Capacity development Archives | Page 23 of 292

Windows 11 gains enterprise 5G management through Ericsson partnership

Ericsson and Microsoft have integrated advanced 5G into Windows 11 to simplify secure enterprise laptop connectivity. The update embeds AI-driven 5G management, enabling IT teams to automate connections and enforce policy-based controls at scale.

The solution combines Microsoft Intune with Ericsson Enterprise 5G Connect, a cloud-based platform that monitors network quality and optimises performance. Enterprises can switch service providers and automatically apply internal connectivity policies.

IT departments can remotely provision eSIMs, prioritise 5G networks, and enforce secure profiles across laptop fleets. Automation reduces manual configuration and ensures consistent compliance across locations and service providers.

The companies say the integration addresses long-standing barriers to adopting cellular-connected PCs, including complexity and fragmented management. Multi-market pilots have preceded commercial availability in the United States, Sweden, Singapore, and Japan.

Additional launches are planned in 2026 across Spain, Germany, and Finland. Executives from both firms describe the collaboration as a step toward AI-ready enterprise devices with secure, always-on connectivity.

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Google outlines progress in responsible AI development

Google published its latest Responsible AI Progress Report, showing how AI Principles guide research, product development, and business decisions. Rising model capabilities and adoption have moved the focus from experimentation to real-world industry integration.

Governance and risk management form a central theme of the report, with Google describing a multilayered oversight structure spanning the entire AI lifecycle.

Advanced testing methods, including automated adversarial evaluations and expert review, are used to identify and mitigate potential harms as systems become more personalised and multimodal.

Broader access and societal impact remain key priorities. AI tools are increasingly used in science, healthcare, and environmental forecasting, highlighting their growing role in tackling global challenges.

Collaboration with governments, academia, and civil society is presented as essential for maintaining trust and setting industry standards. Sharing research and tools continues to support responsible AI innovation and broaden its benefits.

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Hyperscale data centres planned under Meta and NVIDIA deal

Meta announced a multiyear partnership with NVIDIA to build large-scale AI infrastructure across on-premises and cloud systems. Plans include hyperscale data centres designed for both training and inference workloads, forming a core part of the company’s long-term AI roadmap.

Deployment will include millions of Blackwell and Rubin GPUs, plus expanded use of NVIDIA CPUs and Spectrum-X networking. According to Mark Zuckerberg, the collaboration is intended to support advanced AI systems and broaden access to high-performance computing capabilities worldwide.

Jensen Huang highlighted the scale of Meta’s AI operations and the role of deep hardware-software integration in improving performance.

Efficiency gains remain a central objective, with Meta increasing the rollout of Arm-based NVIDIA Grace CPUs to improve performance per watt in data centres. Future Vera CPU deployment is being considered to expand energy-efficient computing later in the decade.

Privacy-focused AI development forms another pillar of the partnership. NVIDIA Confidential Computing will first power secure AI features on WhatsApp, with plans to expand across more services as Meta scales AI to billions of users.

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New Mastercard Move integration powers Ericsson fintech platform

Ericsson and Mastercard will integrate Mastercard Move into the Ericsson Fintech Platform to expand digital wallets and cross-border transfers. The partnership targets telecom operators, banks, and fintechs seeking to launch new payment services and reach underserved communities.

By combining Ericsson’s cloud-native fintech infrastructure with Mastercard Move’s money transfer network, the companies aim to simplify integration, deployment, and compliance. The integration is designed to reduce operational complexity and accelerate time-to-market for digital payment services.

Mastercard Move supports transfers in over 200 countries and territories and enables transactions in 150 currencies. Ericsson’s fintech platform operates in 22 countries, serving more than 120 million users and processing over 4 billion transactions per month.

The companies said the collaboration is intended to create new revenue streams and strengthen digital ecosystems in both emerging and developed markets. A global rollout will begin in the Middle East and Africa, where demand for mobile money and interoperable payment systems continues to grow.

Executives said the partnership will support faster, more secure cross-border transfers and promote financial inclusion. The integration aims to help telecom providers and financial institutions scale digital payment services and expand access to the digital economy.

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AI to transform India’s $400 billion IT ambition by 2030

India’s IT sector could reach $400 billion by 2030, Prime Minister Narendra Modi said in an interview with ANI, highlighting AI as a key growth driver. Services exports remain central to India’s economic expansion, with AI expected to reshape outsourcing and domain-specific automation.

Modi argued that AI is not replacing the IT industry but transforming it. General-purpose AI tools are becoming widespread, while enterprise-grade adoption remains concentrated in specific sectors where established IT firms continue solving complex business challenges.

Government policy is anchored in the IndiaAI Mission, which aims to expand access to computing infrastructure and strengthen domestic innovation. Modi said GPU targets have already been exceeded, with further investment planned to ensure affordable access for startups and enterprises.

Four Centres of Excellence have been established in healthcare, agriculture, education and sustainable cities, alongside five National Centres of Excellence for Skilling. Authorities aim to equip the workforce with industry-relevant AI expertise to support long-term competitiveness.

Strategic ambition extends beyond service delivery toward building AI products and platforms for domestic and global markets. Policymakers in India position AI as a catalyst for higher productivity, stronger digital infrastructure, and broader economic resilience.

