Digital business models

Meta under fire over AI deepfake celebrity chatbots

Meta faces scrutiny after a Reuters investigation found its AI tools created deepfake chatbots and images of celebrities without consent. Some bots made flirtatious advances, encouraged meet-ups, and generated photorealistic sexualised images.

The affected celebrities include Taylor Swift, Scarlett Johansson, Anne Hathaway, and Selena Gomez.

The probe also uncovered a chatbot of 16-year-old actor Walker Scobell producing inappropriate images, raising serious child safety concerns. Meta admitted policy enforcement failures and deleted around a dozen bots shortly before publishing the report.

A spokesperson acknowledged that intimate depictions of adult celebrities and any sexualised content involving minors should not have been generated.

Following the revelations, Meta announced new safeguards to protect teenagers, including restricting access to certain AI characters and retraining models to reduce inappropriate content.

California Attorney General Rob Bonta called exposing children to sexualised content ‘indefensible,’ and experts warned Meta could face legal challenges over intellectual property and publicity laws.

The case highlights broader concerns about AI safety and ethical boundaries. It also raises questions about regulatory oversight as social media platforms deploy tools that can create realistic deepfake content without proper guardrails.

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Apple creates Asa chatbot for staff training

Apple is moving forward with its integrated approach to AI by testing an internal chatbot designed for retail training. The company focuses on embedding AI into existing services rather than launching a consumer-facing chatbot like Google’s Gemini or ChatGPT.

The new tool, Asa, is being tested within Apple’s SEED app, which offers training resources for store employees and authorised resellers. Asa is expected to improve learning by allowing staff to ask open-ended questions and receive tailored responses.

Screenshots shared by analyst Aaron Perris show Asa handling queries about device features, comparisons, and use cases. Although still in testing, the chatbot is expected to expand across Apple’s retail network in the coming weeks.

The development occurs amid broader AI tensions, as Elon Musk’s xAI sued Apple and OpenAI for allegedly colluding to limit competition. Apple’s focus on internal AI tools like Asa contrasts with Musk’s legal action, highlighting disputes over AI market dominance and platform integration.

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Walmart rolls out AI agents to transform shopping and operations

Walmart has unveiled four AI agents to ease the workloads of shoppers, employees, and suppliers. The tools, revealed at the company’s Retail Rewired event, include Marty for suppliers, Sparky for customers, an Associate Agent for staff, and a Developer Agent.

The retailer is leaning on AI as inflation, tariffs, and policy pressures weigh on consumer spending. Its agents cover payroll, time-off requests, merchandising, and personalised shopping recommendations.

Sparky is set to eventually handle automatic reordering of staples, aiming to simplify everyday restocking for households.

Walmart is also investing in ‘digital twins,’ virtual replicas of stores that allow early detection of operational issues. The company says this technology cut emergency alerts by 30% last year and reduced refrigeration maintenance costs by nearly a fifth.

Machine learning is further being applied to improve delivery-time predictions, helping to boost efficiency and customer satisfaction.

Rival retailers are making similar moves. Amazon reported a surge in generative AI use during its Prime Day sales, while Google Cloud AI has partnered with Lush to cut training costs.

Analysts suggest such tools could reshape the retail experience as companies search for ways to hold margins in a tighter economy.

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Beijing seeks to curb excess AI investment while sustaining growth

China has pledged to rein in excessive competition in AI, signalling Beijing’s desire to avoid wasteful investment while keeping the technology central to its economic strategy.

The National Development and Reform Commission stated that provinces should develop AI in a coordinated manner, leveraging local strengths to prevent duplication and overlap. Officials in China emphasised the importance of orderly flows of talent, capital, and resources.

The move follows President Xi Jinping’s warnings about unchecked local investment. Authorities aim to prevent overcapacity problems, such as those seen in electric vehicles, which have fueled deflationary pressures in other industries.

While global investment in data centres has surged, Beijing is adopting a calibrated approach. The state also vowed stronger national planning and support for private firms, aiming to nurture new domestic leaders in AI.

At the same time, policymakers are pushing to attract private capital into traditional sectors, while considering more central spending on social projects to ease local government debt burdens and stimulate long-term consumption.

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Meta faces turmoil as AI hiring spree backfires

Mark Zuckerberg’s ambitious plan to assemble a dream team of AI researchers at Meta has instead created internal instability.

High-profile recruits poached from rival firms have begun leaving within weeks of joining, citing cultural clashes and frustration with the company’s working style. Their departures have disrupted projects and unsettled long-time executives.

Meta had hoped its aggressive hiring spree would help the company rival OpenAI, Google, and Anthropic in developing advanced AI systems.

Instead of strengthening the company’s position, the strategy has led to delays in projects and uncertainty about whether Meta can deliver on its promises of achieving superintelligence.

The new arrivals were given extensive autonomy, fuelling tensions with existing teams and creating leadership friction. Some staff viewed the hires as destabilising, while others expressed concern about the direction of the AI division.

