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Meta launches new AI glasses with Muse Spark assistant

Meta has launched a new generation of AI glasses in partnership with EssilorLuxottica, expanding its push to make wearable AI a mainstream consumer technology.

The new Meta Glasses build on the company’s existing AI eyewear portfolio and will launch with 26 styles across different colours, lenses and frames.

Meta said the glasses include hands-free photo and video capture, open-ear audio, voice control, calls and messaging, live translation and access to Meta AI. The company also said the device offers more than eight hours of battery life, with a charging case providing up to 40 additional hours.

The glasses are the first in Meta’s AI eyewear line to launch with Meta AI powered by Muse Spark from day one. Meta said the model, developed by Meta Superintelligence Labs, gives the assistant stronger multimodal capabilities, including a better understanding of what users are seeing.

The company said the assistant can answer questions, suggest local recommendations, support daily tasks and help users manage schedules hands-free. Meta is also adding features such as dynamic photo capture, pedestrian navigation for displayless glasses and live translation support for 14 additional languages.

The launch reflects growing competition in AI wearables, as technology companies seek new interfaces beyond smartphones. By combining AI assistance with everyday eyewear, Meta is trying to position smart glasses as a practical gateway to always-available AI services.

Why does it matter?

AI glasses move digital assistants closer to the physical world, giving AI systems access to what users see, hear and do throughout the day. That could make AI more useful for translation, navigation, accessibility and hands-free computing, but it also raises questions over privacy, bystander consent, data collection and dependence on platform-controlled AI assistants.

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World Bank says AI could boost Poland’s GDP by up to 12% by 2035

The World Bank Group says AI could increase Poland’s real GDP by between 1.3% and 12.1% by 2035, depending on the pace of business adoption, workforce adaptation and supportive public policies.

In its report, ‘Navigating the Age of AI: Implications for Poland’s Economy‘, the World Bank Group said AI-driven productivity gains could begin emerging within three years. However, with only 8% of Polish firms currently using AI, the report identifies substantial scope for further adoption and productivity gains.

The report suggests that AI‘s most significant impact is likely to be on how work is organised and performed rather than on the overall composition of the economy. The business services sector is expected to be among the first to experience significant change as routine and repetitive tasks become increasingly automated.

The report argues that capturing AI’s benefits will require sustained investment in digital infrastructure, skills development and innovation, alongside labour-market measures designed to support workforce transition and adaptation. The report was developed in collaboration with the Government of Poland, academia, think tanks and international partners in Warsaw.

Why does it matter?

The report highlights the growing importance of AI as a driver of productivity and economic growth. For countries such as Poland, the potential gains from AI will depend not only on technological adoption but also on the ability of businesses, workers and institutions to adapt to changing economic conditions.

The findings also reinforce a broader policy lesson emerging globally: AI’s economic impact is likely to be shaped as much by investments in skills, infrastructure and labour-market resilience as by the technology itself. Countries that successfully combine innovation with workforce development may be better positioned to capture productivity gains while limiting disruption and inequality during the transition.

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OECD report highlights AI’s growing role in workforce training

AI is beginning to reshape how vocational education and training (VET) systems design qualifications, update curricula and respond to rapidly changing labour market demands, according to a new OECD report.

As economies undergo digital and green transitions, education authorities face growing pressure to ensure training programmes remain aligned with evolving workforce needs.

The report finds that AI is already being used across parts of the vocational education ecosystem to analyse labour market trends, identify emerging skills gaps, map competencies and support curriculum development.

Countries, including the Netherlands, Switzerland, Estonia and Germany, have launched pilot initiatives using AI tools to accelerate and improve qualification design and revision processes.

AI is also being explored as a mechanism for supporting modular learning pathways and micro-credentials in sectors experiencing rapid technological change.

Despite growing interest, the OECD stresses that AI adoption remains uneven and largely experimental. Most systems continue to rely on traditional governance structures involving employers, industry representatives, educators and public authorities.

