Market intelligence platform Klue has publicly confirmed a recent security incident that allowed threat actors to steal OAuth tokens used to connect to customers’ Salesforce environments, as the new “Icarus” extortion group publicly claims the attack.

The disclosure comes after cybersecurity firms Huntress and ReliaQuest detailed how attackers abused compromised Klue Battlecards integrations to steal Salesforce CRM data from multiple organizations.

In a statement published this week, Klue CEO Jason Smith confirmed that the company discovered unauthorized activity on June 12 affecting part of Klue’s integration infrastructure.

“On June 12, we identified unauthorized activity affecting a portion of Klue’s integration infrastructure. Since then, we’ve been working alongside trusted cybersecurity experts to understand what happened, support our customers, and restore the connections you rely on,” wrote Smith.

“Our investigation determined that an attacker gained access through a compromised legacy credential associated with an integration service. The attacker used that access to obtain OAuth tokens used to connect Klue with certain third-party platforms, including Salesforce, and subsequently accessed data within a number of connected customer environments.”

The company says there is currently no evidence that customer content stored directly within the Klue platform was impacted and that the incident was limited to third-party integrations.

Klue says it immediately revoked affected credentials and tokens, removed unauthorized code, disabled impacted integrations, launched an investigation, and notified law enforcement. The company also confirmed it engaged CrowdStrike to assist with the response.

ReliaQuest and Huntress found that the attackers used stolen OAuth credentials associated with Klue integrations to access customer Salesforce environments and conduct large-scale data theft.

ReliaQuest observed attackers generating OAuth tokens and using Python scripts to query Salesforce’s API for extended periods, as data was stolen.

Huntress later disclosed that its own Salesforce environment was affected by the Klue breach and that the stolen data included business contacts, sales communications, pricing information, and other records.

Icarus claims responsibility

While BleepingComputer and Huntress previously linked the incident to the Icarus extortion operation, the threat actors have now publicly claimed responsibility on their data leak site.

“As you’ve probably already heard, Klue.com has been impacted by us recently. A number of other companies’ Salesforce instances, which were partners to Klue, were exfiltrated,” reads the Icarus post.

The threat actors went on to pressure Klue and affected organizations to contact them through the Session messaging platform to prevent the leaking of stolen data.

The post comes after BleepingComputer previously reported that the attacks were linked to Icarus, after sources shared extortion emails sent to affected organizations. Huntress also independently connected the operation to Icarus through Session Messenger IDs used in the extortion emails and the group’s data leak site.

Since then, additional victims have disclosed that they were affected by the attacks, including Recorded Future, Tanium, Jamf, Sprout Social, Gong, and Insurity.

Almost all say the incident led to the theft of data from their Salesforce instances and did not affect their platforms, infrastructure, payment information, or internal systems.

Several organizations warned that the stolen business contact information could be used in follow-on phishing, social engineering, and extortion campaigns and urged customers to be vigilant.

Security teams log 54% of successful attacks and alert on just 14%. The rest move through your environment unseen.

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AI infrastructure startup Tensordyne has taped out its first commercial accelerator, with fabrication on TSMC’s 3nm process already underway.

Developed in collaboration with Juniper Networks and Broadcom, Tensordyne’s systems promise higher throughput and lower power consumption than GPUs. It claims to achieve this using an unorthodox approach to mathematics that uses logarithms – which you might recall from high school arithmetic – to make matrix multiplication heavy AI workloads less computationally intensive to run.

In conventional computing, addition is cheap, and multiplication is expensive. Logarithms flip this on its head. Using logs, multiplication essentially becomes an addition problem. a*b becomes log(a) + log(b). 

The trick is converting those values to logs and back again efficiently. There are a couple of ways of dealing with this. One of the easier options would have been to use a lookup table (LUT). However, Tensordyne cofounder Gilles Backhus tells El Reg that relying on LUTs would have been too large to be practical.

Instead, the company uses a heuristic, specifically the Mitchell approximation, to estimate log and antilog for each value. This is still an approximation and on its own introduces too much error to be tenable. To overcome this, Backhus tells us Tensordyne has implemented a section-wise correction mechanism in hardware that delivers accuracy equivalent to that of FP16. However, it’s worth noting that Napier will also support FP8 and 4-bit block floating data types.

In effect, Tensordyne claims to have built a chip in which the multiply accumulate (MAC) unit works without actually doing multiplication in the conventional sense. The result is a chip that delivers power efficiency significantly greater than what you’d see on modern GPUs. Or at least that’s the claim.

