Category: Tech

Apple HQ has seemingly sprung a leak in the days ahead of its WWDC 2025 keynote, as new details about the company’s upcoming software updates continue to find their way online. After spoiling a few surprises pertaining to iOS 26 on Tuesday, 9to5Mac returned today with updates about new features likely coming to Apple’s AirPods this fall.

According to 9to5Mac, there are several new features currently in the works for Apple’s line of wireless earbuds. The expectation is that these new features will be included in the iOS 26 and macOS 26 software updates, but the site also warns that Apple may “choose to delay or tweak” these features, so there’s no guarantee we’ll see them this fall.

With that out of the way, let’s dig into the rumored AirPods upgrades.

New AirPods features set for iOS 26

AirPods Pro 2 with USB-C port. Image source: Christian de Looper for BGR

Of the rumored features, the most intriguing is camera control. 9to5Mac says AirPods users will be able to press the AirPods stem in order to snap a photo with a connected iPhone. This exact feature was available on Apple’s EarBuds, but has yet to appear on AirPods.

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The report also notes that AirPods will soon support new head gestures. Apple introduced head gestures on AirPods Pro 2 and AirPods 4 in 2024, allowing users to move their heads to answer or decline phone calls as well as interact with messages and notifications. On iOS 26, Apple will reportedly add even more gestures, potentially including one that would give users the ability to end or extend a Conversation Awareness volume adjustment.

Other new features coming to Apple’s AirPods in iOS 26 include sleep detection to automatically pause content when the user dozes off, a “studio quality” mic mode similar to the iPhone’s Audio Mix feature, and an improved pairing experience.

Tune in to WWDC 2025

WWDC 2025 begins on June 9. Image source: Apple Inc.

As for which AirPods will get these features, we’ll have to wait until Monday to find out. Apple’s WWDC 2025 keynote is scheduled to begin on June 9 at 10:00 a.m. PT / 1:00 p.m. ET. Even if these new features aren’t announced during the keynote, we always find a wide variety of new features that Apple didn’t have time to discuss once the dust settles after the event.

We’ll be keeping our eyes peeled for these AirPods upgrades and more on Monday.

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Apple fans around the world are probably anxiously waiting for next week’s main keynote, which will open this year’s WWDC. The event is where Apple unveils its latest operating systems each year, making them available in beta to testers eager to try the new features right after the show.

This year’s OS reveals are even more exciting, since we’re not just getting new features for iPhone, iPad, Mac, Apple Watch, Apple TV, AirPods, and Vision Pro. Apple is giving all its operating systems a big redesign, one that has leaked several times over the past few months.

A name change is also coming, with Apple replacing the expected iOS 19 label with a new iOS 26 moniker meant to designate the year of release. The official iOS 26 launch will happen in September or late 2025, making it the newest iPhone OS for most of 2026.

This new naming policy will apply across the board. All of Apple’s operating systems will follow the same numbering scheme.

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With all that in mind, iOS 26 is easily the most anticipated OS coming out of WWDC. It’s the operating system people will want to try right away on their smartphones, to see how the new design works and test whatever iOS 26 features are available to early adopters on day one.

Unfortunately, some older iPhones still in use won’t be able to run iOS 26.

Apple has an impressive track record when it comes to supporting older iPhones. The latest iOS features might not show up on phones that launched five years ago, but they’ll still get most of the iOS functionality and the new design.

Apple Intelligence will be one of the iOS 26 features limited to newer models, but that’s due to specific hardware requirements for AI.

Otherwise, the visionOS-inspired design in iOS 26 will be available on older devices. The same goes for new features built into iOS 26 apps.

The first iOS 26 beta won’t include all the new features Apple planned for this release. Only the ones ready for testing will be available to users.

Also, just a reminder that Apple gives developers first access to the beta. They get it at WWDC, and the public beta usually follows about a month later.

As for supported hardware, iOS 26 will work on nearly all iPhones that can run iOS 18. A report from a trusted source mentioned a few months ago that only the 2018 iPhones wouldn’t be upgraded to iOS 26 (still called iOS 19 at the time). Apple will confirm the list next week, but that same group of iPhones has resurfaced online.

