I first met Robert Woo in 2011, during his third time walking in a powered exoskeleton. The architect had been paralyzed in a construction accident four years earlier, but he was determined to get back on his feet. Watching him clunk across a rehab room in an exoskeleton prototype, the technology felt astonishing. I had the same reaction when reporting on early brain-computer interfaces (BCIs), which enabled paralyzed people to move robotic arms or communicate by thought alone. Both types of bionic technology seemed to verge on magic.

But that initial sense of awe, I’ve learned over many years of reporting on these technologies, is only a starting point. What matters is not what these systems can do in a carefully staged demo but how they perform in the real world. Do they work reliably? Can people with disabilities use them for their intended purposes? And what does it actually cost—in time, effort, and trade-offs—to do so? The question isn’t whether the technology looks impressive the first time but whether it holds up on the hundredth.

The special report in this issue, “Cyborg Tech From the Inside” takes that perspective seriously. In my feature article on Woo, an exoskeleton super-user who has spent 15 years testing these systems, the story of the technology is inseparable from the story of its use. Woo’s relentless feedback has driven steady, incremental improvements. In Edd Gent’s reporting on the pioneers testing the earliest BCIs, the experience of these extraordinary technologies likewise resolves into something more complex. As one trial participant notes, these early adopters are like the first astronauts, who barely reached space before coming back down to Earth. Together, these stories reframe these individuals not as passive medical patients but as the ultimate beta testers and co-engineers of the bionic age.

I saw the gap between demonstration and daily use firsthand when I interviewed Woo in a Manhattan showroom recently, where he was testing a new self-balancing exoskeleton from Wandercraft. The device is a striking advance that kept him upright without crutches, but it also revealed the friction of the real world. As Woo tried to walk out the door, barely an inch of slope on the Park Avenue sidewalk was enough to trigger the machine’s safety sensors and halt his progress. It was a stark reminder of how far these systems must evolve before they fit seamlessly into everyday life.

For the people who use them, that seamless integration is the ultimate goal. Getting there will depend not just on technical breakthroughs but on how well these systems hold up outside controlled environments, over time, and under real conditions. Looking from the inside doesn’t make these technologies any less remarkable, but it does change how we judge them—not by what they can do once for a photo but by what they can sustain over a lifetime. That’s the standard their users have been applying all along.

Our commitment to evaluating technology from the user’s perspective extends beyond this special report. To provide a necessary corrective to the “techno-solutionism” that often dominates coverage of assistive devices, IEEE Spectrum created the Taenzer Fellowship for Disability-Engaged Journalism, under which six writers with disabilities are contributing articles about the devices they rely on daily. As Special Projects Director Stephen Cass notes, these journalists “aren’t afraid to ask clear-eyed questions about the tech and are deeply aware of how it impacts humans.” You can read the fellows’ work at spectrum.ieee.org/tag/taenzer-fellowship.

By OpenAI COO’s own admission last February, “we have not yet really seen AI penetrate enterprise business processes.” But for enterprise software giant SAP, whose stock has dropped significantly in 2026 in part from the “SaaSpocalypse,” the issue is still front and center.

On Monday, the European heavyweight announced its intention to acquire German AI startup Prior Labs for an undisclosed amount. Pending regulatory approval, SAP plans to invest €1 billion (approximately $1.16 billion) into the business over the next four years to grow it into an AI lab focused on structured data — the tables and databases where enterprise information typically sits.

SAP declined to disclose how much it spent on the acquisition itself, but sources told Pathfounders that this was a healthy exit: an “almost all cash” deal, with well over half a billion dollars in cash up front for the startup’s founders — Frank Hutter, Noah Hollmann, and Sauraj Gambhir.

The trio co-founded Prior Labs just 18 months ago with a focus on tabular foundation models (TFMs) — AI models that can make predictions from data that sits in tables and databases. This is potentially a better fit for enterprises than language models. It is certainly a better fit for SAP, whose widely used software products for accounting, HR, procurement and expense management rely on its database.

However, Germany’s most valuable company also seems be playing defense as the tech industry marches toward agentic AI. While it works to create its own AI lab, the company has blocked OpenClaw and any other agent tech that it has not explicitly authorized, The Information was first to spot.

In response to a request for comment, SAP’s press department referred TechCrunch to the company’s latest API policy, which does say that SAP “prohibits” AI agents from accessing its products through its API except for those that are “SAP-endorsed architectures.”

