Capacity development

China’s Silk Typhoon hackers filed patents for advanced spyware tools

A Chinese state-backed hacking group known as Silk Typhoon has filed more than ten patents for intrusive cyberespionage tools, shedding light on its operations’ vast scope and sophistication.

These patents, registered by firms linked to China’s Ministry of State Security, detail covert data collection software far exceeding the group’s previously known attack methods.

The revelations surfaced following a July 2025 US Department of Justice indictment against two alleged members of Silk Typhoon, Xu Zewei and Zhang Yu.

Both are associated with companies tied to the Shanghai State Security Bureau and connected to the Hafnium group, which Microsoft rebranded as Silk Typhoon in 2022.

Instead of targeting only Windows environments, the patent filings reveal a sweeping set of surveillance tools designed for Apple devices, routers, mobile phones, and even smart home appliances.

Submissions include software for bypassing FileVault encryption, extracting remote cellphone data, decrypting hard drives, and analysing smart devices. Analysts from SentinelLabs suggest these filings offer an unprecedented glimpse into the architecture of China’s cyberwarfare ecosystem.

Silk Typhoon gained global attention in 2021 with its Microsoft Exchange ProxyLogon campaign, which prompted a rare coordinated condemnation by the US, UK, and EU. The newly revealed capabilities show the group’s operations are far more advanced and diversified than previously believed.

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OpenAI and Nscale to build an AI super hub in Norway

OpenAI has revealed its first European data centre project in partnership with British startup Nscale, selecting Norway as the location for what is being called ‘Stargate Norway’.

The initiative mirrors the company’s ambitious $500 billion US ‘Stargate’ infrastructure plan and reflects Europe’s growing demand for large-scale AI computing capacity.

Nscale will lead the development of a $1 billion AI gigafactory in Norway, with engineering firm Aker matching the investment. These advanced data centres are designed to meet the heavy processing requirements of cutting-edge AI models.

OpenAI expects the facility to deliver 230MW of computing power by the end of 2026, making it a significant strategic foothold for the company on the continent.

Sam Altman, CEO of OpenAI, stated that Europe needs significantly more computing to unlock AI’s full potential for researchers, startups, and developers. He said Stargate Norway will serve as a cornerstone for driving innovation and economic growth in the region.

Nscale confirmed that Norway’s AI ecosystem will receive priority access to the facility, while remaining capacity will be offered to users across the UK, Nordics and Northern Europe.

The data centre will support 100,000 of NVIDIA’s most advanced GPUs, with long-term plans to scale as demand grows.

The move follows broader European efforts to strengthen AI infrastructure, with the UK and France pushing for major regulatory and funding reforms.

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Google rolls out AI age detection to protect teen users

In a move aimed at enhancing online protections for minors, Google has started rolling out a machine learning-based age estimation system for signed-in users in the United States.

The new system uses AI to identify users who are likely under the age of 18, with the goal of providing age-appropriate digital experiences and strengthening privacy safeguards.

Initially deployed to a small number of users, the system is part of Google’s broader initiative to align its platforms with the evolving needs of children and teenagers growing up in a digitally saturated world.

‘Children today are growing up with technology, not growing into it like previous generations. So we’re working directly with experts and educators to help you set boundaries and use technology in a way that’s right for your family,’ the company explained in a statement.

The system builds on changes first previewed earlier this year and reflects Google’s ongoing efforts to comply with regulatory expectations and public demand for better youth safety online.

Once a user is flagged by the AI as likely underage, Google will introduce a range of restrictions—most notably in advertising, content recommendation, and data usage.

According to the company, users identified as minors will have personalised advertising disabled and will be shielded from ad categories deemed sensitive. These protections will be enforced across Google’s entire advertising ecosystem, including AdSense, AdMob, and Ad Manager.

The company’s publishing partners were informed via email this week that no action will be required on their part, as the changes will be implemented automatically.

