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  • Next-Gen AI Needs Liquid Cooling

    Walk into a typical data center and one of the first things that jumps out at you is the noise—the low, buzzing sound of thousands of fans: fans next to individual computer chips, fans on the back panels of server racks, fans on the network switches. All of those fans are pushing hot air away from the temperature-sensitive computer chips and toward air-conditioning units.

    But those fans, whirr as they might, are no longer cutting it. Over the past decade, the power density of the most advanced computer chips has exploded. In 2017, Nvidia came out with the A100 came out, drawing up to 400 W. The now-popular

  • Inside Nvidia’s ‘grid-to-chip’ vision: How Vera Rubin and Spectrum-XGS push toward AI giga-factories

    Inside Nvidia’s ‘grid-to-chip’ vision: How Vera Rubin and Spectrum-XGS push toward AI giga-factories

    Nvidia will be front-and-center at this week’s Global Summit for members of the Open Compute Project (OCP), emphasizing its “grid-to-chip” philosophy.

    The company is making announcements on several fronts, including the debut of Vera Rubin MGX, its next-gen architecture fusing CPUs and GPUs, and Spectrum-XGS Ethernet, a networking fabric designed for “giga-scale” AI factories.

    [ RelatedMore Nvidia news and insights ]

    It’s all part of a bigger play by Nvidia to position itself as a connective tissue throughout the AI tech stack, embedding itself across every layer including chips and networking to full data center infrastructure and software orchestration.

    “Data centers are evolving toward giga scale,” said Nvidia senior product marketing manager Joe Delaere ahead of the event. “AI factories that manufacture intelligence generate revenue, but to maximize that revenue, the networking, the compute, the mechanicals, the power and the cooling, all have to be designed as one.”

    Putting numbers on next-gen Vera Rubin infrastructure

    Nvidia will provide more detailed specifications for its Vera Rubin NVL144 MGX-generation open architecture rack servers at the event — although the servers themselves will not be available until late 2026.

    The Vera Rubin chip architecture is the successor to Nvidia’s Blackwell. It is purpose-built for “massive-context” processing to help enterprises dramatically speed AI projects to market.

    Vera Rubin MGX brings together Nvidia’s Vera CPUs and Rubin CPX GPUs, all using the same open MGX rack footprint as Blackwell. The system allows for numerous configurations and integrations.

    “MGX is a flexible, modular building block-based approach to server and rack scale design,” Delaere said. “It allows our ecosystem to create a wide range of configurations, and do so very quickly.”

    Vera Rubin MGX will deliver almost eight times more performance than Nvidia’s GB 300 for certain types of calculation, he said. The architecture is liquid-cooled and cable-free, allowing for faster assembly and serviceability. Operators can quickly mix and match components such as CPUs, GPUs, or storage, supporting interoperability, Nvidia said.

    Matt Kimball, principal data center analyst at Moor Insights and Strategy, highlighted the modularity and cleanness of the MGX tray design.

    “This simplifies the manufacturing process significantly,” he said. For enterprises managing tens or even hundreds of thousands of racks, “this design enables a level of operational efficiency that can deliver real savings in time and cost.”

    Nvidia is also showing innovation with cooling, Kimball said. “Running cooling to the midplane is a very clean design and more efficient.”

    With electricity supplies under increasing pressure, there’s a new trade-off between the cost of chips and their energy efficiency, making chips like Nvidia’s latest more attractive. Brandon Hoff, research director for enabling technologies at IDC, said, “You get more tokens per watt. That’s kind of where we’re ending up. People have the money, they don’t have the power.”

    Dovetailing with the Vera advances, Nvidia and its partners are gearing up for the 800 VDC era. Moving from traditional 415 VAC or 480 VAC three-phase systems offers data centers increased scalability, improved energy efficiency, reduced materials usage, and higher capacity for performance in data centers, according to Nvidia. The advanced infrastructure necessary has already been adopted by the electric vehicle and solar industries.