Tensordyne says its rack systems will spit out up to 17x more tokens per watt and achieve 13x higher throughput than Nvidia’s Blackwell systems.

Dissecting Napier

Tensordyne’s first commercial chip, Napier, boasts many of the same specs you’d have seen from a high-end GPU just a couple of years ago. 

The accelerator boasts a 300-watt nominal TDP, 144 GB of HBM3e spread across four stacks, 4.7 TB/s of memory bandwidth, and up to 2.1 petaFLOPS of dense FP8 performance. This makes it roughly comparable to Nvidia’s H200 accelerators announced in 2023, while using nearly 60 percent less power.

Having said that, max achieved FLOPS often fall far short of peak FLOPS, so take that comparison with a grain of salt. We won’t know how Napier actually compares to Nvidia or AMD’s latest generation of GPUs until it arrives next year.

Backhus tells us that Tensordyne is leaning heavily on the scalability of its accelerators rather than individual performance. Each chip features roughly a terabyte of interconnect bandwidth, allowing for rack-scale deployments of up to 72 accelerators per pod.

The TDN72

Tensordyne’s system, codenamed the TDN72, consists of eight air-cooled compute blades, each with a single 10-core Intel Xeon-D host CPU and nine Napier accelerators.

These chips are interconnected by a high-speed interconnect fabric topology reminiscent of the one used by Nvidia’s GB200 NVL72 rack systems.

Each chip connects to six proprietary fabric switch blades developed by Tensordyne’s networking partner Juniper, located at the back of the system, in an all-to-all fabric.

Despite some similarities to Nvidia’s NVL72 racks, Tensordyne’s TDN72 will be much smaller and won’t require liquid cooling, which should make it easier to deploy in older brownfield datacenters.

According to Backhus, up to four 30 kW TDN72 systems can be packed into an – admittedly large – 52U rack. That works out to 608 petaFLOPS in a 120 kW footprint, or about 1.68x more dense FP8 compute per rack than Nvidia’s GB200 NVL72. That doesn’t take into consideration the fact that Nvidia’s kit supports NVFP4 acceleration while Napier is limited to FP4 weights. But again, don’t read too much into that comparison. Peak FLOPS are not representative of real-world performance.

Tensordyne’s TDN72 launches next year, and it’ll be competing against Nvidia’s next-gen Vera Rubin and Vera Rubin Ultra systems, which will no doubt be a stiffer fight, especially when software compatibility is taken into consideration.

Software promises

Since building its first prototype silicon a few years ago, the company has gone to great lengths to keep its software platform as simple and easy for customers to deploy, as possible.

For example, the prototype lacked the error correction found in its Napier chips, and would have required users to use quantization-aware training to adapt their models to run accurately on the hardware – not exactly feasible for those looking to run trillion-parameter models.

The software has also matured such that the hardware’s compiler can convert existing models to run directly on its latest hardware, an approach we’ve seen from other chip startups like Tenstorrent.

For inference, Tensordyne has developed its own proprietary serving platform, as well as a runtime environment that Backhus says will allow customers to use their preferred inference servers, such as vLLM. PyTorch support is under development.

Before the chip has even shipped, the company is making some bold performance claims. Backhus expects the chips to deliver upwards of 1,000 tokens a second, and that’s without relying on multi-token prediction or other forms of speculative decoding to boost token generation.

Tensordyne’s platform has certainly attracted the attention of neocloud providers like Cirrascale and BlueSky Compute, both of which have expressed interest in deploying the company’s hardware when available.

But, as we’ve seen with AMD and others, software can make or break a chipmaker. With Napier slated for release in Q2 or Q3 of 2027, Tensordyne won’t have long to get things right. ®

Shibu Kaithalamattathil, a senior engineer at MSD, explores the day to day as an engineer in the biopharma space and having the opportunity to watch his son enter the industry.

Shibu Kaithalamattathil is a senior engineer at MSD Biotech in Dublin.

In this role, he oversees the day-to-day engineering activities that support manufacturing, “ensuring that equipment, processes and systems operate safely, reliably and in full compliance with site standards”, he tells SiliconRepublic.com.

Kaithalamattathil says that no two days feel alike in her job, which he puts down to the team and the culture on-site.

“You’re genuinely excited to go to work every morning,” he says.

Never was this truer, Kaithalamattathil says, than last year, when he had a “unique opportunity”.

“My son Alan joined MSD Biotech, Dublin as an intern and worked on-site alongside me,” he explains. “Alan is studying chemical engineering in college and to be able to work alongside him for that period of time was amazing, not just because of the feeling of pride I got knowing my son was following in my footsteps, but also the sense that he’s taking his first professional steps in what will be a hugely exciting and rewarding career.

