Artificial intelligence

LIBE backs new Europol Regulation despite data protection and discrimination warnings

The European Parliament’s civil liberties committee (LIBE) voted to endorse a new Europol Regulation, part of the ‘Facilitators Package’, by 59–10 with four abstentions.

Rights groups and the European Data Protection Supervisor had urged MEPs to reject the proposal, arguing the law fuels discrimination and grants Europol and Frontex unprecedented surveillance capabilities with insufficient oversight.

If approved in plenary later this month, the reform would grant Europol broader powers to collect, process and share data, including biometrics such as facial recognition, and enable exchanges with non-EU states.

Campaigners note the proposal advanced without an impact assessment, contrary to the Commission’s Better Regulation guidance.

Civil society groups warn that the changes risk normalising surveillance in migration management. Access Now’s Caterina Rodelli said MEPs had ‘greenlighted the European Commission’s long-term plan to turn Europe into a digital police state’. At the same time, Equinox’s Sarah Chander called the vote proof the EU has ‘abandoned’ humane, evidence-based policy.

EDRi’s Chloé Berthélémy said the reform legitimises ‘unaccountable and opaque data practices’, creating a ‘data black hole’ that undermines rights and the rule of law. More than 120 organisations called on MEPs to reject the text, arguing it is ‘unlawful, unsafe, and unsubstantiated’.

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Snap brings Perplexity’s answer engine into Chat for nearly a billion users

Starting in early 2026, Perplexity’s AI will be integrated into Snapchat’s Chat, accessible to nearly 1 billion users. Snapchatters can ask questions and receive concise, cited answers in-app. Snap says the move reinforces its position as a trusted, mobile-first AI platform.

Under the deal, Perplexity will pay Snap $400 million in cash and equity over a one-year period, tied to the global rollout. Revenue contribution is expected to begin in 2026. Snap points to its 943 million MAUs and reaches over 75% of 13–34-year-olds in 25+ countries.

Perplexity frames the move as meeting curiosity where it occurs, within everyday conversations. Evan Spiegel says Snap aims to make AI more personal, social, and fun, woven into friendships and conversations. Both firms pitch the partnership as enhancing discovery and learning on Snapchat.

Perplexity joins, rather than replaces, Snapchat’s existing My AI. Messages sent to Perplexity will inform personalisation on Snapchat, similar to My AI’s current behaviour. Snap claims the approach is privacy-safe and designed to provide credible, real-time answers from verifiable sources.

Snap casts this as a first step toward a broader AI partner platform inside Snapchat. The companies plan creative, trusted ways for leading AI providers to reach Snap’s global community. The integration aims to enable seamless, in-chat exploration while keeping users within Snapchat’s product experience.

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How GEMS turns Copilot time savings into personalised teaching at scale

GEMS Education is rolling out Microsoft 365 Copilot to cut admin and personalise learning, with clear guardrails and transparency. Teachers spend less time on preparation and more time with pupils. The aim is augmentation, not replacement.

Copilot serves as a single workspace for plans, sources, and visuals. Differentiated materials arrive faster for struggling and advanced learners. More time goes to feedback and small groups.

Student projects are accelerating. A Grade 8 pupil built a smart-helmet prototype, using AI to guide circuitry, code, and documentation. The idea to build functionally moved quickly.

The School of Research and Innovation opened in August 2025 as a living lab, hosting educator training, research partners, and student incubation. A Microsoft-backed stack underpins the campus.

Teachers are co-creating lightweight AI agents for curriculum and analytics. Expert oversight and safety patterns stay central. The focus is on measurable time savings and real-world learning.

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New AI tool helps identify suicide-risk individuals

Researchers at Touro University have found that an AI tool can identify suicide risk that standard diagnostic methods often miss. The study, published in the Journal of Personality Assessment, shows that LLMs can analyse speech to detect patterns linked to perceived suicide risk.

Current assessment methods, such as multiple-choice questionnaires, often fail to capture the nuances of an individual’s experience.

The study used Claude 3.5 Sonnet to analyse 164 participants’ audio responses, examining future self-continuity, a key factor linked to suicide risk. The AI detected subtle cues in speech, including coherence, emotional tone, and detail, which traditional tools overlooked.

While the research focused on perceived risk rather than actual suicide attempts, identifying individuals who feel at risk is crucial for timely intervention. LLM predictions could be used in hospitals, hotlines, or therapy sessions as a new tool for mental health professionals.

Beyond suicide risk, large language models may also help detect other mental health conditions such as depression and anxiety, providing faster, more nuanced insights into patients’ mental well-being and supporting early intervention strategies.

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Naver expands physical AI ambitions with $690 million GPU investment

South Korean technology leader Naver is deepening its AI ambitions through a $690 million investment in graphics processing units from 2025.

A move that aims to strengthen its AI infrastructure and drive the development of physical AI, a field merging digital intelligence with robotics, logistics, and autonomous systems.

Beyond its internal use, Naver plans to monetise its expanded computing power by offering GPU-as-a-Service to clients across sectors, creating new revenue opportunities aligned with its AI ecosystem.

Chief Executive Choi Soo-yeon described physical AI as the firm’s next growth pillar, combining robotics, data, and generative AI to reshape both digital and industrial environments. The company already holds a significant share of the global robotics operating system market, underlining its technological maturity.

An investment that marks a strategic shift from software-based AI to infrastructure-driven intelligence, positioning Naver as a leader in integrating AI with real-world applications.

As global competition intensifies, Naver’s model of coupling high-performance computing with robotics innovation signals the emergence of South Korea as a centre for applied AI technology.

