT-Africa, Sonangol (Angola’s national energy company), and the Instituto Superior Politécnico de Tecnologias e Ciências (ISPTEC). The collaboration was formalized at a signing ceremony on MIT’s campus in June with key stakeholders from all three institutions present, including Diamantino Pedro Azevedo, the Angolan minister of mineral resources, petroleum, and gas, and Sonangol CEO Gaspar Martins.

“This partnership marks a pivotal step in the Angolan government’s commitment to leveraging knowledge as the cornerstone of the country’s economic transformation,” says Azevedo. “By connecting the oil and gas sector with science, innovation, and world-class training, we are equipping future generations to lead Angola into a more technological, sustainable, and globally competitive era.”

The sentiment is shared by the MIT-Africa Program leaders. “This initiative reflects MIT’s deep commitment to fostering meaningful, long-term relationships across the African continent,” says Mai Hassan, faculty director of the MIT-Africa Program. “It supports our mission of advancing knowledge and educating students in ways that are globally informed, and it provides a platform for mutual learning. By working with Angolan partners, we gain new perspectives and opportunities for innovation that benefit both MIT and our collaborators.”

In addition to its new collaboration with MIT-Africa, Sonangol has joined MIT’s Industrial Liaison Program (ILP), breaking new ground as its first corporate member based in sub-Saharan Africa. ILP enables companies worldwide to harness MIT resources to address current challenges and to anticipate future needs. As an ILP member, Sonangol seeks to facilitate collaboration in key sectors such as natural resources and mining, energy, construction, and infrastructure.

The MIT-Africa Program manages a portfolio of research, teaching, and learning initiatives that emphasize two-way value — offering impactful experiences to MIT students and faculty while collaborating closely with institutions and communities across Africa. The new Angola collaboration is aligned with this ethos, and will launch with two core activities during the upcoming academic year:

1. Global Classroom: An MIT course on geo-spatial technologies for environmental monitoring, taught by an MIT faculty member, will be brought directly to the ISPTEC campus, offering Angolan students and MIT participants a collaborative, in-country learning experience.
2. Global Teaching Labs: MIT students will travel to ISPTEC to teach science, technology, engineering, arts, and mathematics subjects on renewable energy technologies, engaging Angolan students through hands-on instruction.

“This is not a traditional development project,” says Ari Jacobovits, managing director of MIT-Africa. “This is about building genuine partnerships rooted in academic rigor, innovation, and shared curiosity. The collaboration has been designed from the ground up with our partners at ISPTEC and Sonangol. We’re coming in with a readiness to learn as much as we teach.”

The pilot marks an important first step in establishing a long-term collaboration with Angola. By investing in collaborative education and innovation, the new initiative aims to spark novel approaches to global challenges and strengthen academic institutions on both sides.

These agreements with MIT-Africa and ILP “not only enhance our innovation and technological capabilities, but also create opportunities for sustainable development and operational excellence,” says Gaspar. “They advance our mission to be a leading force in the African energy sector.”

“The vision behind this initiative is bold,” says Hassan. “It’s about co-creating knowledge and building capacity that lasts.”

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.

Peter Temin PhD ’64, the MIT Elisha Gray II Professor of Economics, emeritus, passed away on Aug. 4. He was 87. 

Temin was a preeminent economic historian whose work spanned a remarkable range of topics, from the British Industrial Revolution and Roman economic history to the causes of the Great Depression and, later in his career, the decline of the American middle class. He also made important contributions to modernizing the field of economic history through his systematic use of economic theory and data analysis.

“Peter was a dedicated teacher and a wonderful colleague, who could bring economic history to life like few before or since,” says Jonathan Gruber, Ford Professor and chair of the Department of Economics. “As an undergraduate at MIT, I knew Peter as an engaging teacher and UROP [Undergraduate Research Opportunities Program] supervisor. Later, as a faculty member, I knew him as a steady and supportive colleague. A great person to talk to about everything, from research to politics to life at the Cape. Peter was the full package: a great scholar, a great teacher, and a dedicated public goods provider.”

When Temin began his career, the field of economic history was undergoing a reorientation within the profession. Led by giants like Paul Samuelson and Robert Solow, economics had become a more quantitative, mathematically rigorous discipline, and economic historians responded by embracing the new tools of economic theory and data collection. This “new economic history” (today also known as “cliometrics”) revolutionized the field by introducing statistical analysis and mathematical modeling to the study of the past. Temin was a pioneer of this new approach, using econometrics to reexamine key historical events and demonstrate how data analysis could lead to the overturning of long-held assumptions.

