Network security

SAP elevates customer support with proactive AI systems

AI has pushed customer support into a new era, where anticipation replaces reaction. SAP has built a proactive model that predicts issues, prevents failures and keeps critical systems running smoothly instead of relying on queues and manual intervention.

Major sales events, such as Cyber Week and Singles Day, demonstrated the impact of this shift, with uninterrupted service and significant growth in transaction volumes and order numbers.

Self-service now resolves most issues before they reach an engineer, as structured knowledge supports AI agents that respond instantly with a confidence level that matches human performance.

Tools such as the Auto Response Agent and Incident Solution Matching enable customers to retrieve solutions without having to search through lengthy documentation.

SAP has also prepared organisations scaling AI by offering support systems tailored for early deployment.

Engineers have benefited from AI as much as customers. Routine tasks are handled automatically, allowing experts to focus on problems that demand insight instead of administration.

Language optimisation, routing suggestions, and automatic error categorisation support faster and more accurate resolutions. SAP validates every AI tool internally before release, which it views as a safeguard for responsible adoption.

The company maintains that AI will augment staff rather than replace them. Creative and analytical work becomes increasingly important as automation handles repetitive tasks, and new roles emerge in areas such as AI training and data stewardship.

SAP argues that progress relies on a balanced relationship between human judgement and machine intelligence, strengthened by partnerships that turn enterprise data into measurable outcomes.

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Cyber Resilience Act signals a major shift in EU product security

EU regulators are preparing to enforce the Cyber Resilience Act, setting core security requirements for digital products in the European market. The law spans software, hardware, and firmware, establishing shared expectations for secure development and maintenance.

Scope captures apps, embedded systems, and cloud-linked features. Risk classes run from default to critical, directing firms to self-assess or undergo third-party checks. Any product sold beyond December 2027 must align with the regulation.

Obligations apply to manufacturers, importers, distributors, and developers. Duties include secure-by-design practices, documented risk analysis, disclosure procedures, and long-term support. Firms must notify ENISA within 24 hours of active exploitation and provide follow-up reports on a strict timeline.

Compliance requires technical files covering threat assessments, update plans, and software bills of materials. High-risk categories demand third-party evaluation, while lower-risk segments may rely on internal checks. Existing certifications help, but cannot replace CRA-specific conformity work.

Non-compliance risks fines, market restrictions, and reputational damage. Organisations preparing early are urged to classify products, run gap assessments, build structured roadmaps, and align development cycles with CRA guidance. EU authorities plan to provide templates and support as firms transition.

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ChatGPT users gain Jira and Confluence access through Atlassian’s MCP connector

Atlassian has launched a new connector that lets ChatGPT users access Jira and Confluence data via the Model Context Protocol. The company said the Rovo MCP Connector supports task summarisation, issue creation and workflow automation directly inside ChatGPT.

Atlassian noted rising demand for integrations beyond its initial beta ecosystem. Users in Europe and elsewhere can now draw on Jira and Confluence data without switching interfaces, while partners such as Figma and HubSpot continue to expand the MCP network.

Engineering, marketing and service teams can request summaries, monitor task progress and generate issues from within ChatGPT. Users can also automate multi-step actions, including bulk updates. Jira write-back support enables changes to be pushed directly into project workflows.

Security updates sit alongside the connector release. Atlassian said the Rovo MCP Server uses OAuth authentication and respects existing permissions across Jira and Confluence spaces. Administrators can also enforce an allowlist to control which clients may connect.

Atlassian frames the initiative as part of its long-term focus on open collaboration. The company said the connector reflects demand for tools that unify context, search and automation, positioning the MCP approach as a flexible extension of existing team practices.

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Uzbekistan sets principles for responsible AI

A new ethical framework for the development and use of AI technologies has been adopted by Uzbekistan.

The rules, prepared by the Ministry of Digital Technologies, establish unified standards for developers, implementing organisations and users of AI systems, ensuring AI respects human rights, privacy and societal trust.

A framework that is part of presidential decrees and resolutions aimed at advancing AI innovation across the country. It also emphasises legality, transparency, fairness, accountability, and continuous human oversight.