Rather than replacing existing governance processes, AI is currently being used to support evidence gathering, stakeholder consultations and administrative functions. The organisation notes that countries with strong digital infrastructures and advanced labour market intelligence systems are better positioned to move from isolated pilots to broader implementation.

The report also warns that broader AI adoption could introduce new risks for vocational education systems. Concerns include biased outputs, poor data quality, reduced transparency, cybersecurity vulnerabilities and the possibility of weakening collaborative decision-making.

To address these challenges, the OECD argues that AI deployment must remain human-centred and operate within robust governance frameworks. Maintaining accountability, ensuring stakeholder participation and protecting data integrity will be critical as governments increasingly integrate AI into education and workforce development policies.

Why does it matter?

Vocational education systems play a critical role in preparing workers for changing labour markets. As digitalisation, automation and the green transition reshape skills demand, governments are looking for ways to update qualifications and training programmes more quickly. The OECD report suggests that AI could help education systems identify emerging workforce needs, improve labour market intelligence and make curriculum development more responsive.

At the same time, the report highlights that technological innovation alone is unlikely to solve skills challenges. The effectiveness of AI in vocational education will depend on strong governance, reliable data, stakeholder participation and human oversight. How governments balance efficiency gains with transparency, accountability and trust could shape the future of workforce development and lifelong learning policies.

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EU agrees tougher child protection rules against AI-generated abuse

The agreement between the European Parliament and the Council updates legislation first adopted in 2011, reflecting the growing role of digital technologies and AI in facilitating abuse.

Under the revised directive, designing, adapting or distributing AI systems intended to generate child sexual abuse material would become a criminal offence. The updated rules would also cover deepfake abuse material, livestreamed child sexual abuse, sexual extortion, and the possession or distribution of instructions on how to commit such crimes.

The agreement also strengthens rules on consent. It clarifies that consent must be given voluntarily, cannot be inferred from silence, lack of resistance or a previous relationship, and can be withdrawn at any time.

Grooming offences would be expanded to cover situations involving coercion, threats or deception, including cases where offenders falsely present themselves as peers of the child.

Victim protection would also be strengthened through access to healthcare, legal aid, helplines, accommodation support and compensation mechanisms. The agreement also extends limitation periods, recognising that many victims need years or decades before reporting abuse.

The revised directive still requires formal adoption by the European Parliament and the Council before entering into force.

Why does it matter?

The agreement shows how EU criminal law is being adapted to AI-enabled and online forms of child sexual abuse. Criminalising AI systems designed to generate abusive material is especially significant because it targets not only harmful content but also the tools used to produce it. The revised directive also strengthens victim support and prosecution timelines, addressing the reality that many survivors report abuse years after it occurred.

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Reflection secures SpaceXAI compute deal for open-source AI models

Open-source AI startup Reflection has signed a major compute agreement with SpaceXAI, giving the company access to Colossus 2 data centre capacity as it works to develop frontier AI models.

According to Axios, Reflection will begin paying $150 million per month from 1 July 2026 for access to the infrastructure through 2029. The deal is intended to give the Nvidia-backed startup the computing power needed to compete with leading AI companies.

Reflection is developing open-source AI models at a time when access to advanced chips and large-scale data centre capacity has become a major barrier to frontier model development.

The agreement highlights the growing importance of specialised AI infrastructure providers. Rather than building all capacity internally, AI developers are increasingly relying on large compute partnerships to secure the resources needed for training and operating advanced models.

It also points to SpaceXAI’s expanding role in the AI infrastructure market. The company has been offering access to Colossus data centre capacity to AI developers, turning large-scale compute into a strategic asset within the AI ecosystem.

The deal reflects a broader shift in the AI race, where access to GPUs, power, data centres and long-term infrastructure contracts can be as important as model design or software talent.

Why does it matter?

