There’s a lot for Mark Zuckerberg to cover at this year’s keynote.

New and updated smart glasses

‘Phoenix’ Mixed Reality headset

Meta (via UploadVR)

Avatars and the metaverse

AI and developers

The BlackBerry-like phone also got a spec bump and an impending price hike.

Availability

Clicks

• Russia’s Scientific and Production Center Ushkuynik says ten disassembled Skorlupa hulls fit in one GAZelle van
• Each hull can be assembled in an estimated four hours (by Russian estimates) using a cordless screwdriver and can travel up to 200 km while carrying up to 250 kg of payloads
• The Skorlupa comes with up to four communication modules and can carry up to four fiber-optic drones, allowing it to serve as both a mothership for attack or recon drones and a one-way attack craft

Russia’s Scientific and Production Center Ushkuynik has released new details on Skorlupa, a light uncrewed surface vessel whose headline feature isn’t speed, stealth, or sensors.

According to www1.ru, company CEO Alexey Chadayev says ten of the boats fit into the cargo bed of a single GAZelle light van when broken down, and that one hull goes together in about four hours with an ordinary screwdriver.

Sony’s all-new show, Family Full House With Rohit Sharma, is set to go on floors this Saturday, September 19, 2026. Indian cricket star Sharma, best known for his three ODI double centuries and leading India to the 2024 T20 World Cup title, is all set for yet another debut – this time, off the field.

The date is special for Rohit himself, as it was the same date when he made his T20I debut. This time, though, fans will be seeing Rohit off the field in his quirky, outspoken “Shana” avatar. He’s well known for his cheeky stump-cam remarks, which have gone viral on multiple occasions.

Sony Music Entertainment and Universal Music Group (UMG) are suing AI music generator Suno for allegedly infringing on their copyright with its newest v6 models, Variety reports. The claim challenges the story Suno has generally told about its latest AI models, which are the first it’s released since signing licensing deals with Warner Music Group and BMG.

While Suno used licensed material to create the v6 lineup, in their lawsuit (obtained by Music Business Worldwide), Sony Music and UMG specifically take issue with the company’s public acknowledgement that the models were also trained on “users’ ‘interactions’ with Suno’s service,” which they take to mean “the outputs of, and preference signals derived from, prior models that Suno built by copying Plaintiffs’ recordings without authorization.” Under that understanding, both companies claim Suno could be responsible for infringing on the copyright of at least 60,202 sound recordings. That leaves it liable for up to $9 billion in damages under US copyright law, plus up to $2,500 for each time Suno circumvented YouTube’s anti-downloading tech to scrape songs, according to MusicBusinessWorldwide.

Naturally, the company disagrees with Sony Music and UMG. “These claims remain fundamentally flawed on both the facts and the law,” the company said in a statement to Engadget, while reaffirming that “Suno exists so that more people can make new music.”

“Over the past two years, we have doubled down on this goal, launching v6 in partnership with WMG, BMG, and Believe,” the company continued. “v6 was trained on content licensed from our partners, interactions including creations and preference signals from our community, and the accumulated learnings from our team. We are excited for a future where AI and the music industry continue to strengthen one another and build entirely new product experiences for artists, fans and the broader music community.”

This new lawsuit builds on Sony Music, UMG and WMG’s previous suit against the company, and a July 2026 hack of Suno’s data that revealed the AI company scraped millions of songs and lyrics from platforms like YouTube Music, Deezer and Genius to train its earlier models. In the past, Suno has justified scraping music to train AI as falling under the fair use doctrine. Alongside the release of its v6 models, though, the company ended support for its older models, which at least suggests it thinks offering a product trained on licensed material is more palatable to critics. If a judge is swayed by record companies’ understanding of how Suno trained its models, that might not be enough.

The research from the Global Undergraduate Awards highlighted the concerns held by undergraduate students as they prepare to enter the workforce.

According to new research published by the Global Undergraduate Awards (GUA), during the announcement of the undergraduate winners for 2026, more than half of students who took part in the report regard AI as a significant concern. 

Data was collected from 400 globally diverse undergraduate students across more than 200 universities in nearly 100 countries, from 8-15 June.

