A representative TU Darmstadt survey of more than 2,000 people in Germany found that about 43% of those with very strong AI knowledge expect AI could soon take over their work, a higher share than among those who understand it less. Only 15% of respondents have had any AI training, eighteen months after the AI Act’s literacy obligation began to apply.

The better people understand AI, the more they expect it to take their job. About 43% of those with very strong AI knowledge think so, TU Darmstadt found.

The survey covered more than 2,000 people in Germany, carried out with YouGov. It is representative, and the answers are measured against last year’s edition.

“Those who understand AI best are also the most aware of its disruptive potential,” said Peter Buxmann, who led the study. He called the pattern both remarkable and worrying.

Industry matters less than output. If your work produces text, analysis, reports, code or slides, you are more exposed, Digital Trends reported.

The worries themselves are unglamorous, which is the second surprise. Hallucinations and data protection top the list, well ahead of anything about machine superintelligence.

Only 40% think superintelligence is even likely. TNW has argued that what AI is doing to jobs in Europe looks different from the headline version.

Younger workers are more anxious than older ones, which inverts the usual expectation too. Concern about job security rose across every occupational group since last year.

One number should trouble employers more than the rest of it. Just 15% of respondents have had any AI training at all.

Europe has had a rule about that for eighteen months. Article 4 of the AI Act has applied since 2 February 2025.

It obliges providers and deployers of AI systems to take measures supporting AI literacy among the staff who operate them, weighed against their training and the context of use.

It sets no particular level and binds only organisations actually using such systems, so 15% is not a compliance rate. TNW has asked whether the Act can protect jobs at all.

It is a readiness figure instead. Eighteen months of a literacy duty, and most German workers have had nothing.

Which is Buxmann’s point. He wants training and honest answers rather than reassurance, because losing a job costs more than income.

Security

McKesson admits breach as ShinyHunters demands $55.2M

Two major healthcare businesses, Boston Scientific and McKesson, disclosed more details over the weekend about separate cyberattacks that disrupted global operations and resulted in stolen patient data, respectively.

Medical-device maker Boston Scientific, whose IT systems were hacked by unknown intruders last week, said the cyberattack remains ongoing. It also noted that pacemakers and other heart devices implanted after the August 25 breach cannot provide remote monitoring and data transmission as intended.

“New remote monitoring communicators cannot be activated, thus available device data will NOT be transmitted to remote patient management systems until the communicator can be activated,” the medtech firm said in a late Friday update. 

This applies to all new cardiac rhythm management implants other than insertable cardiac monitors (ICM). 

ICM devices must be activated using the Boston Scientific Clinic Assistant app to ensure the device correctly records patients’ heart rhythms, the company added. 

Because of the cyberattack, “new ICMs are unable to pair to the patient remote monitoring mobile phone, therefore available episode data recorded by the ICM will NOT be transmitted to the remote monitoring system until the ICM can be paired to the patient mobile app,” according to the update. 

The devices will still record any episodes, and patients can transmit these to the remote monitoring system by in-person transmission via the Clinic Assistant app. This is done by selecting the “interrogate” button, according to the company.

Once its IT systems are back up and running, and the heart devices can pair with home monitoring equipment, they will again transmit recorded data to the remote systems.

However, the company does not have a timeline for full restoration. “We are currently working on restoring affected functions and systems access,” Boston Scientific said on Saturday.

The digital intrusion also affected the firm’s manufacturing, shipping, and ordering, it noted. “We are expeditiously working towards partial restoration for the shipping of some products this week,” according to a Sunday update. “Once we can demonstrate the restoration is fully operable, we anticipate ordering and shipping will ramp up to full capacity.”

Boston Scientific has hired CrowdStrike to assist with the investigation and restoration efforts, and said the attack did not affect its cloud-based systems and apps – just “certain on-premise systems” – and added that it has seen no indication of unauthorized IT activity since August 25.

The firm has repeatedly declined to answer The Register’s questions about the compromise, including whether it was a ransomware infection and which criminal crew is responsible.

