Best of the rest Research roundup: 7 stories we almost missed Also: drumming chimpanzees, picking styles of two jazz greats, and an ancient underground city's soundscape Jennifer Ouellette – May 31, 2025 5:37 pm | 4 Time lapse photos show a new ping-pong-playing robot performing a top spin. Credit: David Nguyen, Kendrick Cancio and Sangbae Kim Time lapse photos show a new ping-pong-playing robot performing a top spin. Credit: David Nguyen, Kendrick Cancio and Sangbae Kim Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only   Learn more It's a regrettable reality that there is never time to cover all the interesting scientific stories we come across each month. In the past, we've featured year-end roundups of cool science stories we (almost) missed. This year, we're experimenting with a monthly collection. May's list includes a nifty experiment to make a predicted effect of special relativity visible; a ping-pong playing robot that can return hits with 88 percent accuracy; and the discovery of the rare genetic mutation that makes orange cats orange, among other highlights. Special relativity made visible Credit: TU Wien Perhaps the most well-known feature of Albert Einstein's special theory of relativity is time dilation and length contraction. In 1959, two physicists predicted another feature of relativistic motion: an object moving near the speed of light should also appear to be rotated. It's not been possible to demonstrate this experimentally, however—until now. Physicists at the Vienna University of Technology figured out how to reproduce this rotational effect in the lab using laser pulses and precision cameras, according to a paper published in the journal Communications Physics. They found their inspiration in art, specifically an earlier collaboration with an artist named Enar de Dios Rodriguez, who collaborated with VUT and the University of Vienna on a project involving ultra-fast photography and slow light. For this latest research, they used objects shaped like a cube and a sphere and moved them around the lab while zapping them with ultrashort laser pulses, recording the flashes with a high-speed camera. Getting the timing just right effectively yields similar results to a light speed of 2 m/s. After photographing the objects many times using this method, the team then combined the still images into a single image. The results: the cube looked twisted and the sphere's North Pole was in a different location—a demonstration of the rotational effect predicted back in 1959. DOI: Communications Physics, 2025. 10.1038/s42005-025-02003-6  (About DOIs). Drumming chimpanzees A chimpanzee feeling the rhythm. Credit: Current Biology/Eleuteri et al., 2025. Chimpanzees are known to "drum" on the roots of trees as a means of communication, often combining that action with what are known as "pant-hoot" vocalizations (see above video). Scientists have found that the chimps' drumming exhibits key elements of musical rhythm much like humans, according to  a paper published in the journal Current Biology—specifically non-random timing and isochrony. And chimps from different geographical regions have different drumming rhythms. Back in 2022, the same team observed that individual chimps had unique styles of "buttress drumming," which served as a kind of communication, letting others in the same group know their identity, location, and activity. This time around they wanted to know if this was also true of chimps living in different groups and whether their drumming was rhythmic in nature. So they collected video footage of the drumming behavior among 11 chimpanzee communities across six populations in East Africa (Uganda) and West Africa (Ivory Coast), amounting to 371 drumming bouts. Their analysis of the drum patterns confirmed their hypothesis. The western chimps drummed in regularly spaced hits, used faster tempos, and started drumming earlier during their pant-hoot vocalizations. Eastern chimps would alternate between shorter and longer spaced hits. Since this kind of rhythmic percussion is one of the earliest evolved forms of human musical expression and is ubiquitous across cultures, findings such as this could shed light on how our love of rhythm evolved. DOI: Current Biology, 2025. 10.1016/j.cub.2025.04.019  (About DOIs). Distinctive styles of two jazz greats Jazz lovers likely need no introduction to Joe Pass and Wes Montgomery, 20th century guitarists who influenced generations of jazz musicians with their innovative techniques. Montgomery, for instance, didn't use a pick, preferring to pluck the strings with his thumb—a method he developed because he practiced at night after working all day as a machinist and didn't want to wake his children or neighbors. Pass developed his own range of picking techniques, including fingerpicking, hybrid picking, and "flat picking." Chirag Gokani and Preston Wilson, both with Applied Research Laboratories and the University of Texas, Austin, greatly admired both Pass and Montgomery and decided to explore the underlying the acoustics of their distinctive playing, modeling the interactions of the thumb, fingers, and pick with a guitar string. They described their research during a meeting of the Acoustical Society of America in New Orleans, LA. Among their findings: Montgomery achieved his warm tone by playing closer to the bridge and mostly plucking at the string. Pass's rich tone arose from a combination of using a pick and playing closer to the guitar neck. There were also differences in how much a thumb, finger, and pick slip off the string:  use of the thumb (Montgomery) produced more of a "pluck" compared to the pick (Pass), which produced more of a "strike." Gokani and Wilson think their model could be used to synthesize digital guitars with a more realistic sound, as well as helping guitarists better emulate Pass and Montgomery. Sounds of an ancient underground city Credit: Sezin Nas Turkey is home to the underground city Derinkuyu, originally carved out inside soft volcanic rock around the 8th century BCE. It was later expanded to include four main ventilation channels (and some 50,000 smaller shafts) serving seven levels, which could be closed off from the inside with a large rolling stone. The city could hold up to 20,000 people and it  was connected to another underground city, Kaymakli, via tunnels. Derinkuyu helped protect Arab Muslims during the Arab-Byzantine wars, served as a refuge from the Ottomans in the 14th century, and as a haven for Armenians escaping persecution in the early 20th century, among other functions. The tunnels were rediscovered in the 1960s and about half of the city has been open to visitors since 2016. The site is naturally of great archaeological interest, but there has been little to no research on the acoustics of the site, particularly the ventilation channels—one of Derinkuyu's most unique features, according to Sezin Nas, an architectural acoustician at Istanbul Galata University in Turkey.  