Digital cooperation Archives | Page 38 of 230

Enterprises rethink cloud amid digital sovereignty push

Digital sovereignty has moved to the boardroom as geopolitical tensions rise and cloud adoption accelerates. Organisations are reassessing infrastructure to protect autonomy, ensure compliance, and manage jurisdictional risk. Cloud strategy is increasingly shaped by data location, control, and resilience.

Regulations such as NIS2, DORA, and national data laws have intensified scrutiny of cross-border dependencies. Sovereignty concerns now extend beyond governments to sectors such as healthcare and finance. Vendor selection increasingly prioritises sovereign regions and stricter data controls.

Hybrid cloud remains dominant. Organisations place sensitive workloads on private platforms to strengthen oversight while retaining public cloud innovation. Large-scale repatriation is rare due to cost and complexity, though compliance pressures are driving broader multicloud diversification.

Government investment and oversight are reinforcing the shift. Sovereignty is becoming part of national resilience policy, prompting stricter audits and governance expectations. Enterprises face growing pressure to demonstrate control over critical systems, supply chains, and data flows.

A pragmatic approach, often described as minimum viable sovereignty, helps reduce exposure without unnecessary complexity. Organisations can identify critical workloads, secure enforceable vendor commitments, and plan for disruption. Early adaptation supports resilience and long-term flexibility.

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Commission delays high risk AI guidance

The European Commission has confirmed it will again delay publishing guidance on high-risk AI systems under the EU AI Act. The guidelines were due by 2 February 2026, but will now follow a revised timeline.

According to Euractiv, the document is intended to clarify which AI systems fall into the high-risk category and therefore face stricter obligations. Officials said more time is needed to incorporate significant stakeholder feedback.

The delay marks the second missed deadline and adds to broader implementation setbacks surrounding the EU AI Act. Several member states have yet to designate national enforcement bodies, complicating oversight preparations.

Brussels is also considering postponing the application of high-risk rules through a digital simplification package. Parliament and Council appear supportive of moving the August deadline back by more than a year, easing pressure on companies awaiting guidance.

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Global privacy regulators warn of rising AI deepfake harms

Privacy regulators from around the world have issued a joint warning about the rise of AI-generated deepfakes, arguing that the spread of non-consensual images poses a global risk instead of remaining a problem confined to individual countries.

Sixty-one authorities endorsed a declaration that draws attention to AI images and videos depicting real people without their knowledge or consent.

The signatories highlight the rapid growth of intimate deepfakes, particularly those targeting children and individuals from vulnerable communities. They note that such material often circulates widely on social platforms and may fuel exploitation or cyberbullying.

The declaration argues that the scale of the threat requires coordinated action rather than isolated national responses.

European authorities, including the European Data Protection Board and the European Data Protection Supervisor, support the effort to build global cooperation.

Regulators say that only joint oversight can limit the harms caused by AI systems that generate false depictions, rather than protecting individuals’ privacy as required under frameworks such as the General Data Protection Regulation.

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Anthropic uncovers large-scale AI model theft operations

Three AI laboratories have been found conducting large-scale illicit campaigns to extract capabilities from Anthropic’s Claude AI, the company revealed.

DeepSeek, Moonshot, and MiniMax used around 24,000 fraudulent accounts to generate more than 16 million interactions, violating terms of service and regional access restrictions. The technique, called distillation, trains a weaker model on outputs from a stronger one, speeding AI development.

Distilled models obtained in this manner often lack critical safeguards, creating serious national security concerns. Without protections, these capabilities could be integrated into military, intelligence, surveillance, or cyber operations, potentially by authoritarian governments.

The attacks also undermine export controls designed to preserve the competitive edge of US AI technology and could give a misleading impression of foreign labs’ independent AI progress.

Each lab followed coordinated playbooks using proxy networks and large-scale automated prompts to target specific capabilities such as agentic reasoning, coding, and tool use.

Anthropic attributed the campaigns using request metadata, infrastructure indicators, and corroborating observations from industry partners. The investigation detailed how distillation attacks operate from data generation to model launch.

In response, Anthropic has strengthened detection systems, implemented stricter access controls, shared intelligence with other labs and authorities, and introduced countermeasures to reduce the effectiveness of illicit distillation.

The company emphasises that addressing these attacks will require coordinated action across the AI industry, cloud providers, and policymakers to protect frontier AI capabilities.

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AWS warns of AI powered cybercrime

Amazon Web Services has revealed that a Russian-speaking threat actor used commercial AI tools to compromise more than 600 FortiGate firewalls across 55 countries. AWS described the campaign as an AI-powered assembly line for cybercrime.

According to AWS, the attacker relied on exposed management ports and weak single-factor credentials rather than exploiting software vulnerabilities. The campaign targeted FortiGate devices globally and focused on harvesting credentials and configuration data.