A prolific scholar who authored 17 books and edited six, Temin made important contributions to an incredibly diverse set of topics. “As kindly as he was brilliant, Peter was a unique type of academic,” says Harvard University Professor Claudia Goldin, a fellow economic historian and winner of the 2023 Nobel Prize in economic sciences. “He was a macroeconomist and an economic historian who later worked on today’s social problems. In between, he studied antitrust, health care, and the Roman economy.”

Temin’s earliest work focused on American industrial development during the 19th century and honed the signature approach that quickly made him a leading economic historian — combining rigorous economic theory with a deep understanding of historical context to reexamine the past. Temin was known for his extensive analysis of the Great Depression, which often challenged prevailing wisdom. By arguing that factors beyond monetary policy — including the gold standard and a decline in consumer spending — were critical drivers of the crisis, Temin helped recast how economists think about the catastrophe and the role of monetary policy in economic downturns.

As his career progressed, Temin’s work increasingly expanded to include the economic history of other regions and periods. His later work on the Great Depression placed a greater emphasis on the international context of the crisis, and he made significant contributions to our understanding of the drivers of the British Industrial Revolution and the nature of the Roman economy.

“Peter Temin was a giant in the field of economic history, with work touching every aspect of the field and original ideas backed by careful research,” says Daron Acemoglu, Institute Professor and recipient of the 2024 Nobel Prize in economics. “He challenged the modern view of the Industrial Revolution that emphasized technological changes in a few industries, pointing instead to a broader transformation of the British economy. He took on the famous historian of the ancient world, Moses Finley, arguing that slavery notwithstanding, markets in the Roman economy — especially land markets — worked. Peter’s influence and contributions have been long-lasting and will continue to be so.”

Temin was born in Philadelphia in 1937. His parents were activists who emphasized social responsibility, and his older brother, Howard, became a geneticist and virologist who shared the 1975 Nobel Prize in medicine. Temin received his BA from Swarthmore College in 1959 and went on to earn his PhD in Economics from MIT in 1964. He was a junior fellow of Harvard University’s Society of Fellows from 1962 to 1965.

Temin started his career as an assistant professor of industrial history at the MIT Sloan School of Management before being hired by the Department of Economics in 1967. He served as department chair from 1990t o 1993 and held the Elisha Gray II professorship from 1993 to 2009. Temin won a Guggenheim Fellowship in 2001, and served as president of the Economic History Association (1995-96) and the Eastern Economic Association (2001-02).

At MIT, Temin’s scholarly achievements were matched by a deep commitment to engaging students as a teacher and advisor. “As a researcher, Peter was able to zero in on the key questions around a topic and find answers where others had been flailing,” says Christina Romer, chair of the Council of Economic Advisers under President Obama and a former student and advisee. “As a teacher, he managed to draw sleepy students into a rousing discussion that made us think we had figured out the material on our own, when, in fact, he had been masterfully guiding us. And as a mentor, he was unfailingly supportive and generous with both his time and his vast knowledge of economic history. I feel blessed to have been one of his students.”

When he became the economics department head in 1990, Temin prioritized hiring newly-minted PhDs and other junior faculty. This foresight continues to pay dividends — his junior hires included Daron Acemoglu and Abhijit Banerjee, and he launched the recruiting of Bengt Holmström for a senior faculty position. All three went on to win Nobel Prizes and have been pillars of economics research and education at MIT.

Temin remained an active researcher and author after his retirement in 2009. Much of his later work turned toward the contemporary American economy and its deep-seated divisions. In his influential 2017 book, “The Vanishing Middle Class: Prejudice and Power in a Dual Economy,” he argued that the United States had become a “dual economy,” with a prosperous finance, technology, and electronics sector on one hand and, on the other, a low-wage sector characterized by stagnant opportunity.

“There are echoes of Temin’s later writings in current department initiatives, such as the Stone Center on Inequality and Shaping the Future of Work” notes Gruber. “Temin was in many ways ahead of the curve in treating inequality as an issue of central importance for our discipline.”