    But the transition requires collaboration from all the layers of the stack, and Nvidia is working with more than 20 industry leaders to create a shared blueprint, it said.

    Supporting ‘giga-scale’ AI super-factories

    Along with Vera Rubin MGX, Nvidia will this week introduce Spectrum-XGS Ethernet support for OCP.

    Who wins/loses with the Intel-Nvidia union?

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  • In a First, Artificial Neurons Talk Directly to Living Cells

    In a First, Artificial Neurons Talk Directly to Living Cells

    The bacteria Geobacter sulfurreducens came from humble beginnings; it was first isolated from dirt in a ditch in Norman, Okla. But now, the surprisingly remarkable microbes are the key to the first ever artificial neurons that can directly interact with living cells.

    The G. sulfurreducens microbes communicate with one another through tiny, protein-based wires that researchers at the University of Massachusetts Amherst harvested and used to make artificial neurons. These neurons can, for the first time, process information from living cells without an intermediary device amplifying or modulating the signals, the researchers say.

    While some artificial neurons already exist, they require electronic amplification to sense the signals our bodies produce, explains Jun Yao, who works on bioelectronics and nanoelectronics at UMass Amherst. The amplification inflates both power usage and circuit complexity, and so counters efficiencies found in the brain.

    The neuron created by Yao’s team can understand the body’s signals at their natural amplitude of around 0.1 volts. This is “highly novel,” says Bozhi Tian, a biophysicist who studies living bioelectronics at the University of Chicago and was not involved in the work. This work “bridges the long-standing gap between electronic and biological signaling” and demonstrates interaction between artificial neurons and living cells that Tian calls “unprecedented.”

    Real neurons and artificial neurons

    Biological neurons are the fundamental building blocks of the brain. If external stimuli are strong enough, charge builds up in a neuron, triggering an action potential, a spike of voltage that travels down the neuron’s body to enable all types of bodily functions, including emotion and movement.

    Scientists have been working to engineer a synthetic neuron for decades, chasing after the efficiency of the human brain, which has so far seemed to escape the abilities of electronics.

    Yao’s group has designed new artificial neurons that mimic how biological neurons sense and react to electrical signals. They use sensors to monitor external biochemical changes and memristors—essentially resistors with memory—to emulate the action-potential process.

    As voltage from the external biochemical events increases, ions accumulate and begin to form a filament across a gap in the memristor—which in this case was filled with protein nanowires. If there is enough voltage, the filament completely bridges the gap. Current shoots through the device and the filament then dissolves, dispersing the ions and stopping the current. The complete process mimics a neuron’s action potential.

    The team tested its artificial neurons by connecting them to cardiac tissue. The devices measured a baseline amount of cellular contraction, which did not produce enough signal to cause the artificial neuron to fire. Then the researchers took another measurement after the tissue was dosed with norepinephrine—a drug that increases how frequently cells contract. The artificial neurons triggered action potentials only during the medicated trial, proving that they can detect changes in living cells.

    The experimental results were published 29 September in Nature Communications.

    Natural nanowires

    The group has G. sulfurreducens to thank for the breakthrough.

    The microbes synthesize miniature cables, called protein nanowires, that they use for intraspecies communication. These cables are charge conductors that survive for long periods of time in the wild without decaying. (Remember, they evolved for Oklahoma ditches.) They’re extremely stable, even for device fabrication, Yao says.

    To the engineers, the most notable property of the nanowires is how efficiently ions move along them. The nanowires offer a low-energy means of transferring charge between human cells and artificial neurons, thus avoiding the need for a separate amplifier or modulator. “And amazingly, the material is designed for this,” says Yao.

    The group developed a method to shear the cables off bacterial bodies, purifying the material and suspending it in a solution. The team laid the mixture out and let the water evaporate, leaving a one-molecule-thin film made from the protein nanowire material.