Google’s blog post titled ‘Ensuring a safer online experience for US kids and teens’ explains that its machine learning model estimates age based on behavioural signals, such as search history and video viewing patterns.

If a user is mistakenly flagged or wishes to confirm their age, Google will offer verification tools, including the option to upload a government-issued ID or submit a selfie.

The company stressed that the system is designed to respect user privacy and does not involve collecting new types of data. Instead, it aims to build a privacy-preserving infrastructure that supports responsible content delivery while minimising third-party data sharing.

Beyond advertising, the new protections extend into other parts of the user experience. For those flagged as minors, Google will disable Timeline location tracking in Google Maps and also add digital well-being features on YouTube, such as break reminders and bedtime prompts.

Google will also tweak recommendation algorithms to avoid promoting repetitive content on YouTube, and restrict access to adult-rated applications in the Play Store for flagged minors.

The initiative is not Google’s first foray into child safety technology. The company already offers Family Link for parental controls and YouTube Kids as a tailored platform for younger audiences.

However, the deployment of automated age estimation reflects a more systemic approach, using AI to enforce real-time, scalable safety measures. Google maintains that these updates are part of a long-term investment in user safety, digital literacy, and curating age-appropriate content.

Similar initiatives have already been tested in international markets, and the company announces it will closely monitor the US rollout before considering broader implementation.

‘This is just one part of our broader commitment to online safety for young users and families,’ the blog post reads. ‘We’ve continually invested in technology, policies, and literacy resources to better protect kids and teens across our platforms.’

Nonetheless, the programme is likely to attract scrutiny. Critics may question the accuracy of AI-powered age detection and whether the measures strike the right balance between safety, privacy, and personal autonomy — or risk overstepping.

Some parents and privacy advocates may also raise concerns about the level of visibility and control families will have over how children are identified and managed by the system.

As public pressure grows for tech firms to take greater responsibility in protecting vulnerable users, Google’s rollout may signal the beginning of a new industry standard.

The shift towards AI-based age assurance reflects a growing consensus that digital platforms must proactively mitigate risks for young users through smarter, more adaptive technologies.

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Microsoft’s Cloud and AI strategy lifts revenue beyond expectations

Microsoft has reported better-than-expected results for the fourth quarter of its 2025 fiscal year, attributing much of its success to the continued expansion of its cloud services and the integration of AI.

‘Cloud and AI are the driving force of business transformation across every industry and sector,’ said Satya Nadella, Microsoft’s chairman and chief executive, in a statement on Wednesday.

For the first time, Nadella disclosed annual revenue figures for Microsoft Azure, the company’s cloud computing platform. Azure generated more than $75 billion in the fiscal year ending 30 June, representing a 34 percent increase compared to the previous year.

Nadella noted that this growth was ‘driven by growth across all workloads’, including those powered by AI. On average, Azure contributed approximately $19 billion in revenue per quarter.

While this trails Amazon Web Services (AWS), which posted net sales of $29 billion in the first quarter alone, Azure remains a strong second in the cloud market. Google Cloud, by comparison, has an annual run rate of $50 billion, according to parent company Alphabet’s Q2 2025 earnings report.

‘We continue to lead the AI infrastructure wave and took share each quarter this year,’ Nadella told investors during the company’s earnings call.

However, he did not provide specific figures showing how AI factored into the results, a point of interest for financial analysts given Microsoft’s projected $80 billion in capital expenditures this fiscal year to support AI-related data centre expansion.

During the call, Bernstein Research senior analyst Mark Moerdler asked how businesses might ultimately monetise AI as a software service.

Nadella responded with a broad comparison to the cloud business, suggesting the two were now deeply connected. It was left to CFO Amy Hood to offer a more structured explanation.

‘There’s a per-user logic,’ Hood explained. ‘There are tiers of per-user. Sometimes those tiers relate to consumption. Sometimes there are pure consumption models. I think you’ll continue to see a blending of these, especially as the AI model capability grows.’