In “The Vanishing Middle Class,” Temin also explored the role that historical events, particularly the legacy of slavery and its aftermath, played in creating and perpetuating economic divides. He further explored these themes in his last book, “Never Together: The Economic History of a Segregated America,” published in 2022. While Temin was perhaps best known for his work applying modern economic tools to the past, this later work showed that he was no less adept at the inverse: using historical analysis to shed light on modern economic problems.

Temin was active with MIT Hillel throughout his career, and outside the Institute, he enjoyed staying active. He could often be seen walking or biking to MIT, and taking a walk around Jamaica Pond was a favorite activity in his last few months of life. Peter and his late wife Charlotte were also avid travelers and art collectors. He was a wonderful husband, father, and grandfather, who was deeply devoted to his family.

Temin is lovingly remembered by his daughter Elizabeth “Liz” Temin and three grandsons, Colin and Zachary Gibbons and Elijah Mendez. He was preceded in death by his wife, Charlotte Temin, a psychologist and educator, and his daughter, Melanie Temin Mendez.

By reducing its reserves, the Texas Windstorm Insurance Association can keep prices steady for policyholders on the coast. But it may struggle to pay claims.

The hiring burst follows a wave of departures at the National Weather Service during the first few months of the Trump administration.

Nonprofits and state agencies involved in the solar initiative for low-income households say they’ve been warned grants could be terminated this week.

The Tuesday ruling stops the Trump administration from spending $4 billion it pulled from a grant program that funded disaster-protection projects.

Lawmakers considered measures responding to last month's deadly floods without Democrats who fled the state to block Republican gerrymandering.

ConEd says it needs to charge higher rates to fortify the power grid against a growing threat: climate change.

The country has issued multiple heat alerts this year and also set tougher rules for employers to ensure workers are protected.

Climate experts say the increasing frequency of extreme weather has changed the playbook for assessing infrastructure risks and rebuilding efforts.

Similar trends are emerging in Peru and El Salvador, where governments have limited oversight, and in Brazil, which has eased licensing for Amazon projects.

Earlier this week, the Trump administration narrowed export controls on advanced semiconductors ahead of US-China trade negotiations. The administration is increasingly relying on export licenses to allow American semiconductor firms to sell their products to Chinese customers, while keeping the most powerful of them out of the hands of our military adversaries. These are the chips that power the artificial intelligence research fueling China’s technological rise, as well as the advanced military equipment underpinning Russia’s invasion of Ukraine...

Artificial intelligence is changing the way businesses store and access their data. That’s because traditional data storage systems were designed to handle simple commands from a handful of users at once, whereas today, AI systems with millions of agents need to continuously access and process large amounts of data in parallel. Traditional data storage systems now have layers of complexity, which slows AI systems down because data must pass through multiple tiers before reaching the graphical processing units (GPUs) that are the brain cells of AI.

Cloudian, co-founded by Michael Tso ’93, SM ’93 and Hiroshi Ohta, is helping storage keep up with the AI revolution. The company has developed a scalable storage system for businesses that helps data flow seamlessly between storage and AI models. The system reduces complexity by applying parallel computing to data storage, consolidating AI functions and data onto a single parallel-processing platform that stores, retrieves, and processes scalable datasets, with direct, high-speed transfers between storage and GPUs and CPUs.

Cloudian’s integrated storage-computing platform simplifies the process of building commercial-scale AI tools and gives businesses a storage foundation that can keep up with the rise of AI.

“One of the things people miss about AI is that it’s all about the data,” Tso says. “You can’t get a 10 percent improvement in AI performance with 10 percent more data or even 10 times more data — you need 1,000 times more data. Being able to store that data in a way that’s easy to manage, and in such a way that you can embed computations into it so you can run operations while the data is coming in without moving the data — that’s where this industry is going.”

From MIT to industry

As an undergraduate at MIT in the 1990s, Tso was introduced by Professor William Dally to parallel computing — a type of computation in which many calculations occur simultaneously. Tso also worked on parallel computing with Associate Professor Greg Papadopoulos.

“It was an incredible time because most schools had one super-computing project going on — MIT had four,” Tso recalls.

As a graduate student, Tso worked with MIT senior research scientist David Clark, a computing pioneer who contributed to the internet’s early architecture, particularly the transmission control protocol (TCP) that delivers data between systems.

“As a graduate student at MIT, I worked on disconnected and intermittent networking operations for large scale distributed systems,” Tso says. “It’s funny — 30 years on, that’s what I’m still doing today.”

