Petal, the next step in Meta’s subsea innovation, will be the first subsea cable to deliver petabit capacity at transoceanic distances, connecting France and the United States over approximately 7,000 km (4,300 mi). Expected to enter service in 2029, it will be the first subsea cable system to deploy multi-core fiber technology at scale, doubling the capacity per fiber without a proportional increase in power or physical infrastructure. Petal will be built in partnership with NEC and Sumitomo Electric Industries, with support on the French landing from Orange. Today, we’re announcing Petal, the first transoceanic subsea cable at petabit capacity, and the first to deploy multi-core fiber at scale. Spanning 7,000 km between France and the United States, Petal will deliver 1 Pbps (1 petabit per second or 1,000 terabits per second), doubling what today’s most advanced subsea cables carry at this distance. That&#8217;s roughly the network capacity required for 75% of the world&#8217;s population to stream music at the same time.* Petal is a key piece of Meta’s subsea cable investments bringing greater capacity, stronger resiliency, and future-proof infrastructure to Europe as demand for communications and reliable connectivity continues to increase. The road to this point has taken years of collaborative engineering with our partners and a complete rethinking of the subsea industry’s approach to cable design. Subsea Capacity Innovation A subsea cable is the least visible, yet one of the most critical layers of the internet. Approximately 99% of intercontinental data traffic – nearly every message, phone, or video call between continents – travels through glass strands on the ocean floor. Since the introduction of the erbium-doped fiber amplifier (EDFA) in the 1980s, there have been several transformational shifts in subsea cable capacity. In the 2010s, coherent optical transmission technology and dispersion-uncompensated cable designs launched the industry into a decade of dramatic fiber capacity increases of 10x and more until the ever-looming Shannon Limit finally pushed back. To overcome this, the industry pivoted to spatial division multiplexing (SDM) to increase the number of fibers within a subsea cable. Meta scaled its subsea cable approach from Marea’s eight fiber pairs, to Amitié’s 16 fiber pairs, and recently to Anjana’s 24 fiber pairs – the first 0.5 Pbps transatlantic cable system. Three innovations could double capacity again: Continue on the conventional path to increase the number of fibers to reach 48 fiber pairs. Expand the optical transmission band by using the L-band, as we did with the PLCN cable, resulting in 24 fiber pair C+L transmission. Adopt a 2-core fiber-based solution. With Petal, we’ve opted for 2-core fiber technology in a 24 fiber-pair system, equivalent to 48 fiber pairs, to make the leap to 1 Pbps at transatlantic distances. This is double Anjana’s capacity and makes Petal the single largest generational increase in cable capacity of any repeatered subsea system, ever. A few of Meta’s cable investments. Our latest cable investment, Petal, will be 5.5x the capacity of Marea, our first transatlantic investment. The Challenges of Engineering a 2-Core Fiber Ecosystem Carrying a petabit through one cable significantly reduces materials, resources, and carbon footprint compared to building two 0.5 Pbps systems. However, transitioning to a 2-core fiber ecosystem comes with challenges that affect the fiber and subsea repeaters. A snapshot of a Sumitomo Electric preform of a multicore fiber strand showing two cores for light propagation. This will be stretched from 2-3 m long and 20 cm wide to 1000s of kilometers long and 125 µm wide, about the diameter of a hair. Fiber: Transitioning From Single to 2-Core Fiber There are two main challenges to enabling 2-core fiber for Petal. First is ensuring low attenuation while maintaining the physical dimensions of the outer fiber, including the 125 μm width. Second is minimizing crosstalk between the cores to maximize optical performance and capacity. The former is achieved by using ultra-pure synthetic silica during the manufacture of the preform. The latter is achieved by carefully controlling for high refractive indexes in the cores against lower indexes within the surrounding medium and counter-propagating the optical signals, resulting in nearly immeasurable crosstalk. 