Alberta uses Claude Code to review government systems

The Government of Alberta has used Anthropic’s Claude Code to review and secure provincial government systems, according to a case study published by the company. Anthropic said Alberta’s Ministry of Technology and Innovation used Claude Code with its Opus and Sonnet models to analyse code, identify vulnerabilities and support remediation.

According to Anthropic, the ministry scanned 466 million lines of code in about 20 hours, covering systems used across 27 provincial ministries. Around 50 AI agents worked in parallel to identify security vulnerabilities, infrastructure weaknesses and documentation gaps.

The ministry manages about 1,280 applications and 3,400 code repositories supporting services including social services, public safety and wildfire response. Anthropic said many had never undergone comprehensive security reviews, resulting in accumulated technical debt and incomplete documentation.

Alberta used a two-stage review process. A rules engine first identified known patterns, after which Claude Code analysed the results and cited the relevant files and lines for each finding. Anthropic said the approach uncovered issues that conventional automated scanning tools had missed.

Claude Code was also used to generate fixes, write tests where needed and assist with modernising legacy systems. Anthropic said ministry engineers reviewed and approved all proposed patches before deployment, maintaining human oversight throughout the remediation process.

Alberta also developed specialised Claude-based review agents for continuous security testing during software development. These include red-team agents that probe applications for vulnerabilities, blue-team agents that assess compliance with security standards, and additional agents that review code quality and public-facing content.

Why does it matter?

The case illustrates how governments are beginning to use AI coding agents to modernise and secure large portfolios of legacy software, an area that has traditionally required significant time and specialised expertise. If these tools prove reliable, they could help public administrations reduce technical debt, improve cybersecurity and accelerate software maintenance across critical public services.

At the same time, the deployment highlights the importance of governance in public-sector AI adoption. Alberta’s reported use of human review before implementing AI-generated changes reflects a growing emphasis on combining AI-assisted development with oversight, accountability and established security practices.

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Portugal presents AMALIA as open European Portuguese language model

Portugal has presented AMALIA, its first open language model developed in European Portuguese, as part of a wider effort to strengthen national AI capacity and modernise the public sector.

Prime Minister Luís Montenegro said the project shows Portugal’s ability to develop advanced technology and contribute to Europe’s strategic autonomy.

AMALIA, short for Automatic Artificial Intelligence Multimodal Language Assistant, was developed by a consortium of Portuguese universities and research centres.

The project received an initial €5.5 million through Portugal’s Recovery and Resilience Facility, with a further €1.5 million planned for a new development phase in 2027.

Available as open code, AMALIA is intended to allow public administration bodies, companies, universities and research centres to develop their own applications.

The government says the model can support customer service, administrative process automation, knowledge management and decision-making across public services.

The AMALIA website says the project is designed to promote European Portuguese, preserve Portuguese cultural representation and support data sovereignty by enabling AI use in public administration without sensitive data leaving national territory.

The model is also expected to support use cases in education, culture and museums, media and science.

Why does it matter?

AMALIA addresses a gap in AI language infrastructure by focusing specifically on European Portuguese, a language variety often underrepresented or conflated with Brazilian Portuguese in multilingual AI systems. Open access also matters because it allows public bodies, universities and companies to adapt the model rather than relying only on closed commercial tools. The project fits a broader European debate on AI sovereignty, where governments are seeking domestic or regional capabilities in language models, data governance and public-sector AI infrastructure.

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Japan to establish AI council to drive national AI adoption

Japan’s government has approved plans to establish a new council to accelerate AI adoption and review the legal frameworks governing its development and use. The initiative forms part of the country’s 2026 policy guidelines and reflects growing efforts to integrate AI into key sectors of the economy.

The new body will replace a digital administrative and fiscal reform council established under former Prime Minister Fumio Kishida. Authorities said it will lead to what they describe as an ‘AI transformation’, a broad effort to reshape public services, business processes and working practices through AI.

Japan sees AI as an important tool for addressing the challenges of an ageing population and a shrinking workforce. Priority areas include healthcare, elderly care, transportation, infrastructure, workplace productivity and public administration, alongside broader digitalisation measures such as expanding the use of electronic medical records.