Following his graduation, Tso worked at Intel’s Architecture Lab, where he invented data synchronization algorithms used by Blackberry. He also created specifications for Nokia that ignited the ringtone download industry. He then joined Inktomi, a startup co-founded by Eric Brewer SM ’92, PhD ’94 that pioneered search and web content distribution technologies.

In 2001, Tso started Gemini Mobile Technologies with Joseph Norton ’93, SM ’93 and others. The company went on to build the world’s largest mobile messaging systems to handle the massive data growth from camera phones. Then, in the late 2000s, cloud computing became a powerful way for businesses to rent virtual servers as they grew their operations. Tso noticed the amount of data being collected was growing far faster than the speed of networking, so he decided to pivot the company.

“Data is being created in a lot of different places, and that data has its own gravity: It’s going to cost you money and time to move it,” Tso explains. “That means the end state is a distributed cloud that reaches out to edge devices and servers. You have to bring the cloud to the data, not the data to the cloud.”

Tso officially launched Cloudian out of Gemini Mobile Technologies in 2012, with a new emphasis on helping customers with scalable, distributed, cloud-compatible data storage.

“What we didn’t see when we first started the company was that AI was going to be the ultimate use case for data on the edge,” Tso says.

Although Tso’s research at MIT began more than two decades ago, he sees strong connections between what he worked on and the industry today.

“It’s like my whole life is playing back because David Clark and I were dealing with disconnected and intermittently connected networks, which are part of every edge use case today, and Professor Dally was working on very fast, scalable interconnects,” Tso says, noting that Dally is now the senior vice president and chief scientist at the leading AI company NVIDIA. “Now, when you look at the modern NVIDIA chip architecture and the way they do interchip communication, it’s got Dally’s work all over it. With Professor Papadopoulos, I worked on accelerate application software with parallel computing hardware without having to rewrite the applications, and that’s exactly the problem we are trying to solve with NVIDIA. Coincidentally, all the stuff I was doing at MIT is playing out.”

Today Cloudian’s platform uses an object storage architecture in which all kinds of data —documents, videos, sensor data — are stored as a unique object with metadata. Object storage can manage massive datasets in a flat file stucture, making it ideal for unstructured data and AI systems, but it traditionally hasn’t been able to send data directly to AI models without the data first being copied into a computer’s memory system, creating latency and energy bottlenecks for businesses.

In July, Cloudian announced that it has extended its object storage system with a vector database that stores data in a form which is immediately usable by AI models. As the data are ingested, Cloudian is computing in real-time the vector form of that data to power AI tools like recommender engines, search, and AI assistants. Cloudian also announced a partnership with NVIDIA that allows its storage system to work directly with the AI company’s GPUs. Cloudian says the new system enables even faster AI operations and reduces computing costs.

“NVIDIA contacted us about a year and a half ago because GPUs are useful only with data that keeps them busy,” Tso says. “Now that people are realizing it’s easier to move the AI to the data than it is to move huge datasets. Our storage systems embed a lot of AI functions, so we’re able to pre- and post-process data for AI near where we collect and store the data.”

AI-first storage

Cloudian is helping about 1,000 companies around the world get more value out of their data, including large manufacturers, financial service providers, health care organizations, and government agencies.

Cloudian’s storage platform is helping one large automaker, for instance, use AI to determine when each of its manufacturing robots need to be serviced. Cloudian is also working with the National Library of Medicine to store research articles and patents, and the National Cancer Database to store DNA sequences of tumors — rich datasets that AI models could process to help research develop new treatments or gain new insights.

“GPUs have been an incredible enabler,” Tso says. “Moore’s Law doubles the amount of compute every two years, but GPUs are able to parallelize operations on chips, so you can network GPUs together and shatter Moore’s Law. That scale is pushing AI to new levels of intelligence, but the only way to make GPUs work hard is to feed them data at the same speed that they compute — and the only way to do that is to get rid of all the layers between them and your data.”

If you’ve urgently ordered a package from Amazon — and exhaled when it arrived on your doorstep hours later — you likely have three graduates of the MIT Leaders for Global Operations (LGO) program to thank: John Tagawa SM ’99; Diego Méndez de la Luz MNG ’04, MBA ’11, SM ’11; or Chuck Cummings MBA ’11, SM ’11.

Each holds critical roles within the company. Tagawa oversees Amazon’s North American operations. Méndez de la Luz heads up operations in Mexico. Cummings leads customer fulfillment throughout Canada. They also mentor LGO students and recent graduates throughout the organization and credit LGO’s singular blend of operational and leadership strength for their success as Amazon grows.