“With the way science is advancing, I think it’s safe to say his day to day will eventually look very different to my own, but there’s so much excitement in that.”

What skills do you use on a daily basis?

One of the things I enjoy most about my role is that every day I have to use both technical and non-technical skills alike. My role is as much about dealing with machinery, systems and equipment as it is about dealing with people, so it’s a mix of very technical troubleshooting skills as well as communications, teamwork and project management.

And at the heart of it, the biggest skill I think is problem-solving, whether looking at equipment or looking at our ways of working, it’s about being able to adapt and solve any issues or challenges as they arise.

That is something I think Alan experienced first-hand during his internship as well. While at university, you’re so focused on the technical side of things with the science, the engineering and chemistry. Across STEM, softer skills can sometimes be an afterthought. But on a day-to-day basis, whatever area you end up specialising in, the skills that will come in handy are usually communication and problem-solving.

What is the hardest part of your working day?

The most challenging part of the day is dealing with the unexpected. It creates a sense of excitement and learning, but at the same time it is always a challenge to manage unexpected breakdowns or issues, all while ensuring that planned work is completed on time no matter what is going on.

That requires quick decisions and effective prioritisation, as well as a real passion for problem-solving. Whatever issue is in front of you, it’s really about just stepping back, looking at it holistically and then figuring out what the best way to fix or address it is. It’s about not just finding a solution, but making sure you’re finding the best solution.

Do you have any productivity tips that help you through the working day?

I start my day by taking a few minutes to prioritise my workload, focusing on key tasks and then I get working on the to-do list. Engineering roles can be fast-paced and unpredictable, so having a clear structure helps me stay focused and calm, even when challenges arise.

I tend to break tasks into smaller, manageable steps, which keeps me organised and makes it easier to maintain momentum throughout the day. I also make a point of taking short breaks to reset, especially during busy periods. Staying refreshed helps me think more clearly and safely, both are essential in a biotech environment. And finally, I’ve learned the value of leaning on the team.

When you first started this job, what were you most surprised to learn was important in the role?

I was struck by the importance of adaptability. Even with years of experience, I quickly learned that continuous learning is part of daily life here.

The facility is equipped with modern, cutting‑edge technology and the systems evolve regularly as the industry advances. Being open to new tools, new processes and new ideas has been just as important as any technical skill I brought with me. Having my son on-site with me, I tried to encourage those same habits and behaviours for him too as I really do think they make a difference. And it’s been brilliant to see him taking them on, both in his academic and professional development.

How has this role changed as this sector has grown and evolved?

The biopharmaceutical sector is expanding rapidly and with that growth has come significant technological advancement. My role has evolved from focusing mainly on hands-on engineering tasks to now also incorporating more data-driven decision-making and working with highly sophisticated equipment, which has been very exciting.

Automation, digital systems and advanced monitoring tools have become part of our daily operations, allowing us to work more efficiently while maintaining the highest standards of safety and quality. I’m also sure that by the time Alan finishes university and moves fully into the workforce, the role will have evolved even further, given the pace at which technology, automation and digital systems continue to develop across the sector.

However, although the tools and processes have evolved, what hasn’t changed is the purpose behind the work. We’re producing medicines that make a real difference to people’s health and you can really feel how much that sense of responsibility guides everything our team does.

What do you enjoy most about the job?

What I enjoy most is the atmosphere on-site. There’s a real sense of community at MSD Biotech, Dublin. People are friendly, supportive and proud of the work they do. It genuinely feels like a home away from home in a way and that makes a huge difference in an industry where teamwork and trust are so important.

Every day, I also get to work with colleagues who share the same commitment to quality and the same passion for improving patients’ lives. That always feels very powerful too.

Seeing Alan walk into the same site where I work and watching him experience the same warm, welcoming environment was such a proud moment. It just reinforced everything I love about this job, the strong culture, the sense of belonging and the meaningful work we do every day.

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• Intuitive new OS.
• Excellent contrast and picture quality.
• Massive number of art images.
• Anti-glare coating actually works.
• High refresh rate for gaming.

TIRED

• Monthly subscription required to access most artwork.

I still remember the moment I realized Samsung’s The Frame Pro 2026 is the best art television around. I loaded Van Gogh’s The Starry Night painting with its various shades of blue. The masterpiece came alive with texture and realism thanks to the contrast ratio and clear picture quality. I marched friends and family members down to my office to gaze in wonder.