In essence, Microsoft intends to monetise AI in a manner similar to its traditional software offerings—charging either per user, by usage tier, or based on consumption.

With AI now embedded across Microsoft’s portfolio of products and services, the company appears to be positioning itself to keep attributing more of its revenue to AI-powered innovation.

The numbers suggest there is plenty of revenue to go around. Microsoft posted $76.4 billion in revenue for the quarter, up 18 percent compared to the same period last year.

Operating income stood at $34.3 billion (up 23 percent), with net income reaching $27.2 billion (up 24 percent). Earnings per share climbed 24 percent to $3.65.

For the full fiscal year, Microsoft reported $281.7 billion in revenue—an increase of 15 percent. Operating income rose to $128.5 billion (up 17 percent), while net income hit $101.8 billion (up 16 percent). Annual earnings per share reached $13.64, also up by 16 percent.

Azure forms part of Microsoft’s Intelligent Cloud division, which generated $29.9 billion in quarterly revenue, a 26 percent year-on-year increase.

The Productivity and Business Processes group, which includes Microsoft 365, LinkedIn, and Dynamics, managed to earn $33.1 billion, upping its revenue by 16 percent. Meanwhile, the More Personal Computing segment, covering Windows, Xbox, and advertising, grew nine percent to $13.5 billion.

Despite some concerns among analysts regarding Microsoft’s significant capital spending and the ambiguous short-term returns on AI investments, investor confidence remains strong.

Microsoft’s share price jumped roughly eight percent after the earnings announcement, pushing its market capitalisation above $4 trillion in after-hours trading. It became only the second company, after Nvidia, to cross that symbolic threshold.

Market observers noted that while questions remain over the precise monetisation of AI, Microsoft’s aggressive positioning in cloud infrastructure and AI services has clearly resonated with shareholders.

With AI now woven into the company’s strategic fabric, Microsoft appears determined to maintain its lead in the next phase of enterprise computing.

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Apple’s $20B Google deal under threat as AI lags behind rivals

Apple is set to release Q3 earnings on Thursday amid scrutiny over its Google search deal dependencies and ongoing struggles with AI progress.

Typically, Apple’s fiscal Q3 garners less investor attention, with anticipation focused instead on the upcoming iPhone launch in Q4. However, this quarter is proving to be anything but ordinary.

Analysts and shareholders alike are increasingly concerned about two looming threats: a potential $20 billion hit to Apple’s Services revenue tied to the US Department of Justice’s (DOJ) antitrust case against Google, and ongoing delays in Apple’s AI efforts.

Ahead of the earnings report, Apple shares were mostly unchanged, reflecting investor caution rather than enthusiasm. Apple’s most pressing challenge stems from its lucrative partnership with Google.

In 2022, Google paid Apple approximately $20 billion to remain the default search engine in the Safari browser and across Siri.

The exclusivity deal has formed a significant portion of Apple’s Services segment, which generated $78.1 billion in revenue that year, making Google’s contribution alone account for more than 25% of that figure.

However, a ruling expected next month from Judge Amit Mehta in the US District Court for the District of Columbia could threaten the entire arrangement. Mehta previously found Google guilty of operating an illegal monopoly in the search market.

The forthcoming ‘remedies’ ruling could force Google to end exclusive search deals, divest its Chrome browser, and provide data access to rivals. Should the DOJ’s proposed remedies stand and Google fails to overturn the ruling, Apple could lose a critical source of Services revenue.

According to Morgan Stanley’s Erik Woodring, Apple could see a 12% decline in its full-year 2027 earnings per share (EPS) if it pivots to less lucrative partnerships with alternative search engines.

The user experience may also deteriorate if customers can no longer set Google as their default option. A more radical scenario, Apple launching its search engine, could dent its 2024 EPS by as much as 20%, though analysts believe this outcome is the least likely.