Authorized architectures of course include SAP’s own offering, Joule Agents, still in beta, which lets customers create their own agents. Nvidia also announced in March that SAP’s Joule supports Nvidia’s Agent Toolkit, which is software for managing agents. This toolkit is the foundation for Nvidia’s enterprise-ready, security-focused OpenClaw competitor, NemoClaw. Hence SAP customers will be authorized to use NemoClaw agents.

For a giant incumbent player like SAP, AI is both a threat and an opportunity. “It’s all about how quickly [we can] as SAP actually also embark [on] these technologies in our R&D portfolio to keep the relative economies of scale advantage,” CFO Dominik Asam told CNBC in January.

SAP hasn’t been sitting on its hands. The German company invested in generative AI companies that develop language models large and small: In 2023, it backed OpenAI rival Anthropic — as well as Aleph Alpha and Cohere, which now intend to merge to form “a global AI powerhouse.”

It had also developed SAP-RPT-1, a relational pretrained transformer model. “Early on, SAP recognized that the greatest untapped opportunity in enterprise AI wasn’t large language models; it was AI built for the structured data that runs the world’s businesses,” SAP CTO Philipp Herzig declared in a statement. 

But Prior Labs’ acquisition is a significant shortcut in that direction. Its TabPFN model series has experienced a lot of traction among developers. In a blog post on the deal, the startup’s founders said that its open source models have been downloaded over three million times.

In a press release, SAP promised that Prior Labs will maintain the open source versions: “The lab will operate as an independent unit to ensure research velocity while SAP provides long-term investment and a direct path to productization across the SAP portfolio with SAP AI Core and SAP Business Data Cloud as well as the agentic layer with Joule.”

SAP and the startup headquartered in Freiburg, Germany, hope that this investment will lead to TFMs that can grab data in the tables where it lives, combine that with language, reasoning, and domain knowledge.

More than that, they hope that Prior Labs, with this “massive boost” from SAP, can become a new “globally-leading frontier AI lab for structured data — in Europe, in the open,” founder and CEO Frank Hutter celebrated in a post on X.

In February 2025, the startup had previously raised some $9.3 million in a pre-seed funding round led by Balderton Capital — more than competitor Neuralk-AI, but a lot less than Fundamental, which emerged out of stealth with a $255 million Series A in February. 

In a post on X, Balderton partner James Wise called Prior Labs’ acquisition “one of Germany’s biggest ever venture outcomes.” As for SAP, its stock is currently trading slightly upwards.

Meanwhile, SAP is being very strict as to the agents it will allow into its ecosystem. This is a wildly different approach than Salesforce, another incumbent caught in the SaaSpocalypse. It is allowing enterprise to choose their own agents, including OpenClaw if they so wish, with its new Headless 360 architecture.

One of the follow-on payloads pushed to about a dozen organizations was what Kaspersky described as a “minimalistic backdoor.” It has the ability to execute commands, download files, and run shellcode payloads in memory—making the infection harder to detect.

Kaspersky said that it observed a more complex backdoor dubbed QUIC RAT, installed on a single machine belonging to an educational institution located in Russia. Initial analysis found that it can inject payloads into the notepad.exe and conhost.exe processes and supports a variety of C2 communication protocols, including HTTP, UDP, TCP, WSS, QUIC, DNS, and HTTP/3.

The 100 infected organizations were primarily located in Russia, Brazil, Turkey, Spain, Germany, France, Italy, and China. Kaspersky’s visibility into the attack is limited because it’s based solely on telemetry provided by its own products.

Kaspersky researchers wrote:

The analysis shows that 10% of the affected systems belong to businesses and organizations. Attackers attempted to infect most of the affected machines only with the information collector payload. However, the other backdoor payload, which is more complex, has been observed only on a dozen machines of government, scientific, manufacturing and retail organizations located in Russia, Belarus and Thailand. This manner of deploying the backdoor to a small subset of infected machines clearly indicates that the attacker had intentions to conduct the infection in a targeted manner. However, their intent – whether it is cyberespionage or ‘big game hunting’ – is currently unclear.

More recent supply-chain attacks have hit Trivy, Checkmarx, and Bitwarden and more than 150 packages available through open source repositories. Last year, there were at least six notable such attacks.