McKesson confirms breach as ShinyHunters claims responsibility

Meanwhile, in another cybersecurity incident that has been very publicly claimed by the criminal perpetrator: pharmaceutical and medical supply giant McKesson over the weekend confirmed an intrusion after ShinyHunters on Friday told The Register it broke into the company’s Snowflake and Salesforce instances and stole millions of patients’ data.

“Based on our investigation thus far, including assessments by leading cybersecurity industry experts supporting our response, we’ve confirmed that the unauthorized access to certain third-party applications and the exfiltration of certain data was associated with a subset of customers within our Oncology & Multispecialty and Medical-Surgical business units,” Francisco Fraga, McKesson executive VP, chief information officer and chief technology officer, said in a Saturday statement. 

The medical firm did not immediately respond to The Register’s questions, including how many patients were affected and what “certain data” was stolen. McKesson supports about 3,300 oncology providers in 29 states, according to its website. 

Fraga’s statement noted that distribution centers remain operational and McKesson continues to ship products. The firm has “reasonable assurance” that the digital intruders have been kicked out of the third-party environments and aren’t lurking around McKesson’s systems, he added.

A ShinyHunters spokesperson told us that the notorious extortion group compromised more than 284 million records of patient data, and demanded McKesson pay $55.2 million or else they would leak the stolen data.

However, as Have I Been Pwned boss Troy Hunt recently reminded everyone: Don’t confuse criminals’ claims with gospel truth, and “take headline numbers with a grain of salt unless you’re confident in the processes of those making the claims.” 

This was after Hunt’s HIBP service reported 12.9 million individuals affected by retailer Carhartt’s alleged breach. This number was around half of what ShinyHunters claimed when they leaked the company’s data earlier this month.

The McKesson records, according to the ShinyHunters spokesperson, include patients’ full names, home and email addresses, phone numbers, dates of birth, Social Security numbers, appointment dates and notes, and sensitive illness details including cancer locations on people’s bodies. The group also claims to have swiped emails containing private information from doctors to patients.

The spokesperson told us they accessed the company’s Snowflake and Salesforce instances by voice phishing “multiple employees.” This is a tried-and-true method popularized by the data-theft-and-extortion gang, which has victimized other medical providers in recent months. These include pacemaker manufacturer Medtronic in April, and cancer diagnostics business Exact Sciences in July. ®

Taiwanese authorities said they questioned 18 people, including 14 Unimicron employees.

Nvidia’s printed circuit board (PCB) supplier Unimicron is under investigation by Taiwanese authorities over suspicions of shipping Chinese-made PCBs using ‘made in Taiwan’ labels in violation of forgery laws.

Taiwan’s Taoyuan District Prosecutor’s Office said it searched Unimicron’s headquarters and a factory, and questioned 14 company employees – including the PCB business division’s general manager and deputy manager – alongside four related witnesses.

The prosecutors said the defendants are suspected of violations of Taiwan’s criminal code under laws around forging private documents and falsely labelling goods. Bail was set from around $9,500 to $470,000 for five of the defendants, while the remainder have been released.

Unimicron, in a statement to the Taiwan stock exchange, confirmed that its offices had been searched and said it would fully cooperate with the prosecutors.

Last week’s investigation comes just days after the US said it is losing roughly $19bn to $26bn in annual tariff revenue from goods that are transshipped through third countries to avoid US import duties, with a majority of the losses stemming from Chinese goods.

Earlier this month, Taiwanese prosecutors indicted nine people – including one Nvidia and two Supermicro employees – for allegedly smuggling AI servers into China. Those arrests are part of an ongoing investigation by authorities probing illegal transfers of AI servers built by Supermicro using Nvidia GPUs to China.

In March, the US charged three people associated with Supermicro, including co-founder Yih-Shyan Liaw, over allegations of helping smuggle at least $2.5bn of AI technology into China.

Late last month, authorities arrested a Taiwanese national – reportedly an Nvidia employee – as part of the same investigation. Earlier in July, Supermicro said that two workers at its Taiwan unit were arrested as part of the investigation, while a previous round saw three people being detained.

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Need some help with today’s Mini Crossword? I was not expecting a British Royal Family clue, but 4-Down came through with one. Keep calm, and carry on for all the answers.