Chief Cabinet Secretary Minoru Kihara said AI and digital technologies should reduce burdens on citizens and businesses while improving public services. The government said it intends to accelerate digital transformation as part of its broader programme of economic and administrative reform.

Why does it matter? 

Japan’s decision reflects how governments are increasingly embedding AI into long-term economic and public-sector strategies rather than treating it as a standalone technology initiative. For countries facing ageing populations and labour shortages, AI is becoming a key policy tool for sustaining productivity, modernising public services and addressing workforce constraints.

The new council also illustrates the growing convergence of AI policy and regulatory reform. By reviewing legal frameworks alongside promoting adoption, Japan is seeking to ensure that governance evolves in step with technological deployment, balancing innovation with public trust and accountability.

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OpenAI rolls out GPT-5.5 Instant Mini in ChatGPT

OpenAI has started rolling out GPT-5.5 Instant Mini in ChatGPT as the fallback model users reach after hitting GPT-5.5 Instant or Auto rate limits.

The model replaces GPT-5.3 Instant Mini in that fallback role.

Because GPT-5.5 Instant Mini is used only as a fallback model, it will not appear in the model picker.

OpenAI said the update does not affect the API or Codex.

According to the company’s release notes, GPT-5.5 Instant Mini performs better than GPT-5.3 Instant Mini at tracking evolving user intent, calibrating tone and avoiding repetitive or overly structured responses.

OpenAI also said testing showed stronger personalisation and fewer factual issues than the previous fallback model.

Why does it matter?

Fallback models shape the experience users receive when they hit rate limits, especially on high-demand ChatGPT plans. Improving that fallback path can make the transition less disruptive by preserving tone, context and reliability more effectively. The update also shows OpenAI refining its everyday model-routing infrastructure, not just the flagship models available in the picker.

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Sysdig reports first documented agentic ransomware case

Cloud security firm Sysdig says it has documented the first known case of agentic ransomware, after observing an AI-driven extortion operation it tracks as JADEPUFFER.

According to Sysdig, the operation began with exploiting CVE-2025-3248 on an internet-facing Langflow instance. Langflow is an open-source framework for building LLM-driven applications and agent workflows.

The attacker then pivoted towards a production database server running MySQL and Alibaba Nacos.

Sysdig said the operation was driven by a large language model rather than a traditional human-led toolkit. The agent carried out reconnaissance, credential harvesting, lateral discovery, persistence and destructive database activity.

The company said JADEPUFFER executed more than 600 distinct payloads and adapted to failures in real time. In one case, the agent moved from a failed login attempt to a corrected working approach in 31 seconds.

CyberScoop later reported Sysdig’s clarification that the attack was not fully human-free. A person still set up and directed the operation, provisioned command-and-control and staging infrastructure, chose the victim, and supplied credentials likely obtained through a prior compromise.

Sysdig also said API keys for OpenAI, Anthropic, DeepSeek and Gemini were among the material the agent collected from the compromised environment. That does not confirm which model powered the attack.

The case is notable less for novel techniques than for automation. Sysdig said the attack relied on known vulnerabilities and exposed infrastructure, but an AI agent chained the steps together quickly and carried out a ransomware-style database extortion workflow.

Why does it matter?

JADEPUFFER shows how agentic AI could change cybercrime by automating work that previously required skilled operators. Even if humans still choose targets and set up infrastructure, agents can speed up reconnaissance, credential theft, lateral movement and destructive activity once access is available. The defensive lesson is immediate: exposed AI tools, unpatched systems, leaked credentials, and internet-facing databases become more dangerous when attackers can automate exploitation and adaptation at machine speed.

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UK FCA review warns agentic AI could reshape retail finance

A new FCA-commissioned review has warned that agentic AI could reshape retail financial services by allowing consumers to delegate more financial decisions to autonomous tools.

The Mills Review examines how AI could transform retail finance by 2030 and beyond, including banking, payments, savings, investments, insurance and debt advice.

The review says AI is moving financial services from human-led and episodic activity towards services that are AI-enabled, continuous and delegated.

Over time, AI agents could help consumers manage finances, compare products, execute tasks and optimise financial choices within agreed limits.