1-core fiber allows the industry to counter-propagate traffic using a pair of fibers. Petal’s 2-core fiber will combine this capacity into one fiber strand. Repeater: Amplifying 96 Fiber Cores in a Single Body Repeater A 7,000 km subsea cable typically needs about a hundred repeaters to amplify the digital signals along the length of the cable. Petal’s single-body 96 amp repeater uses single-core fiber amplification with a Fan-In/Fan-Out (FIFO) interface to transition 2-core fiber into two single-core fibers within each repeater and then back to 2-core fiber following amplification. This design allows Petal to retain the highest efficiency and reliability of single-core amplification with an SDM pump-sharing architecture. FIFO, combined with highly efficient amplification and high-quality, low-loss fiber, will enable Petal to double capacity without a proportional increase to required power. Petal will remain within existing power feeding equipment limits, rated up to 18 kV, which avoids triggering a requalification of the subsea ecosystem necessary at higher equipment voltages. The Partnerships Behind Petal Meta’s vision for Petal wouldn’t be possible without the engineering capabilities of our partners at NEC, Sumitomo Electronic Industries, and Orange. NEC, our turnkey system supplier, engineered and qualified the world’s first petabit transoceanic system around the next generation SDM foundation – cable with 2-core fiber, repeaters, FIFO systems, system powering – and is responsible for manufacturing and installing the final product. NEC has made deep investments in their manufacturing facilities to produce petabit-class SDM repeaters, multicore fiber cable as well as associated technologies. “Achieving petabit-per-second capacity across a transoceanic submarine system represents a major technological milestone in the history of global telecommunications. This achievement reflects NEC’s sustained investment in research and development, combined with decades of experience delivering some of the world’s most advanced, reliable, and secure submarine networks that interconnect the globe,” &#8211; Eduardo Mateo, Chief Strategy Officer, Submarine Network Division, NEC Corporation Sumitomo Electric Industries, NEC’s fiber supplier, developed and manufactured the 2-core fiber with ultra low losses and practically immeasurable crosstalk for counterpropagating signals, resulting in optical performance nearly identical to single-core fiber. &#8220;We are thrilled that Sumitomo Electric’s innovative submarine multi-core fiber, “2C Z-PLUS ULL Fiber” will contribute to “Petal”, an epoch-making Pb-class transatlantic cable system. As a pioneer with nearly four decades of experience in ultra-low loss submarine fiber manufacturing, we are committed to supporting the global network expansion essential to realizing a highly digital future.&#8221; -Takehiko OKADA, General Manager of Optical Fiber & Cable Division, Sumitomo Electric Industries, Ltd. Orange and Meta are working together on plans to land Petal ashore France&#8217;s Atlantic coast including the terrestrial interconnection into the European network. “Reaching one petabit on a transatlantic link, 25 years after the terabit milestone, represents a significant breakthrough to meet the exponential traffic growth while optimizing network capacity. This makes us very proud to welcome this new generation petabit subsea cable with dual-core fiber technology in our infrastructure, as the landing party in France. This new project reinforces our commitment with Meta and demonstrates our leading expertise in landing subsea systems, and extending connectivity to other European countries. It underlines our dedication to developing reliable infrastructure that guarantees the security and resilience of the terrestrial segment of those connections.” &#8211; Jean-Louis Le Roux, EVP, Orange International Networks New Capacity for a New Era Meta has been one of the world’s largest investors in subsea cable infrastructure, building the digital backbone that connects continents and strengthens the global internet, enabling a future that is for everyone. We’re moving multi-core fiber from experimental to mainstream, making it a practical design for building subsea systems at scale – a shift the entire industry can benefit from. Our aim is to set a new standard for what undersea infrastructure can deliver and invite the ecosystem to invest alongside us. *Calculation based on a total capacity of 1 Pbps with an audio stream bitrate of ~0.16 Mbps (160 kbps) for ≈ 6.25 billion simultaneous streams. The post Inside Petal: Building the World’s First Petabit-Class Transoceanic Subsea Cable appeared first on Engineering at Meta.