Anyone who uses Daemon Tools should take time to scan the entirety of their machines using reputable antivirus software. Windows users should additionally check for indicators of compromise listed in the Kaspersky post. For more technically advanced users, Kaspersky recommends monitoring “suspicious code injections into legitimate system processes, especially when the source is executables launched from publicly accessible directories such as Temp, AppData, or Public.”

LegalZoom is one of those online legal services that in most cases can handle basic legal tasks for you. I recently tried it out to make an LLC for my cosmic country band, Steel Fringe (shameless plug), and it appears to have worked just fine (we’re still waiting on a full evaluation from legal experts for a future guide to these services). If you use a LegalZoom promo code right now, you will get a discount on the service.

I found it super easy to set up my LLC, and after about $500 and 30 minutes of my time, I was off to the races with an LLC for my band. I did make the mistake of spelling my co-bandleader’s middle name as his last name (I blame his wrongly named Instagram handle for this), so I had to toss them another $129 to fix that. My bad.

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Microplastics absolutely saturate the Earth’s environment, and that’s probably not a good thing unless you’re looking for a sediment marker for the Anthropocene period. On the other hand, environmental contamination only becomes a really big problem if it bioaccumulates– that is, builds up in the tissues of plants and animals. At least when it comes to worms, that’s not the case with microplastics, according to new research from the Canadian Light Source at the University of Saskatchewan.

The Canadian Light Source isn’t just some hoseheads in an igloo with a flashlight– it’s a 2.9 GeV Synchrotron tuned to produce high-energy photons. Back when Synchrotrons were used for particle physics, Synchrotron radiation was a very annoying energy sink, but nobody cares about 2.9 GeV electrons anymore. So rather than slam them into each other or a static target, the electrons just whip about endlessly, giving off both soft- and hard X-rays for material science studies– or, in this case, to observe the passage of polyethelyne microplastic particles through the guts of some very confused earth worms. To make them detectable by x-ray, the polyethylene was bonded to barium sulfate, an x-ray absorber. Equally opaque barium titanite glass microspheres were used with different worms, as a control.

Despite being fed plastic enriched with far more plastic than you’ll find outside of a 3D print farm, it seems the worm’s digestive system was able to reject the particles, even those as fine as 5 microns. That’s a good thing, because if the worms were absorbing plastic from the soil, it’s likely their predators would absorb it from the flesh of the worms, so and so forth up the food chain in the sort of cascade that made DDT a problem and makes mercury compounds so serious. If the worms are rejecting these compounds, there’s a chance other creatures can too– and at the very least, it means they aren’t building up on this bottom rung of the foot chain. If you’re looking for a more technical read, the full paper is available here.

It’s too early to say what this means for how microplastics get into humans and other animals, but it’s hopeful. Equally hopeful was the recent finding that studies that don’t rely on football-field sized X-ray machines might be picking up on microplastics from lab gloves, skewing results.

Header image: the digestive systems of earth worms as imaged by the Canadian Light Source. Credit Letwin, et al,
Environmental Toxicology and Chemistry, vgag072, https://doi.org/10.1093/etojnl/vgag072

China has more than 150 humanoid robot companies. It shipped roughly 90 per cent of the world’s humanoid robots in 2025. Its two largest makers, Unitree and AgiBot, are preparing initial public offerings that would value them at a combined 13 billion dollars. Morgan Stanley doubled its delivery forecast for the Chinese market this year to 28,000 units, a 133 per cent increase over 2025. And yet, when Morgan Stanley surveyed the companies that are supposed to buy these robots, only 23 per cent said they were satisfied with the products available. Battery life tops out at two to three hours per charge. Most deployments remain confined to exhibitions, showrooms, and Spring Festival galas where robots perform kung-fu routines for television cameras. The technology has arrived. The customers have not. China’s humanoid robot industry is the most capitalised, most productive, and most overpopulated robotics sector in the world, and it is heading for a reckoning that its government has already warned is coming.

The warning

In late 2025, China’s National Development and Reform Commission issued a rare public statement about the humanoid robot sector. Spokesperson Li Chao noted that the number of companies had climbed past 150 and was still growing, with more than half being startups or cross-industry entrants. The NDRC warned of redundant products, duplicated investment, and compressed space for genuine research and development. The language was measured. The implication was not. Beijing’s top economic planning agency was telling the market that it saw a bubble forming in the industry it had designated as one of ten priority sectors in the 15th Five-Year Plan, backed by a one-trillion-yuan state fund.