Alongside regulatory threats, Apple is also facing growing doubts about its ability to compete in AI. Apple has not yet set a clear timeline for releasing an upgraded version of Siri, while rivals accelerate AI hiring and unveil new capabilities.

Bank of America analyst Wamsi Mohan noted this week that persistent delays undermine confidence in Apple’s ability to deliver innovation at the pace. ‘Apple’s ability to drive future growth depends on delivering new capabilities and products on time,’ he wrote to investors.

‘If deadlines keep slipping, that potentially delays revenue opportunities and gives competitors a larger window to attract customers.’

While Apple has teased upcoming AI features for future software updates, the lack of a commercial rollout or product roadmap has made investors uneasy, particularly as rivals like Microsoft, Google, and OpenAI continue to set the AI agenda.

Although Apple’s stock remained stable before Thursday’s earnings release, any indication of slowing services growth or missed AI milestones could shake investor confidence.

Analysts will be watching closely for commentary from CEO Tim Cook on how Apple plans to navigate regulatory risks and revive momentum in emerging technologies.

The company’s current crossroads is pivotal for the tech sector more broadly. Regulators are intensifying scrutiny on platform dominance, and AI innovation is fast becoming the new battleground for long-term growth.

As Apple attempts to defend its business model and rekindle its innovation edge, Thursday’s earnings update could serve as a bellwether for its direction in the post-iPhone era.

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VPN dangers highlighted as UK’s Online Safety Act comes into force

Britons are being urged to proceed with caution before turning to virtual private networks (VPNs) in response to the new age verification requirements set by the Online Safety Act.

The law, now in effect, aims to protect young users by restricting access to adult and sensitive content unless users verify their age.

Instead of offering anonymous access, some platforms now demand personal details such as full names, email addresses, and even bank information to confirm a user’s age.

Although the legislation targets adult websites, many people have reported being blocked from accessing less controversial content, including alcohol-related forums and parts of Wikipedia.

As a result, more users are considering VPNs to bypass these checks. However, cybersecurity experts warn that many VPNs can pose serious risks by exposing users to scams, data theft, and malware. Without proper research, users might install software that compromises their privacy rather than protecting it.

With Ofcom reporting that eight per cent of children aged 8 to 14 in the UK have accessed adult content online, the new rules are viewed as a necessary safeguard. Still, concerns remain about the balance between online safety and digital privacy for adult users.

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Australian companies unite cybersecurity defences to combat AI threats

Australian companies are increasingly adopting unified, cloud-based cybersecurity systems as AI reshapes both threats and defences.

A new report from global research firm ISG reveals that many enterprises are shifting away from fragmented, uncoordinated tools and instead opting for centralised platforms that can better detect and counter sophisticated AI-driven attacks.

The rapid rise of generative AI has introduced new risks, including deepfakes, voice cloning and misinformation campaigns targeting elections and public health.

In response, organisations are reinforcing identity protections and integrating AI into their security operations to improve both speed and efficiency. These tools also help offset a growing shortage of cybersecurity professionals.

After a rushed move to the cloud during the pandemic, many businesses retained outdated perimeter-focused security systems. Now, firms are switching to cloud-first strategies that target vulnerabilities at endpoints and prevent misconfigurations instead of relying on legacy solutions.

By reducing overlap in systems like identity management and threat detection, businesses are streamlining defences for better resilience.

ISG also notes a shift in how companies choose cybersecurity providers. Firms like IBM, PwC, Deloitte and Accenture are seen as leaders in the Australian market, while companies such as TCS and AC3 have been flagged as rising stars.

The report further highlights growing demands for compliance and data retention, signalling a broader national effort to enhance cyber readiness across industries.

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AI won’t replace coaches, but it will replace coaching without outcomes

Many coaches believe AI could never replace the human touch. They pride themselves on emotional intelligence — their empathy, intuition, and ability to read between the lines. They consider these traits irreplaceable. But that belief could be costing them their business.