Mini across clues and answers

1A clue: Peering pair
Answer: EYES

 5A clue: “Hugs and kisses” sign-off
Answer: XOXO

6A clue: Support, as for a corporate plan
Answer: BUYIN

7A clue: Words exchanged at the wedding altar
Answer: IDOS

8A clue: Email sign-off
Answer: BEST

Mini down clues and answers

1D clue: Give off strongly
Answer: EXUDE

2D clue: Toys on strings
Answer: YOYOS

3D clue: Be in the world
Answer: EXIST

4D clue: Prince Archie, to Harry and Meghan
Answer: SON

6D clue: Neckwear for a baby
Answer: BIB

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CNET editor Gael Fashingbauer Cooper, a journalist and pop-culture junkie, is co-author of “Whatever Happened to Pudding Pops? The Lost Toys, Tastes and Trends of the ’70s and ’80s,” as well as “The Totally Sweet ’90s.” She’s been a journalist since 1989, working at Mpls.St.Paul Magazine, Twin Cities Sidewalk, the Minneapolis Star Tribune, and NBC News Digital. She’s Gen X in birthdate, word and deed. If Marathon candy bars ever come back, she’ll be first in line.

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The proliferation of custom AI ASICs, or XPUs, from OpenAI, Meta, Microsoft, and others has led many to question Nvidia’s grip on the market. After all, if everybody’s building their own, who needs the GPUs the AI arms dealer has made its fortune on?

But Nvidia isn’t concerned in the least and has instead invited its competition to raid – or, rather, license – the GPU giant’s IP holdings, particularly those related to networking.

On Monday, MediaTek became the latest to embrace Nvidia’s NVLink Fusion high-speed interconnect technology for its fledgling datacenter XPU offering. In exchange, Nvidia has invested $3.5 billion in convertible bonds issued by MediaTek. The GPU giant will also continue to license the Taiwanese SoC provider’s own designs for use in future DGX and RTX Spark systems.

If you’re curious, we explored MediaTek’s datacenter ambitions last month. But the designer, best known for its Arm-based smartphone and tablet processors, is only one of several high-profile chip designers that plan to integrate the tech. Amazon, Fujitsu, Qualcomm, Arm, and Marvell are all on the same list.

NVLink Fusion started as a commercialized version of Nvidia’s high-speed inter-GPU interconnect, introduced early last year. Initially, it was offered in two varieties: a chip-to-chip (C2C) variant for connecting CPUs to GPUs (or XPUs) in a memory coherent fabric, and a switched fabric used to stitch together multiple accelerators into one big logical rack-scale chip. It’s since expanded to become the blanket offering by which Nvidia licenses its semiconductor IP.

Given how long it’s taken Broadcom and others to develop competitive alternatives to NVLink, it’s not surprising companies like MediaTek would license the tech, rather than reinventing the wheel, or piping alternative interconnects, like UALink, over regular old Ethernet.

By licensing Nvidia’s NVLink Fusion tech, companies can focus on building competitive accelerators without worrying about how they’re going to scale in production.

And because Nvidia’s MGX rack designs are part of the Open Compute Project, MediaTek and its partners not only benefit from Nvidia’s scale-up networking tech, but also can essentially take existing NVL72 racks and slot in their compute blades. This should dramatically reduce the system design and mechanical engineering experience required to go from silicon to AI racks.

And this isn’t theoretical. Amazon is doing just that with its Trainium series of AI accelerators. As we wrote at the time, Amazon used Nvidia’s MGX NVL72 reference design for its Trainium3-based rack systems launched last year. Meanwhile Trainium4, expected late this year, will ditch Amazon’s in-house NeuronLink interconnect tech for NVLink Fusion.

Nvidia’s cut

So, what does Nvidia get from letting rival chip designers piggyback off its hard-won networking tech?

A lot more than licensing fees: It’s also a way to keep companies hooked on its other products.

When NVLink Fusion was first announced, customers had two options. They could pair their XPUs with Nvidia’s CPUs or their CPUs with Nvidia’s GPUs. Customers also were on the hook for NVSwitches if they wanted to take advantage of the tech’s scale up networking capabilities.

