Category: Tech

What comes after the iPhone? Some suggest it could be AI-related. While early AI devices like Humane’s AI Pin and the R1 Rabbit were a complete failure, it seems the next batch might revolutionize the market. Besides that, if Apple’s former design chief is behind a new tech product, we should probably pay attention.

According to The Information, OpenAI is considering buying the startup founded by Jony Ive and Sam Altman, which is said to be worth at least $500 million. The io Products company develops AI-powered devices, which the publication believes could include a phone without a screen and other AI-enabled products. That said, Jony Ive could be potentially developing an AI phone, the ultimate iPhone replacement.

Still, while people familiar with the matter insist it is “not a phone,”—of course it isn’t—the idea behind it could be as revolutionary as the first iPhone. Still, the report highlights Jony Ive and Altman’s collaboration is still in the early stages, without a product concept in hand.

What makes this project even more enticing is that Laurene Powell Jobs’ Emerson Collective also funds the venture. The startup even includes former Apple designers like Tang Tan and Evans Hankey, who worked with Ive on the iPhone.

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At the end of the day, the full acquisition could become a partnership, where OpenAI would get the technology and engineering team while retaining its AI capabilities. At the same time, Jony Ive’s LoveFrom studio would take care of the design part.

Since he left Apple, Jony Ive hasn’t worked on new hardware. However, its design kept making the headlines with the King of England, Ferrari’s partnership, Moncler, and so on.

Reports about Jony Ive working with OpenAI aren’t new. At least since 2023, BGR has reported that Apple’s former design chief has been working on the future iPhone AI. However, with OpenAI planning to buy the startup, the company may be about to arrive at a breakthrough tech point, which means we could soon see hardware from OpenAI that is as innovative as the first iPhone.

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CIOs have been under immense pressure for some time to deliver successful digital initiatives while navigating budget constraints and increasing demands from senior executives. A recent Gartner survey reveals that 92% of CIOs anticipate integrating artificial intelligence (AI) into their organisations by 2025, yet 49% struggle to assess and showcase the technology’s value. Are we going round in circles here?

Amid these challenges, small language models (SLMs) have emerged as a compelling solution, promising lower-cost and more secure AI capabilities that can fit with strategic priorities. So much about SLMs makes sense.

“The AI community has been actively exploring small language models like Mistral Small and DeepSeek R1,” says Amer Sheikh, chief data scientist at BearingPoint. “These models have seen significant traction, as evidenced by the number of downloads on Hugging Face. Their popularity stems from their ability to trade off accuracy, speed and cost-effectiveness.”

Adding intelligence at the edge

And that’s the key point. It is a trade-off – but one that is clearly worth making. SLMs, by their very nature, offer a practical alternative for organisations seeking to implement AI without the overheads associated with large language models (LLMs). They are also driving the next wave of edge AI adoption, enabling AI models to run on smartphones, internet of things (IoT) devices and industrial systems without relying on cloud infrastructure.

“Small models open up the possibility to push execution to the edge,” says Peter van der Putten, director of the AI Lab at Pegasystems and assistant professor of AI at Leiden University. “This could mean running on high-end smartphones, IoT devices such as cameras and, with proper consent, unlocking completely new data sources to learn from that are currently not available on the open internet.”

Despite the promise, real-world applications of SLMs in mobile and IoT devices remain in the early stages. Some practical implementations include DeepSeek’s R1 model, which has been integrated into Chinese automakers’ infotainment systems (such as Geely), and Phi-3, a small model designed for mobile AI applications. In education, Stanford’s Smile Plug uses small AI models to deliver interactive learning experiences on Raspberry Pi devices without internet connectivity. These examples demonstrate the growing potential of SLMs.

“SLMs can and are being deployed in a number of industries where there is a requirement for specific domain knowledge,” adds Sheikh, highlighting their use in customer service chatbots, virtual assistants and text summarisation.

Unlike LLMs, which require vast computational power and cloud resources, SLMs can run locally, cutting costs and mitigating security risks, hence their suitability for enhancing edge device intelligence. “There is a massive reduction in inference costs. However, there will be small costs for fine-tuning and self-hosting,” he adds.

SLMs can be augmented with smaller, more focused datasets, says Isabel Al-Dhahir, principal analyst at GlobalData. “Employing SLMs circumvents several challenges associated with general-purpose LLMs, including computational power requirements, exorbitant costs and insufficient domain knowledge.”

This ability to focus on precise, industry-specific use cases is why regulated sectors such as telecoms, accounting and law are adopting SLMs more readily.