Inside Petal: Building the World’s First Petabit-Class Transoceanic Subsea Cable

David Siegel SM ’86, PhD ’91, a computer scientist, entrepreneur, and philanthropist, will serve as the next MIT Innovation Fellow during the 2026-27 academic year. Working with the MIT Schwarzman College of Computing, Siegel will explore how artificial intelligence can accelerate scientific discovery at the Institute and beyond.“From the MIT Schwarzman College of Computing to the MIT Siegel Family Quest for Intelligence, David has been a superb thought partner for me and other Institute leaders on a range of very significant initiatives, so we're delighted to have him join us now as an MIT Innovation Fellow,” says MIT President Sally Kornbluth. “Our community has long benefited from David's exceptional technical insight, entrepreneurial experience, instinct for connecting people, and infectious love for MIT. We look forward to working with him now as he helps us identify new opportunities at the intersection of AI and scientific discovery.” “MIT has played a foundational role in shaping how I view technology’s potential to address complex challenges,” says Siegel. “I’m thrilled to return to campus as an Innovation Fellow to collaborate with brilliant students, researchers, and faculty at a pivotal juncture in how technology shapes our world.”A long-standing connection to MITSiegel’s relationship with MIT began during his graduate studies, where he earned a master’s degree in 1986 and PhD in 1991, after earning his bachelor’s degree in electrical engineering and computer science from Princeton University in 1983. Immersed in the field during a foundational era for computer science, he worked at the MIT Artificial Intelligence Lab (now the Computer Science and Artificial Intelligence Laboratory) in Professor Tomás Lozano-Pérez’s research group on human-machine interaction, contributing to the development of a pioneering humanlike robotic hand. Siegel has remained deeply involved with the Institute in the years since. He is a life member of the MIT Corporation, previously served on its Executive Committee, and co-chairs the External Advisory Committee for the MIT Schwarzman College of Computing. Additionally, Siegel was an early champion of the MIT Quest for Intelligence, an Institute-wide initiative studying intelligence in brains and machines, recently renamed the MIT Siegel Family Quest for Intelligence.Entrepreneurship, philanthropy, and AI leadershipAfter completing his PhD, Siegel founded several early internet ventures before co-founding Two Sigma in 2001. A leading global investment firm, Two Sigma approaches investing through a data science and engineering lens, echoing Siegel’s experience in the MIT AI Lab. With the scientific method embedded in its culture, the firm uses artificial intelligence, machine learning, and advanced quantitative modeling. Siegel retired from day-to-day management of Two Sigma in 2024; however, he remains co-chair. Currently, Siegel’s work spans several fields, with a strong emphasis on science, technology, and philanthropy. Through the Siegel Family Endowment, a philanthropic foundation that he established in 2011, Siegel supports leaders, researchers, and organizations that are examining how technological change affects society and how to guide that shift for the public good. The endowment backs organizations such as the Scratch Foundation, Center on Rural Innovation, Khan Academy, Pursuit, and The Aspen Institute.Recognizing the critical resource gap between academic research labs and frontier AI, Siegel founded the nonprofit Open Athena in 2024. Open Athena equips academic research labs with elite AI talent, data engineering expertise, and computational resources to enable groundbreaking discoveries at scale. The organization is also developing Marin, a 535-billion-parameter foundation model built entirely in public. By sharing every dataset and experiment in real-time, Marin ensures that the science of frontier AI remains a shared public asset for researchers and innovators worldwide. Open Athena works with leading global institutions including MIT and is funded by philanthropic partners including Bloomberg Philanthropies, Google, The Huang Foundation, and Schmidt Sciences. Siegel actively serves on several governance and advisory boards. He is vice-chair of the Scratch Foundation, which he co-founded in 2013 with MIT Professor Mitch Resnick, a member of the Cornell Tech Council, and a board member of organizations such as Re:Build Manufacturing, Khan Academy, and NYC FIRST Robotics. In 2025, Siegel was appointed to the U.S. Department of Energy’s Office of Science Advisory Committee, providing counsel on complex scientific and technical issues impacting federal scientific research programs.Outside of philanthropy, Siegel remains actively engaged in the global AI ecosystem as an investor, hands-on advisor, and thought leader. Through his family office Shinrai Management, he focuses on supporting entrepreneurs and investing in high-growth startups, including several founded by MIT students and alumni.Siegel’s debut book, “When Machines Act: The Promise and Peril of Navigating Our Agentic AI Future,” co-authored with Yale University’s Jeffrey Sonnenfeld and Stephen Henriques, will be published by MIT Press next March, coinciding with his residency as an MIT Innovation Fellow. Drawing on interviews with top tech leaders and off-the-record discussions with over 300 CEOs, the book provides a practical roadmap for autonomous AI, outlining where to deploy it, how to govern it, and which rules truly matter.