The consumer A/V industry keeps consolidating, and the headphone category is no longer watching from the cheap seats. Sony’s acquisition of Audeze made that clear in 2023, AXPONA changed ownership almost before the elevators at the Schaumburg Renaissance had recovered from the 2026 show, and now Fidelity Collective has acquired Westone Audio and Etymotic. That puts two of the most respected names in professional and enthusiast IEMs under one newly formed company, and it is another reminder that even niche audio brands with fiercely loyal followings are now very much in play.

Who is Fidelity Collective?

This is where the story gets more interesting.

Most recent A/V industry acquisitions have followed a familiar pattern: one established company, investment group, or brand owner buying or partnering with another established player. This one appears to be different. Fidelity Collective is not an old name with a deep catalog of legacy brands. It is a newly formed holding company that seems to have been created specifically to bring Westone Audio and Etymotic under one roof.

Fidelity Collective is led by CEO Sam Roney, known for his work with Dekoni Audio and Grell Audio, and COO Tal Kocen. The deal was finalized on Friday, May 15, 2026, with both Westone Audio and Etymotic now operating under their leadership.

That distinction matters. This is not simply another large A/V company adding a respected audio brand to the shelf. It is a new entity built around two very specific names in the IEM and earphone categories. That suggests a more targeted play, and one that could have real consequences for professional audio users, hearing-health customers, musicians, and personal audio enthusiasts who have followed these brands for decades.

What Westone Audio and Etymotic Bring To The Table

This strategic move opens a new chapter for Westone Audio and Etymotic, two brands with deep roots in in-ear audio, hearing protection, professional monitoring, and precision listening. Together, they represent decades of work in products used by touring musicians, audio professionals, hearing specialists, and serious listeners who care about what actually reaches their ears. Imagine that.

The new leadership team also brings direct familiarity with both brands, which matters. Tal Kocen previously worked with Westone Audio and Etymotic, while Gary Boyer will remain on board as EVP, providing some continuity as both companies move under the Fidelity Collective umbrella.

CEO Sam Roney also brings broader audio industry experience through his involvement with Dekoni Audio, Grell Audio, and Dark Matter Audio Labs. Combined, the leadership team appears to understand the history, product philosophies, and customer bases behind both Westone Audio and Etymotic. That does not guarantee success, but it is a better starting point than handing two specialist IEM brands to people who think “balanced armature” sounds like a yoga injury.

Westone Audio was founded in 1959 and has been a major influence in the development and manufacturing of custom in-ear monitors for musicians, with its background in hearing protection and acoustics helping shape products used on stage, in studios, and by serious listeners. 

Etymotic, founded in 1983, is known for its research-led approach to hearing and sound. They helped define the category for high-isolation, precision in-ear listening, with products developed from a foundation in auditory research, diagnostics, and hearing protection. Its ER4SR and XR series became a reference point for accurate in-ear sound, while its wider product range continues to serve musicians, professionals, and listeners who value clarity and faithful sound reproduction. Etymotic’s hearing protection products are also widely recognized for providing solutions for one of the biggest frustrations with traditional earplugs by maintaining clarity and balance while simply reducing volume.

The Fidelity Collective Umbrella

Under Fidelity Collective umbrella, Westone, and Etymotic will continue their research and product heritage. The company’s focus will be on maintaining the distinct identities and core values that made Westone Audio and Etymotic trusted names.

At the same time, the new group is expected to bring fresh energy, expanded R&D, renewed product development, and long-term investment into both brands and their passionate user base.

Fidelity Collective says the goal is not to abandon or reinvent what made the brands successful, but to build on their foundation with new momentum, modern innovation, and long-term vision across both professional and consumer audio categories.

“Westone Audio and Etymotic are brands with genuine history and credibility,” said Sam Roney, CEO of Fidelity Collective. “Tal and I share a vision of bringing startup-level energy to these epic legacy brands while fully respecting the heritage they’ve built over decades serving musicians, audio professionals, and hearing protection users.”

Tal Kocen, COO of Fidelity Collective, added: “For me, this is incredibly personal because these are brands I already know closely. There’s already a strong foundation here, and our role is to build on that with fresh ideas, modern product development, and long-term commitment to the communities around both brands.”

