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The MICROBS Lab’s microfliers. 2026 EPFL/MICROBS – CC-BY-SA 4.0. By Celia Luterbacher When you blow air across the neck of a bottle, you’re not just producing a pleasant tone: you’re also demonstrating a phenomenon called Helmholtz resonance. This occurs when airflow passing across an opening causes air trapped inside a cavity (like a glass bottle) […]
Researchers have used AI to uncover the DNA signature of a key genetic “switch” involved in turning genes on. After analyzing about 500,000 DNA sequences, the model identified the initiator in roughly 60% of human genes. The breakthrough could help predict the effects of harmful mutations and eventually contribute to decoding the broader genetic instructions that control gene activity throughout the body.
Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.Humanoids Summit Seoul: 22–23 September 2026, SEOULIROS 2026: 27 September–1 October 2026, PITTSBURGHCoRL 2026: 9–12 November 2026, AUSTINEnjoy today’s videos! This is very, very cool. But I’m trying to think of what the commercial use case will be, you know? I guess, high speed, incredibly dangerous package delivery to second-floor windows or something...?[ Unitree ]Humans have a remarkable ability to perform new physical skills from only one or a few examples. Our latest robot foundation model, GEN-1.5, exhibits the beginnings of that same ability: It can learn a new task in seconds, from a single example, without gradient updates or fine-tuning. It displays broad capabilities across one-shot and few-shots learning from demonstration, as well as zero-shot physical generalization. Although the tasks are simple and short-horizon, this is the first model we know for which one-shot and few-shots learning of physical skills have emerged at scale. We view these results as a significant step toward our mission of building general intelligence for the physical world.I will make the cautionary point that for many of these “the model figured it out” tasks, the blog post can only say that there was no relevant pretraining data “to the best of our knowledge.”[ Generalist ]BeanBot is a robot inspired by Mexican jumping beans, and I need say no more.[ IIT ]As a professional bagpiper who definitely pays very close attention to whatever that annoying tapping noise is coming from the back of the band, I can attest to this group of robot drummers being absolutely top-notch.[ AgileX Robotics ]What does it take for an aerial robot to move through a sequence of arbitrary poses—fast, precisely, and continuously? Rather than teaching the robot a behavior from data, we asked how far a first-principles analytical model could take us. Through a collaboration between the AIMS Group at the Hong Kong Polytechnic University and DRAGON Lab at the University of Tokyo, we developed the first sequential-convex-programming-based trajectory-optimization framework for generalized multirotors, covering both conventional and omnidirectional platforms.[ DRAGON Lab ]Thanks, Moju!This is a nifty idea that adapts a kind of interface frequently used for robot training and uses it for human training instead.[ MIT ]Gravis Robotics brings robotic intelligence to heavy construction machines. Our retrofit kit, the Gravis Rack, turns off-the-shelf hydraulic machines into robots. Cameras, lidar, and onboard compute lets your machine see and understand its surroundings, and learning-based control lets it work close to its limits, moving more dirt with full, fast cycles.[ Gravis Robotics ]Robust brachiation requires precise hand movements to grasp and release bars together with highly coordinated whole-body motion. To address this challenge, we propose a learning-based framework centered on waypoint-guided reinforcement learning (WGRL). WGRL guides the end effector through waypoints while allowing RL to explore and generate dynamic whole-body behaviors. With this approach, the learned policy demonstrated robust brachiation across diverse courses with different bar heights, spacings, and orientations in sim-to-sim experiments. In the real world, our life-size dual-arm robot successfully traversed four consecutive bars.[ EVARL ]Thanks, Ayumu!Well, here’s a different approach to welding in shipyards with robots.[ Kawasaki ]We should have a lot more robots in agriculture, if only they’d lettuce.[ Flexiv ]We’ve all had refs like these.[ PHYBOT ]I got stuck after the first 15 seconds of this video trying to imagine what any of these home humanoids would usefully do if they dropped a glass.[ Zhejiang Humanoid ]Shakey the Robot doesn’t get enough love.[ SRI ]This work introduces a novel approach to physical human-robot interaction (pHRI) by leveraging the joint torque sensors of standard collaborative robots. By mounting a passive, uninstrumented plexiglass touchpad to the robot’s flange, we transform the robot into a handwriting-based input interface.[ TS-Robotics ]
Alphabet-owned company is seeking to persuade US regulators to clear a path for fully autonomous taxi services.
Florent Delgrange won the Best Blue Sky Paper Award at AAMAS 2026 for his work Foundation World Models for Agents that Learn, Verify, and Adapt Reliably Beyond Static Environments. We caught up with him to find out more about his vision for agent learning. What is the topic of your Blue Sky Ideas paper and […]
Cryptographic Context Injection is only the latest way to break an LLM safety guardrail.