The report says the shift could help address long-standing market problems, including advice gaps, low switching, financial exclusion and poor savings outcomes.

It also warns that greater autonomy will create new risks around consent, accountability, redress, market power, cyber threats and financial crime.

The review recommends that the FCA consider developing trusted frameworks for AI agent participation in financial services, including clearer expectations for identity, consent, control and liability.

It also calls for stronger AI-enabled supervision so the FCA can detect risks across firms, shared models, cloud platforms and data sources more quickly.

The report says human accountability must remain central, with firms remaining responsible for outcomes produced by AI systems.

Why does it matter?

The review points to a shift from AI as a financial services support tool to AI as an active participant in consumer finance. If agents begin comparing products, moving money, managing portfolios or taking out insurance within delegated limits, regulators will need clearer rules on consent, liability, identity, redress and oversight. The report also raises a broader infrastructure question: agentic finance will depend not only on AI models, but also on trusted data access, digital identity, payments systems and supervisory tools that can detect risks across the market.

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CSIS says Chinese AI models are narrowing the gap with US systems

Chinese AI models are narrowing the gap with leading US systems, according to a new analysis by the Center for Strategic and International Studies.

CSIS said recent releases from Z.ai, Moonshot, DeepSeek and Alibaba-backed Qwen show that China’s rapid progress in AI was not limited to DeepSeek-R1, but reflects a broader pattern of fast technical catch-up.

The analysis points to Z.ai’s GLM-5.2 model, which performs close to the top US closed models in coding and agent-based tasks. It also highlights strong results from Moonshot’s Kimi, DeepSeek V4-Pro and Qwen3.7-Max across software engineering, reasoning and agent benchmarks.

CSIS argues that Chinese models are now only months, rather than years, behind US frontier systems in several practical areas.

The report identifies knowledge distillation, open-weight research communities and efficiency-driven engineering as key factors behind this progress. Chinese labs can learn quickly from stronger models, shared research practices and open-source ecosystems, while US chip export controls have pushed them towards more efficient training and inference strategies.

Cost is another important factor. CSIS said Chinese models are often cheaper to access than leading US closed systems because open-source releases can be hosted by many providers, increasing price competition and making them easier for developers and governments to adopt.

The analysis says US firms still retain major advantages in frontier capabilities, cloud platforms, enterprise products and user feedback loops. However, Chinese models are now capable, affordable and open enough to shape global AI competition.

CSIS argues that US policy should therefore focus not only on protecting technological advantage, but also on building global trust, lowering access costs and ensuring partners see the American AI stack as reliable.

Why does it matter?

The analysis shows that AI competition is not only about which country has the most powerful frontier model. Chinese open-weight models are spreading because they are increasingly capable, cheaper to run and easier to deploy through third-party hosts or local infrastructure. That could shape global adoption, especially for governments, startups and developers that cannot afford or do not want to depend entirely on US closed-model providers. For the US, the challenge is no longer only maintaining a technical lead, but also making its AI ecosystem trusted, affordable and reliable for international partners.

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UK launches toy safety review as AI-enabled toys emerge

The UK government has launched a Call for Evidence on toy safety, including whether existing rules remain suitable as AI-enabled toys and online shopping create new risks for children.

The review is led by the Department for Business and Trade and the Office for Product Safety and Standards. It aims to assess whether the UK’s toy safety framework is fit for modern products and purchasing habits.

The government said the Call for Evidence will examine issues including chemical safety and toys that use AI features.

Consumer Protection Minister Kate Dearden said toy safety rules must keep pace with changes in how people shop and the types of toys children use.

The Call for Evidence is open until 6 October 2026 and invites views from parents, consumer groups, businesses, enforcement authorities and the wider public.

The review forms part of a wider UK programme to reform product safety rules, including measures aimed at unsafe goods sold through online marketplaces.

It does not introduce new toy safety rules immediately, but it will help the government decide how to update the framework.

Why does it matter?

AI-enabled toys raise product safety questions that go beyond traditional concerns such as chemicals, small parts or physical defects. Connected and interactive toys may involve software, data use, voice interaction, recommendation systems or adaptive behaviour, creating new risks for children and new responsibilities for manufacturers, retailers and online marketplaces. The UK review shows how AI is entering mainstream consumer product safety policy, not only digital regulation.