    This efficiency allows the artificial neuron to yield huge power savings. Yao’s group integrated the film into the memristor at the core of the neuron, lowering the energy barrier for the reaction that causes the memristor to respond to signals recognized by the sensor. With this innovation, the researchers say, the artificial neuron uses one-tenth the voltage and 1/100 the power of others.

    Chicago’s Tian thinks this “extremely impressive” energy efficiency is “essential for future low-power, implantable, and biointegrated computing systems.”

    The power advantages make this synthetic-neuron design attractive for all kinds of applications, the researchers say.

    Responsive wearable electronics, like prosthetics that adapt to stimuli from the body, could make use of these new artificial neurons, Tian says. Eventually, implantable systems that rely on the neurons could “learn like living tissues, advancing personalized medicine and brain-inspired computing” to “interpret physiological states, leading to biohybrid networks that merge electronics with living intelligence,” he says.

    The artificial neurons could also be useful in electronics outside the biomedical field. Millions of them on a chip could replace transistors, completing the same tasks while decreasing power usage, Yao says. The fabrication process for the neurons does not involve high temperatures and utilizes the same kind of photolithography that silicon chip manufacturers do, he says.

    Yao does, however, point out two possible bottlenecks producers could face when scaling up these artificial neurons for electronics. The first is obtaining more of the protein nanowires from G. sulfurreducens. His lab currently works for three days to generate only 100 micrograms of material—about the mass of one grain of table salt. And that amount can coat only a very small device, so Yao questions how this step in the process could scale up for production.

    His other concern is how to achieve a uniform coating of the film at the scale of a silicon wafer. “If you wanted to make high-density small devices, the uniformity of film thickness actually is a critical parameter,” he explains. But the artificial neurons his group has developed are too small to do any meaningful uniformity testing for now.

    Tian doesn’t expect artificial neurons to replace silicon transistors in conventional computing, but instead sees them as a parallel offering for “hybrid chips that merge biological adaptability with electronic precision,” he says.

    In the far future, Yao hopes that such bioderived devices will also be appreciated for not contributing to e-waste. When a user no longer wants a device, they can simply dump the biological component in the surrounding environment, Yao says, because it won’t cause an environmental hazard.

    “By using this kind of nature-derived, microbial material, we can create a greener technology that’s more sustainable for the world,” Yao says.

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  • California’s next big one could be faster and far more destructive

    Supershear earthquakes, moving faster than seismic waves, could cause catastrophic shaking across California. USC researchers warn that many faults capable of magnitude 7 quakes might produce these explosive ruptures. Current construction standards don’t account for their directional force. Stronger monitoring and building codes are urgently needed.

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  • Could We Really Turn Mars Green?

    Mars captured by Valles Marineris, taken by the Viking 1 probe (Credit : NASA)

    Science fiction is edging closer to reality. A team of scientists has created a detailed roadmap for transforming Mars from a frozen, lifeless desert into a world where plants could grow and humans might one day breathe without spacesuits. The plan isn’t about launching missions tomorrow, it’s about whether we should even try, and what recent breakthroughs in biology, climate engineering, and space launch technology tell us about what’s now possible. But there’s a catch, terraforming a planet like Mars might erase its geological history forever, destroying any traces of ancient Martian life and eliminating our chance to understand how worlds evolve. The question has shifted from “could we turn Mars green?” to something far more profound “should we?”


    📰 Original Source: Universe Today

    This article was automatically imported from our UAP intelligence monitoring network.

  • Imaging Dark Matter One Clump at a Time

    Imaging Dark Matter One Clump at a Time

    What if you could photograph something completely invisible? To our rather limited eyes that’s what astronomers seem to do all the time with infra red and radio astronomy to name a few. But, astronomers can do this in a rather intriguing way with something that does seem to be truly invisible! A team of astronomers have captured the latest “image” of a dark matter object a million times more massive than our Sun, not by seeing it, but by watching how it warps the light from galaxies billions of light years beyond it. Using an Earth sized telescope network they have revealed one of the smallest dark matter clumps ever found, offering a glimpse into the hidden structure of our universe.