She gave a talk at a meeting of the Acoustical Society of America in New Orleans, LA, about her work on the site's acoustic environment. Nas analyzed a church, a living area, and a kitchen, measuring sound sources and reverberation patterns, among other factors, to create a 3D virtual soundscape. The hope is that a better understanding of this aspect of Derinkuyu could improve the design of future underground urban spaces—as well as one day using her virtual soundscape to enable visitors to experience the sounds of the city themselves. MIT's latest ping-pong robot Robots playing ping-pong have been a thing since the 1980s, of particular interest to scientists because it requires the robot to combine the slow, precise ability to grasp and pick up objects with dynamic, adaptable locomotion. Such robots need high-speed machine vision, fast motors and actuators, precise control, and the ability to make accurate predictions in real time, not to mention being able to develop a game strategy. More recent designs use AI techniques to allow the robots to "learn" from prior data to improve their performance. MIT researchers have built their own version of a ping-pong playing robot, incorporating a lightweight design and the ability to precisely return shots. They built on prior work developing the Humanoid, a small bipedal two-armed robot—specifically, modifying the Humanoid's arm by adding an extra degree of freedom to the wrist so the robot could control a ping-pong paddle. They tested their robot by mounting it on a ping-pong table and lobbing 150 balls at it from the other side of the table, capturing the action with high-speed cameras. The new bot can execute three different swing types (loop, drive, and chip) and during the trial runs it returned the ball with impressive accuracy across all three types: 88.4 percent, 89.2 percent, and 87.5 percent, respectively. Subsequent tweaks to theirrystem brought the robot's strike speed up to 19 meters per second (about 42 MPH), close to the 12 to 25 meters per second of advanced human players. The addition of control algorithms gave the robot the ability to aim. The robot still has limited mobility and reach because it has to be fixed to the ping-pong table but the MIT researchers plan to rig it to a gantry or wheeled platform in the future to address that shortcoming. Why orange cats are orange Credit: Astropulse/CC BY-SA 3.0 Cat lovers know orange cats are special for more than their unique coloring, but that's the quality that has intrigued scientists for almost a century. Sure, lots of animals have orange, ginger, or yellow hues, like tigers, orangutans, and golden retrievers. But in domestic cats that color is specifically linked to sex. Almost all orange cats are male. Scientists have now identified the genetic mutation responsible and it appears to be unique to cats, according to a paper published in the journal Current Biology. Prior work had narrowed down the region on the X chromosome most likely to contain the relevant mutation. The scientists knew that females usually have just one copy of the mutation and in that case have tortoiseshell (partially orange) coloring, although in rare cases, a female cat will be orange if both X chromosomes have the mutation. Over the last five to ten years, there has been an explosion in genome resources (including complete sequenced genomes) for cats which greatly aided the team's research, along with taking additional DNA samples from cats at spay and neuter clinics. From an initial pool of 51 candidate variants, the scientists narrowed it down to three genes, only one of which was likely to play any role in gene regulation: Arhgap36. It wasn't known to play any role in pigment cells in humans, mice, or non-orange cats. But orange cats are special; their mutation (sex-linked orange) turns on Arhgap36 expression in pigment cells (and only pigment cells), thereby interfering with the molecular pathway that controls coat color in other orange-shaded mammals. The scientists suggest that this is an example of how genes can acquire new functions, thereby enabling species to better adapt and evolve. DOI: Current Biology, 2025. 10.1016/j.cub.2025.03.075  (About DOIs). Not a Roman "massacre" after all Credit: Martin Smith In 1936, archaeologists excavating the Iron Age hill fort Maiden Castle in the UK unearthed dozens of human skeletons, all showing signs of lethal injuries to the head and upper body—likely inflicted with weaponry. At the time, this was interpreted as evidence of a pitched battle between the Britons of the local Durotriges tribe and invading Romans. The Romans slaughtered the native inhabitants, thereby bringing a sudden violent end to the Iron Age. At least that's the popular narrative that has prevailed ever since in countless popular articles, books, and documentaries. But a paper published in the Oxford Journal of Archaeology calls that narrative into question. Archaeologists at Bournemouth University have re-analyzed those burials, incorporating radiocarbon dating into their efforts. They concluded that those individuals didn't die in a single brutal battle. Rather, it was Britons killing other Britons over multiple generations between the first century BCE and the first century CE—most likely in periodic localized outbursts of violence in the lead-up to the Roman conquest of Britain. It's possible there are still many human remains waiting to be discovered at the site, which could shed further light on what happened at Maiden Castle. DOI: Oxford Journal of Archaeology, 2025. 10.1111/ojoa.12324  (About DOIs). Jennifer Ouellette Senior Writer Jennifer Ouellette Senior Writer Jennifer is a senior writer at Ars Technica with a particular focus on where science meets culture, covering everything from physics and related interdisciplinary topics to her favorite films and TV series. Jennifer lives in Baltimore with her spouse, physicist Sean M. Carroll, and their two cats, Ariel and Caliban. 4 Comments

Scientific research across fields like chemistry, biology, and artificial intelligence has long relied on human experts to explore knowledge, generate ideas, design experiments, and refine results. Yet, as problems grow more complex and data-intensive, discovery slows. While AI tools, such as language models and robotics, can handle specific tasks, like literature searches or code analysis, they rarely encompass the entire research cycle. Bridging the gap between idea generation and experimental validation remains a key challenge. For AI to autonomously advance science, it must propose hypotheses, design and execute experiments, analyze outcomes, and refine approaches in an iterative loop. Without this integration, AI risks producing disconnected ideas that depend on human supervision for validation. Before the introduction of a unified system, researchers relied on separate tools for each stage of the process. Large language models could help find relevant scientific papers, but they didn’t directly feed into experiment design or result analysis. Robotics can assist in automating physical experiments, and coding libraries like PyTorch can help build models; however, these tools operate independently of each other. There was no single system capable of handling the entire process, from forming ideas to verifying them through experiments. This led to bottlenecks, where researchers had to connect the dots manually, slowing progress and leaving room for errors or missed opportunities. The need for an integrated system that could handle the entire research cycle became clear. Researchers from the NovelSeek Team at the Shanghai Artificial Intelligence Laboratory developed NovelSeek, an AI system designed to run the entire scientific discovery process autonomously. NovelSeek comprises four main modules that work in tandem: a system that generates and refines research ideas, a feedback loop where human experts can interact with and refine these ideas, a method for translating ideas into code and experiment plans, and a process for conducting multiple rounds of experiments. What makes NovelSeek stand out is its versatility; it works across 12 scientific research tasks, including predicting chemical reaction yields, understanding molecular dynamics, forecasting time-series data, and handling functions like 2D semantic segmentation and 3D object classification. The team designed NovelSeek to minimize human involvement, expedite discoveries, and deliver consistent, high-quality results. The system behind NovelSeek involves multiple specialized agents, each focused on a specific part of the research workflow. The “Survey Agent” helps the system understand the problem by searching scientific papers and identifying relevant information based on keywords and task definitions. It adapts its search strategy by first doing a broad survey of papers, then going deeper by analyzing full-text documents for detailed insights. This ensures that the system captures both general trends and specific technical knowledge. The “Code Review Agent” examines existing codebases, whether user-uploaded