Digital standards Archives | Page 3 of 359

Publishers challenge OpenAI over alleged copyright infringement

Legal pressure is increasing on OpenAI as Encyclopaedia Britannica and Merriam-Webster file a lawsuit accusing the company of large-scale copyright violations.

According to the complaint, nearly 100,000 copyrighted articles were allegedly used without authorisation to train large language models. Publishers also argue that AI-generated outputs can reproduce parts of their content, raising concerns about unauthorised distribution.

Additional claims focus on how AI systems retrieve and present information. The lawsuit argues that retrieval-augmented generation tools may rely on proprietary databases, potentially undermining publishers’ business models by reducing traffic to original sources.

Concerns are also raised about inaccurate outputs attributed to publishers, which could affect trust in established information providers. The case highlights ongoing tensions between AI development and intellectual property protections.

Growing legal disputes involving media organisations, including The New York Times, suggest that courts will play a key role in defining how copyrighted material can be used in AI training.

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ECA Digital law raises pressure on Big Tech in Brazil

Brazil is set to enforce a new law aimed at strengthening protections for children online, marking a significant shift in how digital platforms are regulated in the country. The legislation, known as ECA Digital, introduces stricter rules for technology companies and will test whether stronger oversight can translate into real-world impact.

The law, which takes effect this week, allows authorities to impose warnings and fines of up to $10 million for violations. In severe cases, courts may order the suspension or banning of platforms operating in B razil. The measure was passed rapidly following public outrage over online content involving the sexualisation of minors.

ECA Digital builds on Brazil’s existing child protection framework and adapts it to the digital environment. It introduces obligations such as age verification, stricter content moderation, and mechanisms to remove harmful material involving minors without requiring a court order.

The law also targets platform design, requiring companies to limit features that may encourage compulsive use among children. This includes restrictions on excessive notifications, profiling for targeted advertising, and design elements that prolong user engagement.

Enforcement of ECA Digital will be led by Brazil’s data protection authority, ANPD, alongside a new screening centre within the Federal Police. However, implementation challenges remain, including limited regulatory capacity and the short timeline between the law’s approval and enforcement.

Experts say the law reflects a broader global trend, with dozens of countries considering similar measures. While technology companies have introduced tools such as age verification and parental controls, critics argue that bigger changes to platform design and content moderation are still needed.

Brazil’s experience may serve as a test case for how governments balance child protection, platform responsibility, and enforcement capacity. The effectiveness of ECA Digital will depend not only on its legal framework but also on how rigorously it is applied in practice.

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Google launches AI skills initiative to support Europe’s workforce transition

At the Future of Work Forum, Google introduced ‘AI Works for Europe’, a programme aimed at strengthening digital skills and supporting workforce adaptation to AI across the region.

Funding of $30 million will be directed through Google.org to expand training opportunities, alongside broader access to AI certification programmes designed to help individuals and businesses adopt new technologies in practical contexts.

A central focus involves preparing workers and students for labour market changes.

Partnerships with organisations such as INCO are supporting the development of targeted training programmes, particularly in sectors where demand for AI-related skills is increasing, including finance, logistics and marketing.

New educational pathways are also being introduced, including an expanded AI Professional Certificate available in multiple European languages. These initiatives aim to improve AI literacy and provide hands-on experience aligned with employer expectations.

Collaboration with local organisations and institutions remains a key element, reflecting a broader strategy to ensure access to training across different regions and communities.

Efforts to expand AI capabilities across Europe highlight the growing importance of skills development as AI becomes more integrated into economic activity.

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MIT research highlights embedded and enacted risks in AI

Generative AI offers major productivity and growth opportunities, but also brings new risks as organisations move from experiments to full deployment. MIT research highlights key risk areas, including training data, foundation models, user prompts, and system prompts.

Researchers identify two types of risk.

Embedded risks come from the technology itself, shaped by model behaviour, data quality, and vendor updates, and are mostly outside an organisation’s control.

Enacted risks arise from choices in deploying AI, from prompt design to agent permissions, and require strong governance.

Advanced uses such as retrieval-augmented generation (RAG) and autonomous AI agents increase exposure. RAG uses internal data to improve outputs, but may reveal sensitive information or control gaps. AI agents acting across multiple tools can lead to ‘autonomy creep,’ performing tasks without proper oversight.

To manage AI risk, organisations should map tools, assign ownership, track outputs, and use separate strategies for embedded and enacted risks. Vendor engagement, governance frameworks, and technical controls are essential for safe AI use.

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AI-powered MRI previews aim to reduce errors and rescans

Philips is creating AI-driven predictive MRI previews to improve scan planning and reduce operator variability. Using NVIDIA accelerated computing and foundation models, the system creates a pre-scan image to validate protocols, optimise positioning, and spot potential issues.

The technology is based on a dedicated MR foundation model trained on diverse datasets covering anatomies, field strengths, protocols, and artefacts.

When combined with NVIDIA’s NV‑Generate, NV‑Segment, and NV‑Reason models, the platform integrates image generation, segmentation, and interpretation. It creates a single intelligent workflow that supports consistent and efficient MRI procedures.

Predictive previews reduce rescans, enhance image quality, and increase technologist confidence, especially in complex exams or areas with limited expertise. Early guidance helps confirm protocols, optimise positioning, and flag issues that could affect diagnostic outcomes.