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  • 7 new tips and tricks for your iPhone 17 or iPhone Air

    7 new tips and tricks for your iPhone 17 or iPhone Air

    Apple has four new iPhones for 2025: the iPhone 17, iPhone 17 Pro, iPhone 17 Pro Max, and the super-slim iPhone Air (with no number 17 attached). If you’ve picked up one of these, then you’re probably wondering how to get the most out of it, and what you can try that’s new.

    Together with the latest iOS 26 software that comes on board these devices, you’ve got lots to explore—including improvements to the way you take photos, manage calls, and boost battery life. Here are some tricks and tips to get you started with your new iPhone.

    1. Take selfies with Center Stage

    All four new iPhones have a square selfie camera sensor on the front, and that shift in shape means you can snap landscape photos even when you’re holding your phone in the portrait orientation. Even better, the iOS Camera app will automatically recognize when more people join your selfie photo, and expand the frame of view accordingly.

    It’s called Center Stage after the similar feature on iPads and Macs, and you can enable it in the Camera selfie mode by tapping the Center Stage button (the icon looks like a person in a frame). There are two settings you can toggle on or off: Auto Zoom (expands the frame when a face is detected) and Auto Rotate (rotates the frame to fit in more people).

    2. Get your iPhone to screen your calls

    New in iOS 26 is Call Screening, which means that calls from unknown numbers get routed to your own personal answering service. The caller will be asked who they are and what they want, with a text transcript shown on your screen—you can then decide to pick up or not. It’s like an enhanced version of voicemail, which can help you filter out spam calls.

    This won’t happen for contacts who are in your iPhone’s address book, and you can enable and disable the feature as needed. Head to iOS Settings, tap Apps then Phone, and you can choose from three options: Ask Reason for Calling (which is Call Screening), Never (no Call Screening), and Silence (unknown callers go straight to voicemail).

    Get your iPhone to screen your calls for you. Screenshot: Apple

    3. Load up Apple Games

    New in iOS 26 is a central hub for your mobile games called Apple games—and you canfind it across iPadOS 26 and macOS Tahoe 26, so you can keep track of your gaming exploits across multiple devices. As well as launching your current games and checking your progress, you can also discover new titles via personalized recommendations.

    This Apple Games app will appear on every iPhone running iOS 26, but it’s worth noting that the iPhone 17 Pro and Pro Max have a new vapor cooling system installed. In theory, that should mean the most demanding games run more smoothly, while also keeping your phone cooler—so it’s worth loading up some of your more intense games to test it.

    4. Get live translations in your AirPods

    One of the best new features in iOS 26 is Live Translation, and it’s a feature that works really well with Apple AirPods—as long as they’re the AirPods 4 with active noise cancellation, the AirPods Pro 2, or the AirPods Pro 3. When enabled, it means when people talk to you in a foreign language, you get an almost-instant translation in your ears.

    You need to have Apple Intelligence enabled, and the right languages downloaded: Tap your AirPods then Languages in Settings. Next, open the Apple Translate app, tap the Live button at the bottom and choose your languages: Once you tap Start Conversation, you should be able to chat to someone in a different language via your iPhone and AirPods.

    5. Customize the Action Button

    If you’ve got one of the new 2025 iPhones—or an iPhone 15 Pro or Pro Max, or any iPhone 16—then you’ve got access to the Action Button, on the top of the left side as you look at the phone in portrait orientation. One of the first customizations you should consider for your new iPhone is changing what happens when you press and hold on this button.

    By default, the action will switch between Silent and Ring modes, like the traditional switch that the Action Button replaced. However, if you go to iOS Settings and choose Action Button, you’ll see there are several options to swipe between: They include Camera, Visual Intelligence, Voice Memo, Magnifier, Focus, and Translate.