Fidelity Collective also confirmed that they will be investing in staffing, engineering, product development, and operational infrastructure as both brands move into this next phase, including the re-establishment of sales operations in Dallas and engineering and lab facilities in Chicago.

Both brands will continue serving existing users, including professional musicians, stage performers, engineers, hearing-conscious listeners, and music enthusiasts, while expanding into new product categories and market opportunities.

Further product announcements from both Westone Audio and Etymotic are expected in the coming months of 2026 and beyond.

The Bottom Line 

Fidelity Collective’s acquisition of Westone Audio and Etymotic matters because it gives a newly formed company two established IEM brands at a time when wired earphones are clearly gaining momentum again.

Recent CanJam shows in New York, Singapore, and Dubai made that obvious, with brands like Noble, Shure, DUNU, Astell&Kern, Meze Audio, and Sennheiser fighting for the same serious listener. Westone brings professional IEM credibility, while Etymotic brings accuracy, isolation, and hearing-focused design.

What is missing are the details: new products, updated lineups, and how much engineering or distribution overlap we will actually see. But the intent is clear. Fidelity Collective is not entering the IEM market quietly. It now has two respected names, and the rest of the category should be paying attention.

Pricing & Availability

While we wait to see what new initiatives and products result from these new company relationships, here are some currently available products from Westone and Etymotic. 

Westone Audio Earphones

Etymotic Earphones

Related Reading:

Amgen’s Helena Mulvihill explores how organisations in 2026 are navigating issues of environment, health and safety in the workplace.

“I often hear EHS (environment, health and safety) described as a broad discipline, but it really comes down to protecting people while supporting safe and reliable operations,” explained Helena Mulvihill, an EHS manager at biotech Amgen. 

She told SiliconRepublic.com, “It brings together environmental compliance, occupational health and safety, and in practice connects every part of the site. That means working closely with operations and support teams, often across multiple departments in the same day.” 

Her work largely involves the implementation of EHS management systems such as risk assessments, incident management, training, auditing and performance metrics; a big part of the role is also communication, making sure expectations are clear and that teams feel supported in applying EHS principles.

She said, “There isn’t really a typical day, which is something I enjoy. While I can plan my week, priorities often shift depending on operational needs. That balance between planned and reactive work keeps things varied and means I need to stay adaptable.”

How important is it to involve everyone in EHS and does that work in practice?

Involving everyone is essential because EHS cannot operate in isolation. It must be embedded across all levels of the organisation, from leadership to the people carrying out day-to-day tasks. I’ve found that the colleagues closest to the work have the clearest understanding of how tasks are actually performed. They’re making real-time decisions, so their input is critical.

While EHS teams provide guidance and structure, it’s important that individuals take ownership of applying those principles in practice. That’s what makes procedures meaningful.

I build that through collaboration and engagement. I spend time in operational areas, listen to feedback and learn about challenges from different perspectives. When people feel involved and see the reasoning behind decisions, EHS becomes part of how work is done rather than something separate.

What does a strong EHS culture feel like when you’re part of it?

You really notice it in the everyday decisions people make. Safety and operational impact are considered as part of the task, rather than something that’s addressed afterwards. It also comes down to trust. People need to feel comfortable raising concerns, asking questions or even stopping work if something doesn’t seem right. That openness is what allows issues to be picked up and addressed early.

When that culture is in place, you see people take responsibility, look out for one another and think about the wider impact of what they’re doing. Over time, that consistency makes a real difference to both safety performance and how effectively the site operates.

How can employees support EHS in their day-to-day roles, even if it’s not their main focus?

Supporting EHS often comes down to simple, consistent behaviours. One approach used at Amgen is ‘Take Five’, which encourages people to pause before starting a task and assess the situation. That might mean reviewing the environment, thinking through the task, identifying potential risks and choosing the safest way to complete the work. It also involves putting the right controls in place and communicating clearly with anyone who could be affected.

I’ve seen how effective that can be in practice. It helps people stay aware of their surroundings and think about the impact of their actions. Even if EHS isn’t their main role, those small actions make a real difference in reducing risk and supporting a safer workplace.