Rob Strechay, until recently managing director and principal analyst at theCUBE Research, has joined VentureBeat as our first Lead Analyst and a founding analyst of VentureBeat Research. His arrival is the next step in a deliberate move at VentureBeat toward deeper specialization: analysis built for the technical decision-makers — the directors, VPs, CIOs, and CTOs — who are evaluating, buying, and deploying enterprise AI.The enterprise AI stack is being rewritten in real time, and the decision-makers I talk with are starved for objective, defendable data. Rob Strechay has the mix of technical rigor and operating experience needed to dissect the architecture behind the next phase of enterprise AI deployment.The questions enterprise technology leaders are asking have changed. As organizations move past experimentation with generative AI toward production deployment, they want to know how to orchestrate multi-vendor environments, where the security gaps in their agentic pipelines sit, and how to fix the utilization problems draining their infrastructure budgets. Answering those questions requires more depth than news coverage alone provides, and that is the gap this research offering is built to fill.An analyst who has sat on every side of the tableStrechay brings nearly three decades of experience as a practitioner, product executive, and industry analyst. Before becoming an analyst, he was an executive at numerous startups, including Zerto; he joined Amazon Web Services to help build a new analytics service; and he held executive roles across enterprise infrastructure. He later served as a senior analyst at Enterprise Strategy Group and most recently as managing director and principal analyst at theCUBE Research and SiliconANGLE, where he hosted executive interviews and analyzed the evolution of cloud, data, and AI infrastructure.Strechay will initially focus his coverage on cloud infrastructure, advanced data infrastructure, platform engineering and DevOps orchestration and observability, and the intersection points where AI and enterprise security collide.Already at work: GPU utilization and the VB Pulse surveysStrechay has already been contributing to VentureBeat's research. In May he published an analysis of enterprise GPU utilization, examining the compute waste sitting inside enterprise AI infrastructure, and he provided a substantive review of our AI Infrastructure & Compute survey before it went into the field.His infrastructure-level focus complements the research engine VentureBeat has built around its monthly VB Pulse surveys, which track five areas of enterprise AI adoption: agentic orchestration, agent reliability and evals, agentic security and identity, AI infrastructure and compute, and context layers, including retrieval-augmented generation (RAG). Our June report on agentic orchestration, drawn from a survey of 145 enterprises, found that two-thirds of those enterprises had hedged their AI model strategy rather than committing to a single provider — a posture whose value the June outage of Anthropic's Claude models made plain.VB In Conversation: The first vehicleA core vehicle for this expanded research footprint will be a deepening of VentureBeat's existing VB In Conversation video interview series, which Strechay will host. Rather than high-level industry overviews, the series will bring architectural blueprints, actual deployment barriers, and back-end infrastructure realities to light through in-depth technical interviews with the architects and product leaders behind leading enterprise AI systems — an unvarnished look at which tools perform under production-grade pressure."VentureBeat has built an audience of enterprise builders and technology buyers that any analyst would want to serve," Strechay said. "My goal is to use deep empirical metrics and VentureBeat's proprietary tracking data to help enterprise buyers and the people building for them make sound platform and infrastructure decisions during the most disruptive transition enterprise technology has seen."The expanded VB In Conversation series will appear on VentureBeat and on VentureBeat's YouTube channel, alongside Rob's written analysis on the site. Enterprise practitioners who want to take part in our monthly VB Pulse surveys, or arrange an analyst briefing with Rob, can reach the research team here.
Robots have been a prolific theme in Japanese pop culture and media since the 1950s, which includes global icons like the Transformers, Astro Boy, and Doraemon (1). Perhaps not coincidentally, Japanese citizens have a positive outlook on robotic technologies and their use in the labor sector compared to many other nations (2); much to their […]
Researchers have built microscopic, light-driven robots that can rapidly navigate through liquid, collect bacteria, and deposit them in chosen locations. These tiny “cleaners” could open new possibilities for manipulating cells and microbes with remarkable precision.
Secret parameter allowed hackers to steal passwords when a target clicked on a link.