or sourced from public repositories like GitHub, to understand how current methods work and identify areas for improvement. It checks how code is structured, looks for errors, and creates summaries that help the system build on past work. The “Idea Innovation Agent” generates creative research ideas, pushing the system to explore different approaches and refine them by comparing them to related studies and previous results. The system even includes a “Planning and Execution Agent” that turns ideas into detailed experiments, handles errors during the testing process, and ensures smooth execution of multi-step research plans. NovelSeek delivered impressive results across various tasks. In chemical reaction yield prediction, NovelSeek improved performance from a baseline of 24.2% (with a variation of ±4.2) to 34.8% (with a much smaller variation of ±1.1) in just 12 hours, progress that human researchers typically need months to achieve. In enhancer activity prediction, a key task in biology, NovelSeek raised the Pearson correlation coefficient from 0.65 to 0.79 within 4 hours. For 2D semantic segmentation, a task used in computer vision, precision improved from 78.8% to 81.0% in just 30 hours. These performance boosts, achieved in a fraction of the time typically needed, highlight the system’s efficiency. NovelSeek also successfully managed large, complex codebases with multiple files, demonstrating its ability to handle research tasks at a project level, not just in small, isolated tests. The team has made the code open-source, allowing others to use, test, and contribute to its improvement. Several Key Takeaways from the Research on NovelSeek include: NovelSeek supports 12 research tasks, including chemical reaction prediction, molecular dynamics, and 3D object classification. Reaction yield prediction accuracy improved from 24.2% to 34.8% in 12 hours. Enhancer activity prediction performance increased from 0.65 to 0.79 in 4 hours. 2D semantic segmentation precision improved from 78.8% to 81.0% in 30 hours. NovelSeek includes agents for literature search, code analysis, idea generation, and experiment execution. The system is open-source, enabling reproducibility and collaboration across scientific fields. In conclusion, NovelSeek demonstrates how combining AI tools into a single system can accelerate scientific discovery and reduce its dependence on human effort. It ties together the key steps, generating ideas, turning them into methods, and testing them through experiments, into one streamlined process. What once took researchers months or years can now be done in days or even hours. By linking every stage of research into a continuous loop, NovelSeek helps teams move from rough ideas to real-world results more quickly. This system highlights the power of AI not just to assist, but to drive scientific research in a way that could reshape how discoveries are made across many fields. Check out the Paper and GitHub Page . All credit for this research goes to the researchers of this project. Also, feel free to follow us on Twitter and don’t forget to join our 95k+ ML SubReddit and Subscribe to our Newsletter. NikhilNikhil is an intern consultant at Marktechpost. He is pursuing an integrated dual degree in Materials at the Indian Institute of Technology, Kharagpur. Nikhil is an AI/ML enthusiast who is always researching applications in fields like biomaterials and biomedical science. With a strong background in Material Science, he is exploring new advancements and creating opportunities to contribute.Nikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces ARM and Ada-GRPO: Adaptive Reasoning Models for Efficient and Scalable Problem-SolvingNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces WEB-SHEPHERD: A Process Reward Model for Web Agents with 40K Dataset and 10× Cost EfficiencyNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces MMaDA: A Unified Multimodal Diffusion Model for Textual Reasoning, Visual Understanding, and Image GenerationNikhilhttps://www.marktechpost.com/author/nikhil0980/This AI Paper Introduces Differentiable MCMC Layers: A New AI Framework for Learning with Inexact Combinatorial Solvers in Neural Networks

What just happened? The Department of Energy has announced plans for a new supercomputer designed to significantly accelerate research across a wide range of scientific fields. The initiative highlights the growing convergence between commercial AI development and the computational demands of cutting-edge scientific discovery. The advanced system, to be housed at Lawrence Berkeley National Laboratory and scheduled to become operational in 2026, will be named "Doudna" in honor of Nobel laureate Jennifer Doudna, whose groundbreaking work on CRISPR gene editing has revolutionized molecular biology. Dell Technologies has been selected to deliver the Doudna supercomputer, marking a significant shift in the landscape of government-funded high-performance computing. While companies like Hewlett Packard Enterprise have traditionally dominated this space, Dell's successful bid signals a new chapter. "A big win for Dell," said Addison Snell, CEO of Intersect360 Research, in an interview with The New York Times, noting the company's historically limited presence in this domain. Dell executives explained that the Doudna project enabled them to move beyond the longstanding practice of building custom systems for individual laboratories. Instead, they focused on developing a flexible platform capable of serving a broad array of users. "This market had shifted into some form of autopilot. What we did was disengage the autopilot," said Paul Perez, senior vice president and technology fellow at Dell. The Perlmutter supercomputer at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. A defining feature of Doudna will be its use of Nvidia's Vera Rubin platform, engineered to combine the strengths of traditional scientific simulations with the power of modern AI. Unlike previous Department of Energy supercomputers, which relied on processors from Intel or AMD, Doudna will incorporate a general-purpose Arm-based CPU from Nvidia, paired with the company's Rubin AI chips designed specifically for artificial intelligence and simulation workloads. // Related Stories The architecture aims to meet the needs of the laboratory's 11,000 users, who increasingly depend on both high-precision modeling and rapid AI-driven data analysis. Jensen Huang, founder and CEO of Nvidia, described the new system with enthusiasm. "Doudna is a time machine for science – compressing years of discovery into days," he said, adding that it will let "scientists delve deeper and think bigger to seek the fundamental truths of the universe." In terms of performance, Doudna is expected to be over 10 times faster than the lab's current flagship system, making it the Department of Energy's most powerful resource for training AI models and conducting advanced simulations. Jonathan Carter, associate lab director for computing sciences at Berkeley Lab, said the system's architecture was shaped by the evolving needs of researchers – many of whom are now using AI to augment simulations in areas like geothermal energy and quantum computing. Doudna's design reflects a broader shift in supercomputing. Traditional systems have prioritized 64-bit calculations for maximum numerical accuracy, but modern AI workloads often benefit from lower-precision operations (such as 16-bit or 8-bit) that enable faster processing speeds. Dion Harris, Nvidia's head of data center product marketing, noted that the flexibility to combine different levels of precision opens new frontiers for scientific research. The supercomputer will also be tightly integrated with the Energy Sciences Network, allowing researchers nationwide to stream data directly into Doudna for real-time analysis. Sudip Dosanjh, director of the National Energy Research Scientific Computing Center, described the new system as "designed to accelerate a broad set of scientific workflows."