How does the work you do in EHS contribute to wider organisational goals at Amgen?

My role focuses on implementing the EHS management system onsite, which supports wider organisational goals by helping the site operate safely, consistently and in line with regulatory expectations. A key part of the role is anticipating and controlling risks before they lead to incidents, while working closely with different teams to identify and implement improvements effectively. Strengthening the EHS management system, while helping to build an inclusive, high-performing safety culture, supports reliable manufacturing operations and continuous improvement. 

What kind of opportunities are there for people working in this field?

One of the most appealing things about EHS is the range of opportunities it offers. You have the chance to specialise in areas like safety, environmental compliance, industrial hygiene or process safety, depending on where your interests lie. It also gives you exposure to various parts of the business from manufacturing and laboratory environments to supply chain and supporting functions. That helps build a broader understanding of how everything connects, and over time, many people move between these areas to develop a well-rounded skill set. You also get the chance to collaborate with global colleagues and learn from other sites, which brings fresh perspectives and helps you continue developing over time.

What skills are best suited to professionals in this space?

I’ve come to realise that adaptability and patience are core skills because priorities can change quickly and you’re often responding to different situations. Being able to adjust and stay focused is key. Communication is just as important. A large part of the role involves listening, asking questions and understanding how work is conducted in practice so risks can be identified early. It also means explaining things clearly, so expectations are aligned.

Curiosity and initiative are also central. Taking the time to engage with people, understand processes and build relationships makes a real difference. Combined with a willingness to keep learning, these skills help you develop in a field that is constantly evolving.

Don’t miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic’s digest of need-to-know sci-tech news.

In December of last year, Microsoft told thousands of its engineers, product managers and designers that they could use Claude Code, Anthropic’s command-line coding agent, on the company dime.

By spring, the tool had spread well beyond engineering: into the kind of non-technical roles that, in earlier waves of enterprise software, would have waited years for a seat. Inside Microsoft, the rollout was framed as a learning exercise. Outside it, the surface signal was simpler.

The world’s largest software company, the one with its own foundation models and its own coding assistant, had just paid a competitor to put a rival product in front of its workforce.

Six months later, that experiment is being wound down. According to reporting in Windows Central and other outlets following The Verge’s original scoop, Microsoft is cancelling most direct Claude Code licences inside its Experiences and Devices group, the division that builds Windows, Microsoft 365, Outlook, Teams and Surface.

Affected engineers have been told to migrate to GitHub Copilot CLI by 30 June, the last day of Microsoft’s fiscal year. The official reason is toolchain unification. The unofficial reason is in the calendar.

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The Claude pullback is the most credible signal yet that the unit economics of enterprise AI coding do not, at current token prices, work. Not because the tools are bad. The opposite: they are good enough that engineers use them constantly, and the constant use is what breaks the maths.

The clearest evidence is at Uber, which is not Microsoft and does not have Microsoft’s financial cushion. Praveen Neppalli Naga, Uber’s chief technology officer, told The Information in April that the company had burned through its entire planned 2026 AI coding budget in four months.

By March, Naga’s own figures had Claude Code use jumping from 32 per cent to 84 per cent of his roughly 5,000-engineer organisation. Individual engineers were spending between $500 and $2,000 a month on tokens. Around 70 per cent of code committed at Uber now originates with AI, and on the order of one in ten live backend updates is shipped by an agent with no human in the loop.

“I’m back to the drawing board,” Naga said, “because the budget I thought I would need is blown away already.”

That sentence is the whole story in miniature. The forecast was wrong because the variable being forecast, token consumption, behaves nothing like the licences and seats that finance teams know how to model. A traditional enterprise software deal is denominated in users.

A token-priced deal is denominated in how much the model has to think. Agentic coding makes the model think a lot. Sessions run for hours, spawn parallel threads and generate volumes of context that bear no resemblance to the autocomplete interactions that shaped the original pricing structure.

We have been tracking this fracture for months. In November, GitHub paused new Copilot Pro and Pro+ sign-ups because the agentic workloads of paying customers were generating costs that exceeded their monthly plan price.