    You’ve got lots of options for the Action Button. Screenshot: Apple

    6. Maximize your iPhone’s battery life

    Unbox and set up your new iPhone and you’ll discover there’s a new battery management option in iOS 26: It’s called Adaptive Power, and you can find it by tapping Battery then Power Mode from Settings. Essentially, it helps manage battery life in the background during demanding tasks, which should mean you get more time between battery charges.

    The mode may shut down some background activities, for example, or slightly dim the display of your iPhone—but all of this happens in the background. On the same screen you still have the standard Low Power Mode toggle switch, which uses several tricks to extend battery life even further (it can be activated manually as well as kicking in automatically).

    7. Make use of the Camera Control button

    All of the new iPhone 17 models, like the iPhone 16 devices before them, have a Camera Control button. If you’re holding your iPhone in its portrait orientation with the screen facing you, Camera Control is the button on the right side, lower down. By default you can press it to launch the Camera app immediately, whatever you’re doing with your phone.
    From there you can press the Camera Control button again to snap a picture, or hold it down to start recording video. Alternatively, do a light double-press on the button, and you get the settings options for that mode, which you can scroll through with a swipe on the Camera Control itself: They include Exposure, Depth, Zoom, Styles, and Tone.

    The post 7 new tips and tricks for your iPhone 17 or iPhone Air appeared first on Popular Science.

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  • Pilates started in a WWI internment camp

    Pilates is having a moment. According to a recent report from the Sports and Fitness Industry Association, Pilates participation has shot up from 9.2 million participants to 12.9 million since 2019, a jump of nearly 40% and the largest of any workout type across the United States. Research from Balanced Body found that in a survey of 800 instructors, 67% are consistently selling out classes.

    For many, the term Pilates conjures up an image of leggings-clad women and pricey studios filled with intimidating-looking equipment. While that’s true in some ways (a single studio mat class may cost you upwards of $20, especially in big cities), Pilates is a form of exercise with a fascinating history. It can be geared to anyone, from athletes to patients with chronic illness, and you certainly don’t have to invest a lot of money into a studio membership to see the benefits. 

    “Many people commonly think of Pilates as a trendy fitness class or something limited to stretching and toning,” says Joe Hribick, a clinical assistant professor of physical therapy at Lebanon Valley College. “However, in reality, it is a science-based system of movement training that can be tailored for nearly every body type and ability level.”

    Pilates’s wartime origins 

    The story of Pilates is rife with drama and mystery, and begins with Joseph Pilates. Born in Germany in 1880s, Pilates studied yoga and martial arts in order to help strengthen his own body, says June Kloubec, associate teaching professor of kinesiology at Seattle University. But the exercise really got its start when he was stuck on the Isle of Man during World War I. 

    How he got there is a particularly fascinating tale. Pilates was traveling across England as a performer in a German circus troupe doing a Greek statue act with his brother. But in 1914, anti-German sentiment in the UK led to the passage of the Aliens Restriction Act. This law had dramatic effects, the most important of which for Pilates was the internment of German males of military age.

    The largest of these German internment camps was Knockaloe. Located on the small, blustery Isle of Man, nestled in the Irish Sea between England and Ireland, it housed 23,000 men at its peak. According to the UK-based research collaboration Our Migration Story, a combination of deportation and forced internment brought the German population in the UK down from 53,324 to 22,254 between 1911 and 1919.

    A grainy, black and white archival photo of Joseph Pilates, an older man with white hair, performing a challenging exercise on a mat or piece of equipment. He is wearing a light-colored long-sleeve top and shorts, sitting with his legs extended wide and his arms grasping his feet while keeping his balance. The background is dimly lit with curtains visible behind him.
    Joesph Pilates, founder of the Pilates exercise method, demonstrates his techniques in his New York City eighth avenue studio on October 4, 1961. Image: I C Rapoport / Contributor / Getty Images I C Rapoport

    Pilates watched his fellow inmates get increasingly depressed, sickly, and apathetic, he told Sports Illustrated’s Robert Wernick in a 1962 interview. He was determined to change things. 