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UN scientific panel presents first AI assessment to Global Dialogue on AI Governance

The multidisciplinary Independent International Scientific Panel on Artificial Intelligence presented its first annual report during the United Nations Global Dialogue on AI Governance in Geneva, offering an evidence-based assessment of AI’s opportunities, risks and societal impacts.

The session formed part of the inaugural Global Dialogue on AI Governance, held on 6-7 July. The dialogue was established in 2025 to support open, transparent and inclusive discussions on international AI governance, including AI’s role in sustainable development, digital divides, safety, human rights, transparency, accountability and human oversight.

Opening the presentation, Yoshua Bengio, professor of computer science at the University of Montreal, said the panel’s role was to assess scientific evidence rather than prescribe policy, leaving decisions to UN member states and the Global Dialogue process. He warned that AI is at a turning point because machine intelligence is advancing quickly, while there are still no technical guarantees that AI systems will follow human instructions, norms or laws.

Bengio said current AI systems are already associated with harms, including emotional attachment among vulnerable users, increased cybersecurity vulnerabilities, unequal access and deceptive behaviour that can make evaluation more difficult. He argued that concentrated commercial and geopolitical interests are driving AI development without sufficient guardrails and called for a coordinated international and democratic response guided by scientific evidence.

Maria Ressa, co-chair of the panel, described the report as an independent assessment produced by 40 experts who ‘answered only to the evidence’. She said the report represents the minimum consensus among panellists rather than the upper limit of concern, calling it the ‘floor’ rather than the ‘ceiling’ of the panel’s findings.

Ressa also highlighted AI’s positive uses, including protein structure prediction used by millions of researchers, medical screening in India and food-crisis warning systems deployed in multiple countries. However, she also pointed to concrete harms, including dangerous medical mistranslations, AI tools identifying exploitable software flaws and the death of a 14-year-old boy following prolonged interaction with a chatbot. She urged governments, civil society and industry not to wait for certainty before acting.

The working-group presentations expanded on these findings. Mennatallah El-Assady, Computer Science Professor at ETH Zurich, described AI as a rapidly evolving technology moving from earlier symbolic systems to today’s generative and increasingly agentic models. She warned that independent verification remains weak, public benchmarks are becoming saturated and advanced systems are showing signs of evaluation awareness, including the ability to detect tests or behave differently when being assessed.

El-Assady also raised concerns about auditability as AI systems become more autonomous and capable of invoking external tools. She said interpretability, reliable auditing and independent verification are immediate bottlenecks, especially as AI moves beyond software and into physical systems such as robotics.

Joëlle Barral, Senior Director of Research & Engineering at Google DeepMind, focused on AI’s real-world benefits in science, healthcare, education and agriculture. She said task-specific AI is already producing measurable gains, citing examples such as self-driving laboratories, protein structure prediction and diabetic retinopathy screening in India. However, she stressed that successful deployment depends on local context, institutional capacity, workflows and follow-up systems, rather than technology alone.

In healthcare, Barral distinguished between purpose-built clinical AI and general-purpose systems, warning against the unintended use of general-purpose chatbots for medical advice. In education and agriculture, she similarly argued that AI benefits depend on trained teachers, relevant tools, local institutions and long-term evaluation.

Loreto Bravo, member of the UN Independent International Scientific Panel on AI, addressed AI’s economic implications, arguing that access to AI does not automatically translate into benefit. She said countries, firms and workers also need data, skills, infrastructure, management capacity and institutions to integrate AI into real tasks and workflows.

Bravo said the economic effects of AI are likely to differ across countries, sectors and workers. Large firms may reorganise more quickly, while smaller firms and developing economies may face greater barriers. She said the evidence does not support a single prediction of broad prosperity or mass unemployment, and that outcomes will depend on institutions, deployment choices and who captures the value created by AI.

Balaraman Ravindran, professor at Indian Institute of Technology Madras, examined security, alignment and environmental risks. He said AI development is outpacing risk mitigation, expanding cyber threats against both critical infrastructure and AI systems themselves. He also highlighted unresolved alignment problems, including bias, sycophancy, loss of control and AI-initiated deception.