Cost structures built for lightweight assistance, the company conceded, no longer held.

This is not an Uber problem or a Microsoft problem. It is an industry condition. Bryan Catanzaro, vice-president of applied deep learning at Nvidia, told Axios in April that, for his team, the cost of compute is now far beyond the cost of the employees using it.

This is the chip company saying it. Fortune followed in May with reporting that token-based AI tooling, when used heavily, can cost more per task than the human engineer it was supposed to augment.

A 2024 MIT analysis circulated widely in finance circles since then suggests that, on current pricing, AI automation pencils out as cheaper than human labour for roughly a quarter of the jobs people thought it would replace.

Set that against the spend forecasts. Gartner expects worldwide AI spending to reach $2.5 trillion this year, up 69 per cent on 2025.

The same firm now places generative AI squarely in what it calls the trough of disillusionment, predicting in a May press release that 25 per cent of planned 2026 AI budget will slip into 2027 as proofs of concept die in the procurement pipeline.

A separate Gartner read from April found that only 28 per cent of AI infrastructure projects fully deliver against their business case. That is not the curve of a technology going through an awkward adolescence. That is the curve of a market repricing itself.

Microsoft’s retreat lands inside this repricing, and not by accident. There are two ways to read the move. The first is the one Microsoft has briefed: that Copilot CLI is the strategic destination, that engineers will continue to have access to Claude models inside Copilot, and that the company simply wants a product it can shape directly with GitHub. That story is true.

It is also a story that Microsoft could have told at any point in the past six months and chose not to. What changed was not the strategic logic. What changed was the bill.

The second reading is harder to discount. Microsoft is uniquely positioned to know what enterprise-scale Claude usage actually costs, because its own engineers were the heaviest users outside Anthropic’s customer base. Inside Experiences and Devices, Claude Code had become, by several accounts, the preferred tool.

If the maths had improved with scale, this would be the moment Microsoft locked in a multi-year deal at favourable terms. Instead, it is unwinding the experiment in a window that conveniently closes the books on a fiscal year.

When the company with the most leverage in the room walks away from a vendor whose product its own staff prefer, the signal is not about preference.

Whether this constitutes a bubble depends on definitions. Token-level pricing will fall, as it has fallen at roughly a factor of ten every eighteen months for the past three years. The more interesting question is whether per-task token consumption falls faster than per-token cost.

The evidence so far runs the other way. Each generation of agentic system, by design, consumes more tokens per unit of work, because it reasons longer, plans more elaborately and verifies itself against the world.

Anthropic’s own infrastructure team has spoken publicly about reasoning workloads generating order-of-magnitude more compute per query than chat. That is the bet baked into the next twelve months of model releases. It is also the bet that put Uber back at the drawing board.

There is a worked example in TNW’s own coverage. In April, Anthropic banned a popular open-source agentic framework called OpenClaw from running on consumer Claude subscriptions, after discovering that single instances could chew through the equivalent of $1,000 to $5,000 in API costs in a day of autonomous operation. The framework was running on a $200-a-month Max plan.

The economic transfer was so blatant that Anthropic had to write a new clause into its terms of service. Multiply that pattern across a Fortune 500 engineering organisation, and you have the Uber budget memo.

The counterargument is real and worth stating. The cost of a working AI coding agent compared to the cost of an additional senior engineer is, even at current prices, often favourable on a per-feature basis. The productivity uplift is documented; the substitution is happening. What is breaking is not the value proposition.

It is the procurement model. Companies that signed up for a productivity tool are discovering they signed up for a metered utility, and the meter runs when nobody is looking. The fix may be straightforward: capped budgets per engineer, tiered access for high-leverage roles, agent runtime quotas.

Many of the larger buyers are already there. But the implication is that the era of “give every employee a Claude Code seat” is closing, and what replaces it will look more like AWS billing than like Office licences.

That is what Microsoft’s quiet email to its Windows and Surface teams really announces. Not the end of AI coding. Not even the end of Anthropic at Microsoft, given that Claude models will continue to be reachable through Copilot CLI.