The rumor is likely accurate. These iPhone models should support iOS 26 starting with the first beta release next week:

• iPhone 11, 11 Pro, and 11 Pro Max
• iPhone 12, 12 mini, 12 Pro, and 12 Pro Max
• iPhone 13, 13 mini, 13 Pro, and 13 Pro Max
• iPhone 14, 14 Plus, 14 Pro, and 14 Pro Max
• iPhone 15, 15 Plus, 15 Pro, and 15 Pro Max
• iPhone 16e, 16, 16 Plus, 16 Pro, and 16 Pro Max
• iPhone SE (2nd gen and 3rd gen)

If you’re currently in the iOS 18 beta program, you’ll move to iOS 26 once Apple rolls out the first beta.

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North Lincolnshire Council has received a planning application for a 1,000mW datacentre campus, as its push to become a government-backed artificial intelligence (AI) Growth Zone gathers pace.

According to the project documents, seen by Computer Weekly, the development would be the largest datacentre in the whole of the UK on completion, with the masterplan suggesting up to 15 “different datacentre plots” could be housed there.

“This would be the largest datacentre campus in the northern part of the UK, and indeed the whole of the UK at the time of preparing the planning application,” the Economic needs and benefits document for the project stated.

The development will be located on the site of the former RAF Elsham Wolds World War II airfield, which neighbours a nearby industrial park.

Plans for this latest project were submitted to the council at the end of May 2025.

Based on previous communications from the council, from February 2025, the Elsham Tech Park plan appears to be the third of four projects that will form the backbone of the local area’s bid to become an AI Growth Zone.

A post about the build on the North Lincolnshire Council website said up to £7.5bn will be invested in bringing the plans to fruition, and it is expected the project will generate up to 1,200 highly skilled jobs once the work on it is completed.

Positive sign

Council leader Rob Waltham said the proposed project is “another positive sign of confidence in our economy and in North Lincolnshire as a place to do business”.

“It’s further evidence that the work we are doing to enable growth and create the conditions for private investment is delivering real results and better-paid jobs for our communities,” he said.

As previously reported by Computer Weekly, the government has received hundreds of bids from local authorities across the UK that want their areas to become home to AI Growth Zones.

As detailed in the UK government’s January 2025 AI opportunities action plan policy paper, the plan is to create AI Growth Zones in de-industrialised parts of the country that can be readily redeveloped and have “enhanced access to power and support for planning approvals” so these developments can be fast-tracked.

This is in support of the government’s push to position the UK as an “AI superpower”, and make the use of AI technologies and services more pervasive across the UK.

Furthermore, the government has specified that sites must have access to power connections of at least 500mW, or local authorities must have a clear plan in place to demonstrate how they would generate that amount of power, to have their AI growth zone bids considered.

The project is being overseen datacentre developer Greystoke, and a newly created company, trading as Elsham Tech Park, has been set up to front it.

Two of its directors – Sam Matthew and Nick Aldridge – are also actively involved in another Greystoke datacentre development in the region, known as Humber Tech Park, as confirmed by Companies House.

In a statement, published on the North Lincolnshire Council website in February 2025, Matthew – who also serves as chief operating officer at Greystoke – talked up the benefits acquiring AI Growth Zone status will make to the area.

“It will create exciting new opportunities for national and regional industries,” he said. “North Lincolnshire’s substantial energy infrastructure and extensive skills base make it the ideal location for an AI Growth Zone.”

Outline planning permission for that development, valued at £3bn, was granted by North Lincolnshire Council in August 2024, with that project expected to increase the availability of AI datacentre capacity in the region by 384mW.

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Even though the internet of things (IoT) arena is definitely on the rise, businesses relying on globally connected IoT devices are facing a major shift in how these assets will need to be managed, driven by new technical standards and evolving market complexities, leading to the arrival of the concept of the eSIM orchestrator (eSO), according to a study from industry research firm Transforma Insights. 

Its analysis, The rise of the eSIM orchestrator, produced in collaboration with global IoT connectivity specialist Eseye, fundamentally finds that emerging technologies like the SGP.32 standard for eSIMs, coupled with what the analyst says will be more selective network operator policies, will compel connectivity providers to adopt strategies and specialist roles to maintain control and efficiency.

Created by the GSMA, the industry body responsible for mobile communication standards, SGP.32 is a global, next-generation eSIM standard for remote SIM provisioning in IoT devices – especially those with no user interface. It is designed to enable the large-scale, hands-off management of eSIM profiles, making it easier to deploy and operate IoT without physical access.