    Pilates watched the flexible, stretchy movements of the cats living on the Isle of Man, and started thinking how he could develop an exercise approach inspired by their athletic bodies, he told Wernick. So he spent his time studying and observing animals, eventually practicing a unique form of exercise that used body weight as resistance.

    The story goes that he took his knowledge to the internment camp hospital, where some Pilates practitioners say he began developing new workout equipment using hospital beds and springs: the precursor to the reformer. But that is yet to be confirmed by historical evidence—the Knockaloe Charitable Trust notes that there’s no proof of his hospital involvement.

    The first Pilates gym in New York City

    After the war, Pilates briefly returned to Germany. But in the mid-1920s, he high-tailed it to New York City. With his partner Clara, he founded the first Pilates studio dubbed the Joseph H. Pilates Universal Gymnasium, which remained open for decades. 

    “While Joseph designed the movement patterns, Clara established the crucial tradition of evolving and adapting the Pilates Method to suit individual client needs—a philosophy that ensures the technique, now integrated with modern biomechanical principles, remains highly effective over 95 years later,” adds Jill Drummond, Vice President of Fitness at BODYBAR Pilates

    In New York City, Pilates perfected his technique, trained athletes and dancers, including Martha Graham and George Balanchine, and filed patents for various workout tools like the early reformer and the so-called “exercising apparatus.” He stayed fit and lithe until his death in 1967. 

    There was a bit of hubbub in trying to trademark the Pilates name when he passed. But in 2000, a Manhattan federal court declared that Pilates was an exercise method, and therefore not trademarkable, kind of like yoga or aerobics. 

    The practice and benefits of pilates

    The core principles of Pilates, be it for mat, reformer, or any new rendition, haven’t changed much since its inception: breathing, cervical alignment, rib and scapular stabilization, pelvic mobility, and utilizing the transverse abdominis, says Kloubec. Each exercise begins with preparation of a key set of muscles, such as the abdominal, gluteal, and paraspinal muscles. Then it’s time for movements such as the shoulder bridge or bird dog. These exercises are typically repeated several times, and then it’s on to the next.  

    Experts are beginning to understand the benefits of Pilates-style exercises beyond just the increased balance and muscle strength that comes out of attending a few weekly classes. Hribick says Pilates techniques are sometimes integrated into physical therapy practice for patients with low back pain, postural dysfunction, joint hypermobility, or after orthopedic surgeries. 

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    Most research on Pilates compares it with a non-active control group and has small, often niche, sample sizes. This can make clinical findings on the exercise’s effects on health less solid, says Tiffany Field, research professor at the University of Miami School of Medicine and author of a recent review on Pilates research

    “The gold standard nowadays is that you need to compare a physical exercise of that type with another physical exercise, and a lot of times when that happens they come out almost equivalent,” she tells PopSci. 

    Pilates is low-impact and gentle on joints but provides a challenging workout, adds Drummond, which is a central part of its lasting allure. But it’s not necessarily a replacement for other sports and activities, be it strength training, running, or yoga, adds Hribick. Instead, think of it as a complement to your favorite routines.

    Pretty much anyone can get started with Pilates, from older people to athletes to patients with chronic illness to desk job workers. All you need is a mat, but Kloubec recommends starting in a class with a professional teacher to get the gist of movements and how they feel. Instructors have adapted the workout to include people with limited mobility, but it’s important to check in with your physician before undertaking any kind of new exercise if you’re pregnant or facing health challenges.

    The benefit of Pilates compared to some other forms of exercise is that the barrier to entry is low. Pilates movements are uniquely low-impact and gentle on joints while still being a challenging workout, adds Drummond. This means that pretty much anyone can get started with Pilates, from elderly folks to athletes to patients with chronic illness to desk job workers. All you need is a mat, but Kloubec recommends starting in a class setting with a professional teacher until you get the gist of the movements and how they feel. 