“David’s ties to MIT date back to his doctoral research in the AI Lab and have deepened through his many contributions to the Institute, including his significant involvement with the Quest for Intelligence and the MIT Schwarzman College of Computing,” says MIT Provost Anantha Chandrakasan. “His long-standing commitment to MIT, together with his vision for the future of AI and science, makes him an especially fitting Innovation Fellow. We look forward to the contributions he will make and the connections his work will foster across campus."“For the MIT Schwarzman College of Computing, David’s fellowship is a chance to build on an already strong connection and explore how AI can expand the frontiers of science. Having known David since we were both graduate students at MIT, I’m deeply familiar with his ability to advance AI and its application in various fields,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Panasonic Professor of Electrical Engineering and Computer Science. “He understands both the college’s aspirations and the challenges ahead, and his perspective will help us identify concrete paths for research, education, and broader engagement. I look forward to working with him over the coming year.”A year in residenceMIT Innovation Fellows typically spend a year or more in residence at the Institute. They draw on their experience, expertise, and professional networks to engage with faculty and students, participate in public events, and provide strategic counsel to MIT leaders.The program has brought luminaries from industry and government to MIT. Most recently, Brian Deese, former White House National Economic Council director, served as an Innovation Fellow. Other fellows have included Virginia M. “Ginny” Rometty, former chair, president, and CEO of IBM; Eric Schmidt, former executive chair of Google’s parent company, Alphabet; the late Ash Carter, former U.S. secretary of defense; and former Massachusetts Governor Deval Patrick.As an Innovation Fellow, Siegel will help guide the Institute’s focus on leveraging artificial intelligence to support scientific discovery, working closely with the MIT Schwarzman College of Computing and departments across the college to help extend their impact beyond MIT. “Using AI to accelerate scientific discovery is the ultimate engineering challenge. There is simply no better launchpad in the world for that work than MIT,” says Siegel.

MIT welcomes David Siegel SM ’86, PhD ’91 as its next Innovation Fellow

A few months ago, researchers from the MIT Senseable City Lab published a study about pollution in New York City featuring some new methods. For instance: With machine learning, they identified the types of vehicles appearing in 331 traffic cameras in the city, and estimated the emissions coming from each automobile. Given enough cameras, these visual artificial intelligence techniques could monitor emissions with an unprecedented combination of precision and scale. For that matter, visual AI today can address all kinds of questions for urban planners. Why exactly is traffic snarling? What are the most dangerous aspects of different intersections? Which parts of plazas or parks attract the most people?Across cities, more images means more data, more insight — and more concerns about privacy and fairness. “We can treat these digital images as data and quantify features of the city,” says Fábio Duarte, an MIT researcher and co-author of a new book about visual AI and urban studies. “With computer vision techniques, each image is a dataset.” Still, he adds, “We have to be careful about it.” And while urbanists have long used visual analysis to inform their thinking, now it’s possible to an unprecedented extent. “Everybody has been observing the urban environment and trying to get some insight,” says Martina Mazzarello, an MIT scholar and a co-author of the new book. “But what if we can do that at a large scale and get some insight everywhere?”The scholars explore these topics in “How AI Sees the City: Urban Visual Intelligence,” published this month by Routledge. The authors are Duarte, a principal research scientist and associate director of the MIT Senseable City Lab; Mazzarello, a research scientist and lead of MIT Senseable City Lab global initiatives; Carlo Ratti, a professor of the practice and founder and director of the MIT Senseable City Lab; and Fan Zhang, an assistant professor at the Institute of Remote Sensing and GIS at Peking University.