The Reflection-SpaceXAI deal shows how compute access is becoming a decisive factor in AI competition. Open-source AI developers may benefit from wider access to large-scale infrastructure, but such deals also concentrate strategic power among companies that control chips, energy, data centres and financing. That makes AI infrastructure a governance issue, not only a business or engineering concern.

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Oxford researchers develop AI tool to map hidden effects of high blood pressure

Researchers led by the University of Oxford have developed an AI tool called ‘HyperScore’ that could help doctors better understand how high blood pressure affects different organs and individuals in different ways. The approach could support more personalised treatment strategies in the future.

Using the AI tool, researchers identified six distinct patterns of hypertension-related disease by analysing hundreds of measurements, including cardiac imaging, brain MRI scans, blood tests and assessments of the kidneys, liver and vascular system.

The study found that individuals with higher HyperScores faced a greater risk of future cardiovascular events, even when conventional blood pressure measurements did not fully capture that risk. Changes detected through brain MRI imaging emerged as some of the strongest indicators of hypertension-related organ damage.

The researchers analysed data from more than 27,000 participants in the UK Biobank and validated their findings in an additional cohort of more than 5,500 individuals in the US. The researchers cautioned that the approach remains at an early stage and is not yet ready for routine clinical use in the UK.

Why does it matter?

High blood pressure is one of the world’s leading risk factors for heart disease, stroke and other chronic conditions, yet patients with similar blood pressure readings can experience very different health outcomes. The study suggests that AI may help identify hidden patterns of organ damage that are not captured by conventional measurements, potentially enabling more accurate risk assessment and personalised treatment strategies.

The research also highlights the growing role of AI in precision medicine. By combining imaging, laboratory data and clinical information, AI systems may help clinicians move beyond one-size-fits-all approaches to disease management. Although HyperScore remains at an early research stage, the findings demonstrate how AI could support earlier intervention and more targeted care for patients with complex cardiovascular risks.

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Indonesia plans AI integration across major government programmes

Indonesia plans to integrate AI into major government programmes, including its flagship free meals initiative valued at approximately $15 billion, under a draft presidential regulation awaiting approval from President Prabowo Subianto.

The draft establishes a roadmap for AI adoption across ministries and regional governments between 2026 and 2029. It aims to improve economic growth and strengthen Indonesia’s competitiveness in AI at both regional and global levels.

Under the proposals, AI would support the free meals programme by helping design local menus, monitor food safety and kitchen hygiene, forecast demand, detect irregularities and integrate health data for early-warning systems. AI would also support free health screenings and tuberculosis testing.

The draft also proposes the creation of a sovereign AI fund, fiscal incentives for researchers and safeguards to address risks such as biometric misuse, intellectual property violations and deepfakes. Experts cautioned that significant infrastructure gaps, limited digital skills and uneven technological capacity could pose challenges to implementation, which remains at an early stage.

Why does it matter?

The proposal illustrates how governments are increasingly seeking to integrate AI into core public-service delivery rather than limiting its use to pilot projects or administrative functions. Applying AI to areas such as nutrition programmes, healthcare screening and public-sector operations could improve efficiency, resource allocation and service delivery for millions of citizens.

The initiative also highlights the challenges facing emerging economies as they pursue AI-driven development. While Indonesia is seeking to build domestic AI capacity through funding mechanisms and incentives, successful implementation will depend on investments in digital infrastructure, technical expertise and governance frameworks capable of addressing risks such as deepfakes, privacy concerns and misuse of biometric data.

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Malaysia moves to strengthen laws against AI-enabled crimes

Malaysia is moving to strengthen its legal framework to address AI-enabled offences, including deepfakes, identity impersonation and AI-generated child sexual abuse material, according to Digital Minister Gobind Singh Deo.

Speaking in the Dewan Rakyat, Gobind said Malaysia already has legal protections in several areas, particularly those involving children, but that the country’s regulatory framework must evolve to keep pace with emerging AI-related risks, especially those affecting young people.