Molecular Rebar Design, a nanomaterials company based in Austin, Texas, has patented a new additive manufacturing (AM) composition that utilizes oxidized discrete carbon nanotubes (CNTs) with bonded dispersing agents to enhance 3D printing resins. The patent, published under US20210237509A1, outlines methods to improve resin properties for applications such as vat photopolymerization, sintering, and thermoplastic fusion. The inventors, Clive P. Bosnyak, Kurt W. Swogger, Steven Lowder, and Olga Ivanova, propose formulations that improve electrical conductivity, thermal stability, and mechanical strength, while overcoming dispersion challenges common with CNTs in composite materials. Image shows a schematic diagram of functionalized carbon nanotubes. Image via Molecular Rebar Design. Functionalized CNTs for additive manufacturing At the core of the invention is the chemical functionalization of CNTs with dispersing agents bonded to their sidewalls, enabling higher aspect ratios and more homogeneous dispersions. These dispersions integrate into UV-curable acrylates, thermoplastics, and elastomers, yielding improved green strength, sinterability, and faster cure rates. The patent emphasizes the benefit of using bimodal or trimodal distributions of CNT diameters (single-, double-, or multi-wall) to tune material performance. Additional fillers such as carbon black, silica, and metallic powders can also be incorporated for applications ranging from electronic encapsulation to impact-resistant parts. Experimental validation To validate the invention, the applicants oxidized carbon nanotubes using nitric acid and covalently bonded them with polyether dispersing agents such as Jeffamine M2005. These modified CNTs were incorporated into photopolymer resin formulations. In tensile testing, specimens produced with the dispersions demonstrated enhanced mechanical performance, with yield strengths exceeding 50 MPa and Young’s modulus values above 2.8 GPa. Impact strength improved by up to 90% in certain formulations compared to control samples without CNTs. These performance gains suggest suitability for applications demanding high strength-to-weight ratios, such as aerospace, electronics, and structural components. Nanotube innovations in AM Carbon nanotubes (CNTs) have long been explored for additive manufacturing (AM) due to their exceptional mechanical and electrical properties. However, challenges such as poor dispersion and inconsistent aspect ratios have hindered their widespread adoption in AM processes. Recent advancements aim to overcome these barriers by integrating oxidation and dispersion techniques into scalable production methods. For instance, researchers at Rice University have developed a novel acid-based solvent that prevents the common “spaghetti effect” of CNTs tangling together. This innovation simplifies the processing of CNTs, potentially enabling their scale-up for industrial 3D printing applications. Similarly, a research team led by the University of Glasgow has created a 3D printable CNT-based plastic material capable of sensing its own structural health. This material, inspired by natural porous structures, offers enhanced toughness and strength, with potential applications in medicine, prosthetics, automotive, and aerospace design. Subscribe to the 3D Printing Industry newsletter to keep up with the latest 3D printing news. You can also follow us onLinkedIn and subscribe to the 3D Printing Industry YouTube channel to access more exclusive content. At 3DPI, our mission is to deliver high-quality journalism, technical insight, and industry intelligence to professionals across the AM ecosystem.Help us shape the future of 3D printing industry news with our2025 reader survey. Feature image shows schematic diagram of functionalized carbon nanotubes. Image via Molecular Rebar Design.

For Gen Z, homeownership or even just living alone brings a new set of responsibilities, and, often, a lot of confusion. How do you manage a home without letting it manage you? How do you keep it clean without feeling like you’re constantly at war with dust bunnies and mildew? SCOP helps you with that! A sleek, intelligent, and modular cleaning system designed specifically for the needs, habits, and lifestyles of today’s youth. SCOP is more than a robot vacuum; it’s a quiet, ambient home assistant that handles the unseen, unnoticed tasks you didn’t even know were weighing you down. Gone are the days when cleaning simply meant sweeping and mopping. Gen Z knows better. Home maintenance today is about convenience, wellness, and vibes. But even with the occasional chore, it’s easy to overlook what’s not right in front of you, like the dampness creeping into corners, the musty smell that slowly blends into the air, or the dust silently collecting behind the couch. These are the invisible chores, and SCOP is here to make them visible and manageable. SCOP consists of three core components: SCOP-Hub: A robotic vacuum that doesn’t just clean floors, it acts as the brain of the operation, moving around your space, collecting data, and sensing invisible environmental changes. Think of it as your home’s subtle yet all-seeing eye. SCOP-Humi: A moisture-fighting module using silica gel to prevent mold in areas prone to dampness. It’s perfect for dealing with rainy days, laundry forgetfulness, or muggy bathrooms. SCOP-Odor: This plasma ionizer tackles unpleasant smells at the molecular level. Whether it’s lingering food smells, pet odors, or that “I’ve lived here too long” funk, Odor handles it. Together, they work in harmony, scanning, detecting, acting, and predicting. Once SCOP identifies an issue, it recommends or even automatically deploys the appropriate module. Your only job? Toss, hang, or place Humi and Odor where the SCOP-Hub suggests. SCOP’s design language is minimalist, modern, and quietly confident. The entire set blends seamlessly into your living space, feeling more like curated home decor than cleaning equipment. It’s not another plastic gadget cluttering your floor; it’s an integrated part of your interior. One of SCOP’s most innovative features is its intelligence in when and what to clean. It learns your patterns, when you leave the house, where you tend to leave wet clothes, what corners gather dust, and builds a smart routine. It logs this in the SCOP Log, a sort of memory bank that helps it predict and suggest tasks before problems even occur. Say you’ve got pets, SCOP automatically triggers dust control. If you’re out on a rainy day and leave damp laundry behind, it deploys the Humi module without waiting for you to notice the smell of mildew. That’s the power of predictive, invisible task management. SCOP recognizes that your schedule is packed. It doesn’t ask for your time, it just does what needs to be done and lets you know afterward. No deep dives into cleaning routines, no complicated settings. You don’t have to be a home expert. SCOP already is. It’s a solution made for small homes with big personalities. For shared apartments where no one wants to take out the trash. For city-dwellers who crave order but don’t want to obsess over it. In a world where tech is everywhere, SCOP stands out by being exactly where you need it, without demanding your attention. It shifts the mindset from doing chores to living in a place that just takes care of itself. By mapping your home’s unique personality and addressing even its most hidden needs, SCOP allows you to finally exhale and focus on what truly matters: living.The post The Smart Cleaning System Revolutionizing Home Care for Gen Z Renters and Owners first appeared on Yanko Design.