China’s smartphone supply chain has already begun pivoting to humanoid robot production, with companies like Lingyi iTech, a Foxconn supplier that assembles iPhones, targeting 500,000 humanoid units by 2030. The manufacturing infrastructure is real. The component ecosystem is deep. The problem is that the robots being produced are not yet generating the revenue their valuations imply. Unitree, which filed for a 608 million dollar IPO on Shanghai’s STAR Market, saw humanoid robot revenue surpass its quadruped robot business for the first time in 2025, but the company’s total scale remains modest relative to its targeted seven billion dollar valuation. AgiBot, which is aiming for a six billion dollar listing in Hong Kong, is in a similar position: significant technological capability, significant government backing, and a commercial market that has not yet materialised at the scale the IPO price demands.

The gap

The Morgan Stanley survey, led by China industrials analyst Sheng Zhong, found that 62 per cent of Chinese companies said they were likely to adopt humanoid robots within three years. That willingness, however, collided with a set of practical constraints that the industry has not resolved. The 23 per cent satisfaction rate reflected shortcomings in dexterity, functionality, and pricing. Ninety-two per cent of respondents said robots needed to fall below 200,000 renminbi, roughly 28,000 dollars, before mass adoption became viable. Only about 10 per cent of companies surveyed were currently evaluating or running pilot projects. The demand exists in theory. In practice, the robots are too expensive, too limited in capability, and too short on battery life to justify the investment for most industrial applications.

UBTech, one of the sector’s largest players, offered 18 million dollars to recruit a chief AI scientist, a salary that reflects both the intensity of the talent war and the recognition that the engineering challenges remaining are substantial. The Walker S2, UBTech’s latest industrial humanoid, entered mass production in early 2026 with orders exceeding 800 million yuan, and the company is building a factory in Beijing targeting 10,000 units per year by the end of 2026. But production capacity and commercial demand are different things. Morgan Stanley’s Zhong described 2026 as “a critical year as humanoid integrators strive to reach commercialisation and build up their ecosystems,” and warned of an impending shake-out. Production, he noted, is likely to be materially larger than sales, because major players are manufacturing robots internally for training and verification rather than shipping them to paying customers.

The spectacle

In April, a humanoid robot called Lightning, developed by Chinese smartphone maker Honor, won the Beijing E-Town Half-Marathon in 50 minutes and 26 seconds, beating the human world record by nearly seven minutes. More than a hundred robots competed. The event was covered globally. An engineer on the winning team said the achievement enabled technology transfer into structural reliability and cooling that would eventually benefit industrial applications. Robotics experts were less certain. The skills displayed during a half-marathon, sustained bipedal locomotion on a flat surface, do not translate to the manual dexterity, real-world perception, and adaptive problem-solving required for factory work, logistics, or the service applications that the industry’s business plans depend on.

The gap between spectacle and substance defines China’s humanoid robot moment. The Spring Festival Gala performances, the marathon records, and the viral videos of robots doing backflips generate the attention that attracts capital. The capital funds the next round of development. The development produces more impressive demonstrations. But the cycle does not produce revenue at the scale needed to justify the valuations being assigned. China’s industrial model has historically excelled at commercialising technology faster and cheaper than any Western economy, turning solar panels, electric vehicles, and batteries into globally dominant export industries within a decade. The question is whether humanoid robots follow that pattern or whether they represent a category where the gap between demonstration and deployment is structurally wider than the manufacturing advantage can close.

The competition

China’s dominance in humanoid robot shipments has not gone unnoticed. Boston Dynamics began commercial production of its electric Atlas robot in January 2026 and announced plans to deploy tens of thousands of units at Hyundai Motor Group factories, with a manufacturing facility near Savannah, Georgia, targeting 30,000 units per year by 2028. Figure AI, the leading American humanoid startup, holds a 39 billion dollar private valuation after its September 2025 fundraise, despite shipping a fraction of the volume Chinese companies manage. Tesla’s Optimus is performing basic tasks in its own factories, with Elon Musk projecting mass production and a price point of 20,000 to 30,000 dollars, though the robot is, by Musk’s own admission, “not in usage in a material way.” The Pentagon has awarded 24 million dollars in contracts to Foundation Future Industries for humanoid robot soldiers tested in Ukraine, opening a military market that Chinese companies cannot access but that validates the strategic importance governments are placing on the technology.