John Tagawa

Tagawa came to Amazon — now the world’s largest online retailer — through an LGO alumni connection in 2008, joining the organization during rapid expansion. He led fulfillment centers on the West Coast and went on to oversee operations in India, South America, and in Europe, with a focus on safety, speed, and efficiency.

Today, he’s a resource for other LGO graduates at Amazon, applauding the program’s uniquely multidimensional focus on tech, engineering, and leadership, all of which are key pillars as the organization continues to grow.

“Today, we have hundreds of fulfillment centers worldwide, and Amazon has grown its transportation and last-mile delivery network in an effort to ensure greater resilience and speed in getting products to customers,” he explains.

Tagawa says that LGO’s unique dual-degree program provided a singular blueprint for success as an operations leader and an engineer.

“The technology and engineering education that I received at MIT plays directly into my day-to-day role. We’re constantly thinking about how to infuse technology and innovate at scale to improve outcomes for our employees and customers. That ranges from introducing robotics to our fulfillment centers to using AI to determine how much inventory we should buy and where we should place it to introducing technology on the shop floor to help our frontline leaders. Those components of my LGO education were critical,” he says. 

After receiving his undergraduate degree at the University of Washington, Tagawa pursued engineering and operations roles. But it wasn’t until LGO that he realized how important the fusion of business, operations, and leadership competencies was.

“What drew me to LGO was being able to study business and finance, coupled with an engineering and leadership education. I hadn’t realized how powerful bringing all three of those disciplines together could be,” he reflects. “Amazon’s efficacy relies on how great our leaders are, and a big part of my role is to develop, coach, and build a great leadership team. The foundation of my ability to do that is based on what I learned at MIT about becoming a lifelong learner.”

Tagawa recalls his own classes with Donald Davis, the late chair and CEO of The Stanley Works. Davis was one of LGO’s first lecturers, sharing case studies from his time on the front lines. Davis imparted the concepts of servant-leadership and diversity, which shaped Tagawa’s outlook at Amazon.

“I get energized by the leadership principles at Amazon. We strive to be Earth's best employer​​ and being customer-obsessed. It’s energizing to lead large-scale organizations whose sole mission is to improve the lives of our employees and customers, with a strong focus on developing great leaders. Who could ask for something better than that?” he asks.

Diego Méndez de la Luz

This blend of leadership acumen and engineering dynamism also jump-started the career of Méndez de la Luz, now Amazon’s country director of Mexico operations. LGO’s leadership focus was crucial in preparing him for his Amazon role, where he oversees the vast majority of Amazon’s 10,000 employees in Mexico — those who work in operations — across 40 facilities throughout his home country.

At MIT, he took classes with notable professors, whom he credits with broadening his intellectual and professional horizons. 

“I was a good student throughout my education, but only after joining LGO did I learn what I consider to be foundational concepts and skills,” says Méndez de la Luz, who also started his career in engineering. “I learned about inventory management, business law, accounting, and about how to have important conversations in the workplace — things I never learned as an engineer. LGO was tremendously useful.”

Méndez de la Luz joined Amazon shortly after LGO, working his way up from frontline management roles at fulfillment centers throughout the United States. Today, he oversees the end-to-end network of imports, fulfillment, transportation, and customer delivery.

At Amazon, he believes he’s making a real difference in his native country. With Amazon’s scale comes the responsibility to improve both the planet and local communities, he says. Amazon engages with communities through volunteer programs, literacy efforts, and partnerships with shelters.

Today, Méndez de la Luz says that he’s working in his “dream job — exactly what I went to MIT for,” in a community he loves.

“My role at Amazon is a great source of pride. When I was growing up, I wanted to be the president of Mexico. I still want to make a difference for people in our society. Here, I have the ability to come back to my home country to create good jobs. Having the ability to do that has been a surprise to me — but a very positive development that I just value so much,” he says. “I want people to feel excited that they’re going to come to work and see their friends and colleagues do well.”

Chuck Cummings

This collaborative atmosphere propelled Cummings to pursue a post-MIT career at Amazon after years as a mechanical engineer. He discovered a hospitable workplace that valued growth: He began as an operations management intern, and today he leads the customer fulfillment business in Canada, which includes the country’s fulfillment centers. It’s a big job made better by his LGO expertise, where he always strives for co-worker and customer satisfaction.

