Australia’s regulator targets AI-nudify platform over child safety and deepfake risks

Australia’s eSafety Commissioner has begun enforcement action against another AI-powered ‘nudify’ service accused of failing to protect children from exposure to sexually explicit deepfake images.

The regulator issued a formal Direction to Comply to one of the most visited nudify services in Australia, giving the provider 14 days to implement stronger protections preventing children from accessing the platform. eSafety said the service allows users to upload images of real people and generate sexually explicit deepfake content on demand.

The regulator warned that such technologies can facilitate non-consensual exploitation, cyberbullying, sexual extortion, image-based sexual abuse, misogynistic harassment and exploitation of minors. The service had attracted nearly 40,000 Australian visits per month as of March 2026, following a sharp increase in traffic over the previous six months.

The enforcement action was taken under Australia’s Age-Restricted Material Codes, which came into force in March 2026. The codes are designed to prevent children from accessing or being exposed to age-restricted material, including pornography, high-impact violence, self-harm, suicide or disordered eating content.

eSafety said the Argentina-based provider failed to respond to earlier engagement after the codes took effect and had not committed to improving protections for children. The regulator chose not to name the service to avoid inadvertently promoting it.

If the service does not meet the requirements within the 14-day timeframe, eSafety may pursue further action, including civil penalties of up to AU$49.5 million and delisting notices to search engine providers that help facilitate access to the site.

The action follows earlier enforcement in late 2025 that led three widely used nudify services, which had reportedly been used to generate child sexual exploitation material in schools, to withdraw from Australia. Those services have since relaunched under new ownership with additional safety measures, including mandatory age assurance.

Why does it matter?

The case shows how online safety regulators are beginning to apply age-assurance and child protection rules directly to generative AI services. Nudify platforms are treated as high-risk because they can enable non-consensual sexualised deepfakes, image-based abuse and exploitation involving minors at scale. Australia’s enforcement approach also signals that regulators may target foreign-based AI services when they are accessible to local users and fail to implement safeguards.

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Meta reportedly cuts 8,000 jobs as AI investment and restructuring accelerate globally

Meta is reportedly cutting about 8,000 jobs globally as part of a restructuring aimed at reducing costs while increasing spending on AI infrastructure and products.

According to media reports, the cuts represent about 10% of Meta’s workforce and are intended, in part, to offset the cost of the company’s expanding AI investments. The reductions are expected to affect engineering and product teams in particular, with employees in several regions notified as the restructuring begins.

Reports also indicate that around 7,000 employees are being reassigned to new AI-focused teams, while thousands of open roles have been closed. The restructuring reflects Meta’s effort to redirect resources towards AI products, infrastructure and agent-based tools across its platforms.

In Ireland, reports said around 350 jobs were affected, representing a significant share of Meta’s local workforce. The company has not publicly confirmed all regional figures, but said affected employees and authorities had been notified.

The cuts come as Meta prepares for a major increase in AI-related capital expenditure. Reports say the company expects spending to rise sharply in 2026 as it builds infrastructure for AI models, personalised assistants and other AI-powered features across Facebook, Instagram, WhatsApp and its wider product ecosystem.

Staff concerns have also emerged around the pace of restructuring, internal communication and workplace monitoring linked to AI development. Reports cited employee unease over plans to monitor computer activity as part of AI training practices.

Why does it matter?

Meta’s restructuring shows how major technology companies are reallocating labour and capital around AI. The reported job cuts are not only a cost-saving exercise, but part of a wider shift in which companies are redirecting resources towards AI infrastructure, automation and agentic systems. The development also highlights a growing tension in the tech sector: AI is being presented as a long-term growth engine, while workers face uncertainty over how that transition will reshape roles, teams and investment priorities.

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Japan backs blockchain and AI-based financial infrastructure proposal

Japan has approved a policy proposal focused on blockchain technology and AI within future financial infrastructure development. The proposal reflects broader efforts to integrate digital technologies into financial systems and economic operations.

According to the proposal, backed by the ruling Liberal Democratic Party and endorsed by the government’s Policy Council, the initiative envisions expanded use of automated and continuously operating digital financial systems.

The proposal, titled the ‘Next-generation AI & Onchain Finance Concept’, envisions a system that enables 24/7 digital commerce through blockchain networks, including those supporting cryptocurrencies such as Bitcoin. The proposal describes blockchain technology as a potential foundation for future financial infrastructure because of its verification and record-keeping features.

The strategy includes consideration of tokenised financial instruments, including tokenised stocks and yen-denominated stablecoins. The proposal also discusses possible tokenisation models linked to the Bank of Japan’s current account deposits.

The Financial Services Agency has been tasked with developing a five-year roadmap to encourage both public and private sector investment in the initiative. Policymakers said the initiative is intended to support financial innovation and the development of programmable financial services.