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Mistral AI expands European footprint with acquisition of Koyeb

Mistral AI has strengthened its position in Europe’s AI sector through the acquisition of Koyeb. The deal forms part of its strategy to build end-to-end capacity for deploying advanced AI systems across European infrastructure.

The company has been expanding beyond model development into large-scale computing. It is currently building new data centre facilities, including a primary site in France and a €1.2 billion facility in Sweden, both aimed at supporting high-performance AI workloads.

The acquisition follows a period of rapid growth for Mistral AI, which reached a valuation of €11.7 billion after investment from ASML. French public support has also played a role in accelerating its commercial and research progress.

Mistral AI now positions itself as a potential European technology champion, seeking to combine model development, compute infrastructure and deployment tools into a fully integrated AI ecosystem.

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Rising DRAM prices push memory to the centre of AI strategy

The cost of running AI systems is shifting towards memory rather than compute, as the price of DRAM has risen sharply over the past year. Efficient memory orchestration is now becoming a critical factor in keeping inference costs under control, particularly for large-scale deployments.

Analysts such as Doug O’Laughlin and Val Bercovici of Weka note that prompt caching is turning into a complex field.

Anthropic has expanded its caching guidance for Claude, with detailed tiers that determine how long data remains hot and how much can be saved through careful planning. The structure enables significant efficiency gains, though each additional token can displace previously cached content.

The growing complexity reflects a broader shift in AI architecture. Memory is being treated as a valuable and scarce resource, with optimisation required at multiple layers of the stack.

Startups such as Tensormesh are already working on cache optimisation tools, while hyperscalers are examining how best to balance DRAM and high-bandwidth memory across their data centres.

Better orchestration should reduce the number of tokens required for queries, and models are becoming more efficient at processing those tokens. As costs fall, applications that are currently uneconomical may become commercially viable.

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China boosts AI leadership with major model launches ahead of Lunar New Year

Leading Chinese AI developers have unveiled a series of advanced models ahead of the Lunar New Year, strengthening the country’s position in the global AI sector.

Major firms such as Alibaba, ByteDance, and Zhipu AI introduced new systems designed to support more sophisticated agents, faster workflows and broader multimedia understanding.

Industry observers also expect an imminent release from DeepSeek, whose previous model disrupted global markets last year.

Alibaba’s Qwen 3.5 model provides improved multilingual support across text, images and video while enabling rapid AI agent deployment instead of slower generation pipelines.

ByteDance followed up with updates to its Doubao chatbot and the second version of its image-to-video tool, SeeDance, which has drawn copyright concerns from the Motion Picture Association due to the ease with which users can recreate protected material.

Zhipu AI expanded the landscape further with GLM-5, an open-source model built for long-context reasoning, coding tasks, and multi-step planning. The company highlighted the model’s reliance on Huawei hardware as part of China’s efforts to strengthen domestic semiconductor resilience.

Meanwhile, excitement continues to build for DeepSeek’s fourth-generation system, expected to follow the widespread adoption and market turbulence associated with its V3 model.

Authorities across parts of Europe have restricted the use of DeepSeek models in public institutions because of data security and cybersecurity concerns.

Even so, the rapid pace of development in China suggests intensifying competition in the design of agent-focused systems capable of managing complex digital tasks without constant human oversight.

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New AI innovation hub aims to position Ethiopia as regional leader

Ethiopia has launched a new Artificial Intelligence University Innovation Pod in Addis Ababa, marking a significant step in its ambition to become Africa’s leading AI hub.

The Ethiopian Artificial Intelligence Institute leads the initiative in partnership with Addis Ababa University and the UN Development Programme, under the latter’s Timbuktoo Initiative.

Officials say the centre is designed to strengthen national AI capacity, promote homegrown technological solutions and build a sustainable innovation ecosystem. The AI UniPod will support university students, researchers and start-ups working on advanced digital technologies, with a focus on transforming young people from job seekers into technology creators.

The Ethiopian Artificial Intelligence Institute highlighted recent achievements, including patented tools for breast cancer diagnosis and coffee seed identification, as evidence of the country’s growing technological capability. Leaders described the new facility as a shift from ambition to practical implementation of AI.

Data sovereignty was emphasised as a central pillar of the strategy. Authorities argued that control over digital infrastructure and data resources is essential for national sovereignty, particularly as AI becomes embedded in economic and public systems.

The government views the AI UniPod as a long-term platform for innovation, aimed not only at Ethiopia but also at the wider African continent.

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Parliament halts built-in AI tools on tablets and other devices over data risks

The European Parliament has disabled built-in AI features on tablets issued to lawmakers, citing cybersecurity and data protection risks. An internal email states that writing assistants, summarisation tools, and enhanced virtual assistants were turned off after security assessments.

Officials said some AI functions on tablets rely on cloud processing for tasks that could be handled locally, potentially transmitting data off the device. A review is underway to clarify how much information may be shared with service providers.

Only pre-installed AI tools were affected, while third-party apps remain available. Lawmakers were advised to review AI settings on personal devices, limit app permissions, and avoid exposing work emails or documents to AI systems.

The step reflects wider European concerns about digital sovereignty and reliance on overseas technology providers. US legislation, such as the Cloud Act, allows authorities to access data held by American companies, raising cross-border data protection questions.

Debate over AI security is intensifying as institutions weigh innovation against the risks of remote processing and granular data access. Parliament’s move signals growing caution around handling sensitive information in cloud-based AI environments.

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