This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.Microspines are one of many ways to enable robots to latch onto surfaces like walls and ceilings. Now roboticists in Canada are using the mini spikes to get drones to land on a more challenging, remote surface: icebergs.Like a spider, the Ice Dart can land on and latch onto steep, slippery surfaces such as icebergs and glaciers—an increasingly useful capability as activity in the Arctic increases. The drone can grip onto icy slopes of nearly 60 degrees, which is way beyond what most humans could manage without special equipment. In a recent study, researchers explained how they developed the Ice Dart drone with a special landing gear that absorbs the impact of a hard landing while holding the drone in place with tiny spines that penetrate and grip the ice. Published in IEEE Transactions on Field Robotics, the study describes how the Ice Dart was able to land on icebergs and a glacier in southeast Iceland. Tests took place amid persistent winds and temperatures of 0 to 10 °C along the ruggedly breathtaking Fjallsjökull (pronounced “FYATLS-yuh-kuutl”) glacier, which empties into a lagoon filled with icebergs. The drone was able to successfully perch at speeds of up to three meters per second and slopes of up to 58 degrees, with a success rate of 100 percent even in wind speeds of 30 km/h.The researchers were motivated by a desire to allow drones to land almost anywhere in the world, since the availability of safe landing sites is one of the primary limitations on where and how drones can operate. The researchers already have a history of developing drones that can land on fast-moving trucks as well as trailers, boats, and steep roofs. Ice Perching“The ability to land rather than hover can fundamentally change how drones are used in the field,” says Alexis Lussier Desbiens, a professor of engineering at Université de Sherbrooke, in Sherbrooke, Quebec, Canada, who coauthored the study. “Once a drone has landed, energy consumption drops dramatically, allowing much longer observation periods with a small aircraft. The drone also becomes completely silent and can even reduce or eliminate its thermal and RF signature by shutting down major onboard systems.”Landing on icebergs specifically allows drones to monitor them for days or months, producing more detailed observation than a quick aerial surveillance mission. This could simplify iceberg tracking compared to methods such as helicopter deployment, dropped instruments, or dart-like tracking devices, and provide another data layer to satellite and ship-based iceberg detection, according to the researchers. It could also provide a means of monitoring icebergs that are otherwise untrackable.With its carbon-fiber construction, the Ice Dart drone weighs just 2.65 kg and has four legs arranged in an X shape, attached to its body with a pivot joint. Used in the group’s previous drone research, this landing gear disperses energy to reduce impact and overcomes multiple engineering challenges. The friction shock absorbers consist of 38 disks that generate friction torque as the legs move up and down upon impact. This lowers the UAV’s center of mass and helps spread out the kinetic energy of landing, but the real trick comes in the form of two retractable spines on each foot—one for uphill and one for downhill grip. The larger spine engages on the more heavily loaded downhill feet, and the smaller, thinner spine engages more easily on the uphill feet, even under very low loads on steep slopes. The spines only penetrate the ice as the suspension compresses, generating grip and protecting them from high-impact forces. “The inspiration for the retractable spines in the feet came from looking at a cat’s claws and their ability to deploy only when needed,” says Isaac Tunney, a Université de Sherbrooke postdoc in mechanical and robotics engineering who was lead author of the paper. “I wanted to create feet that would naturally and passively engage their spines in the ice at the right moment, regardless of the drone’s orientation, the surface geometry, or the ice conditions.”Arctic SurveillanceWilliam D. Harcourt is a researcher at the University of Aberdeen, in Aberdeen, Scotland, focused on Arctic glaciers, snow, and sea ice, as well as the use of remote sensing and machine learning techniques. Harcourt was not involved in the study, but he sees several potentially interesting applications of the technology. “Near the front of tidewater glaciers, these systems could enable measurement of stress-strain and help us understand calving processes,” says Harcourt. “Drones can be used as a mobile GPS, literally acting as a receiver on the ice, but the system would need to solve tilting issues as 3D change measurements usually required the antenna to be horizontal. However, if these problems can be solved, it could be used to track iceberg movements.”The researchers want to continue developing the Ice Dart technology for real-world applications, including autonomous landing site selection and an emergency takeoff capability to be used if an iceberg rolls over or breaks apart. This August, the drone will be deployed during a Canadian Arctic mission to land on icebergs, collect data, and help validate ship-based iceberg-detection systems.