AI systems must avoid discrimination based on gender, nationality, religion, language or social origin.

Developers are required to ensure algorithmic clarity, assess risks and bias in advance, and prevent AI from causing harm to individuals, society, the state or the environment.

Users of AI systems must comply with legislation, safeguard personal data, and operate technologies responsibly. Any harm caused during AI development or deployment carries legal liability.

The Ministry of Digital Technologies will oversee standards, address ethical concerns, foster industry cooperation, and improve digital literacy across Uzbekistan.

An initiative that aligns with broader efforts to prepare Uzbekistan for AI adoption in healthcare, education, transport, space, and other sectors.

By establishing clear ethical principles, the country aims to strengthen trust in AI applications and ensure responsible and secure use nationwide.

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Meta expands global push against online scam networks

The US tech giant, Meta, outlined an expanded strategy to limit online fraud by combining technical defences with stronger collaboration across industry and law enforcement.

The company described scams as a threat to user safety and as a direct risk to the credibility of its advertising ecosystem, which remains central to its business model.

Executives emphasised that large criminal networks continue to evolve and that a faster, coordinated response is essential instead of fragmented efforts.

Meta presented recent progress, noting that more than 134 million scam advertisements were removed in 2025 and that reports about misleading advertising fell significantly in the last fifteen months.

It also provided details about disrupted criminal networks that operated across Facebook, Instagram and WhatsApp.

Facial recognition tools played a crucial role in detecting scam content that utilised images of public figures, resulting in an increased volume of removals during testing, rather than allowing wider circulation.

Cooperation with law enforcement remains central to Meta’s approach. The company supported investigations that targeted criminal centres in Myanmar and illegal online gambling operations connected to transfers through anonymous accounts.

Information shared with financial institutions and partners in the Global Signal Exchange contributed to the removal of thousands of accounts. At the same time, legal action continued against those who used impersonation or bulk messaging to deceive users.

Meta stated that it backs bipartisan legislation designed to support a national response to online fraud. The company argued that new laws are necessary to weaken transnational groups behind large-scale scam operations and to protect users more effectively.

A broader aim is to strengthen trust across Meta’s services, rather than allowing criminal activity to undermine user confidence and advertiser investment.

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NVIDIA platform lifts leading MoE models

Frontier developers are adopting a mixture-of-experts architecture as the foundation for their most advanced open-source models. Designers now rely on specialised experts that activate only when needed instead of forcing every parameter to work on each token.

Major models, such as DeepSeek-R1, Kimi K2 Thinking, and Mistral Large 3, rise to the top of the Artificial Analysis leaderboard by utilising this pattern to combine greater capability with lower computational strain.

Scaling the architecture has always been the main obstacle. Expert parallelism requires high-speed memory access and near-instant communication between multiple GPUs, yet traditional systems often create bottlenecks that slow down training and inference.

NVIDIA has shifted toward extreme hardware and software codesign to remove those constraints.

The GB200 NVL72 rack-scale system links seventy-two Blackwell GPUs via fast shared memory and a dense NVLink fabric, enabling experts to exchange information rapidly, rather than relying on slower network layers.

Model developers report significant improvements once they deploy MoE designs on NVL72. Performance leaps of up to ten times have been recorded for frontier systems, improving latency, energy efficiency and the overall cost of running large-scale inference.

Cloud providers integrate the platform to support customers in building agentic workflows and multimodal systems that route tasks between specialised components, rather than duplicating full models for each purpose.

Industry adoption signals a shift toward a future where efficiency and intelligence evolve together. MoE has become the preferred architecture for state-of-the-art reasoning, and NVL72 offers a practical route for enterprises seeking predictable performance gains.

NVIDIA positions its roadmap, including the forthcoming Vera Rubin architecture, as the next step in expanding the scale and capability of frontier AI.

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AWS launches frontier agents to boost software development

AWS has launched frontier agents, autonomous AI tools that extend software development teams. The first three – Kiro, AWS Security Agent, and AWS DevOps Agent – enhance development, security, and operations while working independently for extended periods.