Ravindran warned that the environmental costs of AI are also increasing as demand grows for computing power, energy, water and specialised hardware. He said the Global South faces disproportionate exposure because of structural vulnerabilities, limited local mitigation capacity and reliance on foreign software and infrastructure. He called for coordinated international standards rather than fragmented approaches driven only by companies or individual countries.

Rita Oluchi Orji, a Computer Science professor, focused on AI’s impact on human rights, information integrity and democracy. She said AI can support access to information and civic participation, but can also be engineered to persuade and manipulate people at scale. She warned of epistemic erosion, fragmented shared reality and unequal harms affecting groups such as women, girls, journalists and marginalised communities.

Orji said content moderation alone is insufficient if the systems that produce and amplify harmful material remain unchanged. She argued that governance must address targeting, amplification and optimisation models, not only individual pieces of false or harmful content.

Anna Korhonen, a Professor of Natural Language Processing at the University of Cambridge, addressed cultural and linguistic inclusion, child safety and mental health. She noted that while the world has more than 7,000 languages, current AI systems support only a small fraction of them, mostly the majority languages of the Global North. She said this exclusion is not inevitable and could be addressed through targeted investment and systemic changes.

Korhonen also warned about risks to children, including AI-generated child sexual abuse material, sexualised deepfakes and socially interactive AI toys that may encourage harmful parasocial relationships. On AI companions and mental health, she said such systems may help address loneliness, but also pose risks of emotional dependency, manipulation, privacy harms and reinforcement of harmful beliefs.

Haitao Song, President of the Shanghai Artificial Intelligence Research Institute and Director of the Global Industrial Artificial Intelligence Alliance Center of Excellence, focused on reliability and global governance frameworks. He said policymakers often have to make decisions with incomplete evidence and that current measurement systems cannot keep pace with AI development. He argued that existing approaches remain too narrow, focusing on compute and capabilities while paying insufficient attention to institutional development, talent and impact evaluation.

Song also noted that AI infrastructure and frontier models remain concentrated in a small number of economies, leaving many countries, especially in the Global South, with limited ability to participate in standard-setting. He described open-source AI as one possible contribution to inclusion, while acknowledging that it is not a complete solution.

Across the session, speakers repeatedly stressed that AI’s benefits are real but not automatic. They said successful use of AI depends on infrastructure, institutions, skills, local context, language inclusion and governance capacity. At the same time, they warned that harms are already visible, including cyber vulnerabilities, mistranslation, emotional dependency, manipulation, environmental pressure and risks to children.

The session concluded with Ressa and Bengio formally handing the report to the Global Dialogue. Bengio warned that many people still underestimate the possibility that AI capabilities may continue to grow in ways that could reshape global power dynamics. Ressa urged the Dialogue to act on the evidence presented by the panel, saying the difficult work now lies with policymakers and institutions responsible for shaping AI governance.

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WSIS session calls for meaningful connectivity as AI and e-governance expand

Speakers at the WSIS Forum 2026 warned that AI strategies, digital identity systems and e-government services are advancing faster than meaningful connectivity in many parts of Africa and the wider Global South, leaving rural communities, low-income groups, women and persons with disabilities at risk of further exclusion.

The session, titled ‘Closing Africa’s Connectivity Gap in the Age of AI and E-Governance’, took place during the WSIS Forum 2026 in Geneva. The annual forum, co-organised by ITU, UNESCO, UNDP and UNCTAD, brings together governments, international organisations, civil society, the private sector, academia and technical communities to discuss digital cooperation and sustainable development.

Opening the session, Thobekile Matimbe of Paradigm Initiative framed the discussion around evidence from more than 28 countries. She said governments are increasingly adopting AI strategies, digital IDs and online public services, but many people still lack the connectivity, devices and conditions needed to benefit from them. Based on Paradigm Initiative’s work, she argued that the digital divide is widening rather than narrowing.

Bridget Hanani Ndlovu outlined the scale of exclusion, noting that 2.6 billion people remain unconnected globally and that more than half of Africa’s population is still offline. She stressed that the problem is not only missing infrastructure, but also what she described as ‘deliberate disconnection’, including internet shutdowns.