It announces the end of the experimental phase, the phase in which the world’s largest software companies were willing to absorb arbitrary token costs in exchange for learning. The learning is done.

What comes next is the harder part. Enterprises will keep buying AI coding tools, because the productivity is real and the competitive pressure is unforgiving. But they will buy them the way they buy electricity, with usage caps, with shadow meters, with a finance team in the room.

Somewhere in a Microsoft conference room earlier this spring, someone looked at a Claude Code invoice and did the arithmetic against a Copilot CLI roadmap, and made a decision.

The same arithmetic is now being done in every CFO’s office that bought into the December 2025 rollout. The retreat will not be loud. It will be a series of fiscal-year-end emails, sent on a deadline nobody noticed until the budget was already gone.

Pope Leo XIV has taken a stronger stand against AI. On Monday, Leo released his first papal encyclical — an almost 400-year-old tradition in which the Catholic Church shares its perspective on an issue. In this case, over about 42,300 words (in the English version), the Pope warned of “the misconception of equating this type of ‘intelligence’ with that of human beings.”

“These systems merely imitate certain functions of human intelligence. In doing so, they often surpass human intelligence in speed and computational capacity, offering tangible benefits across many fields,” Pope Leo stated.

He continued: “So-called artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate language, behavior and analytical skills, or even simulate empathy and understanding, but they do not understand what they produce, for they lack the affective, relational and spiritual perspective through which human beings grow in wisdom.”

Notably, the Pontiff presented the remarks alongside Anthropic co-founder Christopher Olah.

The Pope stated that it’s necessary to “establish adequate regulatory tools capable of upholding justice and curbing the distorting effects of technological power.” He emphasized that wealth is already concentrated in the hands of very few people and that it’s up to governments to ensure it doesn’t become even more so. In that vein, he added that leaders must ensure that humans, not AI, make all decisions related to weapons in the future.

He also called for “an educational alliance for the digital age” that encourages teaching young people to think critically about AI, to guard against “apathy for seeking the truth.” Regulations should also protect young people against “violent or degrading” AI-generated content, along with grooming and sexual exploitation.

Leo warned that such technology — and any profits that come with it — shouldn’t be used to justify systematic job loss. As such, he encouraged retraining and employment protections for workers whose jobs are at risk due to AI.

Pope Leo’s remarks weren’t made against AI as a whole, stating that it shouldn’t be seen “as a force antagonistic to humanity.” If carefully managed, he said, it could “open up a horizon extending in all directions.” In February, the Vatican teamed up with language service provider Translated to offer AI-powered live translations to Holy Mass attendees.

This webinar explores how AI‑based virtual sensors can be used to estimate signals that are difficult or costly to measure, such as battery state of charge (SOC) in Battery Management Systems. Using a practical example, the session demonstrates how AI models can be integrated into system‑level design and validated against performance, resource, and deployment constraints. 

The workflow shows how to design, verify, compress, and deploy AI‑based virtual sensors to embedded processors within a single environment. 

You will learn how to: 

• Integrate AI models into Simulink® for system‑level simulation and verification 

• Apply formal verification to assess neural network behavior 

• Optimize models for memory footprint and execution speed 

• Generate and profile library‑free C code for embedded deployment 

• Evaluate design tradeoffs across accuracy, performance, and deployment targets 

Click ‘Watch Now’ to explore this webinar.

Processor design over the last few decades has moved toward RISC processors that aim to implement a few simple operations very efficiently. For a while, though, the trend was toward ever-more-complex CISC designs that let programmers implement complex behaviors using as few instructions as possible. Few processors took this approach further than the Intel iAPX432. This hyper-CISC processor was a commercial failure, largely due to its notoriously poor performance, but [MarkTheQuasiEngineer]’s benchmark suggests that this notoriety wasn’t totally deserved.

The first step before running a benchmark was to build a computer around the processor. The iAPX432 was implemented in three chips, two of which acted as the general data processor (GDP), and one of which handled input and output. [Mark] built an SBC (design and code here) that houses the two GDP chips and an FPGA for I/O. The 432 did have a well-deserved reputation for efficiently turning electricity into heat, and the original voltage regulator failed rather quickly.