The pricing dynamics favour China. Unitree’s H2 is positioned below 30,000 dollars. Kepler, another Chinese maker, is targeting the same range. At CES 2026, the sheer number of Chinese humanoid robots on display, and their aggressive pricing, made clear that the supply-side economics are already competitive. The question is whether demand at those price points exists in sufficient volume to sustain an industry with 150 companies competing for it.

The reckoning

Zhong’s prediction of a shake-out is not a minority view. The NDRC’s warning, the Morgan Stanley satisfaction data, the IPO inspection of Unitree just twelve days after its STAR Market application was accepted, and the simple arithmetic of 150 companies chasing a market that delivered roughly 14,000 units in China in 2025 all point in the same direction. The companies that survive will be those that solve the commercialisation problem: identifying repeatable, scalable use cases where the economics of a humanoid robot are superior to the alternatives, whether those alternatives are purpose-built industrial arms, wheeled platforms, or human workers. The companies that do not will have burned through their funding producing impressive machines that no one outside a trade show needed to buy.

China’s humanoid robot industry has the manufacturing base, the component supply chain, the government support, and the engineering talent to lead the world. What it does not yet have is the market. The one-trillion-yuan state fund and the 15th Five-Year Plan designation ensure that capital will continue to flow. The NDRC warning ensures that Beijing is watching how it flows. Somewhere between the billion-dollar IPOs and the 23 per cent satisfaction rate, between the marathon records and the two-hour battery life, is the answer to whether China’s humanoid robot boom produces the next great Chinese export industry or the most expensive collection of trade show demonstrations the technology sector has ever funded. The robots can run a half-marathon faster than any human alive. They cannot yet work an eight-hour shift.

Mouse P.I. for Hire has caused quite the stir since it was revealed by Polish developer Fumi Games a couple of years back. Its rubberhose animation style, Doom-inspired boomer shooter gameplay, and Mickey Mouse-esque cast of characters helped it to stand out in the indie scene, and it’s already enjoyed a healthy dosage of positive reception from critics and players alike.

So, when I got the chance to try it out on Nintendo Switch 2, it’s safe to say I was pretty excited. Playing detective in a noir, rodent-filled world sounds pretty enticing, right? And given that I had some long-haul flights up ahead, going with the Switch 2 edition to mouse around on the go felt like a no-brainer.

The hacker behind a breach at education technology giant Instructure claims to have stolen 280 million records tied to students and staff from 8,809 colleges, school districts, and online education platforms.

Instructure is a cloud-based education technology company best known for its Canvas learning management system, which schools and universities use to manage coursework, assignments, grading, and communication.

Last Friday, Instructure disclosed that it was investigating a cyberattack and later revealed that it had suffered a data breach, during which users’ names, email addresses, and private messages were exposed.

The ShinyHunters extortion gang claimed responsibility for the attack and says it stole 280 million records for students, teachers, and staff.

The threat actors have now published a list of 8,809 school districts, universities, and educational platforms whose Canvas instances were allegedly impacted by the attack, sharing record counts per institution with BleepingComputer.

The record counts for each educational institution range from tens of thousands to several million per institution.

BleepingComputer is not naming specific organizations listed by the threat actor, as we have not independently verified whether they were impacted by the breach.

The threat actor claims the data was stolen using Canvas data export features, including DAP queries, provisioning reports, and user APIs, and that they harvested hundreds of gigabytes of user records, messages, and enrollment data.

While Instructure has not responded to repeated emails regarding the incident, some universities have begun issuing statements about the potential impact.

“CU is aware of a data breach involving Instructure, the parent company of Canvas, our learning management system. This reported data breach is a nationwide event affecting multiple institutions,” warned the University of Colorado Boulder.

“At present, Rutgers has not been notified of any direct impact to our campus. Canvas remains available and operational to Rutgers faculty, staff, and students,” warned Rutgers.

“An investigation is currently underway to determine what exactly happened and which systems were affected. It has not yet been confirmed whether data of Tilburg University students and staff has been impacted. Further questions have been submitted to the supplier to obtain more clarity,” warns Tilburg University.

BleepingComputer has contacted Instructure again with additional questions and will update this story if we receive a response.

AI chained four zero-days into one exploit that bypassed both renderer and OS sandboxes. A wave of new exploits is coming.

At the Autonomous Validation Summit (May 12 & 14), see how autonomous, context-rich validation finds what’s exploitable, proves controls hold, and closes the remediation loop.

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