    “I think a lot of folks that don’t think they could do Pilates could do it and benefit from it,” Kloubec says. “I believe that this is especially true for individuals with chronic disease, disabilities, or other movement challenges. Pilates is something that they could do and they would see results.”

    The post Pilates started in a WWI internment camp appeared first on Popular Science.


    📰 Original Source: Popular Science

    This article was automatically imported from our UAP intelligence monitoring network.

  • A New Algorithm Makes It Faster to Find the Shortest Paths

    Ben BrubakerScienceOct 12, 2025 7:00 AMthis story appeared in Quanta Magazine.

    If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost. You may end up spending too much time putting the pieces in order.

    This dilemma is especially relevant to one of the most iconic problems in computer science: finding the shortest path from a specific starting point in a network to every other point. It’s like a souped-up version of a problem you need to solve each time you move: learning the best route from your new home to work, the gym, and the supermarket.

    “Shortest paths is a beautiful problem that anyone in the world can relate to,” said Mikkel Thorup, a computer scientist at the University of Copenhagen.

    Intuitively, it should be easiest to find the shortest path to nearby destinations. So if you want to design the fastest possible algorithm for the shortest-paths problem, it seems reasonable to start by finding the closest point, then the next-closest, and so on. But to do that, you need to repeatedly figure out which point is closest. You’ll sort the points by distance as you go. There’s a fundamental speed limit for any algorithm that follows this approach: You can’t go any faster than the time it takes to sort.

    Forty years ago, researchers designing shortest-paths algorithms ran up against this “sorting barrier.” Now, a team of researchers has devised a new algorithm that breaks it. It doesn’t sort, and it runs faster than any algorithm that does.

    “The authors were audacious in thinking they could break this barrier,” said Robert Tarjan, a computer scientist at Princeton University. “It’s an amazing result.”

    The Frontier of Knowledge

    To analyze the shortest-paths problem mathematically, researchers use the language of graphs—networks of points, or nodes, connected by lines. Each link between nodes is labeled with a number called its weight, which can represent the length of that segment or the time needed to traverse it. There are usually many routes between any two nodes, and the shortest is the one whose weights add up to the smallest number. Given a graph and a specific “source” node, an algorithm’s goal is to find the shortest path to every other node.

    The most famous shortest-paths algorithm, devised by the pioneering computer scientist Edsger Dijkstra in 1956, starts at the source and works outward step by step. It’s an effective approach, because knowing the shortest path to nearby nodes can help you find the shortest paths to more distant ones. But because the end result is a sorted list of shortest paths, the sorting barrier sets a fundamental limit on how fast the algorithm can run.

    Illustration: Mark Belan, Samuel Velasco/Quanta Magazine

    In 1984, Tarjan and another researcher improved Dijkstra’s original algorithm so that it hit this speed limit. Any further improvement would have to come from an algorithm that avoids sorting.

    In the late 1990s and early 2000s, Thorup and other researchers devised algorithms that broke the sorting barrier, but they needed to make certain assumptions about weights. Nobody knew how to extend their techniques to arbitrary weights. It seemed they’d hit the end of the road.

    “The research stopped for a very long time,” said Ran Duan, a computer scientist at Tsinghua University in Beijing. “Many people believed that there’s no better way.”

    Duan wasn’t one of them. He’d long dreamed of building a shortest-paths algorithm that could break through the sorting barrier on all graphs. Last fall, he finally succeeded.

    Out of Sorts

    Duan’s interest in the sorting barrier dates back nearly 20 years to his time in graduate school at the University of Michigan, where his adviser was one of the researchers who worked out how to break the barrier in specific cases. But it wasn’t until 2021 that Duan devised a more promising approach.

    The key was to focus on where the algorithm goes next at each step. Dijkstra’s algorithm takes the region that it has already explored in previous steps. It decides where to go next by scanning this region’s “frontier”—that is, all the nodes connected to its boundary. This doesn’t take much time at first, but it gets slower as the algorithm progresses.

    Edsger Dijkstra devised a classic algorithm that finds the shortest path from a specific point in a network to every other point.

