As Meta AI grows smarter on its own, critics warn of regulatory gaps

While OpenAI’s ChatGPT and Google’s Gemini dominate headlines, Meta’s AI is making quieter, but arguably more unsettling, progress. According to CEO Mark Zuckerberg, Meta’s AI is advancing rapidly and, crucially, learning to improve without external input.

In a blog post titled ‘Personal Superintelligence’, Zuckerberg claimed that Meta AI is becoming increasingly powerful through self-directed development. While he described current gains as modest, he emphasised that the trend is both real and significant.

Zuckerberg framed this as part of a broader mission to build AI that acts as a ‘personal superintelligence’, a tool that empowers individuals and becomes widely accessible. However, critics argue this narrative masks a deeper concern: AI systems that can evolve autonomously, outside human guidance or scrutiny.

The concept of self-improving AI is not new. Researchers have previously built systems capable of learning from other models or user interactions. What’s different now is the speed, scale and opacity of these developments, particularly within big tech companies operating with minimal public oversight.

The progress comes amid weak regulation. While governments like the Biden administration have issued AI action plans, experts say they lack the strength to keep up. Meanwhile, AI is rapidly spreading across everyday services, from healthcare and education to biometric verification.

Recent examples include Google’s behavioural age-estimation tools for teens, illustrating how AI is already making high-stakes decisions. As AI systems become more capable, questions arise: How much data will they access? Who controls them? And can the public meaningfully influence their design?

Zuckerberg struck an optimistic tone, framing Meta’s AI as democratic and empowering. However, that may obscure the risks of AI outpacing oversight, as some tech leaders warn of existential threats while others focus on commercial gains.

The lack of transparency worsens the problem. If Meta’s AI is already showing signs of self-improvement, are similar developments happening in other frontier models, such as GPT or Gemini? Without independent oversight, the public has no clear way to know—and even less ability to intervene.

Until enforceable global regulations are in place, society is left to trust that private firms will self-regulate, even as they compete in a high-stakes race for dominance. That’s a risky gamble when the technology itself is changing faster than we can respond.

As Meta AI evolves with little fanfare, the silence may be more ominous than reassuring. AI’s future may arrive before we are prepared to manage its consequences, and by then, it might be too late to shape it on our terms.

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Amazon reports $18.2B profit boost as AI strategy takes off

Amazon has reported a 35% increase in quarterly profit, driven by rapid growth in its AI-powered services and cloud computing arm, Amazon Web Services (AWS).

The tech and e-commerce giant posted net income of $18.2 billion for Q2 2025, up from $13.5 billion a year earlier, while net sales rose 13% to $167.7 billion and exceeded analyst expectations.

CEO Andy Jassy attributed the strong performance to the company’s growing reliance on AI. ‘Our conviction that AI will change every customer experience is starting to play out,’ Jassy said, referencing Amazon’s AI-powered Alexa+ upgrades and new generative AI shopping tools.

AWS remained the company’s growth engine, with revenue climbing 17.5% to $30.9 billion and operating profit rising to $10.2 billion. The surge reflects the increasing demand for cloud infrastructure to support AI deployment across industries.

Despite the solid earnings, Amazon’s share price dipped more than 3% in after-hours trading. Analysts pointed to concerns over the company’s heavy capital spending, particularly its aggressive $100 billion AI investment strategy.

Free cash flow over the past year fell to $18.2 billion, down from $53 billion a year earlier. In Q2 alone, Amazon spent $32.2 billion on infrastructure, nearly double the previous year’s figure, much of it aimed at expanding its data centre and logistics capabilities to support AI workloads.

For the current quarter, Amazon projected revenue of $174.0 to $179.5 billion and operating income between $15.5 and $20.5 billion, slightly below investor hopes but still reflecting double-digit year-on-year growth.

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Gulf states reframe AI as the ‘new oil’ in post‑petroleum push

Gulf states are actively redefining national strategy by embracing AI as a cornerstone of post-oil modernization. Saudi Arabia, through its AI platform Humain, a subsidiary of the Public Investment Fund, has committed state resources to build core infrastructure and develop Arabic multimodal models. Concurrently, the UAE is funding its $100 billion MGX initiative and supporting projects like G42 and the Falcon open-source model from Abu Dhabi’s Technology Innovation Institute.