“We have seen SLMs for professional services in dealing with accounting regulation, telecoms regulation, and various on-device applications and home automation,” Al-Dhahir adds.

With retrieval augmented generation (RAG) techniques, businesses can further refine and enhance the accuracy of these models within their specific domains.

Security key focus for industry growing LLM-weary

Beyond cost, security remains a major factor, especially within edge devices. According to Saman Nasrolahi, principal at InMotion Ventures (Jaguar Land Rover’s investment arm), this is where SLMs are also ticking a few boxes.

Much of the fear around LLMs is associated with a lack of transparency as to what is going on behind the scenes in terms of data collation and analytics. SLMs are the on-premise version of the generative artificial intelligence (GenAI) world.

“In addition to cost reduction, this approach also makes them far more secure and less vulnerable to data breaches as data does not need to leave an organisation’s borders,” says Nasrolahi.

This capability is particularly crucial for the healthcare, financial services and legal sectors, where regulatory compliance and data protection are paramount.

“Approximately one-third of all cyber security attacks occur when data is shared with an external vendor. By keeping data on-site, SLMs can reduce the attack surface and enterprise vulnerabilities,” Nasrolahi adds.

In a time when businesses are increasingly concerned about data sovereignty and compliance, the ability to localise AI processing is surely a significant advantage.

Andrew Bolster, senior research and development manager (data science) at Black Duck, adds that the portability of SLMs, at least compared with “the juggernauts of GPT-4, Claude, or even Llama”, makes them well suited to edge deployment. Security, cost and functionality are attractive propositions.

“SLMs operating on edge devices mean users’ data doesn’t have to leave the device to contribute to an intelligent response or action while potentially improving latency and performance, making intelligent operations feel more ‘relevant’ and ‘snappy’ while protecting users’ privacy,” he says.

With advances in custom chipsets to support these kinds of workloads, the power, memory and performance requirements of SLMs can now be found in most laptops and mid-tier mobile phones, allowing service platforms to shift more intelligence closer to the end user. This ability to process data locally on laptops, mobile devices and industrial IoT systems makes SLMs particularly valuable for low-latency applications, security-sensitive industries and environments with limited internet access. 

Jeff Watkins, chief technology officer (CTO) at CreateFuture, adds that SLMs “can run locally on laptops, desktop computers, smartphones, or even IoT devices. They range in sizes and capabilities – from ones that can run on compact devices to ones that begin to challenge the latest MacBook Pro models”.

With lower costs, enhanced security and the ability to function efficiently on existing hardware, SLMs present an increasingly strategic option for businesses. But as with any emerging technology, challenges remain. Hallucinations, biases and the need for fine-tuning mean it requires careful implementation.

“Hallucinations are still a problem for SLMs, similar to LLMs. Though, more specialised models tend to be less susceptible to these issues,” says Nasrolahi.

Lower the energy, lower the cost, the more mobile it becomes

Another key driver for the adoption of SLMs in edge devices is their ability to operate with lower energy consumption while also reducing cloud dependency. “SLMs are less energy-intensive, making them cheaper, better for the environment, and often small enough to run locally on edge compute such as your mobile or PC without the need for an internet connection,” says Silvia Lehnis, consulting director for data and AI at UBDS Digital.

The environmental and operational cost benefits make SLMs particularly appealing for businesses aiming to reduce their AI carbon footprint while maintaining data security. “Running the model locally without internet access can also have data privacy advantages, as your data is not being shared with an online application for central logging and monitoring, making it suitable for more sensitive use cases,” adds Lehnis.

It’s a recurring theme. This growing awareness that SLMs can enable a shift away from one-size-fits-all LLMs toward more focused, cost-efficient AI models should change how enterprises think about GenAI use. It could have a broader impact on IT buying, certainly in terms of how CIOs think strategically about what is and isn’t possible with GenAI.

Deloitte’s Tech Trends 2025 report suggests enterprises are now considering SLMs and open source options for the ability to train models on smaller, more accurate datasets. It’s a recognition that size isn’t everything, but accuracy and relevance is, aligning any AI deployments with operational objectives.

The trajectory of AI adoption indicates a growing preference for models that balance performance with operational practicality, but there is also a growing desire for more edge computing, real-time and strategically relevant functionality.

Interestingly, back in 2017, Gartner predicted this would happen, claiming that by this year, 75% of enterprise-generated data would be created and processed outside traditional centralised datacentres or the cloud. And that was before we knew anything about SLMs and their role.