The resulting turnover has left Meta struggling to maintain momentum in its most critical area of research.

As Meta faces mounting pressure to demonstrate progress in AI, the setbacks highlight the difficulty of retaining elite talent in a fiercely competitive field.

Zuckerberg’s recruitment drive, rather than propelling Meta ahead, risks slowing down the company’s ability to compete at the highest level of AI development.

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How local LLMs are changing AI access

As AI adoption rises, more users explore running large language models (LLMs) locally instead of relying on cloud providers.

Local deployment gives individuals control over data, reduces costs, and avoids limits imposed by AI-as-a-service companies. Users can now experiment with AI on their own hardware thanks to software and hardware capabilities.

Concerns over privacy and data sovereignty are driving interest. Many cloud AI services retain user data for years, even when privacy assurances are offered.

By running models locally, companies and hobbyists can ensure compliance with GDPR and maintain control over sensitive information while leveraging high-performance AI tools.

Hardware considerations like GPU memory and processing power are central to local LLM performance. Quantisation techniques allow models to run efficiently with reduced precision, enabling use on consumer-grade machines or enterprise hardware.

Software frameworks like llama.cpp, Jan, and LM Studio simplify deployment, making local AI accessible to non-engineers and professionals across industries.

Local models are suitable for personalised tasks, learning, coding assistance, and experimentation, although cloud models remain stronger for large-scale enterprise applications.

As tools and model quality improve, running AI on personal devices may become a standard alternative, giving users more control over cost, privacy, and performance.

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Salt Typhoon hack reveals fragility of global communications networks

The FBI has warned that Chinese hackers are exploiting structural weaknesses in global telecom infrastructure, following the Salt Typhoon incident that penetrated US networks on an unprecedented scale. Officials say the Beijing-linked group has compromised data from millions of Americans since 2019.

Unlike previous cyber campaigns focused narrowly on government targets, Salt Typhoon’s intrusions exposed how ordinary mobile users can be swept up in espionage. Call records, internet traffic, and even geolocation data were siphoned from carriers, with the operation spreading to more than 80 countries.

Investigators linked the campaign to three Chinese tech firms supplying products to intelligence agencies and China’s People’s Liberation Army. Experts warn that the attacks demonstrate the fragility of cross-border telecom systems, where a single compromised provider can expose entire networks.

US and allied agencies have urged providers to harden defences with encryption and stricter monitoring. Analysts caution that global telecoms will continue to be fertile ground for state-backed groups without structural reforms.

The revelations have intensified geopolitical tensions, with the FBI describing Salt Typhoon as one of the most reckless and far-reaching espionage operations ever detected.

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India to host OpenAI’s new Stargate data centre

OpenAI is preparing to build a significant new data centre in India as part of its Stargate AI infrastructure initiative. The move will expand the company’s presence in Asia and strengthen its operations in its second-largest market by user base.

OpenAI has already registered as a legal entity in India and begun assembling a local team.

The company plans to open its first office in New Delhi later this year. Details regarding the exact location and timeline of the proposed data centre remain unclear, though CEO Sam Altman may provide further information during his upcoming visit to India.

The project represents a strategic step to support the company’s growing regional AI ambitions.

OpenAI’s Stargate initiative, announced by US President Donald Trump in January, involves private sector investment of up to $500 billion for AI infrastructure, backed by SoftBank, OpenAI, and Oracle.

The initiative seeks to develop large-scale AI capabilities across major markets worldwide, with the India data centre potentially playing a key role in the efforts.

The expansion highlights OpenAI’s focus on scaling its AI infrastructure while meeting regional demand. The company intends to strengthen operational efficiency, improve service reliability, and support its long-term growth in Asia by establishing local offices and a significant data centre.

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Schneider joins SK Telecom on new AI data centre project in Ulsan

SK Telecom has expanded its partnership with Schneider Electric to develop an AI Data Centre (AIDC) in Ulsan.

Under the deal, Schneider Electric will supply mechanical, electrical and plumbing equipment, such as switchgear, transformers, automated control systems and Uninterruptible Power Supply units.

The agreement builds on a partnership announced at Mobile World Congress 2025 and includes using Schneider’s Electrical Transient Analyser Program within SK Telecom’s data centre management system.

It will allow operations to be optimised through a digital twin model instead of relying only on traditional monitoring tools.

Both companies have also agreed on prefabricated solutions to shorten construction times, reference designs for new facilities, and joint efforts to grow the Energy-as-a-Service business.

A Memorandum of Understanding extends the partnership to other SK Group affiliates, combining battery technologies with Uninterruptible Power Supply and Energy Storage Systems.

Executives said the collaboration would help set new standards for AI data centres and create synergies across the SK Group. It is also expected to support SK Telecom’s broader AI strategy while contributing to sustainable and efficient infrastructure development.

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