Kiro functions as a virtual developer, maintaining context, learning from feedback, and managing tasks across multiple repositories. AWS Security Agent automates code reviews, penetration testing, and enforces organisational security standards.

AWS DevOps Agent identifies root causes of incidents, reduces alerts, and provides proactive recommendations to improve system reliability.

These agents operate autonomously, scale across multiple tasks, and free teams from repetitive work, allowing focus on high-priority projects. Early users, including SmugMug and Commonwealth Bank of Australia, report quicker development, stronger security, and more efficient operations.

By integrating frontier agents into the software development lifecycle, AWS is shifting AI from task assistance to completing complex projects independently, marking a significant step forward in what AI can achieve for development teams.

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Honolulu in the US pushes for transparency in government AI use

Growing pressure from Honolulu residents in the US is prompting city leaders to consider stricter safeguards surrounding the use of AI. Calls for greater transparency have intensified as AI has quietly become part of everyday government operations.

Several city departments already rely on automated systems for tasks such as building-plan screening, customer service support and internal administrative work. Advocates now want voters to decide whether the charter should require a public registry of AI tools, human appeal rights and routine audits.

Concerns have deepened after the police department began testing AI-assisted report-writing software without broad consultation. Supporters of reform argue that stronger oversight is crucial to maintain public trust, especially if AI starts influencing high-stakes decisions that impact residents’ lives.

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Irish regulator probes an investigation into TikTok and LinkedIn

Regulators in Ireland have opened investigations into TikTok and LinkedIn under the EU Digital Services Act.

Coimisiún na Meán’s Investigations Team believes there may be shortcomings in how both platforms handle reports of suspected illegal material. Concerns emerged during an exhaustive review of Article 16 compliance that began last year and focused on the availability of reporting tools.

The review highlighted the potential for interface designs that could confuse users, particularly when choosing between reporting illegal content and content that merely violates platform rules.

An investigation that will examine whether reporting tools are easy to access, user-friendly and capable of supporting anonymous reporting of suspected child sexual abuse material, as required under Article 16(2)(c).

It will also assess whether platform design may discourage users from reporting material as illegal under Article 25.

Coimisiún na Meán stated that several other providers made changes to their reporting systems following regulatory engagement. Those changes are being reviewed for effectiveness.

The regulator emphasised that platforms must avoid practices that could mislead users and must provide reliable reporting mechanisms instead of diverting people toward less protective options.

These investigations will proceed under the Broadcasting Act of Ireland. If either platform is found to be in breach of the DSA, the regulator can impose administrative penalties that may reach six percent of global turnover.

Coimisiún na Meán noted that cooperation remains essential and that further action may be necessary if additional concerns about DSA compliance arise.

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OpenAI expands investment in mental health safety research

Yesterday, OpenAI launched a new grant programme to support external research on the connection between AI and mental health.

An initiative that aims to expand independent inquiry into how people express distress, how AI interprets complex emotional signals and how different cultures shape the language used to discuss sensitive experiences.

OpenAI also hopes that broader participation will strengthen collective understanding, rather than keeping progress confined to internal studies.

The programme encourages interdisciplinary work that brings together technical specialists, mental health professionals and people with lived experience. OpenAI is seeking proposals that can offer clear outputs, such as datasets, evaluation methods, or practical insights, that improve safety and guidance.

Researchers may focus on patterns of distress in specific communities, the influence of slang and vernacular, or the challenges that appear when mental health symptoms manifest in ways that current systems fail to recognise.

The grants also aim to expand knowledge of how providers use AI within care settings, including where tools are practical, where limitations appear and where risks emerge for users.

Additional areas of interest include how young people respond to different tones or styles, how grief is expressed in language and how visual cues linked to body image concerns can be interpreted responsibly.

OpenAI emphasises that better evaluation frameworks, ethical datasets and annotated examples can support safer development across the field.

Applications are open until 19 December, with decisions expected by mid-January. The programme forms part of OpenAI’s broader effort to invest in well-being and safety research, offering financial support to independent teams working across diverse cultural and linguistic contexts.

The company argues that expanding evidence and perspectives will contribute to a more secure and supportive environment for future AI systems.

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