“I sought out LGO because I’ve always loved the shop floor,” he says. “I continue to get excited about: How do we offer faster speeds to Canadian customers? How do we keep lowering our cost structure so that we can continue to invest and offer new benefits for our customers? At the same time, how do I build the absolute best working environment for all of my employees?”

Last year, Cummings’ team launched an Amazon robotics fulfillment center in Calgary, Alberta. This was a significant enhancement for Canadian customers; now, Calgary shoppers have more inventory much closer to home, with delivery speeds to match. Cummings also helped to bring Amazon’s storage and distribution network to a new facility in Vancouver, British Columbia, which will enable nearby fulfillment centers to respond to a wider selection of customer orders at the fastest-possible delivery speeds.

These were substantial endeavors, which he felt comfortable undertaking thanks to his classes at MIT. His experience was so meaningful that Cummings now serves as Amazon’s co-school captain for LGO, where he recruits the next generation of LGO graduates for internships and full-time roles. Cummings has now worked with more than 25 LGO graduates, and he says they’re easy to pick out of a crowd.

“You can give them very ambiguous, complex problems, and they can dive into the data and come out with an amazing solution. But what makes LGO students even more special is, at the same time, they have strong communication skills. They have a lot of emotional intelligence. It’s a combination of business leadership with extreme technical understanding,” he says.

Both Tagawa and Méndez de la Luz interact frequently with LGO students, too. They agree that, while Amazon’s technology is always unfolding, its leadership qualities remain constant — and match perfectly with LGO’s reputation for creating dynamic, empathetic professionals who also prize technical skill.

“Whereas technology has grown and changed by leaps and bounds, leadership principles carry on for decades,” Tagawa says. “The infusion of the engineering, business, and leadership components at LGO are second to none.”

When a technology can have a conversation with you, it’s natural to anthropomorphize that technology—to see it as a person. It’s tempting to see a chatbot as a thinking, speaking robot, but this gives the technology too much credit. This can also lead people—including judges in cases about AI chatbots—to overlook the human expressive choices connected to the words that chatbots produce. If chatbot outputs had no First Amendment protections, the government could potentially ban chatbots that criticize the administration or reflect viewpoints the administration disagrees with.

In fact, the output of chatbots can reflect not only the expressive choices of their creators and users, but also implicates users’ right to receive information. That’s why EFF and the Center for Democracy and Technology (CDT) have filed an amicus brief in Garcia v. Character Technologies explaining how large language models work and the various kinds of protected speech at stake.

Among the questions in this case is the extent to which free speech protections extend to the creation, dissemination, and receipt of chatbot outputs. Our brief explains how the expressive choices of a chatbot developer can shape its output, such as during reinforcement learning, when humans are instructed to give positive feedback to responses that align with the scientific consensus around climate change and negative feedback for denying it (or vice versa). This chain of human expressive decisions extends from early stages of selecting training data to crafting a system prompt. A user’s instructions are also reflected in chatbot output. Far from being the speech of a robot, chatbot output often reflects human expression that is entitled to First Amendment protection.

In addition, the right to receive speech in itself is protected—even when the speaker would have no independent right to say it. Users have a right to access the information chatbots provide.

None of this is to suggest that chatbots cannot be regulated or that the harms they cause cannot be addressed. The First Amendment simply requires that those regulations be appropriately tailored to the harm to avoid unduly burdening the right to express oneself through the medium of a chatbot, or to receive the information it provides.

We hope that our brief will be helpful to the court as the case progresses, as the judge decided not to send the question up on appeal at this time.

Read our brief below.

Sometimes technology feels like a gilded cage, and you’re not the one holding the key. Most people can’t live off the grid, so how do we stop data brokers who track and exploit you for money? Tech companies that distort what you see and hear? Governments that restrict, censor, and intimidate? No one can do it alone, but EFF was built to protect your rights. With your support, we can take back control.

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Think about it: in the face of rising authoritarianism and invasive surveillance, where would we be without an encrypted web? Your security online depends on researchers, hackers, and creators who are willing to take privacy and free speech rights seriously. That's why EFF will eagerly protect the beating heart of that movement at this week's summer security conferences in Las Vegas. This renowned summit of computer hacking events—BSidesLV, Black Hat USA, and DEF CON—illustrate the key role a community can play in helping you break free of the trappings of technology and retake the reins.

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