News Anthropology Males of this ancient human cousin weren’t always bigger than females Proteins from a collection of fossils hint at sex and genetic differences in P. robustus A new analysis of proteins preserved in fossil teeth provides the first molecular assessment of size differences between the sexes and genetic diversity in an ancient African hominid, Paranthropus robustus (skull of own shown). Bernhard Zipfel By Bruce Bower 20 hours ago An ancient, distant human cousin from southern Africa called Paranthropus robustus has for the first time revealed molecular clues to its evolutionary status. Protein sequences preserved in four partial P. robustus teeth from different individuals that lived roughly 2 million years ago indicate that larger and smaller fossils of this hominid species cannot always be classed as male or female, as previously thought, researchers report in the May 29 Science. Sequences of a protein derived from a gene located only on the Y, or male, sex chromosome in present-day humans enabled the scientists to identify two teeth as having belonged to males, molecular biologist Palesa Madupe of the University of Copenhagen and colleagues say. One of those teeth was previously thought to have come from a female, based on its small size. Closer analyses of the two teeth lacking that male-specific protein indicated that those fossils, which are around the same size as the smaller male tooth, came from females. Sign up for our newsletter We summarize the week's scientific breakthroughs every Thursday.

Ready for a front-row seat to the next scientific revolution? That’s the idea behind Doudna — a groundbreaking supercomputer announced today at Lawrence Berkeley National Laboratory in Berkeley, California. The system represents a major national investment in advancing U.S. high-performance computing (HPC) leadership, ensuring U.S. researchers have access to cutting-edge tools to address global challenges. “It will advance scientific discovery from chemistry to physics to biology and all powered by — unleashing this power — of artificial intelligence,” U.S. Energy Secretary Chris Wright (pictured above) said at today’s event. Also known as NERSC-10, Doudna is named for Nobel laureate and CRISPR pioneer Jennifer Doudna. The next-generation system announced today is designed not just for speed but for impact. Nobel laureate and CRISPR pioneer Jennifer Doudna speaking at today’s event in Berkeley, California. To her right, NVIDIA founder and CEO Jensen Huang and Paul Perez, senior vice president and senior technology fellow at Dell Technologies. Powered by Dell Technologies infrastructure with the NVIDIA Vera Rubin architecture, and set to launch in 2026, Doudna is tailored for real-time discovery across the U.S. Department of Energy’s most urgent scientific missions. It’s poised to catapult American researchers to the forefront of critical scientific breakthroughs, fostering innovation and securing the nation’s competitive edge in key technological fields. “I’m so proud that America continues to invest in this particular area,” said NVIDIA founder and CEO Jensen Huang. “It is the foundation of scientific discovery for our country. It is also the foundation for economic and technology leadership.” “It’s an incredible honor to be here,” Doudna said, adding she was “surprised and delighted” that a supercomputer would be named after her. “I think we’re standing at a really interesting moment in biology,” she added, with people with different skills coming together to address global issues. Designed to Accelerate Breakthroughs Unlike traditional systems that operate in silos, Doudna merges simulation, data and AI into a single seamless platform. “The Doudna supercomputer is designed to accelerate a broad set of scientific workflows,” said NERSC Director Sudip Dosanjh. “Doudna will be connected to DOE experimental and observational facilities through the Energy Sciences Network (ESnet), allowing scientists to stream data seamlessly into the system from all parts of the country and to analyze it in near real time.” It’s engineered to empower over 11,000 researchers with almost instantaneous responsiveness and integrated workflows, helping scientists explore bigger questions and reach answers faster than ever. “We’re not just building a faster computer,” said Nick Wright, advanced technologies group lead and Doudna chief architect at NERSC. “We’re building a system that helps researchers think bigger and discover sooner.” Here’s what Wright expects Doudna to advance: Fusion energy: Breakthroughs in simulation that unlocks clean fusion energy. Materials science: AI models that design new classes of superconducting materials. Drug discovery acceleration: Ultrarapid workflow that helps biologists fold proteins fast enough to outpace a pandemic. Astronomy: Real-time processing of data from the Dark Energy Spectroscopic Instrument at Kitt Peak to help scientists map the universe. Doudna is expected to outperform its predecessor, Perlmutter, by more than 10x in scientific output, all while using just 2-3x the power. This translates to a 3-5x increase in performance per watt, a result of innovations in chip design, dynamic load balancing and system-level efficiencies. AI-Powered Discovery at Scale Doudna will power AI-driven breakthroughs across high-impact scientific fields nationwide. Highlights include: AI for protein design: David Baker, a 2024 Nobel laureate, used NERSC systems to support his work using AI to predict novel protein structures, addressing challenges across scientific disciplines. AI for fundamental physics: Researchers like Benjamin Nachman are using AI to “unfold” detector distortions in particle physics data and analyze proton data from electron-proton colliders. AI for materials science: A collaboration including Berkeley Lab and Meta created “Open Molecules 2025,” a massive dataset for using AI to accurately model complex molecular chemical reactions. Researchers involved also use NERSC for their AI models. Real-Time Science, Real-World Impact Doudna isn’t a standalone system. It’s an integral part of scientific workflows. DOE’s ESnet will stream data from telescopes, detectors and genome sequencers directly into the machine with low-latency, high-throughput NVIDIA Quantum-X800 InfiniBand networking. This critical data flow is prioritized by intelligent quality-of-service mechanisms, ensuring it stays fast and uninterrupted, from input to insight. This will make the system incredibly responsive. At the DIII-D national fusion ignition facility, for example, data will stream control-room events directly into Doudna for rapid-response plasma modeling, so scientists can make adjustments in real time. “We used to think of the supercomputer as a passive participant in the corner,” Wright said. “Now it’s part of the entire workflow, connected to experiments, telescopes, detectors.” The Platform for What’s Next: Unlocking Quantum and HPC Workflows Doudna supports traditional HPC, cutting-edge AI, real-time streaming and even quantum workflows. The Mayall 4-Meter Telescope, which will be home to the Dark Energy Spectroscopic Instrument, seen at night at Kitt Peak National