The 432 was designed to use machine code which was almost a high-level language, with built-in object-oriented programming. It had over 200 operators, some of which implemented complex object-oriented operations, and a wide variety of data types, but it had no directly-accessible general-purpose registers. In addition to the lack of registers, it also had a very complex addressing system, allowing both direct and indirect addressing. For better performance, [Mark] used direct addressing.

For the benchmark, [Mark] implemented the Spigot algorithm to calculate the value of Pi. The results were somewhat surprising: calculating 2048 digits, it beat his previous retro-processor benchmarks; an Intel 8086 running the same algorithm took 2.5 times as long. Based on the results of this hand-written code, [Mark] speculates that the 432’s poor performance had more to do with poor compiler optimization than with the fundamental design.

We’ve covered some of the history of this troubled chip before. For a similarly ambitious but ill-fated Intel project, check out the history of Itanium.

I recently had the opportunity to test out a wearable from Bee, the AI wrist gadget that Amazon acquired last year and has since updated with a number of new features.

Like other AI wearables, Bee is designed as a kind personal assistant: it records, transcribes, and summarizes the user’s conversations throughout the day, providing an ongoing note-taking capability that’s useful if you’re forgetful or just want to be more organized about your life. If you sync it with your calendar, it can also send you alerts and reminders about things you’re supposed to do throughout the day.

TechCrunch has written about Bee before, and the way it works is pretty simple: the user powers it up, puts it on, syncs it with the Bee mobile app, and enters some basic personal information. Bee has a built-in recorder that can be turned on and off by clicking the wearable’s button. When Bee is recording, a green light flashes. When it’s not, that green light goes off. After a conversation has been recorded, the app will create an automated summary that is easy to read, as well as an entire transcription of the conversation.

Your mileage may vary on how exciting (or not) this whole conceit is. The problem for me is that I am something of a privacy enthusiast. In a world where the average person is beset from all sides by constant digital surveillance, I appreciate any opportunity I can get to not be recorded. Therefore, the idea of walking around with an eavesdropping gizmo strapped to my wrist 24/7 was not particularly appealing.

Yet, even I have to admit that — in the right context — Bee could have a lot of potential to help organize your life.

Bee really comes through in the context of professional engagements. If your day is full of meetings and you have trouble keeping it all straight, Bee could be a moderately competent assistant.

During a business-related phone call this week, I activated Bee after getting confirmation that I could record our meeting. Afterward, the app faithfully regurgitated a summary of the conversation, helpfully breaking down each segment of our talk so that I could review it later without having to re-listen to our entire conversation. This was undeniably helpful, although it should be noted that this isn’t something that’s markedly different than those offered by other transcription services, like Otter or Granola and others, which also offer transcriptions and auto-generated summaries.

That said, you could envision a situation in which a professional who has to navigate between various meetings throughout the day would be well-served by this device. You could just keep Bee running throughout the day and, later, review the conversation summaries for anything you’re not clear about.

Bee does a relatively good job at summarizing conversations, but the actual transcripts offered by the wearable can be a bit of a mess. Previous critics have noted that you usually have to manually enter the names of other speakers, as Bee doesn’t always know who is talking. During my conversation, I noticed that it had also omitted certain sections of our chat — nothing huge, but it wasn’t a complete account of everything that had been said.

I also took Bee to my semi-weekly movie night with my friends and left it running throughout the night. Given the fact that we watched Reservoir Dogs, I was mildly afraid that the wearable would mistake all of the vulgar carnage for real-life bloodshed and potentially trigger some sort of internal alarm. However, Bee knew — basically — what was happening. The wearable figured out that we were watching a movie and, in the summary of events afterward, the wearable labeled the conversation “Tarantino Film Scene Analysis.”

While Bee shows early promise as a professional tool, I would not want this thing recording me in my personal life. Weirdly enough, Bee has largely been marketed as a product for personal use. To be comfortable with that, you have to be comfortable with Bee having access to a majority of both your offline and digital life.

Indeed, to work well, Bee needs expansive mobile permissions — including access to your location, photos, phone contacts, calendar, and mobile notifications. You can also share your health data with it — should you, for whatever reason, want it to know about your sleep patterns or your resting heart rate.

