Telefónica Tech has partnered with three European firms to bring AI and quantum computing closer together. The collaboration aims to improve how advanced models are developed and deployed across different environments.
The initiative brings together Qilimanjaro Quantum Tech, Multiverse Computing and Qcentroid. Their combined expertise is expected to support more efficient, compact and locally deployable AI systems.
Quantum computing is seen as a way to reduce the heavy processing demands of large AI models. Faster computation could yield more accurate results while reducing the time required to solve complex problems.
Each partner contributes specialised capabilities, from quantum hardware and algorithms to software platforms and orchestration tools. These technologies could support applications such as simulations, edge AI and rapid prototyping.
Telefónica Tech is also strengthening its role in integrating AI and quantum solutions for enterprise clients. The move reflects a broader push to build scalable, sovereign and next-generation digital infrastructure in Europe.
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A large-scale fraud scheme using AI-generated music has exposed vulnerabilities in streaming platforms and royalty systems. Billions of fake streams were used to divert payments away from legitimate artists and rights holders.
The scheme ran from 2017 to 2024 and involved uploading hundreds of thousands of AI-generated tracks. Automated programs were then used to stream the songs at scale, inflating play counts and generating revenue.
The operation relied on thousands of bot accounts, bulk email registrations and cloud-based systems. Streaming activity was spread across many tracks to reduce detection and maintain consistent earnings over time.
Michael Smith, a 54-year-old from North Carolina, has pleaded guilty to conspiracy to commit wire fraud in federal court. Prosecutors say he obtained more than $10 million and agreed to forfeit over $8 million in proceeds.
Authorities say the case highlights how AI and automation can be used to manipulate digital platforms. The court will determine the final sentence as concerns grow over similar schemes.
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Inspired Education has unveiled a new AI-enabled primary teaching model designed to modernise traditional learning systems. The programme aims to better align education with how children learn in a digital and fast-changing environment.
The model combines core academic subjects in the morning with applied learning in the afternoon. Students focus on life skills such as problem-solving, entrepreneurship and communication alongside standard curriculum content.
Learning is structured around mastery rather than age, allowing children to progress at their own pace. AI-powered tools are used to personalise lessons and support faster and more adaptive learning outcomes.
Developers say the approach responds to growing demand from parents for AI-integrated education. The initiative reflects broader efforts to prepare students with digital, practical and future-ready skills.
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Mastercard has introduced a generative AI foundation model trained on billions of anonymised transactions. The model is designed as a backend system to power insights across payments and commerce services.
The company plans to extend AI use beyond fraud detection into cybersecurity, loyalty programmes and small-business tools. The model is being developed with support from Nvidia and Databricks technologies.
Earlier AI tools focused on fraud detection, significantly improving accuracy and reducing false positives. The new model marks a shift towards a broader infrastructure approach across multiple products.
This move aligns with Mastercard’s growing reliance on value-added services, which generated over $13 billion in revenue. These services include security, analytics and digital payment solutions beyond the core network.
Competitors such as Visa and PayPal are also expanding AI-driven commerce platforms. The race is intensifying as firms build integrated systems for payments, automation and intelligent services.
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Parents often believe they understand how their children use AI tools in daily life, but recent studies suggest a clear and growing disconnect. Teenagers are using AI more frequently and in more complex ways than most adults realise.
Research indicates that 64% of teens use AI, while only 51% of parents think their children do. A large share of families have never discussed AI, leaving teenagers to navigate its role without guidance.
Teenagers commonly use AI for schoolwork, research and entertainment as part of their routine activities. However, a notable number also rely on it for advice, conversation and even emotional support in personal situations.
Experts warn that this awareness gap can increase risks linked to misuse and emotional dependence on AI tools. Limited parental understanding means many overlook how strongly AI is influencing behaviour and decision-making.
Despite these concerns, many teenagers feel confident using AI and see it as a helpful tool. Specialists emphasise that open conversations are essential to ensure more responsible and balanced use at home.