So, what does this mean for the future of SLMs and edge computing devices? Certainly, they will have a significant role to play as enterprises see AI on their terms but also to enable differentiation. That will become the new challenge for CIOs – how to get the best out of GenAI to make a big impact on business performance. Angles for this can come from a number of directions – it really depends on the organisation and the industry.

The rise of SLMs is not just about cost savings or security – it’s about AI differentiation. As Jarrod Vawdrey, field chief data scientist at Domino Data Lab, points out, SLMs are already reshaping healthcare, finance and defence, allowing on-device AI to reduce latency, protect sensitive data and enhance real-time decision-making.

“SLMs deployed on medical devices enable real-time patient monitoring and diagnostic assistance,” he notes, while financial institutions are leveraging SLMs for fraud detection and anti-money laundering compliance.

For CIOs, the challenge is shifting. How do you harness GenAI to make a significant impact on business performance? The answer lies in adapting AI models to industry-specific needs – something SLMs are uniquely positioned to do. The next few years will see enterprises move beyond generic AI models, focusing instead on hyper-relevant, domain-trained AI that drives differentiation and competitive advantage. If anything is going to push edge computing into the mainstream, it’s small language models.

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As a result of a trial the concerned parties said exemplified the possibility of significantly expanding spectrum capacities, and making even better use of existing frequency bands and supplementing them with additional resources, operator A1 and technology partner Nokia have claimed to have undertaken pre-6G video stream in the upper 6 GHz spectrum for the first time in Central Europe.

The companies said the trial they carried out at the A1 Technology Centre in Vienna has demonstrated the next step in the evolution of mobile communications.

A1 said the mobile ecosystem was growing rapidly, and included technologies and services such as the internet of things (IoT), extended reality (XR), autonomous vehicles, robots and artificial intelligence (AI).

It added that – just like with other operators in Europe and the world – the combination of new services and devices and a sharp increase in usage have sparked significant growth in data traffic, thus making it necessary to continuously develop existing networks. As part of this development, A1 said a special focus was placed on efficiency, sustainability, safety and the interaction with new technologies.

A1 was of the view that the results of the tests at its technology centre showed the great potential of mobile communications for future 5G-Advanced and 6G applications, and underlined the company’s commitment to the sustainable development of the digital infrastructure.

“I am pleased that we can demonstrate the possibilities of future wireless technologies here at the A1 Technology Centre,” said A1 Austria chief technology officer Christian Laqué.

“After all, we will continue to provide the basis for rapidly advancing digitalisation in the future and take into account the increasing demand for secure connectivity. Today’s pre-6G transmission shows that we can build on existing infrastructures as we continue to develop our networks and make them even more efficient.”

As part of the trial, a Nokia 128TRX Massive MIMO transmitter and a MediaTec test terminal were used as receivers. Under practical conditions, it was shown that the spectrum used in this process could be used in existing macro networks and is compatible with the range of current mobile radio cells.

The test results were also said to have showed possibilities to increase urban capacities significantly, while maintaining an unchanged network of locations. A1 and Nokia were also of the opinion that at the same time, transmission speeds in suburban and rural areas could be significantly improved.

“We are just at the beginning of a long journey, but with this proof of concept, we have demonstrated that 6G will not only meet the growing demand for data traffic, but also unlock groundbreaking possibilities, such as network sensing and the transformative role of AI in the networks of the future in an efficient, sustainable and secure way,” said Christoph Rohr, country manager at Nokia.

Nokia has been at the forefront of 6G development since it was considered, and in 2020, was appointed as the project leader for Hexa-X, the European Commission’s 6G flagship initiative for research into the next generation of wireless networks, and the first official research initiative across the industry ecosystem to accelerate and foster 6G research and drive European leadership in the 6G era.

The company also has a significant presence in the University of Oulu in Finland, which is one of the leading technical facilities for research into the next generation of communications.

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During a discussion at the recent KubeCon + Cloud Native Computing Foundation (CNCF) Europe 2025 event in London, panel members discussed one of the big criticisms of modern software development: why is code deployment still fraught with problems?

Shifting left, where developers take on more responsibility for putting their code into production appears to have stalled in some organisations.

Kendall Roden, tech product lead at Diagrid, said that among the big challenges is the rise of distributed systems. According to Roden, this means developers now have a lot of what she called “additional cognitive load”. “There’s a lot of new responsibility, such as how to do resiliency when [the code] no longer runs as a single process,” she said.