“Great urbanists such as Kevin Lynch and Willian H. Whyte showed us the extraordinary value of ‘looking’ at the city,” Ratti says, referring to two prominent thinkers about city dynamics whose work is described in the book. “Today, visual AI gives us new ways to build on that tradition — allowing us to observe cities at a scale and with a level of detail that was previously impossible.” New tool, long tradition“How AI Sees the City” stems from the work of the MIT Senseable City Lab, founded in 2004, which uses data to better understand urban dynamics. As the authors discuss in the book, there is a long history of visual representations that shape the way we think about cities, from Romans building marble maps to the introduction of photography — which produced influential urban images about things like Hausmann’s reshaping of Paris or the crowding of tenements in New York City’s Lower East Side during the 19th century.More recently, some scholars have used visual studies to better understand city form, including Lynch, a former MIT professor whose 1960 book, “The Image of the City,” influenced many scholars. Whyte, a sociologist famous for his book “The Organization Man,” then became an urbanist closely examining public spaces.By explicitly placing AI in a continuum with these visual urban studies, the authors are making a point: Powerful as it might be, we can still think of AI primarily as a tool serving human purposes, as we seek to design and refine urban form.“Kevin Lynch at MIT was only using paper and pen,” Duarte says. “We can now scale up what he was doing, with visual AI, while also looking at many different dimension of cities.” There are extensive possibilities for applying visual AI to urban planning, ranging from emissions to traffic flow, safety, better imagery of street-level activity and sidewalks, and much more. The book also examines, for instance, urban greenery. While satellite imagery can show us how much tree cover and green spaces cities have, near-ubiquitous images from phones and other sources can also reveal to what extent people glimpse greenery in everyday life, a factor in reported wellness.“The real promise of visual AI is not simply that computers can look at millions of images,” Zhang says. “It is that we can connect what is visible in those images — streets, buildings, greenery, traffic, public space — with larger questions about how cities function and how people experience them.”Better image recognition by AI even extends to urban interiors. By using images from 400,000 AirBnB listings across the world, one recent Senseable City study shows that, contrary to some claims, interior design styles are not becoming globally more homogeneous, but reflect significant geographic differences. “No matter what it is, we can learn from what we can see and then use it as urban designers, planners, policymakers, and citizens,” Mazzarello says. “It can be our eyes, or cameras with computers, but in the end it’s the same methodology, and now we are trying to optimize the ways we can use these tools.”Promise and pitfallsIf the promise of visual AI for urban studies is vast, the pitfalls are concerning. In “How AI Sees the City,” the authors outline multiple potential problems with the technology, including the intrusiveness of widespread visual surveillance and the potential for bias being reinforced through AI systems. The installation of ubiquitous cameras can quickly raise concerns about surveillance. London, an early adopter of CCTV, has about 210 cameras per square mile. But eight of the world’s 10 most camera-heavy cities are in China; Shanghai has over 5,000 cameras per square mile. Such surveillance practices have raised controversy in other parts of the world, with debate over the uses of traffic cameras bubbling up in the U.S. this year as well. In evaluating the potential safety gains from intensive video recording, the authors write, “the benefits must be weighed against the significant erosion of personal freedom and the potential for abuse inherent in a system of constant monitoring.”Meanwhile, AI systems can reinforce social biases as well, leading to the production of data that reinforce prior perceptions as much as underlying realities — about people, neighborhoods, and whole cities. If AI models are trained on majority population groups, they may not evaluate minority groups the same way. “We need to teach AI to see, and depending on how you teach it, it will see what what is embedded in the culture,” Duarte says. “AI is not neutral.”Still, as Mazzarello adds, “our eyes are not neutral, either. Every tool has to be guided in the right way, and trained in the best way.” Other scholars have praised “How AI Sees the City.” Michael Batty of University College London has called it a “fascinating book” that “shows how we are beginning to interpret the world of urban design, suggesting ways in which we might improve design using urban analytics, AI and large language models.”Ultimately, though the authors think there is great value in deploying visual AI to learn more about our cities, how they function, and how they might be improved. With caution and independent thinking, progress is possible. Or, as they conclude in the book, “We should explore this wisely, critically, and creatively.”

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