So, on top of licensing the tech, Nvidia had the potential to sell roughly two GPUs per partner CPU, a Grace or Vera CPU for every two partner XPUs, and up to nine NVSwitches for every 72 or so accelerators, and that’s just the rack.

If you’re already buying NVLink, why not use InfiniBand or Nvidia’s Spectrum-X Ethernet kit to switch those racks together to train and serve even larger models at scale?

Nvidia has since softened its stance and now seems content with the combination of NVSwitch sales and NVLink Fusion licensing. If it hadn’t, Amazon couldn’t have paired Graviton with Trainium.

“The beauty about this platform is it provides the flexibility and the fungibility in order to meet the customers where they are. And so, leveraging the NVLink Fusion platform, they can adopt anywhere from the CPU to the GPU to the scale-up fabric to the scale-out networking across our Spectrum-X and InfiniBand, as well as our DPU within the scale-in fabric to do the north-south storage management as well as security isolation,” Dion Harris, Nvidia’s senior director of HPC and AI Hyperscale Infrastructure, told press on Monday. “So, the five different networking technologies and topologies that we offer in our technology stack are all available to customers via NVLink Fusion.”

Nvidia isn’t quite ready to talk about the licensing structure just yet, but Harris says they won’t be giving it away.

“…It is safe to assume that there will be some licensing elements in place in that Nvidia NVLink Fusion is an Nvidia technology,” Harris said.

It’s not just about networking

Nvidia is already the largest datacenter Ethernet networking provider in the world, thanks in no small part to the AI boom. Its quarterly networking revenue now exceeds $15 billion, and NVLink Fusion licenses and associated NVSwitch sales will only bolster that. However, Nvidia’s licensing ambitions don’t stop there.

Last week, Nvidia detailed its latest IP offering in the form of NVHBM, essentially a custom base with an integrated memory controller.

According to Nvidia, the approach frees up 25 percent of the die for compute while cutting HBM power draw by 15 percent and boosting effective bandwidth by 30 percent.

Amazon’s Annapurna Labs will be among the first to field the tech with its Trainium family of AI ASICs.

But while Amazon’s adoption of NVHBM is a clear win for Nvidia, it should be noted that the idea isn’t unique to Nvidia. As we understand it, both Broadcom and Marvell are developing similar base-die tech as well. But the tech is another example of how Nvidia is leveraging its engineering might to extract revenues from everything associated with AI, including custom ASICs from others.

A deal with the devil or mutually beneficial coexistence

While Nvidia’s fledgling IP offerings are rather narrow for the moment, it’s not hard to imagine Nvidia competing with rivals like Broadcom or partners like Marvell and MediaTek on XPU design before long.

Depending on how things play out, Nvidia, Broadcom, Marvell, and MediaTek could end up looking more like frenemies.

XPUs are quickly becoming big business for both Broadcom and Marvell, but the networking required to scale that compute and system design required to bring it to market remains a competitive advantage for Nvidia.

Sure, both have competent Ethernet switching appliances capable of going toe-to-toe with NVSwitch, but even then you still have to integrate that into a rack. The advantage of being able to slot a custom compute blade into a generic NVL72 system and for it to work out of the box is hard to ignore.

If NVLink Fusion helps the XPU designers sell more chips, it could end up being a net benefit even if it means losing out on switch sales. Nvidia is clearly aware that while the barrier to entry for custom silicon has fallen through the floor, scaling that compute remains the hard part. ®

ai and ml

GenAI now reaches 80% of occupations, but in most of those fewer than half of workers use it

Economists have taken another stab at assessing the impact of generative AI adoption on different occupations and have found that adoption is broad but not very deep.

While generative AI reaches 80 percent of occupations and more than 40 percent of tasks, in most of these occupations fewer than half of workers adopt it.

Occupational use is high in professions where you’d expect – in management and professional occupations, particularly those that are related to finance, business, and computers. It’s lowest in personal service occupations and jobs requiring manual activity or interpersonal interaction.

That in and of itself isn’t surprising – other studies have suggested as much. But AI companies that have looked at occupational exposure to generative AI (Anthropic, Microsoft, OpenAI) based on chat logs come up with results that differ from those described in “What Work Does Generative AI Do?”

