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Microsoft Adds Anthropic AI Models to 365 Copilot, Expanding Beyond OpenAI

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Microsoft announced on Wednesday that it is integrating Anthropic’s AI models into its Copilot assistant, marking a strategic move to diversify beyond its close partnership with OpenAI, the maker of ChatGPT.

While OpenAI’s models will continue to power Copilot by default, users will now be able to choose Anthropic’s Claude Sonnet 4 and Claude Opus 4.1 for tasks within Copilot’s “Researcher” tool and when building custom agents in Microsoft Copilot Studio.

Starting this week, users who opt in to test Claude will be able to switch seamlessly between OpenAI and Anthropic models in Researcher, said Charles Lamanna, president of Microsoft’s business and industry Copilot division.

The shift underscores Microsoft’s effort to broaden the foundation of its AI services. Until now, Copilot’s advanced features across apps such as Word and Outlook have relied primarily on OpenAI.

Although Microsoft is OpenAI’s largest investor, the company has also been developing its own models and integrating those from other AI firms. Earlier this year, it announced plans to offer models from Elon Musk’s xAI and Meta Platforms, all hosted within its data centers. Models from China’s DeepSeek have also been added to Microsoft’s Azure cloud platform.

Anthropic’s Claude models, however, are primarily hosted on Amazon Web Services (AWS), a direct competitor to Microsoft Azure, highlighting a rare cross-cloud collaboration.

Nvidia’s $100B OpenAI deal sparks funding, valuation, and competition questions

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Nvidia’s plan to invest up to $100 billion in OpenAI — while also supplying millions of its GPUs to the ChatGPT maker — is unprecedented in the tech sector and raises major uncertainties about finance, competition, and market impact.

Key open questions:

1. Where does the rest of the money come from?

  • Nvidia has pledged $10B per gigawatt for 10 GW of compute, but CEO Jensen Huang estimates $50B is needed per gigawatt (with $35B of that spent on Nvidia hardware).

  • That leaves a massive $40B funding gap per GW. OpenAI has not disclosed how it will raise the remainder.

2. How does this fit OpenAI’s shift to for-profit?

  • OpenAI is transitioning from a nonprofit into a public benefit corporation overseen by its nonprofit parent.

  • Nvidia’s investment may hinge on this structure, but it’s unclear if funding flows to the nonprofit entity or the restructured PBC.

  • Regulatory approval in Delaware and California is still pending.

3. What does it mean for OpenAI’s valuation?

  • Nvidia’s initial $10B tranche is pegged to OpenAI’s current $500B valuation.

  • But there’s no timeline for deploying the full 10 GW or committing the entire $100B. Future investments may depend on OpenAI’s valuation at the time, raising uncertainty about dilution and pricing.

4. How will competition be affected?

  • Nvidia’s chips remain the most coveted resource in AI. By tying up vast capacity with OpenAI, rivals like Anthropic, Google, or even Microsoft could face constraints in access.

  • Competitors like AMD may find it harder to gain traction if Nvidia prioritizes OpenAI, despite Nvidia’s public pledge to “make every customer a top priority.”

5. What does it mean for Oracle?

  • Oracle has signed hundreds of billions in cloud contracts with OpenAI, but analysts question whether OpenAI has the liquidity to pay.

  • Nvidia’s cash infusion could strengthen Oracle’s revenue outlook, reassuring investors and credit agencies like Moody’s, which flagged funding risks.

Big picture:

The deal deepens the interdependence of AI’s leading players — Nvidia for chips, OpenAI for models, Microsoft for software integration, and Oracle for cloud. But it also amplifies antitrust concerns, as U.S. regulators eye whether such alliances foreclose competition in the AI stack.

Global companies pour billions into AI infrastructure with mega-deals

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A wave of multi-billion dollar investments is reshaping the AI landscape as chipmakers, cloud providers, and tech giants race to secure computing power for next-generation artificial intelligence. The surge follows OpenAI’s launch of ChatGPT in 2022, which sparked unprecedented demand for GPUs, cloud infrastructure, and data centers.

Key deals fueling the AI boom:

  • Nvidia & OpenAI – Nvidia to invest up to $100B in OpenAI and supply advanced AI chips, cementing its dominance in the AI ecosystem.

  • Nvidia & Intel – Nvidia invests $5B for a ~4% stake in Intel.

  • Oracle & Meta – In talks on a $20B cloud deal to boost Meta’s AI compute.

  • Oracle & OpenAI – Landmark deal worth $300B over five years for OpenAI to buy Oracle cloud capacity.

  • CoreWeave & Nvidia – $6.3B order ensuring Nvidia-backed startup CoreWeave absorbs unused cloud demand.

  • Nebius Group & Microsoft – $17.4B, five-year GPU deal to bolster Microsoft’s infrastructure.

  • Meta & Google – Six-year, $10B cloud agreement signed in August.

  • Intel & SoftBank – SoftBank injects $2B into Intel, becoming a top-10 shareholder.

  • Tesla & Samsung – $16.5B chip supply deal for Tesla’s next-gen AI6 chip, produced in Texas.

  • Meta & Scale AI – Meta takes 49% stake ($14.3B) in Scale AI, elevating CEO Alexandr Wang’s role in Meta’s AI strategy.

  • Google & Windsurf – $2.4B licensing deal for AI code generation tech.

  • CoreWeave & OpenAI – $11.9B, five-year contract signed before CoreWeave’s IPO.

  • Stargate Datacenter Project – Joint venture by SoftBank, OpenAI, Oracle, backed by U.S. President Donald Trump, with up to $500B in AI infrastructure funding.

  • Amazon & Anthropic – Amazon doubles down with a total $4B investment in Anthropic, developer of the Claude chatbot.

Why it matters:

  • Capital intensity: AI development is now measured in hundreds of billions, with infrastructure demands rivaling traditional energy projects.

  • Strategic alliances: Tech giants are securing long-term chip and cloud capacity to avoid bottlenecks.

  • Geopolitical edge: Governments, particularly the U.S., are encouraging private-public mega-projects like Stargate to keep ahead in the AI race.

The investment frenzy highlights a simple truth: the future of AI hinges not just on algorithms, but on who controls the world’s computing power.