Installing The Frame Pro is a bit of a process, though. I ended up watching a YouTube video for help. About an inch thin, this model sits mostly flush to the wall. Rather than connecting your streaming boxes directly to the TV, Samsung’s Wireless One Connect breakout box acts as a bridge. I connected my Xbox Series X and PC to the HDMI ports (there are four total) on the breakout box, which then connects to The Frame Pro using Wi-Fi 7 from across the room. Navigating The Frame Pro was also easy, thanks to the intuitive UI and the lightweight, long-lasting remote.

Free users have access to Samsung’s rotating catalog of 30 free images, but subscribers willing to pay $4.99 monthly will have access to 5,000 pieces of art. The Frame Pro 2026 has the widest variety of artwork, including hundreds of masterpieces, but I preferred Amazon’s Ember Artline “moving artwork” feature better.

At $2,000, The Frame Pro is the most expensive option on our list, and it’s worth its price. Even though most manufacturers, Samsung included, don’t list specs for their art TVs, The Frame Pro 2026 displayed artwork and photos with the best contrast and picture quality.

I was blown away by the picture quality for movies. When viewing Netflix’s Awake, which displays a lot of night scenes, I was able to still see all of the action. In comparison, the same scenes looked muddy and dull on the TCL NXTVISION and Amazon Ember Artline.

The 2026 model now supports high-fidelity gaming with a 240 Hz refresh rate when connected to a gaming computer (though it does lower the resolution). I played Crimson Desert and the main character—wearing a black suit of armor—moved realistically and responded quickly to my controller nudges.

For AI features, you have a few options. Samsung lets you pick from Alexa+ or Samsung’s Bixby to control the volume by voice or ask about which thrillers came out this month. You can also use Microsoft Copilot or Perplexity. However, the Amazon Ember Artline was the only art television that let me generate AI artwork by voice.

The Frame Pro 2026 is my top pick for art TVs because paintings looked the most realistic. If you want the best quality and are willing to pay a higher price, it’s a phenomenal choice.

Best on a Budget

WIRED

• More than half of CV writers say the work they receive now contains AI
• AI-generated text risks being impersonal and exaggerative
• But the tech is helping expression, creativity and storytelling

While workers continue to explore ways to adopt AI in their everyday workflows, recruiters are warning they should be doing so when writing their resumes, new research has claimed.

More than half (56%) say they often or always receive resumes that contain at least some AI-generated text – two-thirds (67%) also note an increase in AI-generated content.

Artificial intelligence is rapidly becoming part of everyday life, and that includes classrooms. Students are turning to tools like ChatGPT for homework, research, writing assistance, and even basic questions. But a growing number of educators, researchers, and policymakers are questioning whether introducing children to AI at such a young age could do more harm than good.

Norway appears to agree. The country has announced a near-total ban on generative AI tools for elementary school students, arguing that children need to develop fundamental reading, writing, and math skills without relying on AI. The move could become an early sign of a broader trend, especially as governments around the world take a tougher stance on children’s use of technology.

Why is Norway restricting AI in schools?

Norwegian Prime Minister Jonas Gahr Støre said the government is concerned that AI could cause younger students to skip important stages of learning. The administration argues that reading, writing, and mathematics should remain the primary focus during a child’s early education.

That said, Norway is not completely shutting the door on AI in education. Under the new guidance, students aged 6 to 13 should generally not use generative AI tools, while those between 14 and 16 may use them under teacher supervision. Students in upper secondary education, aged 17 to 19, will be taught how to use AI responsibly so they are better prepared for higher education and the workplace.

A recent study found that even short periods of AI-assisted work may reduce independent critical thinking. Participants who relied on AI assistance were significantly more likely to struggle or give up when that assistance was removed, suggesting that frequent reliance on AI may reduce persistence and independent thinking.

The study focused on adults, which raises an obvious question. If mature minds can become dependent on AI after only brief exposure, what happens when children with developing brains use these tools every day? That question is becoming increasingly difficult for educators and policymakers to ignore, and Norway’s new restrictions suggest some governments are no longer willing to wait for a definitive answer.

Are AI restrictions the next big policy trend?

Norway’s AI restrictions are part of a wider trend. The country has already banned smartphones in schools and has proposed tighter controls on children’s access to social media. Similar debates are taking place around the world as governments become increasingly willing to intervene when new technologies are seen as posing risks to young users.

Just a few years ago, the idea of restricting children’s access to social media platforms was viewed by many as unrealistic. Today, age-verification laws, smartphone bans, and social media restrictions are becoming increasingly common. AI could be heading down a similar path.