In Roden’s experience, a lot of organisations don’t have the platform team to help take on these responsibilities. “Developers are less productive; the DevOps experience has become a little bit bloated and there’s not clear delineation of responsibility,” she warned.

While some organisations may adopt platform engineering to support developers, it still remains a challenge for developers to put code into production. Randy Bias, vice-president of open source strategy and technology at Mirantis, said the goal of DevOps and practices like platform engineering was to break down the walls between developers and operators “so that everybody could operate like Google”.

Platform engineering’s role is to sit between IT operations staff and software developers, where a team provides a platform, which is usually built on top of Kubernetes. This, he said, adds a layer of abstraction and provides developers with a path to production. 

However, Bias added: “If you look at the average enterprise, they have no chance in hell of operating like Google. The silos are as siloed as ever, and there are huge barriers between developers and operations people.” He pointed out that developers don’t want to know about IT infrastructure. “They don’t care about it,” said Bias. “They want to develop their applications and have them magically deployed.”

Kubernetes’ relationship with AI

Artificial intelligence (AI) and machine learning (ML) workloads represent something entirely new for the Kubernetes committee, according to Jago Macleod, director of engineering at Google Cloud. “This new round of AI and ML workloads is really different to what the CNCF and KubeCon communities have built so far,” he said.

AI and ML are large training workloads. In the world of Kubernetes, workloads are deployed in pods but given the size of AI and ML workloads. Macleod said this means using one pod per node. “If any one of the nodes stops, you need to get another one in place and then restart [the workload] from a checkpoint,” he said. “These new kinds of workloads are not very fault tolerant.”

According to Macleod, another challenge is the fact that AI researchers who work with AI foundation models tend to program using Python.

“Many come from academia and they write Python code, which is not what we would call elegant code in software engineering, and there’s no source [code] control,” he said, adding that the AI researchers then try to distribute these Python workloads across tens of thousands of nodes.

“It’s a completely different mental model compared to our preferred way, with IT operations, and you check it into the source and then that blasts out in a controlled manner; it’s a very different world,” said Macleod.

AI and ML present very different problems to other Kubernetes workloads. Roden said that in the AI space, there needs to be a shift in mindset among developers to improve their understanding of how they can work with AI. “I don’t necessarily know if the scale of usage from the average enterprise developer is actually there, because it is quite complex and it does require a different skill set, a different approach and a different set of infrastructure,” she added.

Bias went further, adding: “People don’t realise that these are HPC workloads,” referring to the fact that AI and ML share similar problems to supercomputing. He said the problem of AI and ML resiliency was the same kind of problem that supercomputing centres have been tackling for decades. “We don’t have to reinvent the wheel,” said Bias. “We just need to go back and take that knowledge that’s been in the HPC niche.”

Global pressure

Beyond writing and managing code, among the questions asked during the panel discussion was one looking at how geopolitical tension was impacting open source and the Linux Foundation. “There’s a tonne of perils and pitfalls in front of us,” said Bias.

At the CNCF event in Hong Kong, he said the presenters were all Mandarin speakers discussing projects being developed in China. “There is a danger of regional fractionalisation,” said Bias.

But while, from a geopolitical perspective, open source tends to be neutral and the community tries to operate across international boundaries, politics can influence this openness.

“There are geopolitical realities for an organisation like the Linux Foundation because it operates primarily inside the United States,” he said, referring to the Linux Foundation’s decision in November 2024 to exclude a cohort of Russian Linux kernel maintainers.

Bias suggested that given it’s based out of the US, the Linux Foundation is no longer well-placed to oversee the global open source community. Instead, he said what is needed is a United Nations for open source that operates in a geographically neutral region.

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Mobile virtual network operator Pelion has launched Pelion Plans, a managed internet of things (IoT) product and service proposition.

Established in 2000, Pelion serves more than 1,000 enterprise clients across a range of industries, including transport, healthcare, energy and utilities, industrial IoT, asset tracking, and logistics. The business has received investment from technology giants including Arm and Softbank, and became an independent company backed by Scottish Equity Partners in 2022.

Pelion said it has now refreshed and revitalised its brand identity, and launched Pelion Plans as part of its growth strategy to target domestic and international growth.

Explaining the go-to-market strategy, Pelion CEO Dave Weidner said: “At Pelion, we’ve focused on developing flexible, multi-carrier connectivity which has, in turn, enhanced reliability for our clients deploying in a single country or across the globe. We have less than half an hour of downtime per year, compared with the industry average of 87 hours. The cost of that downtime is significant – in the US, that 87 hours costs the average enterprise $22.8m per year – so bringing that as low as possible is key.”