Humanoids desperately need to stop making YouTube videos and get a job already, and Persona AI is one of the few humanoid companies which seems to be entirely focused on making that happen. Persona’s approach has been to carefully select a job that is economically viable for robots right now, and they’ve found one that was also the job of one of the very first industrial robots ever sold: welding.IEEE Spectrum first spoke with Persona two years ago, shortly after it was founded by Nic Radford and Jerry Pratt. Radford led NASA JSC’s Valkyrie program back in the day and was also the founder of Nauticus Robotics, while Pratt led IHMC’s DARPA Robotics Challenge team before spending a couple of years as CTO of Figure. The Challenge of HumanoidsAs of our first conversation in 2024, Persona had committed to building an economically viable humanoid, but they hadn’t yet figured out where their focus was going to be. “We were all over the place,” Radford says. “Warehousing, automotive, we probably even mentioned the home.” These are the same environments with the same sorts of potential applications that basically every other humanoid robotics company is attempting to make economically viable, and despite an ever more exhaustive number of demonstrations, so far none have succeeded at any sort of useful scale. The challenge for Persona, and really for every robotics company, is that it’s not enough that you have a robot that is simply capable of doing a task. It’s also not enough that your robot can do that task in a way that is efficient and reliable and safe. What’s required is that your robot can make money for both you and your customer. Most humanoid companies seek to achieve this by targeting baseline “unskilled” human labor.Persona did not see economic viability in the unskilled labor approach, Radford says. “We started forming this thesis around skilled trades and tool usage.” Persona is targeting much more expensive skilled labor with its robots, and the reason why this is feasible is because their entry point focuses on the kind of skills that robots are especially good at. “I like to call it ‘last-mover advantage.’ We’ve seen everything that everybody’s doing, and we’ve decided that there’s a different way.” Persona AI/YouTube A Humanoid for Shipyard WeldingThe first task that Persona’s humanoid is focusing on is welding—using a handheld tool to connect one piece of metal to another. “Tool use is pretty difficult,” Pratt says. “And we want to use the same tools that humans do, which makes it more difficult.” That difficulty is offset somewhat by the fact that Persona’s humanoid will first focus on making long, linear welds that are relatively uncomplicated. “This is not the hardest style of weld,” Radford says, “but in shipbuilding you need a lot of them—hundreds of kilometers of linear welds per ship.”Currently, Persona has two public partnerships: one with HD Hyundai, which is the world’s largest shipbuilder, and the other with POSCO, the third-largest steel producer in the world, both in Korea. Persona declined to get into detail, but Radford says that broadly speaking, the company is interested in customers who can support ‘hundreds’ of robots per location.Shipyard welding is an enticing application for Persona because there is a deficit of skilled (and highly paid) workers, it’s taxing physical labor, and it’s a comparatively easy skill for a humanoid to learn.The welding process is skilled in a very robot-friendly way. Because you can only weld as fast as metal melts, the top speed for the task is an easily manageable centimeter per second. And making a high quality weld involves millimeter-scale repeated motions, which robots excel at, especially over long periods of time—whereas humans tend to get tired or bored. Pratt expects that for these uncomplicated welds, performing on-par with humans—if not eventually better—will be achievable soon.Shipyards make a compelling case for a humanoid with legs, as opposed to a more stable wheeled base. “These open-air shipyards are a couple hundred meters long, with horizontal and vertical spars you have to step over all the time,” says Radford. “You’ve got to work on the ground, overhead, and through portholes.” Persona considered other form factors, like four legs (or even more), but determined a two-legged robot would be the least disruptive to existing shipyard rhythms.The Economic Viability of HumanoidsDeploying their robots in shipyards specifically brings additional advantages for Persona. The safety concerns that come with bipedal robots—such as potentially falling over on a human worker—are lessened because a shipyard environment is staffed with workers who are trained to work around potentially dangerous industrial equipment. The company is also less sensitive to competitive pricing because no other company is pursuing the use case. “We’re now in an industry where the value added by our robot can be high enough that we don’t have to cut corners on quality and features in order to reduce the price,” says Pratt. “With a robot for the home, for example, there would be a lot of competition and a ton of price pressure.”The added value for shipbuilders, explains Radford, doesn’t come from replacing humans with robots. “Our current partnerships are running at a significant backlog, and they’re labor-constrained. So we want to help our customers’ top line, not necessarily their bottom line.” In other words, rather than trying to argue that their robots will lower shipbuilding costs, Persona is instead arguing that their robots will allow more ships to be built. “Even if our robot was more expensive than a human, that would still be valuable to these companies, because it could unlock additional revenue,” Radford says. And when the additional skilled labor does not exist, Persona’s robots could be the next-best option for shipbuilders who need to scale. Shipyards are environments where legs are necessary for a robot to be useful.CFOTO/Future Publishing/Getty ImagesPersona’s Multipurpose FutureIn the current commercial humanoid climate where the emphasis seems to be on developing a “general purpose” (whatever that means) robot that will somehow justify itself through some undefined scale in some equally undefined and perpetually receding future, Persona stands out with their focus on a seemingly viable, near-term, and very specific business case. It hasn’t been easy, though. “It hurts us a little bit,” Radford says. “We’ve been told that we’re not thinking big enough.” But a tool-using heavy industrial humanoid has plenty of future applications, many of which can be expanded from the welding skill even within shipyards. “Shipbuilding is a great beachhead,” says Pratt. “There are tons of adjacent markets, like grinding, painting, and other kinds of fabrication.” Persona’s ambition, adds Radford, is to be “the largest repository of industrial skills.” It’s going to take time to get there. That time will be needed to collect tens of thousands of hours of expert demonstration data, create high-fidelity simulations, and conduct real-world testing. And however promising Persona’s approach may seem, the company still has to prove that its idea for an economically viable robotics company can be realized. It’s the same challenge that every humanoid robot company is facing. “A lot of the technical problems are the same no matter whether you’re in a house or a shipyard,” Pratt says. “Everybody’s got a great team and smart people, and we’re all knocking these problems out together.”