Ndlovu said Paradigm Initiative’s 2025 review of 29 African countries found that nine had implemented internet shutdowns. She cited Kenya and Tanzania as examples where connectivity can be disrupted even when infrastructure exists, arguing that such measures limit people’s ability to access information, public services and economic opportunities.

She also warned that AI-powered digital identity systems can deepen exclusion when introduced in unequal contexts. Referring to Uganda, Ndlovu said elderly people, women and persons with disabilities had faced difficulties accessing services linked to digital ID systems. She said digital systems must be designed and implemented with affected communities in mind, rather than assuming that technology will automatically improve access.

Affordability was another recurring concern. Ndlovu said data costs remain prohibitive in several African countries, giving Zimbabwe as an example where internet access can be unaffordable for low-income users. She also pointed to infrastructure problems in parts of Nigeria, including Zamfara North, where communities continue to experience limited or unreliable access.

Shumaila Shahani, a human rights lawyer, said similar challenges exist in South Asia and urged participants to focus on the human consequences of weak connectivity. She said poor access is not only about slow speeds or failed downloads, but can determine whether people receive essential services. As an example, she said biometric failures can prevent people from receiving food rations.

Shahani also linked connectivity to electricity access, explaining that unreliable power and limited charging options can make mobile devices unusable. She said women and persons with disabilities are often particularly affected when charging points, devices, and digital services are not accessible to them.

Her main warning was that AI-enabled and digital systems become harmful when they replace older offline channels before everyone can use the new systems. She said the ‘new AI door’ is not the problem by itself, but that exclusion occurs when it becomes the only door available.

The panel also discussed Universal Service Funds (USFs), which are intended to support connectivity in underserved areas. Ndlovu said many African countries have USFs in law, but implementation is often weak, transparency is limited and public information on budgets and progress is difficult to find.

She cited several country examples, saying Ethiopia had created a framework without an operational fund, Somalia lacked a functioning USF, Sudan had repeatedly established a fund without effective implementation, and telecom operators in the Democratic Republic of the Congo had not made required contributions. She added that South Africa showed stronger transparency around its fund, while Namibia had begun rollout work and Tunisia had pursued alternative coverage models through ‘white zones’.

Shahani suggested that USFs should be complemented by other affordability measures, including reduced taxes on handsets, device financing, targeted support for women’s connectivity and legal obligations requiring private operators to extend rural coverage. She said the connectivity policy should also address the electricity infrastructure, including solar-powered towers.

The speakers also called for stronger accountability before governments deploy AI-integrated public systems. Ndlovu said governments should conduct human rights impact assessments before adopting digital identity or AI systems and should consult affected communities early, not only at the end of the policy process.

She argued that governments and international processes should measure harms and impacts, not only infrastructure rollout or the number of AI tools adopted. Matimbe supported this point, saying implementation must include civil society and other stakeholders at the national level, not only governments and companies.

Shahani added that connectivity statistics should better reflect meaningful access. She said counting someone as connected because they have 2G access does not capture whether they can actually use digital public services, AI tools or online education. Measurement, she argued, should include device capability, speed, affordability and daily use.

She also said national AI strategies must include explicit connectivity budgets, warning that ‘any national AI strategy without a connectivity budget’ is ‘just a press release’.

In the audience discussion, speakers addressed whether women’s connectivity should be treated separately from household access. Ndlovu said women are often specifically disadvantaged in access to technology and should not have to depend on devices controlled by others. Shahani added that if a woman relies on her partner’s phone, that access is not meaningful or independent.

Across the session, speakers agreed that meaningful connectivity in the AI era requires more than network coverage. It also depends on affordability, electricity, devices, protection from shutdowns, functioning Universal Service Funds, inclusive design, offline alternatives and rights-based assessments before new systems are deployed.

The discussion concluded with a shared emphasis on implementation. Speakers argued that governments, companies, civil society and technical experts need to work together to ensure that AI, digital identity and e-governance systems do not deepen exclusion, but instead expand access to services and opportunities for communities that remain offline or underserved.

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