Why does it matter? 

Japan’s move is a major shift in how a leading economy is attempting to merge traditional monetary systems with blockchain and AI, potentially setting a benchmark for other countries exploring programmable finance and tokenised assets.

It could accelerate competition among jurisdictions to define standards for digital financial infrastructure, influencing how central banks, regulators and markets approach the integration of crypto, tokenisation and automated financial systems.

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Việt Nam highlights AI in national digital transformation strategy

Việt Nam’s Ministry of Science and Technology has highlighted AI as part of the country’s digital transformation and innovation strategy. Officials said AI is being prioritised alongside technologies including big data, cloud computing, blockchain, and the Internet of Things.

The comments were made during a workshop focused on AI products and technology cooperation. Participants said businesses are showing growing interest in AI adoption while facing implementation and investment challenges.

Discussions also addressed data infrastructure, computing capacity, and explainable AI systems for public administration and urban management.

Participants said stronger infrastructure, workforce development, and research support could help expand Việt Nam’s role in the regional AI and digital technology sectors. The workshop took place in Hà Nội, Việt Nam.

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Singapore and Google strengthen collaboration on AI innovation and digital governance

Google and Singapore’s Ministry of Digital Development and Information have announced an expanded National AI Partnership designed to accelerate the deployment of frontier AI technologies across the country’s economy and public sector.

The initiative builds on earlier collaboration between Google and Singapore’s digital authorities and aims to support healthcare innovation, scientific research, workforce development, enterprise transformation, and AI governance. Officials said the partnership aligns with Singapore’s National AI Strategy and broader ambitions to position the country as a global AI hub.

A major focus of the collaboration involves healthcare and life sciences. Google DeepMind is exploring AI co-clinician systems with Singapore’s public healthcare sector, examining how AI agents could support doctors and patients throughout medical treatment and decision-making processes.

Google DeepMind will also collaborate with the National Research Foundation to train researchers on agentic AI systems designed to accelerate scientific discovery. Additional partnerships with the Agency for Science, Technology and Research will focus on AI-enabled research and secure cloud-based scientific analysis tools.

The agreement also expands AI deployment in education. Google and Singapore’s Ministry of Education plan to strengthen educator training programmes and integrate AI-powered teaching support tools across schools. Officials said the partnership aims to improve digital learning capabilities while supporting broader AI workforce readiness initiatives.

Singapore and Google additionally announced plans to collaborate on AI safety, governance, and cybersecurity frameworks. A joint initiative involving Cyber Security Agency of Singapore and other agencies is examining how AI agents interact with real-world digital systems and how governance rules should evolve around autonomous AI technologies.

Officials described the partnership as part of a wider effort to deploy frontier AI responsibly while supporting economic growth, public services, and digital transformation.

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MIT researchers explore AI-driven approaches to drug discovery

AI is increasingly being used in drug discovery to analyse large chemical datasets and identify potential therapeutic compounds. Researchers estimate that the number of potentially useful small-molecule compounds is too large for experimental testing alone, increasing reliance on computational screening methods.

Researchers at MIT are developing machine learning models designed to predict molecular behaviour and chemical reaction pathways. The research focuses on identifying promising drug candidates and improving how chemical reactions can be simulated and understood using data-driven methods.

The research incorporates chemical principles such as reaction mechanisms and physical constraints into AI models. The group has developed models including ShEPhERD, which predicts molecular interactions with proteins, and FlowER, which models chemical reaction outcomes.

Research in the group also extends to automated experimentation, structure analysis and experimental design, aiming to build more efficient workflows for drug discovery. According to the researchers, the broader aim is to improve the realism and accuracy of computational predictions in chemistry.

Why does it matter? 

AI-driven chemistry significantly reduces the time and cost required to identify viable drug candidates by narrowing down vast chemical search spaces that would otherwise be impossible to evaluate experimentally.

Embedding chemical principles into machine learning models also improves reliability, making computational predictions more useful for real-world pharmaceutical development and potentially accelerating the delivery of new treatments.

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Google explores AI-assisted scientific discovery through Gemini for Science

Google has introduced Gemini for Science, a collection of AI tools and experiments designed to support scientific research workflows. The initiative combines capabilities from systems including Co-Scientist, AlphaEvolve, Empirical Research Assistance, and NotebookLM.

According to Google, the AI-based tools are intended to support tasks such as hypothesis generation, literature analysis, and computational research.

Google said three experimental tools will initially be released through Google Labs, focusing on hypothesis generation, computational discovery and literature analysis. The company also announced Science Skills for Google Antigravity, integrating multiple life sciences databases and research tools.

Google said the programme is being developed in collaboration with more than 100 research institutions and scientific organisations. The company also highlighted research partnerships and conference collaborations linked to AI-supported scientific research.