The reason AI poses a real threat to coaching isn’t because machines are becoming more human. It’s because they’re becoming more effective. And clients aren’t hiring coaches for human connection — they’re hiring them for outcomes.

People seek coaches to overcome challenges, make decisions, or experience a transformation. They want results — and they want them as quickly and painlessly as possible. If AI can deliver those results faster and more conveniently, many clients will choose it without hesitation.

So what should coaches do? They shouldn’t ignore AI, fear it, or dismiss it as a passing fad. Instead, they should learn how to integrate it. Live, one-to-one sessions still matter. They provide the deepest insights and most lasting impact. But coaching must now extend beyond the session.

Coaching must be supported by systems that make success inevitable — and AI is the key to building those systems. Here lies a fundamental disconnect: coaches often believe their value lies in personal connections.

Clients, on the other hand, value results. The gap is where AI is stepping in — and where forward-thinking coaches are stepping up. Currently, most coaches are trapped in a model that trades time for money. More sessions, they assume, equals more transformation.

However, this model doesn’t scale. Many are burning out trying to serve everyone personally. Meanwhile, the most strategic among them are turning their coaching into scalable assets: digital products, automated workflows, and AI-trained tools that do their job around the clock.

They’re not being replaced by AI. They’re being amplified by it. The coaches are packaging their methods into online courses that clients can revisit between sessions. They’re building tools that track client progress automatically, offering midnight reassurance when doubts creep in.

The coaches are even training AI on their own frameworks, allowing clients to access support informed by the coach’s actual thinking — not generic chatbot responses. The business model in question isn’t science fiction. It’s already happening.

AI can be trained on your transcripts, methodologies, and session notes. It can conduct initial assessments and reinforce your teachings between meetings. Your clients receive consistent, on-demand support — and you free up time for the deep, human work only you can do.

Coaches who embrace this now will dominate their niches tomorrow. Even the content generated from coaching sessions is underutilised. Every call contains valuable insights — breakthroughs, reframes, moments of clarity.

The insights shouldn’t stay confined to just one client. Strip away personal details, extract the universal truths, and turn those insights into content that attracts your next ideal client. AI can also help you uncover patterns across your coaching history.

Feed your notes into analysis tools, and you might find that 80% of your executive clients hit the same obstacle in month three. Or that a particular intervention consistently delivers rapid breakthroughs.

The insights help you refine your practice and anticipate challenges before they arise — making your coaching more effective and less predictable. Then there’s the admin. Scheduling, invoicing, progress tracking — all of it can be automated.

Tools like Zapier or Make can optimise such repetitive tasks, giving you back hours each week. That’s time better spent on transformation, not operations. Your clients don’t want tradition. They want transformation.

The coaches who succeed in this new era will be those who understand that human insight and AI systems are not in competition. They’re complementary. Choose one area where AI could support your work — a progress tracker, a digital guide, or a content workflow. Start there.

The future of coaching doesn’t belong to the ones who resist AI. It belongs to those who combine wisdom with scalability. Your enhanced coaching model is waiting to be built — and your future clients are waiting to experience it.

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Alignment Project to tackle safety risks of advanced AI systems

The UK’s Department for Science, Innovation and Technology (DSIT) has announced a new international research initiative aimed at ensuring future AI systems behave in ways aligned with human values and interests.

Called the Alignment Project, the initiative brings together global collaborators including the Canadian AI Safety Institute, Schmidt Sciences, Amazon Web Services (AWS), Anthropic, Halcyon Futures, the Safe AI Fund, UK Research and Innovation, and the Advanced Research and Invention Agency (ARIA).

DSIT confirmed that the project will invest £15 million into AI alignment research – a field concerned with developing systems that remain responsive to human oversight and follow intended goals as they become more advanced.