The downtime cost figure cited was based on a study from Berg Insight – Achieving reliable connectivity for scalable cellular IoT deployments – which noted that across industries such as healthcare, manufacturing, and transport and logistics, businesses were increasingly dependent on reliable connectivity to ensure smooth operational processes and preserve efficiency.

Moreover, it warned that downtime can have far-reaching effects that extend beyond temporary inconveniences, impacting revenue, productivity, customer outcomes and reputation.

Mobile network operators (MNOs) generally assure a specific level of operational support and uptime via service level agreements. The study examined the impact of downtime and how multi-network connectivity, embedded subscriber identity modules (eSIMs) and thoughtful hardware selection can help businesses maintain high levels of service availability for their cellular IoT device deployments.

Pelion Plans to use Pelion IoT eSIMs to provide organisations with different levels of technological deployment and managed service, helping businesses scale IoT investment in line with deployment and connectivity needs.

The Pelion IoT eSIM is an embedded universal integrated circuit card, eUICC-enabled IoT SIM that provides future-proofed connectivity, and eUICC is a software offering that provides the capability to store multiple MNO profiles on a single SIM so that eUICC-enabled SIMs can switch seamlessly between MNOs.

This provides Pelion enterprise customers with the flexibility to change the MNO profile based the location, quality of service or cost profile they are trying to achieve wherever they are deploying. If an MNO is experiencing an outage, the customer’s deployment is quickly switched to a new provider, minimising downtime.

“The last two years have been a period of really fine-tuning our offer to provide the most reliable and secure service,” said Weidner. “Now that we’ve done that work, we’re moving into growth mode, looking to expand our work with enterprises large and small in both domestic and international markets. Our evolved brand and Pelion Plans are the starting point for setting us apart.”

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The Investigatory Powers Tribunal (IPT) has rejected government demands for complete secrecy over Apple’s legal challenge against a Home Office order requiring the tech giant to give UK law enforcement “backdoor” access to encrypted data stored by users of its Advanced Data Protection (ADP) service.

The tribunal today rejected arguments from the Home Office that public disclosure of even the “bare details” of the involvement of Apple or the Home Office would be damaging to national security.

Following weeks of government officials refusing to confirm or deny the court action, the IPT confirmed that Apple has filed a complaint challenging the secretary of state’s powers to issue technical capability notices (TCNs) under the Investigatory Powers Act 2016.

The existence of the order, which was first reported by the Washington Post, has raised tensions between the UK and the US, attracting criticism from Donald Trump and US lawmakers that the order will allow UK law enforcement access to the encrypted data of US citizens using Apple’s ADP service in the US and other countries.

The tribunal’s decision follows legal submissions from Computer Weekly jointly with nine other media organisations, PA Media, members of US Congress, and civil society groups Big Brother Watch, Privacy International and Liberty, “strongly arguing in favour of open justice” and against the case being heard in secret.

“There has been extensive media reporting to the effect that the United Kingdon government has signed a technical capability notice requiring the claimant to be able to maintain access to its users’ data in decrypted form, so that such data is available to be passed to the intelligence agencies,” the tribunal said.

In the ruling issued today, tribunal chairman Lord Justice Singh and Justice Johnson rejected Home Office arguments that disclosing the “bare details of the case” – including publicly acknowledging the identity of Apple and the Home Office – would damage national security or prejudice the public interest.

They did not rule on whether future hearings in the case would be held in open court but left open the possibility that it “may well be possible” for some or all future hearings into the case to incorporate a public element with or without reporting restriction.

Apple brought the case against the Home Office after it received a technical capability notice from the Home Office requiring it to extend existing UK law enforcement powers to access encrypted data stored by users on Apple’s iCloud to users of its Advanced Data Protection service.

Apple responded to the order in February by withdrawing ADP from users in the UK, in a move that was criticised as exposing UK citizens to greater cyber threats. “As we have said many times before, we have never built a backdoor or master key to any of our products or services, and we never will,” Apple said in a statement at the time.

According to the ruling, the Home Office wrote to the tribunal asking it not to disclose the existence of a planned tribunal hearing on 14 March into Apple’s complaint in court listings “so that the hearing would take place entirely in secret” for national security reasons.

Apple told the tribunal on 6 March 2025 that there was no reason not to list the fact that a hearing was taking place, even if Apple and the Home Office were not named, and that open justice required judicial proceedings to be published in the absence of compelling reasons to the contrary.

