DeepSeek V4 tests China’s AI ambitions against US rivals

China’s DeepSeek is reportedly preparing to release its latest AI model, according to a Financial Times report. The planned debut of the company’s V4 large language model is seen as another test of China’s ability to compete with leading US AI firms.

Sources cited by the report said V4 will be a multimodal model capable of generating images, video, and text. DeepSeek has reportedly worked with Huawei and Cambricon to optimise the model for Chinese AI chips.

The release is expected ahead of the annual Two Sessions parliamentary meetings in China, which begin on 4 March. Analysts say the timing could reinforce DeepSeek’s positioning as a national AI champion.

The launch would be the company’s first major model release since its R1 reasoning system debuted in January last year. DeepSeek claimed R1 matched leading US models while using less computing power, a development some compared to a ‘Sputnik moment’ for American technology firms.

Separately, AI researcher Andrew Ng said the industry remains decades away from achieving artificial general intelligence (AGI). He argued that systems capable of matching human intellectual breadth remain distant, despite steady advances in model performance.

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AI data centre boom drives global memory chip shortage

Global demand for AI data centres is creating a severe shortage of memory chips, disrupting supply chains across the consumer electronics industry. Manufacturers warn shortages of RAM could lead to higher prices and delayed shipments for devices including laptops, smartphones and gaming consoles.

Only three companies dominate global RAM production, with capacity increasingly redirected towards high-bandwidth memory used in AI systems. Analysts say rapid investment in AI infrastructure has absorbed available supply faster than manufacturers can expand production facilities.

Major technology firms are already feeling pressure as memory costs rise and inventories tighten. Companies including Apple, HP, Dell and Qualcomm have warned investors that pricing increases and weaker forecasts may follow if shortages persist.

Gaming and computer manufacturers are exploring different responses, ranging from price increases to redesigning products that require less memory. Experts expect supply constraints to continue through the year as chipmakers attempt to balance AI demand with consumer electronics needs.

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Cloud-native networks drive AI connectivity

Mobility is emerging as the digital economy’s backbone, with Cisco outlining its latest strategy at Mobile World Congress. Cloud-native, programmable networks are being framed as platforms that enable new revenue models while reducing operational complexity across industries and cities.

Recent updates focus on the Cisco Mobility Services Platform, plus IoT-as-a-service and a programmable core built to scale global networks.

Partnerships with operators such as AT&T, Tele2 IoT, and Wind Tre Group aim to speed up enterprise connectivity and reduce deployment times for industrial use cases.

Preparation for the AI era remains a core theme. Collaboration with NVIDIA focuses on embedding intelligence into wireless infrastructure while ensuring networks can support distributed AI workloads with low latency and predictable performance.

Ecosystem expansion includes joining the Linux Foundation initiative, while industry rankings signal momentum as operators move toward 5G Advanced and AI-native networks.

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OpenAI and Microsoft strengthen their long-term AI collaboration

Microsoft and OpenAI have reaffirmed their long-standing collaboration after new funding and partnerships raised speculation about their relationship.

Both firms stressed that recent announcements leave their original agreements intact, preserving a framework built on technical integration, trust and shared ambitions for AI development.

Microsoft’s exclusive licence to OpenAI’s intellectual property remains untouched, as does its position as the sole cloud provider for stateless APIs powering OpenAI models.

These APIs can be accessed through either company. Yet all such calls, including those arising from third-party partnerships such as OpenAI’s work with Amazon, continue to run on Azure rather than on alternative clouds. OpenAI’s own products, including Frontier, also stay hosted on Azure.

Revenue-sharing arrangements are unchanged, alongside the contractual definition and evaluation process for artificial general intelligence.

Both companies emphasised that the partnership was designed to allow independent initiatives while preserving deep cooperation across research, engineering and product innovation.

OpenAI retains the freedom to secure additional compute capacity elsewhere, supported by large-scale initiatives such as the Stargate project.

Even with broader collaborations emerging across the industry, both firms present their alliance as central to advancing responsible AI and expanding access to powerful tools worldwide.

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Data sovereignty becomes an infrastructure strategy in the AI era

For most of the past decade, data governance was treated as a legal issue. IT built networks and bought tools, while regulators were someone else’s problem. That division no longer holds. Cloud adoption and AI have turned data sovereignty into a core infrastructure and strategy question.

Regulatory frameworks such as GDPR, NIS2, and DORA are expanding and being enforced more strictly. Governments are also scrutinising foreign cloud providers and cross-border access. Local data storage no longer ensures absolute data sovereignty if critical control layers remain outside national jurisdiction.

Traditional SASE and SSE models were not built for this environment. Many still separate outbound cloud traffic from inbound controls. That split creates blind spots in distributed architectures and complicates consistent policy enforcement.

AI workloads intensify the pressure. Retailers, banks, and manufacturers are deploying models locally, not just in hyperscale clouds. Securing east-west traffic across systems and APIs without undermining data sovereignty is becoming a central architectural challenge.

Managed sovereign infrastructure is one response. It reduces reliance on external cloud paths while preserving operational scale. Ultimately, organisations must align security, AI deployment, and governance with long-term resilience goals.

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European businesses gain AI-powered contract tools with local data hosting

Workday has rolled out its Contract Lifecycle Management (CLM) platform with EU-hosted data in Frankfurt, allowing European organisations to use AI contract tools while keeping all data within the EU.

German, French, and Spanish language support is live, with more languages planned. The update is part of Workday’s EU Sovereign Cloud strategy, targeting the CLM market, which is set to grow to $1.9 billion by 2033.

The platform uses AI agents to automate contracts. The Contract Intelligence Agent extracts terms, obligations, and renewal dates to create a searchable repository, while the Contract Negotiation Agent flags deviations, drafts redlines, and speeds approvals.