The minister said the government is pursuing a two-pronged strategy that combines safety-by-design measures during AI development with stronger enforcement mechanisms when AI-generated content violates existing laws.

Gobind added that the government is consulting academics, religious leaders and other stakeholders as part of its review process to ensure future regulations remain effective as AI technologies continue to evolve.

Why does it matter?

The initiative reflects a growing challenge facing governments worldwide: adapting legal systems to address harms created or amplified by AI technologies. Deepfakes, synthetic identities and AI-generated abuse material are creating new enforcement challenges that often do not fit neatly within existing legal frameworks designed for earlier digital technologies.

Malaysia’s approach also highlights an emerging policy trend that combines prevention and enforcement. Rather than relying solely on criminal penalties, governments are increasingly exploring safety-by-design requirements, risk management measures and stakeholder consultation to reduce harm before it occurs. The outcome of Malaysia’s review could influence how other countries in the region approach AI governance, online safety and digital rights.

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Los Angeles AI arts museum Dataland opens with Google Cloud support

Dataland, a Los Angeles museum dedicated to AI-based art, has opened to the public with Google serving as a technology and creative collaborator.

The museum was co-founded by media artist Refik Anadol and Efsun Erkılıç and is located at The Grand LA in downtown Los Angeles. Google says the 25,000-square-foot space is designed as an interactive environment where data, machine learning and sensory experiences form part of the artwork.

Its inaugural exhibition, ‘Machine Dreams: Rainforest’, uses Anadol’s Large Nature Model, an AI system trained on environmental datasets, to transform natural-world data into large-scale generative visuals.

Google Cloud provides infrastructure for the museum’s real-time image generation, soundscapes, scent augmentation and interactive visitor experiences. Google says the system uses tools including Gemini, diffusion models and generative adversarial networks.

The project builds on a decade of collaboration between Google and Anadol, including work using LA Philharmonic archives, Google Quantum AI data, planetary datasets and the ‘Machine Dreams: Biophilia’ installation at Google’s Mountain View campus.

Google Arts & Culture is also supporting the Dataland AI Artist Residency, a six-month programme for four artists. The residency will provide grants, mentorship from Refik Anadol Studio and access to Google Cloud tools and machine learning models.

Why does it matter?

Dataland shows how AI art is moving from experimental installations into permanent cultural infrastructure. It also highlights the role of cloud providers and large AI platforms in shaping creative production, exhibition design and access to machine-learning tools. For cultural institutions, the project raises broader questions about authorship, data provenance, sustainability, audience interaction and the dependence of new creative formats on private technology infrastructure.

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EPO places AI and quality at the centre of SACEPO discussions

The European Patent Office used the 58th meeting of the Standing Advisory Committee before the EPO to discuss patent quality, AI and the digital transformation of the European patent system.

The annual Main SACEPO meeting brought together users of the patent system to review the EPO’s Quality Action Plan 2026, legal changes, the Unitary Patent system and activities of the EPO Observatory and IP Lab.

A key focus was the use of AI to support the patent-granting process. The EPO said AI tools are intended to help examiners improve efficiency, consistency and completeness, while all patent decisions remain under human responsibility.

Participants also discussed progress on quality measures, stakeholder feedback and continued investment in examiner expertise, quality assurance and user engagement.

The meeting reviewed the EPO’s transition to a paperless patent-granting process, planned for April 2027, as well as updates to MyEPO services and DOCX filing.

Discussions also covered recent legal changes, the operational development of the Unitary Patent system, patent validation agreements, implementation of the WIPO treaty on genetic resources and traditional knowledge, and new activities from the EPO Observatory on Patents and Technology.

Why does it matter?

The meeting shows how AI is becoming part of the everyday infrastructure of patent administration. For patent offices, AI can support searches, classification, workflows and consistency, but legal certainty still depends on human responsibility and procedural safeguards. The EPO’s approach also reflects a wider shift towards fully digital public services in intellectual property, where automation, quality control and user trust need to develop together.

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