The large accumulation of data Bee collects is stored in the cloud, which — again, for the digital privacy enthusiast — presents its own concerns. In a message to tech YouTuber Becca Farsace, Bee apparently unveiled a demo of the device running entirely locally. Were the company able to produce such a device, I would be thoroughly impressed — and might even consider buying one. That said, Amazon hasn’t offered any update on those plans.

As for Bee’s digital privacy protections, the company says that it offers encryption to protect user data — both at rest and in-transit. In its privacy policy, the company states that it has “implemented technical and organizational security measures designed to protect the security of any personal information” that the company processes. Bee also claims that it undergoes “rigorous third-party security audits” and employs continuous security monitoring. That all sounds quite good, although it’s worth noting that Amazon — like many large tech companies — has been subject to the occasional data security issue or two (not exactly surprising for a company that governs as much of the global cloud environment as it does, but still).

In short, Bee is a curious piece of hardware that, given some time and some tweaking, could have some promising professional applications further down the road. As a digital assistant for your personal life, however, it might prove to be a little too invasive for some users.

Offbeat

A French engineer has declared war on AWS, Google and Microsoft using AI-generated sea shanties, satirical poetry, and a multilingual protest campaign

A French SRE has given Amazon, Google, and Microsoft until September to fix cloud lock-in or face an endless barrage of AI-generated protest songs, satirical poetry, and Finnish polka.

Amine Raiti, an infrastructure architect and SRE currently working at a European Central Bank-regulated financial institution, has launched what may be the least conventional anti-cloud campaign in enterprise IT history: a multilingual pressure operation called “Operation Dindon,” complete with satirical poetry, orchestral music, K-pop, and a fictional turkey trapped in cloud dependency.

His demands are fairly simple: let companies cancel multi-year cloud commitments when business tanks, stop charging eye-watering egress fees to move customer data around, and make it possible to leave proprietary cloud services without detonating the IT budget.

Speaking to The Register, Raiti claims one AWS NAT Gateway setup costs roughly €6,700 ($7,777) annually for functionality that Linux admins have been handling with iptables since the late 1990s. He also points to managed Kubernetes pricing he says can exceed €14,000 ($16,251) a year.

Complaints about hyperscaler pricing usually stay confined to conversations between infrastructure teams, the occasional furious LinkedIn post, regulators and Reg readers. 

Raiti took a slightly different approach, producing a 14-part satirical series called The Legend of Dindon, centered around a fictional turkey who locks himself into cloud dependency and cannot escape, with each episode targeting a different cloud pricing or lock-in practice.

Episodes include The Managed Mirage, The Highway to Hell (The AWS NAT Gateway Autopsy), and The Turkey Who Plucked Himself in the Cloud, proving that cloud resentment has finally evolved into performance art.

From there, the campaign evolves from LinkedIn storytelling into a formal public ultimatum aimed directly at the hyperscalers.

Earlier this month, Raiti published what he calls an “Iron Ultimatum” in 11 languages directed at the three hyperscalers. If they agree to meaningful reforms, he says he will publish a celebratory “Diwan” praising their wisdom. If not, the AI-generated campaign continues indefinitely.

According to Raiti, Operation Dindon now includes 50 AI-generated songs spanning opera, gospel, K-pop, sea shanties, Finnish polka, Raï, and Chopin nocturnes, all allegedly produced in around two minutes per track for less than €50 a month.

Raiti says the idea for Operation Dindon came from his time in infrastructure leadership roles at a French adtech company. He says the business was tied to multi-year cloud commitments that continued even as revenues fell and staff were laid off.

Raiti does not directly accuse the cloud providers of causing the layoffs and describes the account as his own view of events. But he says that watching cloud costs continue to tick along while jobs disappeared was the point when vendor lock-in stopped sounding like an abstract IT problem.

The hyperscalers haven’t publicly responded. There are still several months remaining before the September deadline, giving the industry plenty of time to prepare for the possibility that the next phase of cloud criticism may arrive in the form of AI-generated sea shanties about vendor lock-in. ®