55pc of participating undergraduate students cited AI as a concern this year, a figure which rose from 48pc in 2025, moving it from fifth to second place in global rankings of concerns. The report noted that it was the only issue in the top five to rise, even as the overall field of concerns held broadly steady.

The fears around artificial intelligence were second only to social and economic inequality and came ahead of the climate crisis, mental health and environmental issues. Much of the fear was related to concerns around job loss or destruction. 

Commenting on the results report, Jim Barry, the chair of the GUA, said: “The findings clearly show that AI is rising up the agenda as a key area of concern for undergraduates globally. 

“This is something that policymakers need to take note of. The central focus is the job market post-graduation and what sort of impact AI is going to have on career prospects for many. 

“There is a palpable concern about the prospect of jobs destruction. The fact that AI has accelerated in our research findings from fifth to second place in just one year is a tangible demonstration of how quickly it has become a significant issue for students as they look to the future.”

While the changing rankings highlight the growing prominence of AI alongside the longstanding social and environmental challenges facing the next generation, Barry is of the opinion that it is concerning to see other issues fall somewhat to the wayside. 

He explained: “While climate change remains firmly in the top three concerns, it is worrying to see it fall in the rankings as its impacts become increasingly visible and significant. It highlights the challenge of keeping climate change to the forefront as other issues compete for attention and the societal and economic changes required are increasingly weaponised politically.”

Worldwide worry

The GUA report suggests that for students, artificial intelligence is no longer a distant or theoretical concept, rather, it is ingrained in how people study, research and think about their future careers. 

The research said: “There are huge opportunities that come with it, but also a lot of uncertainty about what its rapid development will mean for this generation.”

The GUA’s research comes at a time when there is increasing worldwide concern about the impact the advancement of artificial intelligence is having – particularly in relation to how it might damage career opportunities for both new and established professionals.

SiliconRepublic.com recently spoke to Pluralsight’s Beckey Woodard Cole about the growing issue of AI in the workplace and how it is disassembling the traditional career ladder. 

Earlier in the month, global talent platform Andela released a report which found that in a working landscape being transformed daily by AI, 53pc of AI job postings are asking for skills that don’t match the listed job title, highlighting a disconnect between organisations, recruiters and jobseekers.

Additional research from Microsoft Ireland, via the 2026 Work Trend Index, also found that many Irish employees are considering new career opportunities as AI reshapes the environment. 

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The wireless earbud industry spent the better part of a decade convincing consumers that progress meant sealing their ear canals more effectively, adding increasingly aggressive active noise cancellation and pretending the outside world could safely be placed on mute.

Apparently, a growing number of listeners would like to hear the bus coming.

New market data from Omdia, the global technology research firm owned by Informa TechTarget, shows that open wireless stereo (OWS) products are moving in the opposite direction from conventional true wireless earbuds. Global TWS (aka regular wireless earbuds) shipments slipped 0.7% year over year to 82.1 million units in Q2 2026, the category’s first annual decline since Q2 2023. Conventional in-ear and semi-in-ear TWS declined 2%, while open-ear shipments grew 12% to 11.1 million units. 

Open-ear products now represent 13.5% of global TWS shipments, up from 12% one year ago. That is still a minority of the market, but it is becoming far too large for major headphone brands to treat as a fitness niche populated exclusively by runners who refuse to stop at intersections.

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Clip-On Earbuds Are Driving the Growth

The most revealing number may be the form factor.

Omdia says clip-on models accounted for 61% of OWS shipments during Q2, compared with 39% for ear-hook designs. Clip-ons increasingly blur the line between wearable technology and fashion accessory, while ear hooks remain particularly attractive for sports and activities where staying attached to the listener is generally considered useful. 

Price growth is even more striking. The $100 to $199 segment jumped 253% year over year, driven in part by established brands including Huawei, Shokz and OPPO. Below $50, shipments exploded 323%, demonstrating that open-ear audio is spreading in both directions rather than becoming another premium category with a $299 entrance fee and a velvet rope. 

Omdia expects annual OWS shipments to climb from 43.9 million units in 2026 to 90.5 million by 2030, when open-ear models could represent nearly one in five TWS shipments. 