Tribunal president Lord Justice Singh and Justice Johnson agreed. “It would have been a truly extraordinary step to conduct a hearing entirely in secret without any public revelation of the fact that a hearing was taking place. That would be the most fundamental interference with the principle of open justice,” they said in the ruling.

The IPT listed a closed-door hearing on 14 March, without publicly disclosing the role of Apple or the Home Office. 

The court heard arguments from the Home Office that the “bare details of the case would be prejudicial to national security”. Apple, with some support from the Counsel to the Tribunal, argued that the Home Office’s concerns were “overblown and unjustified”.

Singh and Johnson found in favour of Apple: “We do not accept that the revelation of the bare details of the case would be damaging to the public interest or prejudicial to national security.”

Claims from Privacy International and Liberty

Civil society groups Privacy International and Liberty have filed separate complaints, along with two individuals challenging the Home Office’s powers to issue technical capability notices against Apple and other technology companies. They have asked for their claims to be heard together with Apple’s claim in the Investigatory Powers Tribunal.

The tribunal judges found that there was no need to rule on Privacy International and Liberty’s application for the proceedings to be made public or to make a decision on whether or not to allow them to intervene in the Apple case before the Home Office had submitted a defence.

The tribunal said it was at least possible that the early stages of the litigation would involve the resolution of issues of law, which would mean, by implication, that the early hearings could be heard in open court. It was also possible that Apple’s claim could be stayed behind the Privacy International and Liberty case.

The court also acknowledged the receipt of a letter from US senators and members of Congress, but did not consider it necessary to rule on the issues raised. The letter seeks permission to discuss the technical capability notice issued by the Home Office with US Congress, but the court said it had no power to grant that request.

Public hearings may be possible

A submission from PA Media asked the tribunal to impose the least prescriptive measures possible, including holding a public hearing with reporting restrictions.

“It may well be possible for some or all future hearings to incorporate a public element, with or without reporting restrictions. It is not possible to rule on that at this stage,” the court said.

Commenting on the ruling, a Home Office spokesperson said the government could neither confirm nor deny the existence of the TCN.

“The Investigatory Powers Act and technical capability notices allow the UK to maintain existing and long-standing counter-terrorism and serious crime investigative capabilities in the face of fast-changing technology, especially when we know that terrorists and child abusers organise and seek to hide evidence of their crimes online,” they said.

“TCNs themselves do not directly provide access to data – relevant targeted warrants and authorisations must also be in place. Nor do TCNs extend powers to obtain access to data; their purpose is to ensure that those existing powers can continue to be exercised effectively,” the spokesperson added. 

The Home Office’s order to break encryption represents a massive attack on the privacy rights of millions of British Apple users, which is a matter of significant public interest and must not be considered behind closed doors Rebecca Vincent, Big Brother Watch

Rebecca Vincent, interim director of Big Brother Watch, said the judgment was a welcome step in the right direction and “effectively chipped away” at the pervasive climate of secrecy surrounding the case.

“The Home Office’s order to break encryption represents a massive attack on the privacy rights of millions of British Apple users, which is a matter of significant public interest and must not be considered behind closed doors,” she said. 

Jim Killock, executive director of Open Rights Group, said the case was bigger than the UK and Apple, and would have implications for millions of people around the world. 

“Such an important decision cannot be made behind closed doors and we welcome the IPT’s decision to bring parts of the hearing into the open so that there can be some public scrutiny of the UK government’s decisions to attack technologies that keep us safe online,” he said.

Jemimah Steinfeld, CEO of Index on Censorship, said the judgment did not “stipulate that the case will be held in the open moving forward – as it should be – only that we can know the ‘bare details’. We welcome this news, but we continue to fight for full transparency here.”

The media companies jointly challenging the secrecy of Apple’s appeal in the Investigatory Powers Tribunal are Associated Newspapers Ltd, the British Broadcasting Corporation, Computer Weekly, Financial Times Group, Guardian News & Media, News Group Newspapers, Reuters News and Media, Sky News, Telegraph Media Group and Times Media. PA Media has filed a separate challenge.

According to the judgment, neither Apple nor the Home Office have confirmed or denied that media reporting of the technical capability notice issued against Apple is accurate. “This judgment should not be taken as an indication that the media reporting is or is not accurate,” it said.

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A new Chinese-made cable capable of 8K wired connections could soon make your Thunderbolt cable seem like a VGA cable. Designed to handle ultra-high-resolution content and serious power delivery simultaneously, the 8K-capable cable could simplify setups for gamers, streamers, and power users alike.