Philips envisions autonomous MRI, with AI monitoring image quality, guiding positioning, and assisting radiologists with actionable insights. Predictive imaging boosts consistency, efficiency, and access, improving patient experience and expanding MRI availability.

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xAI faces lawsuit over alleged misuse of AI image generation

Legal action has been filed against xAI in a US federal court, with plaintiffs alleging that its AI system Grok was used to generate harmful and explicitly manipulated images of minors.

The lawsuit claims that xAI failed to implement adequate safeguards to prevent the creation of such content, despite similar protections adopted by other AI developers.

According to the filing, the technology enabled the transformation of real images into explicit material without sufficient restrictions.

Plaintiffs seek to establish a class action, arguing that the company should be held accountable for both direct and third-party uses of its models. Legal arguments focus on whether responsibility extends to external applications built using the same underlying AI systems.

The case also highlights broader regulatory challenges surrounding AI-generated content, particularly the difficulty of preventing misuse when systems can modify real images. Questions around platform liability, safety standards, and enforcement are likely to shape future policy discussions.

Growing scrutiny of AI developers reflects increasing concern over how generative systems are deployed, especially in contexts involving sensitive or harmful content.

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New licensing rules for crypto platforms in Australia

Australia is advancing plans to regulate digital asset platforms under its financial services framework. The Senate committee recommended passing the Digital Assets Framework Bill 2025, bringing Australia closer to licensing crypto exchanges and tokenisation platforms.

Industry groups have raised concerns about definitions such as ‘digital token’ and ‘factual control.’ Broad wording could inadvertently cover infrastructure providers, including multi-party wallet systems, potentially classifying them as financial service operators.

Ripple Labs emphasised the need for precise language to avoid unintended regulation.

The committee supported the Treasury’s approach while planning to refine technical details through future regulations. Coinbase welcomed the progress but noted ongoing banking challenges for crypto firms.

The bill now proceeds to the Senate for debate and a final vote, which could reshape digital asset operations in Australia.

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Microsoft Exchange Online outage affects users globally

A service disruption has affected users of Microsoft Exchange Online, and Microsoft has confirmed ongoing investigations into mailbox access issues affecting enterprise customers worldwide.

Reports indicate that Microsoft users encountered difficulties connecting via multiple access points, including the Microsoft Outlook desktop and mobile applications and browser-based email services. The issue affects specific connection methods rather than the entire platform.

Organisations relying on cloud-based communication tools experienced interruptions in email workflows, calendar scheduling, and shared mailbox functionality. Such disruptions can significantly disrupt operational continuity, particularly for businesses that depend on real-time communication systems.

Updates through Microsoft’s service health channels suggest that engineering teams are working to identify the root cause, though no definitive explanation has yet been provided.

Such incidents highlight broader concerns around resilience in cloud infrastructure, as enterprises increasingly depend on centralised platforms for critical communication services.

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NVIDIA expands physical AI ecosystem to accelerate real world robotics

Partnerships across the robotics sector are positioning NVIDIA at the centre of what is increasingly described as ‘physical AI’, a shift towards intelligent machines capable of perceiving, reasoning and acting in real environments.

A new generation of tools, including NVIDIA Cosmos world models and updated NVIDIA Isaac simulation frameworks, aims to support developers in training and validating robots before deployment.

These systems enable companies to simulate complex environments, reducing the risks and costs of real-world testing.

Industrial robotics leaders such as ABB Robotics, KUKA, and FANUC are integrating NVIDIA technologies into digital twin environments, enabling more accurate modelling of production lines and automation systems.

Advances are also extending into humanoid robotics, where companies are using AI models to develop machines capable of more flexible and adaptive behaviour.

New foundation models, including GR00T systems, are designed to give robots general-purpose capabilities instead of limiting them to specific tasks.

Healthcare and logistics represent additional areas of deployment, with robotics platforms being tested in surgical systems, warehouse automation and manufacturing environments. These applications highlight how physical AI could reshape industries requiring precision, safety and scalability.

Growing collaboration across cloud providers, manufacturers and AI developers suggests that robotics is moving toward a more integrated ecosystem, where simulation, data generation and deployment are increasingly interconnected.

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6G will make wireless networks capable of thinking for themselves

Unlike its predecessors, 6G is being designed from the ground up with AI as a core feature rather than a performance add-on.

From user devices and base stations through to the network core, AI and machine learning will enable 6G networks to self-optimise, manage interference, predict user mobility, and make real-time decisions with minimal human intervention.

One of 6G’s most distinctive capabilities will be Integrated Sensing and Communication (ISAC), which allows radio signals to simultaneously carry data and sense the surrounding environment, effectively turning the network into a vast, distributed sensor capable of detecting motion, tracking objects, and supporting applications such as predictive maintenance and autonomous vehicles.

AI plays a central role in interpreting this sensing data in real time, enabling split-second responses to real-world conditions.

Standardisation efforts are already underway, with 3GPP’s Release 20 exploring how AI and machine learning can optimise the air interface and improve tasks such as channel state information compression.

Commercial 6G deployment is expected in the early 2030s, by which point AI is projected to act as the brain and nervous system of key parts of the network, constantly learning, adapting, and optimising with little human oversight.

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