    Photograph: Hamilton Richards

    Duan instead envisioned grouping neighboring nodes on the frontier into clusters. He would then only consider one node from each cluster. With fewer nodes to sift through, the search could be faster at each step. The algorithm also might end up going somewhere other than the closest node, so the sorting barrier wouldn’t apply. But ensuring that this clustering-based approach actually made the algorithm faster rather than slower would be a challenge.

    Duan fleshed out this basic idea over the following year, and by fall 2022 he was optimistic that he could surmount the technical hurdles. He roped in three graduate students to help work out the details, and a few months later they arrived at a partial solution—an algorithm that broke the sorting barrier for any weights, but only on so-called undirected graphs.

    In undirected graphs, every link can be traversed in both directions. Computer scientists are usually more interested in the broader class of graphs that feature one-way paths, but these “directed” graphs are often trickier to navigate.

    “There could be a case that A can reach B very easily, but B cannot reach A very easily,” said Xiao Mao, a computer science graduate student at Stanford University. “That’s going to give you a lot of trouble.”

    Promising Paths

    In the summer of 2023, Mao heard Duan give a talk about the undirected-graph algorithm at a conference in California. He struck up a conversation with Duan, whose work he’d long admired.

    “I met him for the first time in real life,” Mao recalled. “It was very exciting.”

    After the conference, Mao began thinking about the problem in his spare time. Meanwhile, Duan and his colleagues were exploring new approaches that could work on directed graphs. They took inspiration from another venerable algorithm for the shortest-paths problem, called the Bellman-Ford algorithm, that doesn’t produce a sorted list. At first glance, it seemed like an unwise strategy, since the Bellman-Ford algorithm is much slower than Dijkstra’s.

    “Whenever you do research, you try to take a promising path,” Thorup said. “I would almost call it anti-promising to take Bellman-Ford, because it looks completely like the stupidest thing you could possibly do.”

    Duan’s team avoided the slowness of the Bellman-Ford algorithm by running it for just a few steps at a time. This selective use of Bellman-Ford enabled their algorithm to scout ahead for the most valuable nodes to explore in later steps. These nodes are like intersections of major thoroughfares in a road network.

    “You have to pass through [them] to get the shortest path to a lot of other stuff,” Thorup said.

    In March 2024, Mao thought of another promising approach. Some key steps in the team’s original approach had used randomness. Randomized algorithms can efficiently solve many problems, but researchers still prefer nonrandom approaches. Mao devised a new way to solve the shortest-paths problem without randomness. He joined the team, and they worked together over the following months via group chats and video calls to merge their ideas. Finally, in the fall, Duan realized they could adapt a technique from an algorithm he’d devised in 2018 that broke the sorting barrier for a different graph problem. That technique was the last piece they needed for an algorithm that ran faster than Dijkstra’s on both directed and undirected graphs.

    The finished algorithm slices the graph into layers, moving outward from the source like Dijkstra’s. But rather than deal with the whole frontier at each step, it uses the Bellman-Ford algorithm to pinpoint influential nodes, moves forward from these nodes to find the shortest paths to others, and later comes back to other frontier nodes. It doesn’t always find the nodes within each layer in order of increasing distance, so the sorting barrier doesn’t apply. And if you chop up the graph in the right way, it runs slightly faster than the best version of Dijkstra’s algorithm. It’s considerably more intricate, relying on many pieces that need to fit together just right. But curiously, none of the pieces use fancy mathematics.

    “This thing might as well have been discovered 50 years ago, but it wasn’t,” Thorup said. “That makes it that much more impressive.”

    Duan and his team plan to explore whether the algorithm can be streamlined to make it even faster. With the sorting barrier vanquished, the new algorithm’s runtime isn’t close to any fundamental limit that computer scientists know of.

    “Being an optimist, I would not be surprised if you could take it down even further,” Tarjan said. “I certainly don’t think this is the last step in the process.”

    Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

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