The new standard from China is called the General Purpose Media Interface, or GPMI. It comes from the Shenzhen 8K UHD Video Industry Cooperation Alliance, a group made up of over 50 Chinese tech companies. It’s designed with 8K video in mind, and the group says the cable should help reduce clutter by combining high-speed data and high-wattage power into a single cord.

The 8K cable currently comes in two versions: a Type-C version, which uses the latest USB-C standard. This variation supports 96 Gbps bandwidth and up to 240 watts of power, which more than doubles the speed of Thunderbolt 4 and matches USB4’s power output. Thunderbolt 5, which launched in 2024, also supports up to 240 watts of power and tops out at 80Gbps of bi-directional bandwidth (120Gbps with bandwidth boost.)

However, the real showstopper is the Chinese group’s proprietary Type-B connector, which delivers up to 192 Gbps of bandwidth through the 8K cable and 480 watts of power. That’s more than enough power to support an 8K display and could even charge a high-performance gaming laptop at the same time.

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The new cable is a massive leap over other standards available right now. HDMI 2.1 tops out at 48 Gbps with no power output, while DisplayPort 2.1 reaches 80 Gbps. Thunderbolt 4 caps out at 40 Gbps of bandwidth and 100 watts of power. As such, nothing currently in wide use matches the capabilities promised by this Chinese 8K cable, but Thunderbolt 5 is slowly spreading.

Beyond speed and power, GPMI also includes features like unified control—similar to HDMI-CEC—allowing a single remote to manage all connected devices. In theory, this means fewer wires and fewer power connectors. Of course, the cable’s high power ceiling won’t power your entire gaming PC just yet.

But, reports say it should be enough to power a portable workstation running dedicated graphics. For those who prefer to keep their more powerful setups portable, this Chinese 8K cable could be the exact thing we need to usher in the next generation of computer power and display cables.

Whether GPMI will expand beyond China is still uncertain, but based on specs alone, the Chinese 8K cable looks very promising, though the use of a proprietary connector for the best speeds undoes a lot of the work that has been done in recent years to standardize power connectors for electronics—especially since even Apple has ditched its proprietary connectors in favor of USB-C.

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ChatGPT’s image generation tool is now available to free users—and with that, OpenAI may be taking steps to clearly label what’s AI-made. According to early tests spotted by researchers, a new chatGPT image watermark may be rolling out to mark images created using ChatGPT’s image generation model.

The watermark, which appears subtly on AI-generated images from the free version of ChatGPT, is currently in testing and hasn’t been officially announced. If it does happen, it would be a deviation from some strange responses OpenAI Ceo Sam Altman has made on X about ChatGPT infringing on copyrights with its image generation tools.

However, AI researcher Tibor Blaho and others have reported seeing the watermark mentioned in the code for ChatGPT’s image generation model. It only mentions free generation, though, so it is possible the watermark won’t apply to premium ChatGPT subscriptions.

This change could be significant if it goes through, especially given how viral ChatGPT’s ImageGen model has become in recent days. We’ve seen some crazy images generated by ChatGPT since the update dropped in late March.

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The image watermark is likely OpenAI’s response to concerns about authenticity and user-generated content from ChatGPT. As more users create and share AI-generated art online, the ability to distinguish between real and synthetic content becomes critical—not only for artists and developers but also for the general public. Watermarking is a simple way to indicate that AI generated the image without interfering too much with the end result.

Under the hood, OpenAI says its image generator is trained on a massive dataset of online images and text. This dual training helps the model produce visuals that are both relevant to the prompts and surprisingly coherent—we’ve seen so many Studio Ghibli-styled images in the past week alone.

The company has also confirmed it’s developing an API for the image generation tool, which would make it easier for third-party developers to build their own tools around it. Whether the image watermark will extend to the API, or only to ChatGPT users is unclear, though.

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Myriota, a provider of direct-to-orbit satellite connectivity for internet of things (IoT) and small power-constrained devices, has launched a further four satellites to its UltraLite LEO constellation.

Founded in 2015, Myriota’s space-based network is designed to deliver scalable, affordable IoT data services and energy-efficient hardware in sectors such as agriculture, logistics, water management and environmental conservation.

The company’s network is designed specifically for the IoT industry, supporting applications such as logistics, utilities and agriculture to monitor and collect critical sensor data.

It has a mission to democratise satellite IoT access, delivering critical field-based monitoring services to a global market.