Economic rationale underpins this ambition. Observers suggest that broad AI adoption across GCC sectors, including energy, healthcare, aviation, and government services, could add as much as $150 billion to regional GDP. Yet, concerns persist around workforce limitations, regulatory maturation, and geopolitical complications tied to supply chain dependencies.

Interest in AI has also reached geopolitical levels. Gulf leaders have struck partnerships with US firms to secure advanced AI chips and infrastructure, as seen during high-profile agreements with Nvidia, AMD, and Amazon. Critics caution that hosting major data centres in geopolitically volatile zones introduces physical and strategic risks, especially in contexts of rising regional tension.

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NHS trial shows AI app halves treatment delays

An AI-powered physiotherapy app has significantly reduced NHS back pain treatment waiting lists in Cambridgeshire and Peterborough by 55%.

The trial, run by Cambridgeshire Community Services NHS Trust, diverted 2,500 clinician hours to more complex cases while offering digital care to routine patients.

The app assesses musculoskeletal (MSK) pain through questions and provides personalised video-guided exercises. It became the first AI physiotherapy tool regulated by the Care Quality Commission and is credited with cutting average MSK wait times from 18 to under 10 weeks.

Patients like Annys Bossom, who initially doubted its effectiveness, found the tool more engaging and valuable than traditional paper instructions.

Data showed that 98% of participants were treated and discharged digitally, while only 2% needed a face-to-face referral.

With growing demand and staff shortages in NHS MSK services, physiotherapists and developers say the technology offers scalable support.

Experts emphasise the need for human oversight and public trust as AI continues to play a larger role in UK healthcare.

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OpenAI annual revenue doubles to 12 billion

OpenAI has doubled its revenue in the first seven months of 2025, reaching an annualised run rate of about $12 billion.

Surging demand for both consumer ChatGPT products and enterprise-level AI services is the main driver for this rapid growth.

Weekly active users of ChatGPT have soared to approximately 700 million, reflecting the platform’s expanding global reach and wide penetration. 

At the same time, costs have risen sharply, with cash burn projected around $8 billion in 2025, up from previous estimates.

OpenAI is preparing to release its next-generation AI model GPT‑5 in early August, underscoring its focus on innovation to maintain leadership in the AI market.

Despite growing competition from rival firms like DeepSeek, OpenAI remains confident that its technological edge and expanding product portfolio will sustain momentum.

Financial projections suggest potential revenue of $11 billion this year, with continued expansion into enterprise services.

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AI cloaking helps hackers dodge browser defences

Cybercriminals increasingly use AI-powered cloaking tools to bypass browser security systems and trick users into visiting scam websites.

These tools conceal malicious content from automated scanners, showing it only to human visitors, making it harder to detect phishing attacks and malware delivery.

Platforms such as Hoax Tech and JS Click Cloaker are being used to filter web traffic and serve fake pages to victims while hiding them from security systems.

The AI behind these services analyses a visitor’s browser, location, and behaviour before deciding which version of a site to display.

Known as white page and black page cloaking, the technique shows harmless content to detection tools and harmful pages to real users. However, this allows fraudulent sites to live longer, boosting the effectiveness and lifespan of cyberattacks.

Experts warn that cloaking is no longer a fringe method but a core part of cybercrime, now available as a commercial service. As these tactics grow more sophisticated, the pressure increases on browser developers to improve detection and protect users more effectively.

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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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Taiwan university launches smart farming lab

A new AI-powered agriculture lab in southern Taiwan has opened at the National Pingtung University of Science and Technology. The facility has cutting-edge sensors and automation systems to boost innovative farming capabilities.

Funded by a donation from Taiwan Hipoint, the lab enables real-time monitoring of crop conditions and automated adjustments to growing environments. The AI system analyses sensor and image data to optimise greenhouse conditions and detect early signs of pests or diseases.

Specialised chambers inside the lab simulate various environmental conditions, helping researchers identify ideal settings for plant growth. University staff say the technology is expected to play a crucial role in making agriculture more precise and resource-efficient.

The university also hosted a hands-on greenhouse training camp and showcased its innovations at a major food expo. Located near key research centres, the university aims to become Taiwan’s leading hub for agricultural technology and innovation.

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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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