That is not a fad. It is an adjacent market becoming a substantial one.

Why Now?

The mistake would be interpreting these numbers as consumers suddenly rejecting conventional earbuds. They are not. Sealed TWS remains vastly larger, and ANC still makes considerably more sense on airplanes, trains and anywhere else where situational awareness mostly means hearing somebody else’s child watch YouTube without headphones.

Open-ear audio solves a different set of problems.

Long-term comfort matters to people who dislike having silicone tips inserted for hours. Runners and cyclists need environmental awareness. Office users may need to hear coworkers while listening to music, and parents generally appreciate being able to detect whatever object has just broken in the next room.

Omdia Research Director Jason Low expects vendors to focus increasingly on fitness, commuting and office productivity, while adding smarter ecosystem and AI features. Sound quality remains the harder engineering problem because an open design cannot exploit the acoustic seal that helps conventional earbuds produce deeper bass and greater isolation. 

That explains why the category is suddenly attracting considerably more serious engineering.

The Open-Ear Models Defining the Market

Bose made its intentions very clear this morning with the new $199 Sport Open Earbuds and $299 Ultra Open Earbuds 2nd Gen. The Sport model targets workouts with an IP54 cuff design, while the Ultra adds deeper bass, higher output, improved calling and Cinema Mode. Bose is no longer treating open-ear as one experimental SKU hiding in the catalog. 

Shokz OpenDots ONE ($199.95) sit almost directly in the segment where Omdia is seeing explosive growth. Their clip-on design combines 11.8mm drivers, Dolby Audio, IP54 protection and up to 10 hours of playback, with 40 hours available from the wireless charging case. Shokz is particularly noteworthy because Omdia specifically identifies the company among the brands driving growth in the $100 to $199 tier. 

Sony has gone more premium with the $229.99 LinkBuds Clip, which we reviewed earlier this year. Their strengths were comfort, situational awareness and useful listening modes rather than outright fidelity; our testing also exposed the fundamental challenge facing every manufacturer in this space — open-ear convenience still comes with compromises in bass extension and resolution. 

At the other end, the $99 CMF Clip Pro demonstrates how quickly pricing pressure is arriving. LDAC, multipoint, a 10-hour battery and IP54 protection are now available below $100, which should make companies charging two or three times as much increasingly uncomfortable unless the audible difference justifies it. 

The Bottom Line

Open-ear earbuds are not replacing conventional TWS. They do not need to.

The market is splitting according to use case. Sealed earbuds remain the better option when isolation, ANC and maximum bass performance matter. Open-ear designs increasingly make more sense when comfort, awareness and all-day wear take priority.

The important change is that consumers no longer have to accept terrible sound or awkward hardware to make that trade. Bose, Shokz, Sony and a rapidly expanding group of competitors are spending real engineering money trying to close the performance gap, while lower-cost brands are attacking the category from underneath.

Omdia’s numbers suggest consumers have noticed.

After a decade spent perfecting ways to block out the world, the next big wireless-audio growth story may be about letting some of it back in.

Related Reading:

Spanish Point Technologies’ Daire Cunningham explores the human element that’s key to digital transformation, especially in relation to AI adoption.

Artificial intelligence has become remarkably easy to buy, yet surprisingly difficult to transform a business with.

That distinction matters. McKinsey’s latest global research found that 88pc of organisations are now using AI in at least one business function, yet only around a third have begun scaling their AI programmes across the enterprise.

The gap between those figures points to a challenge that is becoming increasingly apparent. Access to AI is no longer the primary obstacle for most organisations. The harder task is understanding where it can genuinely create value and what needs to change within the business for that value to be realised.

In the rush to adopt AI, organisations can easily begin with the wrong question: Which AI tool should we use?

A better starting point is to ask what problem the organisation is actually trying to solve. Once that is clear, leaders can work backwards. They can identify what information is required, where it sits, who should have access to it, how the existing process operates and where the real bottlenecks lie.

They can also determine which decisions should remain firmly in human hands and where technology could meaningfully improve the outcome. The choice of model or platform should follow those decisions, rather than lead them.

This matters because one of the biggest obstacles to AI transformation is not a shortage of sophisticated technology, but the condition of the organisation underneath it.