Delivered in partnership with global provider of space infrastructure Spire, the four new satellites are designed to bolster Myriota’s UltraLite LEO constellation, strengthening its set of global IoT connectivity options, which includes its 3GPP-aligned HyperPulse GEO satellite service.

The combination is attributed by Myriota as allowing the company to service a broad spectrum of IoT sensor use cases around the globe, with performance, capacity and coverage requirements specifically tailored to individual customers. These are said to range from power-limited, deployment-challenged customers to those seeking seamless terrestrial to non-terrestrial network roaming.

Myriota added that the expanded capacity provided by the new satellites will ensure customers in industries such as logistics, utilities and agriculture can securely monitor and collect data globally, using long-lasting and low-cost IoT sensors.

The nanosatellites are in the process of being onboarded following their launch on SpaceX’s Transporter-13 mission, which took off on 14 March from the Space Launch Complex 4E at Vandenberg Space Force Base in California, with more launches set to further expand the constellation throughout the rest of the year.

“We are maintaining a regular cadence of satellite launches, adding ever more capacity, coverage and resilience to our UltraLite constellation of LEO satellites as we invest in continuous upgrading of our service offerings,” said Myriota CEO Ben Cade.

“Our networks can now support tens of millions of IoT connections around the globe, ensuring access to low-power, cost-effective sensor networks to more countries and industries, ready for our partners to further expand their  solution deployments in 2025 and 2026.”

In December 2024, Myriota announced a $32m funding round led by the Australian Federal government’s National Reconstruction Fund Corporation and venture capital partners Main Sequence, with support from other investors including Inter Valley Ventures.

The Saudi project – in partnership with CST, the Saudi Telecom Company and system integrator Giza Systems – has already seen Myriota deploy a cohort of connected smart water meters in remote locations on behalf of the Saudi Ministry of Environment, Water and Agriculture. The devices, which remain live in the field, are designed to enable remote monitoring of water meters that are in areas with limited or no cellular connectivity.

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The United States’ national metrology institute, the National Institute of Standards and Technology (NIST), is to cease providing updates to tens of thousands of older common vulnerabilities and exposures (CVEs) held within its National Vulnerability Database (NVD).

In an announcement posted last week, the standards body said that every CVE with a published date prior to 1 January 2018 would now be marked as deferred within the NVD dataset.

“We are assigning this status to older CVEs to indicate that we do not plan to prioritise updating NVD enrichment or initial NVD enrichment data due to the CVE’s age,” NIST said in a statement.

NIST’s announcement comes as the organisation struggles to deal with a backlog of thousands of CVEs that need to be analysed and processed. At points last year, this backlog hit 18,000 records as new submissions surged by 32%. It has been exploring the use of new technologies, including machine learning, to try to automate its way out of its dilemma.

Like most other authorities on the matter, NIST expects that vulnerability submission volumes will continue to rise in 2025.

NIST said it would continue to accept and review requests to update the metadata it provides for its CVE records, and it will “continue to prioritise” this work subject to time and resource availability should new information come to light that indicates an update to said data is appropriate.

It will also continue to prioritise any CVEs added to the Cybersecurity and Infrastructure Security Agency’s (CISA’s) Known Exploited Vulnerability catalogue, regardless of their age.

Tim Mackey, head of software supply chain risk at Black Duck, said: “While it may be concerning to see older CVEs, particularly those associated with prominent vulnerabilities, be triaged to a lower priority, the reality is that the CVE remains in the NVD with a recognition that updates to older CVEs are infrequent.

“For practical purposes, I would view any organisation that hasn’t patched or mitigated something now labeled as ‘Deferred’ as having an underperforming patch management or DevOps cyber security programme. Let’s make this event a call to action for product security incident response teams to inventory all software and then triage all vulnerabilities with a Deferred status,” he said.

US cuts

In recent weeks, NIST has additionally been subject to a series of cuts by the Department of Government Efficiency (DOGE), the new body led by Elon Musk that has been tasked with making thousands of redundancies across the federal government, and it is understood that it plans to fire 20% of the workforce at NIST’s parent, the Department of Commerce.

Last week, a number of US politicians pressed commerce secretary Howard Lutnick on these cuts and warned that they may threaten NIST’s work on developing standards and pose a danger to both industrial and consumer safety and security, as well as damaging American leadership and soft power on the global stage.

According to Computer Weekly’s sister title Cybersecurity Dive, CISA has lost at least 170 roles through DOGE’s cuts to the Department of Homeland Security (DHS), while many other staffers at the US’ national cyber agency – which was established by president Trump during his first term – have resigned amid cratering morale.

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