The paper [PDF], by authors Alexander Bick (Federal Reserve Bank of St. Louis), Adam Blandin (Vanderbilt), David J. Deming (Harvard), and Tyler R. Schumacher (Vanderbilt), measures how workers actually use generative AI for their jobs by analyzing Real-Time Population Survey (RPS) data.

The measurement discrepancy is the result, the authors say, of chat log classifiers that associate chats with a few tasks that have generic, activity-based descriptions like “Edit written material or documents.” 

The problem with this approach is that when OpenAI data concludes 15 percent of chats involve that sort of editing, those figures don’t match up with the US Department of Labor’s O*NET database, where only 2.4 percent of workers are in jobs that include that task.

The result, the researchers say, is that the exposure figures from vendors likely overstate how much generative AI is actually relevant to people’s jobs.

“GenAI is used in many occupations and tasks, but few of these exhibit very high adoption rates,” the authors state. “For example, four out of five detailed occupations have adoption rates above 20 percent, but only one out of six occupations exceed 70 percent adoption.”

Most occupations exhibit relatively low adoption rates, but for a few, the figure is substantial. About 15 percent of occupations had adoption rates above 70 percent (largely computer-oriented). And in terms of tasks, only 2.8 percent of tasks had adoption rates above 50 percent and none surpassed 70 percent.

Overall, as of May 2026, 55 percent of US adults between the ages of 18 and 64 used generative AI for non-work reasons and 45 percent of US adults used GenAI for work, according to the paper. The overall adoption rate (work or otherwise) is 62 percent.

One thing that drives AI adoption, they say, is experience. Those who start using it in one domain tend to adopt it in other domains.

Thus the researchers argue it’s at least as important to understand why some workers adopt AI and some don’t as it is to understand which tasks it can handle. ®

Actuators account for 40% to 60% of a humanoid robot’s bill of materials and China refines roughly 90% of the rare earth magnets inside them, which makes the components rather than the models the limit on scale. Europe has a 2030 cap on single country supply under the Critical Raw Materials Act, and one company, Schaeffler, building the actuators at volume.

The hardest problem in physical AI is not the AI. Actuators are in short supply from a small pool of qualified manufacturers, and new capacity takes years, not quarters, Nate Evans wrote in Unite.ai.

The argument arrives with an interest attached. Evans cofounded Fictiv, a manufacturing sourcing platform the Japanese components supplier MISUMI bought for $350M, and now heads MISUMI AI.

The column drops the point just as it gets useful. Actuators are 40% to 60% of a humanoid robot’s bill of materials, McKinsey found, and the gearbox is 30% to 50% of the actuator.

That gearbox is where the queue forms. Harmonic and strain wave drives come from a short list including Harmonic Drive and Nabtesco, and qualification cycles are long.

Inside the motor sits the harder dependency. Every high torque joint needs a neodymium magnet, and China holds about 90% of the processing capacity for rare earth magnets.

The mining figure is lower and less alarming. China accounts for roughly 69% of extraction, so refining rather than ore is what binds.

Europe has written a law about exactly this. Light and heavy rare earths sit on the strategic raw materials list, with a 2030 target that no single third country supplies more than 65% of consumption.

The Critical Raw Materials Act also reaches the robot itself. Articles 28 and 29 name industrial robots directly, and from 2028 magnets above 0.2kg need a label, a digital record and a recycled content figure.

Europe’s industrial answer is currently one company. Schaeffler invested in Humanoid, the London startup that raised $152M in July, and Bosch builds the robots.

Schaeffler also sells the joints. It is preferred supplier for more than half of Humanoid’s joint actuators under an agreement running to 2031, covering a seven-digit number of units.

It is buying as well as supplying. Schaeffler will put a four-digit number of the robots into its own plants by 2032, starting at Herzogenaurach in December. TNW has argued Europe could win on deployment despite China holding 63% of the hardware chain.

Which is where the column’s remedy runs out. An actuator assembled in Herzogenaurach still contains a magnet refined in China, and no amount of supplier qualification changes that.

The gap is a policy one rather than a purchasing one. Europe has a 65% cap dated 2030, a labelling regime dated 2028, and almost no refining capacity to meet either.