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Global efforts to regulate AI are accelerating, but innovation continues to outpace formal rules. Policymakers and industry leaders are increasingly turning to standards to help bridge compliance gaps.
At the AI Standards Hub Global Summit, experts highlighted how technical standards support responsible AI development. These tools are seen as essential for scaling AI safely while regulatory frameworks continue to evolve.
Differences across regions remain significant, with the EU relying on formal regulation and the US leaning on flexible standards. This fragmented landscape is raising concerns over compliance costs and barriers to cross-border deployment.
Experts stress that standards must evolve alongside AI while aligning with global frameworks and enforcement efforts. Without coordination, inconsistencies could limit innovation and weaken trust in AI systems.
Calls are growing for shared definitions, measurable benchmarks and stronger international cooperation. Stakeholders argue that aligning standards with regulation will be critical for future AI governance.
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UAE operator e& (formerly Etisalat) has partnered with Khalifa University to outline a new vision for AI-native 6G networks. Their joint whitepaper presents a framework in which intelligence is embedded at the core of the network architecture rather than added as a feature.
The proposal introduces a dedicated AI plane alongside existing network layers to enable continuous learning and automation. This approach supports sensing, reasoning and autonomous decision-making across radio, core and edge systems.
The framework includes distributed AI agents, digital twin integration and closed-loop automation models. It is designed to support multi-vendor environments while enabling scalable and coordinated intelligence across networks.
Five core pillars underpin the model, including AI frameworks, cloud-edge computing and sustainability-focused design. Together, these elements position 6G as a cognitive infrastructure capable of predictive optimisation and advanced service delivery.
The whitepaper also defines measurable performance indicators such as latency, learning accuracy and energy efficiency. The initiative aims to contribute to global standards while strengthening the UAE’s role in shaping future telecom systems.
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Armenia’s recent technology announcements are helping to form a clearer national AI strategy with stronger coordination. A memorandum with the US on semiconductors and AI now appears to be moving beyond symbolic commitment into action.
Momentum has accelerated with plans to expand a large-scale AI factory backed by significant investment. The project is estimated at around $4 billion and includes tens of thousands of advanced GPUs to support large-scale development.
The initiative is already entering construction, marking a shift from concept to execution in a short timeframe. Officials have described a broader vision of building a network of AI factories across the country.
Energy planning is becoming central, with discussions around deploying a small modular nuclear reactor to meet demand. Stable and scalable power is considered essential for sustaining long-term AI infrastructure growth.
Efforts are also targeting the wider ecosystem through a Virtual AI Institute and planned GPU access for startups. These steps aim to strengthen research capacity and ensure local participation in the country’s AI expansion.
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Britain is opening access to its national AI Research Resource to support domestic AI development. Startups and spinouts can now use supercomputers previously reserved for frontier research.
The AIRR combines infrastructure from government, universities and leading technology firms. It provides the computing power needed to train models and run complex simulations.
Access will be worth around £20 million per year for participating companies. Officials say reducing compute barriers will help startups move faster from prototype to product.
The government’s Sovereign AI Unit, backed by up to £500 million, will also support long-term growth. The programme targets areas including advanced models, scientific discovery and trustworthy AI systems.
Concerns remain over regulatory alignment with the EU’s stricter AI rules. Tensions could shape whether the UK maintains a more flexible environment for innovation.
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A new 110MW data centre microgrid has been launched in Dublin to support rising AI-driven energy demand. The system is designed to provide reliable power during early development stages before full grid connection.
The project combines energy generation, battery storage and heat recovery to improve efficiency and resilience. Developers say the system can help address power constraints affecting large-scale cloud and AI facilities.
Industry leaders in Dublin say the microgrid offers a model for integrating renewable energy with traditional infrastructure. The approach could be replicated in other European markets facing similar grid limitations.
Experts say the system also enables future innovations such as hydrogen integration and district heating. The project reflects a broader shift towards treating energy as a strategic asset in the expansion of AI infrastructure.
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