While eSIM technology has been available for consumer devices, managing these digital SIM profiles in IoT devices comes with unique challenges. For example, many IoT devices lack a user interface, making manual SIM management impractical. SGP.32 has been designed to address such limitations and builds on existing eSIM technology, introducing a more efficient way to remotely manage IoT connectivity. It allows SIM profiles to be managed remotely through a centralised platform, enabling automated updates and provisioning – even for devices without user interfaces or located in hard-to-reach areas.

Transforma Insights reflects this view, stressing that the era of simple, unfettered global connectivity for company devices is evolving, presenting new complexities for businesses.

The report notes that the key challenges and developments driving this transformation include: the launch of SGP.32 for remote SIM provisioning; mobile network operators (MNOs) becoming increasingly cautious about granting network access, particularly for eSIMs, seeking stronger guarantees on device security, certification and network resource utilisation; and a complex and tightening web of international regulations concerning data sovereignty, cyber security and permanent roaming restrictions in many countries.

“Enterprises are navigating a period of significant change in how global device connectivity is delivered and managed,” said Matt Hatton, founding partner at Transforma Insights. “The new SGP.32 standard provides a powerful tool for remote SIM provisioning. In conjunction with a more demanding regulatory and MNO landscape, our analysis points towards a fundamental shift requiring businesses to be more strategic. This is where we see the emergence of roles like the eSIM orchestrator becoming critical.”

The report sees the eSIM orchestrator function as growing to specialise in managing the complexities of this new environment. According to the paper, key responsibilities and characteristics of such a role would include eSIM profile management; profile lifecycle management; network capability awareness; device awareness; billing simplification; customer support; trusted relationships with MNOs; compliance with eSIM management obligations; commercial plans and tariffs management; and “comprehensive” managed services.

The paper also suggests this shift will move the industry beyond basic connectivity resale towards more sophisticated managed service models. For businesses, this means that simply acquiring SIMs will no longer be sufficient: a more holistic approach to managing the lifecycle, compliance and diverse connectivity options of their devices will be necessary.

“The way businesses manage their connected devices globally is undoubtedly transforming,” added Eseye co-founder and chief technology officer Ian Marsden. “Proactive companies will be looking beyond the immediate technical changes, like SGP.32, to understand the broader operational and strategic implications. Having a clear strategy for device connectivity management, which considers the need for specialised eSIM orchestration and unified control, will be increasingly important to de-risk operations, ensure compliance and maintain a competitive edge.”

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Open source AI is gaining momentum across major players. DeepSeek recently announced plans to share parts of its model architecture and code with the community. Alibaba followed suit with the release of a new open source multimodal model aimed at enabling cost-effective AI agents. Meta’s Llama 4 models, described as “semi-open,” are among the most powerful publicly available AI systems.

The growing openness of AI models fosters transparency, collaboration, and faster iteration across the AI community. But those benefits come with familiar risks. AI models are still software – often bundled with extensive codebases, dependencies, and data pipelines. Like any open source project, they can harbour vulnerabilities, outdated components, or even hidden backdoors that scale with adoption.

AI models are, at their core, still code – just with additional layers of complexity. Validating traditional components is like reviewing a blueprint: intricate, but knowable. AI models are black boxes built from massive, opaque datasets and hard-to-trace training processes. Even when datasets or tuning parameters are available, they’re often too large to audit. Malicious behaviours can be trained in, intentionally or not, and the non-deterministic nature of AI makes exhaustive testing impossible. What makes AI powerful also makes it unpredictable, and risky.

Bias is one of the most subtle and dangerous risks. Skewed or incomplete training data bakes in systemic flaws. Opaque models make bias hard to detect – and nearly impossible to fix. If a biased model is used in hiring, lending, or healthcare, it can quietly reinforce harmful patterns under the guise of objectivity. This is where the black-box nature of AI becomes a liability. Enterprises are deploying powerful models without fully understanding how they work or how their outputs could impact real people.

These aren’t just theoretical risks. You can’t inspect every line of training data or test every possible output. Unlike traditional software, there’s no definitive way to prove that an AI model is safe, reliable, or free from unintended consequences.