Observatory. This includes support for scalable quantum algorithm development and the codesign of future integrated quantum-HPC systems, using platforms like NVIDIA CUDA-Q. All of these workflows will run on the next-generation NVIDIA Vera Rubin platform, which will blend high-performance CPUs with coherent GPUs, meaning all processors can access and share data directly to support the most demanding scientific workloads. Researchers are already porting full pipelines using frameworks like PyTorch, the NVIDIA Holoscan software development kit, TensorFlow, NVIDIA cuDNN and NVIDIA CUDA-Q, all optimized for the system’s Rubin GPUs and NVIDIA NVLink architecture. Over 20 research teams are already porting full workflows to Doudna through the NERSC Science Acceleration Program, tackling everything from climate models to particle physics. This isn’t just about raw compute, it’s about discovery, integrated from idea to insight. Designed for Urgency Last year, AI-assisted science earned two Nobel Prizes. From climate research to pandemic response, the next breakthroughs won’t wait for better infrastructure. With deployment slated for 2026, Doudna is positioned to lead a new era of accelerated science. DOE facilities across the country, from Fermilab to the Joint Genome Institute, will rely on its capabilities to turn today’s questions into tomorrow’s breakthroughs. “This isn’t a system for one field,” Wright said. “It’s for discovery — across chemistry, physics and fields we haven’t imagined yet.” As Huang put it, Doudna is “a time machine for science.” It compresses years of discovery into days and gives the world’s toughest problems the power they’ve been waiting for. This post has been updated with comments from Thursday’s event at Lawrence Berkeley National Laboratory. 

In this post, we describe FrodoKEM, a key encapsulation protocol that offers a simple design and provides strong security guarantees even in a future with powerful quantum computers. The quantum threat to cryptography For decades, modern cryptography has relied on mathematical problems that are practically impossible for classical computers to solve without a secret key. Cryptosystems like RSA, Diffie-Hellman key-exchange, and elliptic curve-based schemes—which rely on the hardness of the integer factorization and (elliptic curve) discrete logarithm problems—secure communications on the internet, banking transactions, and even national security systems. However, the emergence of Quantum computers leverage the principles of quantum mechanics to perform certain calculations exponentially faster than classical computers. Their ability to solve complex problems, such as simulating molecular interactions, optimizing large-scale systems, and accelerating machine learning, is expected to have profound and beneficial implications for fields ranging from chemistry and material science to artificial intelligence. Spotlight: AI-POWERED EXPERIENCE Microsoft research copilot experience Discover more about research at Microsoft through our AI-powered experience Start now Opens in a new tab At the same time, quantum computing is poised to disrupt cryptography. In particular, Shor’s algorithm, a quantum algorithm developed in 1994, can efficiently factor large numbers and compute discrete logarithms—the very problems that underpin the security of RSA, Diffie-Hellman, and elliptic curve cryptography. This means that once large-scale, fault-tolerant quantum computers become available, public-key protocols based on RSA, ECC, and Diffie-Hellman will become insecure, breaking a sizable portion of the cryptographic backbone of today’s digital world. Recent advances in quantum computing, such as Microsoft’s Majorana 1 (opens in new tab), the first quantum processor powered by topological qubits, represent major steps toward practical quantum computing and underscore the urgency of transitioning to quantum-resistant cryptographic systems. To address this looming security crisis, cryptographers and government agencies have been working on post-quantum cryptography (PQC)—new cryptographic algorithms that can resist attacks from both classical and quantum computers. The NIST Post-Quantum Cryptography Standardization effort In 2017, the U.S. National Institute of Standards and Technology (NIST) launched the Post-Quantum Cryptography Standardization project (opens in new tab) to evaluate and select cryptographic algorithms capable of withstanding quantum attacks. As part of this initiative, NIST sought proposals for two types of cryptographic primitives: key encapsulation mechanisms (KEMs)—which enable two parties to securely derive a shared key to establish an encrypted connection, similar to traditional key exchange schemes—and digital signature schemes. This initiative attracted submissions from cryptographers worldwide, and after multiple evaluation rounds, NIST selected CRYSTALS-Kyber, a KEM based on structured lattices, and standardized it as ML-KEM (opens in new tab). Additionally, NIST selected three digital signature schemes: CRYSTALS-Dilithium, now called ML-DSA; SPHINCS+, now called SLH-DSA; and Falcon, now called FN-DSA. While ML-KEM provides great overall security and efficiency, some governments and cryptographic researchers advocate for the inclusion and standardization of alternative algorithms that minimize reliance on algebraic structure. Reducing algebraic structure might prevent potential vulnerabilities and, hence, can be considered a more conservative design choice. One such algorithm is FrodoKEM. International standardization of post-quantum cryptography Beyond NIST, other international standardization bodies have been actively working on quantum-resistant cryptographic solutions. The International Organization for Standardization (ISO) is leading a global effort to standardize additional PQC algorithms. Notably, European government agencies—including Germany’s BSI (opens in new tab), the Netherlands’ NLNCSA and AIVD (opens in new tab), and France’s ANSSI (opens in new tab)—have shown strong support for FrodoKEM, recognizing it as a conservative alternative to structured lattice-based schemes. As a result, FrodoKEM is undergoing standardization at ISO. Additionally, ISO is standardizing ML-KEM and a conservative code-based KEM called Classic McEliece. These three algorithms are planned for inclusion in ISO/IEC 18033-2:2006 as Amendment 2 (opens in new tab). What is FrodoKEM? FrodoKEM is a key encapsulation mechanism (KEM) based on the Learning with Errors (LWE) problem, a cornerstone of lattice-based cryptography. Unlike structured lattice-based schemes such as ML-KEM, FrodoKEM is built on generic, unstructured lattices, i.e., it is based on the plain LWE problem. Why unstructured lattices? Structured lattice-based schemes introduce additional algebraic properties that could potentially be exploited in future cryptanalytic attacks. By using unstructured lattices, FrodoKEM eliminates these concerns, making it a safer choice in the long run, albeit at the cost of larger key sizes and lower efficiency. It is important to emphasize that no particular cryptanalytic weaknesses are currently known for recommended parameterizations of structured