A 2026 Dun & Bradstreet survey found that while more than three-quarters of businesses are already reporting some measurable return from AI, just 6pc say their enterprise data is fully ready to support AI at scale.

Businesses have spent decades accumulating information across databases, applications, document repositories and departmental systems. Permissions have evolved over time, processes have been layered on top of other processes, and employees have developed workarounds to get things done. AI has a tendency to make the weaknesses in those arrangements much harder to ignore.

Consider an AI assistant connected to an organisation’s internal information. If an employee asks it a question and receives a confidential document they should never have been able to access, it is tempting to describe that as an AI security problem. In reality, the technology may not have created the underlying vulnerability at all. It may simply have exposed the fact that the employee already had inappropriate access.

As AI makes it dramatically easier to retrieve and connect information, identity, permissions and governance become more important, not less.

‘Technology itself is only part of the story’

We have seen the value of getting those foundations right in identity modernisation projects. At the Royal College of Physicians of Ireland, 13 separate systems were brought into a single identity platform, introducing single sign-on and automated access management for more than 86,000 users across 95 countries.

Administrative overhead was reduced by 50pc. The technology itself is only part of the story. Establishing a clearer way of managing identities, permissions and access provides a much stronger foundation for any organisation introducing technologies capable of searching, connecting and retrieving information across multiple systems.

There is an equally important human dimension to this. I have always thought about digital transformation partly in terms of arming the workforce to adopt and employ modern technology in their working practices. An organisation can deploy an exceptional system, but if employees do not understand where it fits into their jobs, why they should use it or how their responsibilities change around it, its value will remain limited.

McKinsey’s research has found that redesigning workflows is among the factors most strongly associated with organisations seeing financial impact from generative AI. That makes sense: transformation does not happen because somebody has been given access to another piece of software. It happens when organisations rethink how work gets done.

At the same time, AI does not remove the need for professional discipline.

Engineers can use it to accelerate coding, testing and analysis, but generated code still has to be reviewed, systems still have to be tested and security requirements still apply. Someone remains accountable for what ultimately goes into production.

The same principle applies across other professions. AI can accelerate elements of the work, but capable professionals still need to understand the outputs, recognise when something is wrong and exercise judgement over the decisions that follow. As systems become more capable, that human oversight becomes more important rather than redundant.

This is also why the strongest applications of AI tend to make more sense when described in terms of the problem being solved rather than the technology being deployed.

The music industry provides a useful example. Identifying potentially fraudulent music registrations across immense volumes of metadata is a specific problem that becomes increasingly difficult to address at scale.

Applying machine learning and AI-driven metadata analysis to that challenge has enabled suspicious registrations to be identified across large datasets, with processing times reduced by 70pc in one implementation. The significance is not simply that the same work can be completed faster. Greater processing capacity allows skilled people to focus their attention on the cases that genuinely require investigation, judgement and expertise.

That points to a broader question about how businesses measure the value of AI. Much of the discussion still focuses on automation, efficiency and ultimately how much human work can be removed from a process.

Efficiency matters, but it is only one measure of what these technologies can contribute. AI can also make previously impractical work possible by analysing volumes of information that would have required enormous amounts of human time, identifying patterns that warrant further investigation and allowing skilled employees to concentrate on more complex decisions.

Instead of asking only what work AI can remove, businesses should also be asking what their people can now do that they could not realistically do before.

There will always be another model, platform or AI capability arriving on the market, which is precisely why businesses cannot build a transformation strategy around chasing each new development.

They need something more durable: a clear understanding of the problems they want to solve, trusted information, appropriate governance, well-designed processes and employees who understand how to use the technology responsibly.

The organisations that succeed with AI will not necessarily be those that adopt every new tool first. They will be those that know where AI belongs, prepare the foundations beneath it and give capable people the structures and confidence to use it effectively.

Technology certainly enables transformation, but people still have to make it work.

By Daire Cunningham

Daire Cunningham is the COO at Spanish Point Technologies, where he has worked since 2008. Prior to joining Spanish Point Technologies, Cunningham spent some time working in software systems design and development roles at companies such as Dolmen Stockbrokers and Fyntel.

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