Since you can’t fully test AI models or easily mitigate the downstream impacts of their behaviour, the only thing left is trust. But trust doesn’t come from hope; it comes from governance. Organisations implement clear oversight to ensure models are vetted, provenance tracked, and behaviour monitored over time. This isn’t just technical; it’s strategic. Until businesses treat open source AI with the same scrutiny and discipline as any other part of the software supply chain, they’ll be exposed to risks they can’t see with consequences they can’t control.

1. Securing open source AI: A call to action

Businesses should treat open source AI with the same rigour as software supply chain security, and more. These models introduce new risks that can’t be fully tested or inspected, so proactive oversight is essential.

2. Establish visibility into AI usage:

Many organisations don’t yet have the tools or processes to detect where AI models are being used in their software. Without visibility into model adoption, whether embedded in applications, pipelines, or APIs – governance is impossible. You can’t manage what you can’t see.

3. Adopt software supply chain best practices:

Treat AI models like any other critical software component. That means scanning for known vulnerabilities, validating training data sources, and carefully managing updates to prevent regressions or new risks.

4. Implement governance and oversight:

Many organisations have mature policies for traditional open source use, and AI models deserve the same scrutiny. Establish governance frameworks that include model approval processes, dependency tracking, and internal standards for safe and compliant AI usage.

5. Push for transparency:

AI doesn’t have to be a black box. Businesses should demand transparency around model lineage: who built it, what data it was trained on, how it’s been modified, and where it came from. Documentation should be the norm, not the exception.

6. Invest in continuous monitoring:

AI risk doesn’t end at deployment. Threat actors are already experimenting with prompt injection, model manipulation, and adversarial exploits. Real-time monitoring and anomaly detection can help surface issues before they cascade into broader failures.

DeepSeek’s decision to share elements of its model code reflects a broader trend: major players are starting to engage more with the open source AI community, even if full transparency remains elusive. For enterprises consuming these models, this growing accessibility is an opportunity and a responsibility. The fact that a model is available doesn’t mean it’s trustworthy by default. Security, oversight, and governance must be applied downstream to ensure these tools are safe, compliant, and aligned with business objectives.

In the race to deploy AI, trust is the foundation. And trust requires visibility, accountability, and governance every step of the way.

Brian Fox is co-founder and chief technology officer at Sonatype, a software supply chain security company.

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The United States’ Cybersecurity and Infrastructure Security Agency (CISA) is likely to have its funding cut by approximately $495m and may have to lay off around 1,000 employees later this year, according to budget proposals unveiled by President Trump’s administration.

In a written statement, the White House said Trump was “laser-focused on eliminating … weaponised rot” in the American government as he laid out a series of cuts to multiple agencies.

“The Budget eliminates CISA’s disinformation offices and programmes that functioned as a hub in the censorship industrial complex, conspiring against the First Amendment rights of President Trump and his supporters,” the statement reads.

The First Amendment to the Constitution, which dates back to 1791, guarantees freedom of assembly, the press, religion and speech in the US.

“CISA was more focused on cooperating with big tech to target free speech than our nation’s critical systems,” said the White House. “Even CISA’s own systems have fallen prey to attacks. Under President Trump’s leadership, CISA will protect our critical infrastructure instead of censoring Americans. The budget refocuses CISA on its core mission – federal network defence and coordinating with critical infrastructure partners – while eliminating weaponisation and waste. The budget also streamlines the agency by consolidating redundant security advisors and programmes.”

Besides the elimination of its work countering “disinformation”, the budget cuts money from CISA’s government network and critical infrastructure protection operations, and its provision of support and services to companies and local government bodies in America. CISA will also have to take an axe to divisions that work to analyse and predict future threats, among other things.

Other planned cuts potentially affecting the US’ cyber security mission include proposals to trim the budget allocated to the FBI, which deals with cyber crime in the US, and a unit at the Department of Energy that deals with threats to CNI.

A globally recognised force

Officially established during Trump’s first administration, with origins dating back to 2007 when the US established the National Protections and Programs Directorate within the Department of Homeland Security (DHS), CISA has grown into one of the leading western cyber security agencies working alongside the likes of the UK’s National Cyber Security Centre (NCSC) and counterparts in Australia, Canada, Europe and New Zealand.

It frequently leads on multilateral advisories and alerts on cyber matters including cyber crime and ransomware and nation state threats, and its Known Exploited Vulnerabilities (KEV) catalogue is a globally recognised resource.

However, leadership had clashed with Trump in the past – CISA’s founding director Chris Krebs was given his marching orders after the 2020 Presidential Election.