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Study examines local warming effects linked to data centre expansion

New research suggests that expanding data centre infrastructure may contribute to localised warming effects similar to urban heat islands.

The study, published in the Journal of Engineering for Sustainable Buildings and Cities, examined several data centres in the Phoenix metropolitan area and found measurable increases in surrounding air temperatures. Researchers reported temperature increases ranging from approximately 1.5 to 4 degrees Fahrenheit within areas located downwind from facilities.

Data centres generate waste heat through cooling systems used to support high-performance computing operations.

According to the researchers, large data centre campuses can generate concentrated thermal output associated with high energy consumption.

The findings come as global demand for AI, cloud computing, and digital services continues to drive the construction of new facilities across the US and other regions. Northern Virginia, Phoenix, and several European locations have become major hubs for hyperscale infrastructure development.

The researchers said the observed effects differ from traditional urban heat islands because of continuous cooling activity and continuous energy consumption. The study noted that clusters of facilities may produce cumulative effects that require further investigation.

The researchers discussed potential implications for energy demand, infrastructure planning, and surrounding communities. The study said elevated local temperatures could influence cooling demand and related environmental conditions.

Furthermore, scientists stressed that additional peer-reviewed research remains necessary to determine the long-term climatic significance of large-scale data centre expansion.

Why does it matter?

The findings reflect growing scrutiny surrounding the environmental footprint of AI infrastructure. Data centres already face criticism over electricity consumption, water usage, and grid pressure. The possibility that concentrated AI infrastructure may also influence local temperatures introduces another dimension to debates surrounding sustainable digital expansion.

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Anthropic challenges US government restrictions on AI technology use

The US AI company Anthropic attempted to challenge a decision by the US Department of Defense to ban the use of its technology in government institutions. The company had been given 30 days to file an appeal after the Pentagon classified its products as a ‘supply chain risk’.

However, instead of following the proper procedures and sending the appeal to the designated official address, the head of Anthropic’s legal team emailed it directly to two DoW officials.

Reports cited by multiple outlets suggested disagreements between Anthropic and US defence authorities over potential military applications of AI systems and related safety restrictions. The reports referred to discussions about military and intelligence-related AI applications. After Pentagon asked Anthropic to bend its rules and company refused, Anthropic was latter classified as a ‘supply chain risk’.

Reports described the designation as an unusual step involving a major US AI company. According to reports, federal agencies were instructed to suspend use of Anthropic technologies following the classification decision.

Anthropic CEO Dario Amodei has said the company previously cooperated with the US military in areas such as intelligence analysis, modelling and simulation, operational planning, and cyber operations. However, he has also argued that the government’s action was not legally justified and indicated that the company has no choice but to challenge it in court.

Amodei went on to say that Anthropic does not believe private companies should be involved in operational military decision-making, particularly when systems could enable fully autonomous weapons or mass surveillance.

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CNIL reports record complaints and data breaches

The French data protection authority CNIL reported a record year in 2025 for complaints, fines and data breach notifications, while preparing for new responsibilities under the EU AI Act.

CNIL received 20,150 complaints in 2025, up 10% from 2024. The complaints covered issues linked to work, commerce, real estate, social networks and data breaches, with around 1,900 complaints directly concerning breaches.

The authority also received 6,167 data breach notifications, an increase of 9.5% from 2024. Hacking accounted for one in two reported incidents, while cybersecurity failures represented one-third of investigations and nearly 30% of sanctions.

In total, CNIL carried out 323 investigations and issued 259 corrective measures, including 83 sanctions worth nearly €487 million. Two major sanctions accounted for a large share of the total, while the simplified procedure introduced in 2022 allowed faster action in less complex cases.

Cybersecurity will become an even bigger enforcement focus in 2026, with CNIL planning to devote 50% of its controls and enforcement actions to data security. Checks will focus on organisations affected by breaches, those subject to complaints and sectors processing large volumes of sensitive or highly personal data.

The report also highlights CNIL’s role in supporting professionals and public authorities. In 2025, it processed 539 health authorisation applications, handled 1,351 professional advice requests, delivered 90 opinions on draft laws or regulatory texts and launched seven public consultations.

On AI, CNIL is already designated to monitor prohibited uses under the EU AI Act and is expected to become the market surveillance authority for certain high-risk AI systems, including in biometrics, migration, law enforcement, employment and education.

The authority also published AI resources for designers and developers, developed a traceability tool for open-source AI models and joined the PANAME project with ANSSI, Inria and PEReN to test whether AI models process personal data.

Why does it matter?

CNIL’s annual report shows how data protection enforcement is increasingly shaped by cybersecurity and AI. Record breach notifications and complaints point to growing pressure on organisations to secure personal data, while CNIL’s future AI Act responsibilities place the authority at the centre of France’s oversight of prohibited and high-risk AI systems.

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