AWS said the potentially Russian group appeared unsophisticated but achieved scale through AI-assisted mass scanning and automation. When encountering stronger defences, the attackers reportedly shifted to easier targets rather than persist.

The company advised organisations using FortiGate appliances to secure management interfaces, change default credentials and enforce complex passwords. Amazon said it was not compromised during the campaign.

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Wikipedia removes Archive.today links

Wikipedia editors have voted to remove all links to Archive.today, citing allegations that the web archive was involved in a distributed denial of service attack.

Editors said Archive.today, which also operates under domains such as archive.is and archive.ph, should not be linked because it allegedly used visitors’ browsers to target blogger Jani Patokallio. The site has also been accused of altering archived pages, raising concerns about reliability.

Archive.today had previously been blacklisted in 2013 before being reinstated in 2016. Wikipedia’s latest guidance calls for replacing Archive.today links with original sources or alternative archives such as the Wayback Machine.

The apparent owner of Archive.today denied wrongdoing in posts linked from the site and suggested the controversy had been exaggerated. Wikipedia editors nevertheless concluded that readers should not be directed to a service facing such allegations.

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OpenAI model revises proof claim

OpenAI has published its attempts to solve all 10 problems in the First Proof challenge, a research-level maths test designed to assess whether AI can produce checkable, domain-specific proofs. Leading experts created the issues and require extended reasoning rather than short answers.

The company said at least five of its proof attempts are likely correct following expert feedback, although one previously confident submission has now been judged incorrect. Several other attempts remain under review as specialists continue to assess the arguments.

According to OpenAI, the evaluation involved limited human supervision, with researchers sometimes prompting the model to refine or clarify reasoning. The process included exchanges between an internal model and ChatGPT for verification, formatting and style adjustments.

OpenAI described frontier research challenges, such as First Proof, as crucial for testing next-generation AI systems. The company said it plans to deepen its engagement with academics to develop more rigorous evaluation frameworks for research-grade reasoning.

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Stanford speech warns of AI tsunami

Senator Bernie Sanders has warned at Stanford University in California that the US is unprepared for the speed and scale of the AI revolution. Speaking in California alongside Congressman Ro Khanna, he called the moment one of the most dangerous in modern US history.

At Stanford University, Sanders urged a moratorium on the expansion of AI data centres to slow development while lawmakers catch up. He argued that the American public lacks a clear understanding of the economic and social impact ahead and that New York is already considering a pause.

Khanna, who represents Silicon Valley in California, rejected a complete moratorium but called for steering AI growth through renewable energy and water efficiency standards. He outlined principles to prevent wealth from being concentrated among a small group of tech billionaires.

Sanders also raised concerns in California about job losses and emotional reliance on AI, citing projections of widespread automation. He called for a national debate in the US over whether AI will benefit the public or deepen inequality.

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University of Bristol opens free online course on AI

The University of Bristol has launched a free online course called AI Fundamentals, designed to increase public understanding of AI. Many people use AI regularly but feel unsure about how to engage with it effectively, creating a gap that the course aims to address.

AI Fundamentals explores the technology’s complexities, societal impact, and environmental implications. The curriculum emphasises critical thinking about AI, its risks, and its potential, making it relevant for both enthusiasts and the curious general public.

The course runs entirely online over four weeks, requiring about 3 hours of self-paced work per week. No coding or advanced mathematics is needed, allowing learners from all backgrounds to participate and explore AI in a digestible format.

Led by Professors Genevieve Liveley and Seth Bullock, the course draws on expertise across fields including computer science, law, medicine, humanities, and neuroscience. Supported by a £50,000 alum donation and UKRI funding, it is now open for enrolment via FutureLearn.

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Pension savers increasingly rely on AI for retirement planning

AI is becoming a preferred tool for those beginning their retirement planning. Data on searches and website traffic suggests AI is meeting early-stage needs for pension guidance.

Platforms offering general financial information, such as MoneyHelper, have seen traffic fall by 10% over the past six months. At the same time, AI-generated overviews of pension content are on the rise.

AI tools are mainly used to sense-check retirement decisions, model ‘what-if’ scenarios, simplify pension jargon, and assist with tax planning. Users view AI as a thinking partner rather than a replacement for regulated advice.

Despite the rise of AI, bespoke advisory services, such as Pension Wise, have remained relevant, providing personalised guidance that AI cannot fully replace. PensionBee highlights that AI is helpful for basic guidance, but services remain essential for more complex planning.

Experts warn that the retirement sector faces a challenge in maintaining trust and relevance as AI continues to improve. Savers increasingly rely on technology for guidance, signalling a shift in how pensions are researched and managed.

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