Multilingual support ensures smooth workflows across Europe’s largest commercial languages, improving compliance and efficiency.

GDPR compliance remains critical, with fines up to €20 million or 4% of global turnover. EU-hosted CLM removes offshore data risks, which are crucial for the finance, healthcare, and defence sectors. Workday combines AI efficiency with full legal compliance.

Decision-makers should focus on three priorities: EU data residency, leveraging AI agents to accelerate contracts, and integrating CLM with HR and finance systems to maximise value. Workday aims to capture market share in Europe against competitors such as Icertis and DocuSign.

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Agentic AI network slicing launches in 5G Advanced with Nokia and AWS

Nokia and Amazon Web Services have introduced what they describe as the first agentic AI-powered network slicing solution operating in commercial 5G-Advanced networks. Early pilot projects with du and Orange are already underway, marking the transition from laboratory testing to commercial deployment.

For an extended period, network slicing has been presented as a way to tailor connectivity to the needs of enterprises and end users, yet static configurations have until now limited its commercial impact. A more autonomous approach is now being tested, designed to convert operational intent directly into concrete network actions.

The joint system combines Nokia’s network slicing portfolio with AI services delivered via the Amazon Web Services (AWS) Bedrock platform. Software agents analyse real-time data, including traffic levels, location information, and significant events, and automatically adjust radio access network policies. However, this enables capacity to be prioritised in response to congestion, emergencies, or large gatherings.

Enterprise use is central to the deployment. Campuses, factories, and urban areas can receive connectivity aligned with predefined service level targets (SLAs), while public safety teams can activate dedicated network slices during critical incidents. Premium consumer services, such as gaming and streaming, may also benefit from more stable performance during peak demand periods.

The solution spans the radio, transport, and core networks and will be showcased at the Mobile World Congress 2026. Commercial success will depend on whether intent-based slicing can transform what has long been a promised feature into a sustainable and scalable revenue source for operators.

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Google API keys exposed after Gemini privilege expansion

Security researchers warn that exposed Google API keys in public client-side code could be used to authenticate with the Gemini AI assistant and access private data. The issue arose after developers enabled the Generative Language API in existing projects without updating key permissions.

Truffle Security scanned the November 2025 Common Crawl dataset and identified more than 2,800 live Google API keys publicly exposed in website source code. Some belonged to financial institutions, security firms, recruitment companies, and Google infrastructure.

Before Gemini’s launch, Google Cloud API keys were widely treated as non-sensitive identifiers for services such as Maps, YouTube embeds, analytics, and Firebase. After Gemini was introduced, those duplicate Google API keys also acted as authentication credentials for the AI assistant, expanding their privileges.

Researchers demonstrated the risk by using one exposed key to query the Gemini API models endpoint and list available models. They warned that attackers could exploit such access to extract private data or generate substantial API charges on victim accounts.

Google was notified in November 2025 and later classified the issue as a single-service privilege escalation. The company said it has introduced controls to block leaked keys, limit new AI Studio keys to Gemini-only scope, and notify developers of detected exposure.

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Japan probes Microsoft cloud licensing

Japan’s Fair Trade Commission has launched an investigation into Microsoft in Tokyo over suspected antitrust violations. Authorities conducted an on-site inspection of Microsoft’s Japanese subsidiary in Tokyo on Wednesday, according to sources.

Regulators are examining whether Microsoft charged higher licensing fees to customers running Microsoft 365 and Windows on rival cloud platforms rather than on Microsoft Azure. The inquiry centres on concerns that software dominance may have restricted competition in Japan’s cloud market.

Microsoft’s Japanese unit said it would cooperate fully with the Fair Trade Commission in Tokyo. The watchdog is assessing whether pricing practices unfairly hindered rivals such as Amazon and Google, which also compete in Japan’s expanding cloud sector.

Japan’s Fair Trade Commission has intensified oversight of major technology firms in recent years. Previous actions in Japan include investigations into Amazon Japan and a 2025 order requiring Google to end certain preinstallation practices.

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Microsoft backs Australia’s next phase of digital government with new AI and cloud agreement

Australia’s rise to second place in the OECD Digital Government Index signals renewed momentum for national digital transformation.

A shift that comes as Microsoft signs a new five-year Volume Sourcing Arrangement with the Federal Government, designed to underpin modernisation across public services and create a secure, future-ready foundation for responsible AI adoption.

The agreement led by the Digital Transformation Agency gives agencies access to Microsoft Copilot, Azure, Microsoft 365, Dynamics 365 and a strengthened security and compliance framework instead of continuing reliance on ageing systems.

The arrangement sets clearer strategic pathways for innovation, procurement and skills development through an enhanced governance structure.

It recommits both sides to national security requirements, including the Security of Critical Infrastructure legislation, the Cloud Hosting Certification Framework and IRAP.

These measures allow agencies to expand AI use while retaining control of data and meeting the expectations placed on government institutions.

A successful Copilot trial in 2024 already demonstrated personal productivity gains of around one hour per day for participating staff.

Microsoft is also establishing a $1.55 million training fund for the Australian Public Service to support capability building in ethical AI use and modern cloud operations.

The company emphasises that Australia’s partner ecosystem will gain new opportunities because the agreement simplifies how local firms engage with government agencies. Such an approach forms an important part of the wider public sector reform agenda announced last year.

The new deal aligns with national priorities set out in the Whole-of-Government Cloud Computing Policy and the National AI Plan.

Australia now enters a pivotal period in which digital transformation is guided not only by technological capacity but by the frameworks of trust, resilience and public benefit that shape how government services evolve.

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