lattice schemes in comparison to plain LWE. However, our current understanding of the security of these schemes could potentially change in the future with cryptanalytic advances. Lattices and the Learning with Errors (LWE) problem Lattice-based cryptography relies on the mathematical structure of lattices, which are regular arrangements of points in multidimensional space. A lattice is defined as the set of all integer linear combinations of a set of basis vectors. The difficulty of certain computational problems on lattices, such as the Shortest Vector Problem (SVP) and the Learning with Errors (LWE) problem, forms the basis of lattice-based schemes. The Learning with Errors (LWE) problem The LWE problem is a fundamental hard problem in lattice-based cryptography. It involves solving a system of linear equations where some small random error has been added to each equation, making it extremely difficult to recover the original secret values. This added error ensures that the problem remains computationally infeasible, even for quantum computers. Figure 1 below illustrates the LWE problem, specifically, the search version of the problem. As can be seen in Figure 1, for the setup of the problem we need a dimension \(n\) that defines the size of matrices, a modulus \(q\) that defines the value range of the matrix coefficients, and a certain error distribution \(\chi\) from which we sample \(\textit{“small”}\) matrices. We sample two matrices from \(\chi\), a small matrix \(\text{s}\) and an error matrix \(\text{e}\) (for simplicity in the explanation, we assume that both have only one column); sample an \(n \times n\) matrix \(\text{A}\) uniformly at random; and compute \(\text{b} = \text{A} \times \text{s} + \text{e}\). In the illustration, each matrix coefficient is represented by a colored square, and the “legend of coefficients” gives an idea of the size of the respective coefficients, e.g., orange squares represent the small coefficients of matrix \(\text{s}\) (small relative to the modulus \(q\)). Finally, given \(\text{A}\) and \(\text{b}\), the search LWE problem consists in finding \(\text{s}\). This problem is believed to be hard for suitably chosen parameters (e.g., for dimension \(n\) sufficiently large) and is used at the core of FrodoKEM. In comparison, the LWE variant used in ML-KEM—called Module-LWE (M-LWE)—has additional symmetries, adding mathematical structure that helps improve efficiency. In a setting similar to that of the search LWE problem above, the matrix \(\text{A}\) can be represented by just a single row of coefficients. FIGURE 1: Visualization of the (search) LWE problem. LWE is conjectured to be quantum-resistant, and FrodoKEM’s security is directly tied to its hardness. In other words, cryptanalysts and quantum researchers have not been able to devise an efficient quantum algorithm capable of solving the LWE problem and, hence, FrodoKEM. In cryptography, absolute security can never be guaranteed; instead, confidence in a problem’s hardness comes from extensive scrutiny and its resilience against attacks over time. How FrodoKEM Works FrodoKEM follows the standard paradigm of a KEM, which consists of three main operations—key generation, encapsulation, and decapsulation—performed interactively between a sender and a recipient with the goal of establishing a shared secret key: Key generation (KeyGen), computed by the recipient Generates a public key and a secret key. The public key is sent to the sender, while the private key remains secret. Encapsulation (Encapsulate), computed by the sender Generates a random session key. Encrypts the session key using the recipient’s public key to produce a ciphertext. Produces a shared key using the session key and the ciphertext. The ciphertext is sent to the recipient. Decapsulation (Decapsulate), computed by the recipient Decrypts the ciphertext using their secret key to recover the original session key. Reproduces the shared key using the decrypted session key and the ciphertext. The shared key generated by the sender and reconstructed by the recipient can then be used to establish secure symmetric-key encryption for further communication between the two parties. Figure 2 below shows a simplified view of the FrodoKEM protocol. As highlighted in red, FrodoKEM uses at its core LWE operations of the form “\(\text{b} = \text{A} \times \text{s} + \text{e}\)”, which are directly applied within the KEM paradigm. FIGURE 2: Simplified overview of FrodoKEM. Performance: Strong security has a cost Not relying on additional algebraic structure certainly comes at a cost for FrodoKEM in the form of increased protocol runtime and bandwidth. The table below compares the performance and key sizes corresponding to the FrodoKEM level 1 parameter set (variant called “FrodoKEM-640-AES”) and the respective parameter set of ML-KEM (variant called “ML-KEM-512”). These parameter sets are intended to match or exceed the brute force security of AES-128. As can be seen, the difference in speed and key sizes between FrodoKEM and ML-KEM is more than an order of magnitude. Nevertheless, the runtime of the FrodoKEM protocol remains reasonable for most applications. For example, on our benchmarking platform clocked at 3.2GHz, the measured runtimes are 0.97 ms, 1.9 ms, and 3.2 ms for security levels 1, 2, and 3, respectively. For security-sensitive applications, a more relevant comparison is with Classic McEliece, a post-quantum code-based scheme also considered for standardization. In this case, FrodoKEM offers several efficiency advantages. Classic McEliece’s public keys are significantly larger—well over an order of magnitude greater than FrodoKEM’s—and its key generation is substantially more computationally expensive. Nonetheless, Classic McEliece provides an advantage in certain static key-exchange scenarios, where its high key generation cost can be amortized across multiple key encapsulation executions. TABLE 1: Comparison of key sizes and performance on an x86-64 processor for NIST level 1 parameter sets. A holistic design made with security in mind FrodoKEM’s design principles support security beyond its reliance on generic, unstructured lattices to minimize the attack surface of potential future cryptanalytic threats. Its parameters have been carefully chosen with additional security margins to withstand advancements in known attacks. Furthermore, FrodoKEM is designed with simplicity in mind—its internal operations are based on straightforward matrix-vector arithmetic using integer coefficients reduced modulo a power of two. These design decisions facilitate simple, compact and secure implementations that are also easier to maintain and to protect against side-channel attacks. Conclusion After years of research and analysis, the next generation of post-quantum cryptographic algorithms has arrived. NIST has chosen strong PQC protocols that we believe will serve Microsoft and its customers well in many applications. For security-sensitive applications, FrodoKEM offers a secure yet practical approach for post-quantum cryptography. While its reliance on unstructured lattices results in larger key sizes and higher computational overhead compared to