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Microsoft Corporation

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Nebius (NASDAQ: NBIS) has $40bn in AI contracts. Why borrow $3.5bn for one year?

Nebius Group has secured a US$3.5 billion financing facility to accelerate its artificial intelligence infrastructure expansion, despite having more than US$40 billion in long-term customer commitments. The one-year maturity, floating interest rate and secured borrowing structure raise an important question about how the company plans to finance its next phase of growth.
Infographic-style feature image showing a map of Asia-Pacific with network links across seven markets, highlighting four models of telco AI partnerships and key examples such as sovereign cloud, AI compute platforms and network integration.
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Asia-Pacific telco AI alliances split into four models, but only some move carriers up the value chain

Public agreements across seven Asia-Pacific markets show telco and hyperscaler partnerships clustering into four models: physical network integration, sovereign cloud, AI compute platforms and edge automation. The structure matters because some carriers are capturing little more than infrastructure economics, while others are trying to move into higher-value AI services.
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Kenya helped Microsoft build an African engineering hub. What happens if those development jobs disappear?

Microsoft Corporation has confirmed proposed changes affecting its engineering organisation in Kenya while local reporting says employees were told the Nairobi Africa Development Centre would close. Microsoft continues to operate commercially in Kenya, making the immediate issue the future of local engineering jobs rather than a withdrawal from the country.
Infographic showing Microsoft-Decision-1 as a specialised AI model for fast, low-cost decision-making inside applications and complex agentic AI workflows.
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Can Microsoft Decision-1 improve the economics of agentic AI inside Azure and Foundry?

Microsoft Corporation has launched Microsoft-Decision-1, a specialised model designed to make fast, low-cost choices inside AI applications rather than generate open-ended answers. Its significance lies less in competing with frontier language models and more in changing how enterprises could divide work across increasingly complex agentic AI systems.