Gabrielle Hempel, security operations strategist and threat intelligence researcher at the Exabeam TEN18 unit, described a “strategic deprecation” of America’s cyber defence capabilities at a time when threat actors were only widening the scope of their activities.

“Gutting critical programmes …  doesn’t ‘refocus’ the mission – it hollows it out. These teams drive cross-sector collaboration, provide threat modeling to CNI operators and build resilience in a space where private-sector entities own the vast majority of the target surface,” said Hempel.

“If the intent of these cuts is to ‘focus on core mission’, the question is: whose definition of core? Threat visibility, regional coordination, intelligence sharing, and vulnerability analysis are core to a functional national cyber strategy.

“The reality is, we don’t get to pick when or where the next attack happens – but we do decide whether we’ll be ready. Bluntly, this plan is guaranteeing that we won’t be,” she said.

Hempel also lamented the proposed elimination of election security funding at a time when threat actors both within and without the US are actively working to undermine democratic processes.

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UK workers with skills in artificial intelligence (AI) appear to earn 11% more on average, even in sectors where AI is automating parts of their existing job functions.

Workers in sectors exposed to AI, where the technology can be deployed for some tasks, are more productive and command higher salaries, according to PwC’s 2025 Global AI Jobs Barometer. The study, which was based on an analysis of almost one billion job adverts, found that wages are rising twice as fast in industries most exposed to AI.

From a skills perspective, PwC reported that AI is changing the skills required of job applicants. According to PwC, to succeed in the workplace, candidates are more likely to need experience in using AI tools and the ability to demonstrate critical thinking and collaboration.

Phillippa O’Connor, chief people officer at PwC UK, noted that while degrees are still important for many jobs, a reduction in degree requirements suggests employers are looking at a broader range of measures to assess skills and potential.

In occupations most exposed to AI, PwC noted that the skills sought by employers are changing 59% faster than in occupations least exposed to AI. “AI is reshaping the jobs market – lowering barriers to entry in some areas, while raising the bar on the skills required in others,” O’Connor added.

Those with the right AI skills are being rewarded with higher salaries. In fact, PwC found that wages are growing twice as fast in AI-exposed industries. This includes jobs that are classed as “automatable”, which means they contain some tasks that can readily be automated. The highest premiums are attached to occupations requiring AI skills, with an average premium in 2024 of 11% for UK workers in these roles.  

AI is reshaping the jobs market – lowering barriers to entry in some areas, while raising the bar on the skills required in others Phillippa O’Connor PwC UK

PwC’s analysis shows that sectors exposed to AI experience three times higher growth in the revenue generated by each employee. It also reported that growth in revenue per employee for AI-exposed industries surged when large language models (LLMs) such as generative AI (GenAI) became mainstream.

Revenue growth per employee has nearly quadrupled in industries most exposed to AI, such as software, rising from 7% between 2018 and 2022, to 27% between 2018 and 2024. In contrast, revenue growth per employee in industries least exposed to AI, such as mining and hospitality, fell slightly, from 10% between 2018 and 2022, to 9% between 2018 and 2024.

However, since 2018, job postings for occupations with greater exposure to AI have grown at a slower pace than those with lower exposure – and this gap is widening.

Umang Paw, chief technology officer (CTO) at PwC UK, said: “There are still many unknowns about AI’s potential. AI can provide stardust to those ready to adapt, but risks leaving others behind.”

Paw believes there needs to be a concerted effort to expand access to technology and training to ensure the benefits of AI are widely shared.

“In the intelligence age, the fusion of AI with technologies like real-time data analytics – and businesses broadening their products and services – will create new industries and fresh job opportunities,” Paw added.

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OpenAI CEO Sam Altman said on X earlier this week that ChatGPT o3-pro will launch this summer for ChatGPT Pro users paying $200/month. While o3-pro isn’t ready yet, OpenAI has rolled out other updates for ChatGPT users. The company introduced a few new ChatGPT features aimed at delivering a more personal chatbot experience.

That’s not surprising since OpenAI wants to turn ChatGPT into a super-assistant this year. It’s also working on the first ChatGPT io device, expected to launch next year. That kind of hardware will require a much more personal ChatGPT experience.