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Material-level AI emerges in MIT–DeRucci sleep science collaboration

MIT’s Sensor and Ambient Intelligence group, led by Joseph Paradiso, unveiled ‘FiberCircuits’, a smart-fibre platform co-developed with DeRucci. It embeds sensing, edge inference, and feedback directly in fibres to create ‘weavable intelligence’. The aim is natural, low-intrusion human–computer interaction.

Teams embedded AI micro-sensors and sub-millimetre ICs to capture respiration, movement, skin conductance, and temperature, running tinyML locally for privacy. Feedback via light, sound, or micro-stimulation closes the loop while keeping power and data exposure low.

Sleep science prototypes included a mattress with distributed sensors for posture recognition, an eye mask combining PPG and EMG, and an IMU-enabled pillow. Prototypes were used to validate signal parsing and human–machine coupling across various sleep scenarios.

Edge-first design places most inference on the fibre to protect user data and reduce interference, according to DeRucci’s CTO, Chen Wenze. Collaboration covered architecture, algorithms, and validation, with early results highlighting comfort, durability, and responsiveness suitable for bedding.

Partners plan to expand cohorts and scenarios into rehabilitation and non-invasive monitoring, and to release selected algorithms and test protocols. Paradiso framed material-level intelligence as a path to gentler interfaces that blend into everyday environments.

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UK mobile networks and the Government launch a fierce crackdown on scam calls

Britain’s largest mobile networks have joined the Government to tackle scam calls and texts. Through the second Telecommunications Fraud Charter, they aim to make the UK harder for fraudsters to target.

To achieve this, networks will upgrade systems within a year to prevent foreign call centres from spoofing UK numbers. Additionally, advanced call tracing and AI technology will detect and block suspicious calls and texts before they reach users.

Moreover, clear commitments are in place to support fraud victims, reducing the time it takes for help from networks to two weeks. Consequently, victims will receive prompt, specialist assistance to recover quickly and confidently.

Furthermore, improved data sharing with law enforcement will enable them to track down scammers and dismantle their operations. By collaborating across sectors, organised criminal networks can be disrupted and prevented from targeting the public.

Since fraud is the UK’s most reported crime, it causes financial losses and emotional distress. Additionally, scam calls erode public trust in essential services and cost the telecom industry millions of dollars annually.

Therefore, the Telecoms Charter sets measurable goals, ongoing monitoring, and best practice guidance for networks. Through AI tools, staff training, and public messaging, networks aim to stay ahead of evolving scam tactics.

Finally, international collaboration, such as UK-US actions against Southeast Asian fraud centres, complements these efforts.

Overall, this initiative forms part of a wider Fraud Strategy and Government plan to safeguard citizens.

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AI brain atlas reveals unprecedented detail in MRI scans

Researchers at University College London have developed NextBrain, an AI-assisted brain atlas that visualises the human brain in unprecedented detail. The tool links microscopic tissue imaging with MRI, enabling rapid and precise analysis of living brain scans.

NextBrain maps 333 brain regions using high-resolution post-mortem tissue data, which is combined into a digital 3D model with the aid of AI. The atlas was created over the course of six years by dissecting, photographing, and digitally reconstructing five human brains.

AI played a crucial role in aligning microscope images with MRI scans, ensuring accuracy while significantly reducing the time required for manual labelling. The atlas detects subtle changes in brain sub-regions, such as the hippocampus, crucial for studying diseases like Alzheimer’s.

Testing on thousands of MRI scans demonstrated that NextBrain reliably identifies brain regions across different scanners and imaging conditions, enabling detailed analysis of ageing patterns and early signs of neurodegeneration.

All data, tools, and annotations are openly available through the FreeSurfer neuroimaging platform. The public release of NextBrain aims to accelerate research, support diagnosis, and improve treatment for neurological conditions worldwide.

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Tinder tests AI feature that analyses photos for better matches

Tinder is introducing an AI feature called Chemistry, designed to better understand users through interactive questions and optional access to their Camera Roll. The system analyses personal photos and responses to infer hobbies and preferences, offering more compatible match suggestions.

The feature is being tested in New Zealand and Australia ahead of a broader rollout as part of Tinder’s 2026 product revamp. Match Group CEO Spencer Rascoff said Chemistry will become a central pillar in the app’s evolving AI-driven experience.

Privacy concerns have surfaced as the feature requests permission to scan private photos, similar to Meta’s recent approach to AI-based photo analysis. Critics argue that such expanded access offers limited benefits to users compared to potential privacy risks.

Match Group expects a short-term financial impact, projecting a $14 million revenue decline due to Tinder’s testing phase. The company continues to face user losses despite integrating AI tools for safer messaging, better profile curation and more interactive dating experiences.

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Microsoft Elevate expands AI skills training across the UAE

Microsoft has expanded its Microsoft Elevate initiative in the UAE, aiming to equip one million people with AI skills by the end of the decade. The programme is training over 250,000 students and staff, plus 55,000 government employees, to prepare the UAE workforce for an AI-driven future.

Partnerships with educational institutions and nonprofits are central to the initiative. Collaborations with organisations such as GEMS and INJAZ UAE are embedding AI skills into schools, training 10,000 teachers and over 150,000 students.

Higher education institutions, including MBZUAI, UAE University, and the Higher Colleges of Technology, are also participating to advance AI literacy, research, and digital skills across the academic community.

Government employees are a key focus, with 55,000 federal staff set to receive AI training through specialised courses developed with G42 and delivered via the JAHIZ platform. Leadership programmes with INSEAD train senior officials and executives, enhancing strategic skills and promoting responsible AI use.

Microsoft Elevate is closing the UAE’s AI skills gap and expanding opportunities for students, educators, and public servants. The programme combines technical and leadership training to strengthen the UAE’s talent pipeline and global AI leadership.

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