structured lattice-based alternatives, it provides strong security assurances against potential future attacks. Given the ongoing standardization efforts and its endorsement by multiple governmental agencies, FrodoKEM is well-positioned as a viable alternative for organizations seeking long-term cryptographic resilience in a post-quantum world. Further Reading For those interested in learning more about FrodoKEM, post-quantum cryptography, and lattice-based cryptography, the following resources provide valuable insights: The official FrodoKEM website: https://frodokem.org/ (opens in new tab), which contains, among several other resources, FrodoKEM’s specification document. The official FrodoKEM software library: https://github.com/Microsoft/PQCrypto-LWEKE (opens in new tab), which contains reference and optimized implementations of FrodoKEM written in C and Python. NIST’s Post-Quantum Cryptography Project: https://csrc.nist.gov/projects/post-quantum-cryptography (opens in new tab). Microsoft’s blogpost on its transition plan for PQC: https://techcommunity.microsoft.com/blog/microsoft-security-blog/microsofts-quantum-resistant-cryptography-is-here/4238780 (opens in new tab). A comprehensive survey on lattice-based cryptography: Peikert, C. “A Decade of Lattice Cryptography.” Foundations and Trends in Theoretical Computer Science. (2016) A comprehensive tutorial on modern lattice-based schemes, including ML-KEM and ML-DSA: Lyubashevsky, V. “Basic Lattice Cryptography: The concepts behind Kyber (ML-KEM) and Dilithium (ML-DSA).” https://eprint.iacr.org/2024/1287 (opens in new tab). (2024) Opens in a new tab

The anti-aging supplement industry is valued at many billions of dollars, with North America offering the largest market worldwide. Through clever marketing, many such supplements have promised consumers everything from halting to reversing the aging process — often without clear scientific evidence to back it up.However, recent findings from a long-term randomized controlled study have put a widely used and potent supplement into the anti-aging spotlight: Vitamin D.A sub-study from the Vitamin D and Omega-3 Trial (or VITAL Trial), published in The American Journal of Clinical Nutrition and led by researchers at Mass General Brigham and the Medical College of Georgia, has revealed that long-term Vitamin D supplementation may actually slow aging on a cellular level. This adds even more promise to Vitamin D’s already impressive list of health benefits.There's More to Vitamin D Roughly a quarter of Americans take Vitamin D supplements daily — and for good reason. While this fat-soluble vitamin is best known for maintaining bone health by helping regulate calcium and phosphorus, its role in the body extends far beyond that. Vitamin D also supports immune function, regulates inflammation, and influences cell growth to name a few.That said, getting enough Vitamin D naturally can be challenging. It’s found mainly in fatty animal products like fish, red meat, and eggs. Our skin can also synthesize it through sun exposure — which isn’t always a reliable source due to lifestyle, geography, or sunscreen use. This is why many people end up deficient.With the latest findings from the VITAL Trial, the benefits of adequate Vitamin D supplementation may now include not just stronger bones and better immunity but also support for healthy aging.Read More: What's the Difference Between Vitamin D2 and D3?Vitamin D Prevented Aging on Cellular Level“VITAL is the first large-scale and long-term randomized trial to show that vitamin D supplements protect telomeres and preserve telomere length,” said JoAnn Manson, principal investigator of VITAL and chief of the Division of Preventive Medicine at Brigham and Women’s Hospital in a press statement.Telomeres — repetitive DNA sequences at the ends of chromosomes — protect genetic material during cell division. As we age, telomeres naturally shorten, a process linked to increased risk of age-related diseases and general cellular aging.While earlier small-scale studies offered mixed results, the VITAL Telomere sub-study stands out due to its size and rigor. It followed 1,054 participants aged 50 and older over four years, comparing those who took 2,000 IU of Vitamin D3 daily (a high dosage usually recommended for those with deficiency) with those who took a placebo. Telomere length was measured at the start, at two years, and at four years.The results? Vitamin D3 supplementation significantly slowed telomere shortening — effectively preserving the equivalent of close to three years of cellular aging compared to the placebo group.Why Aging Research Matters“Our findings suggest that targeted vitamin D supplementation may be a promising strategy to counter a biological aging process, although further research is warranted,” said study’s first author Haidong Zhu, a molecular geneticist at the Medical College of Georgia in the news release.Aging research often gets lumped in with science fiction-like efforts to stop aging or live forever, but its real goal is far more grounded: to improve health across the lifespan. Instead of chasing immortality, scientists aim to extend the health span — the number of years people live free of chronic disease and disability.By uncovering interventions like Vitamin D that can support healthier aging, researchers hope to help more people enjoy a higher quality of life well into their later years, without resorting to expensive or unproven treatments.This article is not offering medical advice and should be used for informational purposes only.Article SourcesOur writers at Discovermagazine.com use peer-reviewed studies and high-quality sources for our articles, and our editors review for scientific accuracy and editorial standards. Review the sources used below for this article:Cleveland Clinic: Vitamin D DeficiencyNational Institutes of Health, Office of Dietary Supplements: Vitamin D Fact Sheet for Health ProfessionalsHaving worked as a biomedical research assistant in labs across three countries, Jenny excels at translating complex scientific concepts – ranging from medical breakthroughs and pharmacological discoveries to the latest in nutrition – into engaging, accessible content. Her interests extend to topics such as human evolution, psychology, and quirky animal stories. When she’s not immersed in a popular science book, you’ll find her catching waves or cruising around Vancouver Island on her longboard.

Letters to the Editor Readers discuss the biology of sex, plastic in the brain and more By Science News Staff 2 hours ago It’s a matter of size A January executive order by President Donald Trump designates people as female if they make the “large” reproductive cell (the egg) and male if they make the “small” one (the sperm). But the human sexes don’t fit neatly into a male–female binary due to factors such as genetics and hormones, senior molecular biology writer Tina Hesman Saey reported in “The real biology of sex.” Reader Root Gorelick, a biologist at Carleton University in Ottawa, appreciated the feature and wrote in to add some nuanced points. Sign up for our newsletter We summarize the week's scientific breakthroughs every Thursday.