After bringing chat memory support to ChatGPT Free users on Tuesday, OpenAI shifted focus to enterprise users with new ChatGPT features. That might not mean much to those not using Team or Enterprise tiers, but these updates mark early steps toward making ChatGPT a more personal assistant.

OpenAI introduced a new Connectors feature that lets businesses link ChatGPT to specific data sources. This includes Google apps like Gmail and Calendar, Microsoft apps like Outlook and Teams, and cloud storage services such as Box, Dropbox, and Google Drive.

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More interestingly, organizations can add custom Connectors to ChatGPT using that MCP AI feature we mentioned a few days ago. MCP allows AIs like ChatGPT to connect to external sources for information.

As I said, this might sound dull if you’re not using ChatGPT at work, but it’s a key move by OpenAI to solve one of its bigger challenges. Unlike Google and Microsoft, OpenAI doesn’t have its own suite of beloved apps. ChatGPT can’t access first-party apps the way Gemini can. That’s a hurdle if you’re building a super-assistant AI. But if it can link to third-party data sources, that hurdle disappears.

Think of it this way: You could ask ChatGPT to check your Gmail for emails from family and summarize plans for your next get-together. Right now, ChatGPT can’t do that.

But if you’re on an enterprise plan, you’ll be able to let ChatGPT access your work Gmail and extract the info you need.

OpenAI hosted a livestream about 22 minutes long to demo the new Connectors feature. They created a fictional company with generated emails and cloud data to show how ChatGPT can easily connect to external sources.

The clip shows a Deep Research run where the AI pulls data from internal sources like HubSpot, Outlook, SharePoint, and Teams. The final report includes citations so you can check the documents ChatGPT referenced before summarizing.

Another demo involved asking ChatGPT a question about the company’s plans. The AI pulled info from internal documents stored in Google Drive and elsewhere, providing links to files the user could access. ChatGPT will only use data that the user is authorized to see.

The new record button is available in the Composer window. Image source: OpenAI

OpenAI also released a new Record Mode for the Mac ChatGPT app that lets the AI record meetings in real time. It will transcribe the meetings and provide summaries with timestamps, so you can jump back to specific parts of the transcription.

The demos targeted enterprise customers, but this is just the beginning. ChatGPT is likely to get more Connectors down the line, eventually opening them up to personal users as well.

OpenAI said on X that Connectors are “available in deep research for Plus & Pro users (excl. EEA, CH, UK) and Team, Enterprise & Edu users.” So, like usual, I can’t use them yet. Still, this means ChatGPT Plus and Pro users are also getting access.

ChatGPT can record audio via the Mac app. Image source: OpenAI

I’ll also note that the recent ChatGPT redesign makes a lot more sense now. OpenAI was clearly setting up the new Composer window to support Connectors.

It won’t be long before ChatGPT becomes a reliable assistant. With memory support and access to personal data sources, it’s getting close.

While we wait, OpenAI’s full demo video is below:

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One of the great things about Amazon is its fast delivery options, especially if you’re an Amazon Prime subscriber. That speed is made possible by a massive logistics operation. Amazon stocks products in huge warehouses around the world, and those fulfillment centers can quickly ship goods to nearby customers once an order is placed.

Amazon has also come up with new ideas to improve delivery times, like using drones in certain regions or shipping goods directly to your home or car.

It’s no surprise that the next big idea to enhance Amazon deliveries (and reduce costs) involves artificial intelligence. Amazon is reportedly considering using humanoid robots powered by generative AI programs to deliver packages to your door.

That kind of test makes sense, given the AI boom we’re living through. Most of us interact with AI through apps on our phones or desktops, but we’ve also seen impressive advances in genAI for robotics in recent years. Soon enough, humanoid robots will use AI software to understand their surroundings and carry out instructions.

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Those instructions might involve telling a Unitree G1 robot (above) to hop out of a Rivian car when it reaches your neighborhood, grab the correct package from the back, and deliver it to your door. This is no longer science fiction, and Amazon is reportedly testing just such scenarios.

According to The Information (via The Verge), Amazon is conducting tests at one of its San Francisco facilities.

Amazon has reportedly built an indoor humanoid park about the size of a coffee shop. The obstacle course includes a Rivian van so the robots can practice the full package delivery process.

The company is testing various humanoid robots for this task, including the $16,000 Unitree G1 robot we covered a few months ago. I said then that I’d eventually want one of these for help around the house. If Amazon’s tests go well, G1-style robots could be delivering orders before that day comes.