Officials said this reflects growing concerns that today’s control methods may fall short when applied to the next generation of AI systems, which are expected to be significantly more powerful and autonomous.

This positioning reinforces the urgency and motivation behind the funding initiative, before going into the mechanics of how the project will work.

The Alignment Project will provide funding through three streams, each tailored to support different aspects of the research landscape. Grants of up to £1 million will be made available for researchers across a range of disciplines, from computer science to cognitive psychology.

A second stream will provide access to cloud computing resources from AWS and Anthropic, enabling large-scale technical experiments in AI alignment and safety.

The third stream focuses on accelerating commercial solutions through venture capital investment, supporting start-ups that aim to build practical tools for keeping AI behaviour aligned with human values.

An expert advisory board will guide the distribution of funds and ensure that investments are strategically focused. DSIT also invited further collaboration, encouraging governments, philanthropists, and industry players to contribute additional research grants, computing power, or funding for promising start-ups.

Science, Innovation and Technology Secretary Peter Kyle said it was vital that alignment research keeps pace with the rapid development of advanced systems.

‘Advanced AI systems are already exceeding human performance in some areas, so it’s crucial we’re driving forward research to ensure this transformative technology is behaving in our interests,’ Kyle said.

‘AI alignment is all geared towards making systems behave as we want them to, so they are always acting in our best interests.’

The announcement follows recent warnings from scientists and policy leaders about the risks posed by misaligned AI systems. Experts argue that without proper safeguards, powerful AI could behave unpredictably or act in ways beyond human control.

Geoffrey Irving, chief scientist at the AI Safety Institute, welcomed the UK’s initiative and highlighted the need for urgent progress.

‘AI alignment is one of the most urgent and under-resourced challenges of our time. Progress is essential, but it’s not happening fast enough relative to the rapid pace of AI development,’ he said.

‘Misaligned, highly capable systems could act in ways beyond our ability to control, with profound global implications.’

He praised the Alignment Project for its focus on international coordination and cross-sector involvement, which he said were essential for meaningful progress.

‘The Alignment Project tackles this head-on by bringing together governments, industry, philanthropists, VC, and researchers to close the critical gaps in alignment research,’ Irving added.

‘International coordination isn’t just valuable – it’s necessary. By providing funding, computing resources, and interdisciplinary collaboration to bring more ideas to bear on the problem, we hope to increase the chance that transformative AI systems serve humanity reliably, safely, and in ways we can trust.’

The project positions the UK as a key player in global efforts to ensure that AI systems remain accountable, transparent, and aligned with human intent as their capabilities expand.

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White House launches AI Action Plan with Executive Orders on exports and regulation

The White House has unveiled a sweeping AI strategy through its new publication Winning the Race: America’s AI Action Plan.

Released alongside three Executive Orders, the plan outlines the federal government’s next phase in shaping AI policy, focusing on innovation, infrastructure, and global leadership.

The AI Action Plan centres on three key pillars: accelerating AI development, establishing national AI infrastructure, and promoting American AI standards globally. Four consistent themes run through each pillar: regulation and deregulation, investment, research and standardisation, and cybersecurity.

Notably, deregulation is central to the plan’s strategy, particularly in reducing barriers to AI growth and speeding up infrastructure approval for data centres and grid expansion.

Investment plays a dominant role. Federal funds will support AI job training, data access, lab automation, and domestic component manufacturing, instead of relying on foreign suppliers.

Alongside, the plan calls for new national standards, improved dataset quality, and stronger evaluation mechanisms for AI interpretability, control, and safety. A dedicated AI Workforce Research Hub is also proposed.

In parallel, three Executive Orders were issued. One bans ‘woke’ or ideologically biased AI tools in federal use, another fast-tracks data centre development using federal land and brownfield sites, and a third launches an AI exports programme to support full-stack US AI systems globally.

While these moves open new opportunities, they also raise questions around regulation, bias, and the future shape of AI development in the US.

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