The Digit robot in an Amazon warehouse. Image source: Amazon

A few years ago, Amazon confirmed it was testing a humanoid robot called Digit from Agility Robotics. Those tests focused on warehouse work.

The current delivery tests haven’t been officially confirmed, but The Information has a strong track record when it comes to inside scoops on tech companies.

Amazon also made a few AI-related announcements this week about its shipping logistics that seem to back up The Information’s report.

According to Reuters, Amazon has created a new group at its Lab126 device unit focused on developing more capable warehouse robots. These machines will be able to handle more tasks than Amazon’s current robots.

“We’re creating systems that can hear, understand, and act on natural language commands, turning warehouse robots into flexible, multi-talented assistants,” Amazon said in a statement.

The new robots will feature agentic AI that enables them to unload trailers and retrieve parts for repairs. That, in turn, should speed up delivery times for customers, according to Lab126 leader Yesh Dattatreya.

Separately, Amazon plans to use generative AI for improved mapping tools that will help drivers deliver packages more efficiently. The AI will provide more accurate building details than standard mapping apps, including shapes, obstacles, and tricky layouts.

Reuters suggests the tech might be paired with AR glasses Amazon is developing for drivers.

I’d add that this kind of AI software would also benefit humanoid robots making doorstep deliveries.

We don’t yet know when AI-powered robots will start delivering packages or where they’ll be deployed first. But given the pace of development in AI robotics, it probably won’t be long, whether Amazon leads the way or someone else does.

There’s one obvious issue that hasn’t been addressed. Humanoid AI robots will eventually replace human workers, marking another way AI could take over human jobs. It’ll be interesting to see how Amazon handles that messaging, especially considering its less-than-stellar history with employee relations.

You can check out the following video to see what a Unitree G1 robot is capable of right now. For more on AI robotics, here’s what Figure and Google are working on.

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The National Grid has confirmed that it is in the process of building its largest new electrical substation in response to the growing demand for datacentres in West London.

The facility will be sited just outside of Greater London in Buckinghamshire and will, according to the National Grid, enable a dozen new datacentres to be connected to its electricity transmission network.

“The new site forms part of National Grid’s upgrade to its transmission network to meet growing demand for electricity, ensuring it can continue to support the growth of new sectors, such as datacentres, and the economic and employment benefits they can bring,” the National Grid said in a statement. 

Dubbed Uxbridge Moor, the substation is being built next door to another 400kV substation in Iver, Buckinghamshire, that is at full capacity and cannot be expanded further. It will be comprised of two substations, including one 400kV facility and another with 132kV of capacity.

“The requests from datacentres to connect at Uxbridge Moor will require around 1.8GW of new capacity, equivalent to adding a mid-sized city to the grid on the outskirts of London,” said the National Grid. “When built, it will be the largest new substation on National Grid’s network by gigawatt capacity.”

The work is part of a planned five-year investment push, valued at £35bn, by the National Grid that is geared towards increasing the UK’s electricity generation capacity and making it easier for datacentres and gigafactories to connect to the grid.

The part of the country where the substation will be built has seen a influx of datacentres over the course of the past decade, prompting concerns about whether there is sufficient supply and grid capacity to service them all.

This matter came to a head in 2022 when a briefing note from the Greater London Authority’s Development Service began to circulate that claimed an influx of datacentres meant the electricity and transmission networks in West London were struggling to cope with the demand being placed on them.

Energy minister Michael Shanks said that projects such as this are essential to the government’s ability to deliver on initiatives, such as its push to lower the barriers to datacentre developments in the UK.

“Upgrades to the electricity network like this are at the heart of building the industries of our future and support our Plan for Change to deliver economic growth and skilled jobs across the UK,” said Shanks.

“It comes as we progress our reforms to the grid connections queue that will speed up the time it takes to get high-growth firms, like datacentres and AI hubs, plugged into the grid – while also fast-tracking projects that will scale up clean, homegrown power by 2030.”

Laura Mulcahy, project director at National Grid Electricity Transmission, said the substation’s creation will generate a wide range of economic benefits. 

“Our new Uxbridge Moor substation will provide vital access to power for datacentres that are at the heart of Britain’s innovation and economic growth,” she said. “It will enable new jobs and investment in Buckinghamshire, and will support the UK’s digital future.”

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