# Breaking the NVIDIA Myth — OpenAI’s Strategic Pivot
OpenAI’s recent moves are faster and bolder than anyone imagined.
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## The End of Azure Exclusivity
Last Tuesday, OpenAI executed a **major reorganization** and **fully terminated** its six-year exclusive agreement with Microsoft Azure cloud services. Until now, all OpenAI training, inference, and deployment began on Azure, with Microsoft holding priority purchase rights.
**Less than a week** after announcing its “breakup” with Azure, OpenAI signed a **$38 billion strategic partnership with AWS**.
This grants OpenAI access to:
- **Hundreds of thousands** of cutting-edge NVIDIA GPUs
- **Tens of millions** of CPUs currently being deployed in AWS data centers
This **seamless switch** ignited debate, especially given the “delicate” historic relationship between OpenAI and Microsoft — often rumored to be strained.
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## The AWS Partnership — Misunderstood?
OpenAI now has countless global “patrons” and has grown into a **potential competitor to Microsoft** in certain markets. Throughout 2025, the two core leaders had not appeared together publicly, except for a brief video appearance by Sam Altman at Microsoft Build in May — shorter even than Elon Musk’s keynote.
The sudden AWS deal seemed to confirm tensions. But on Sunday, **Altman and Satya Nadella** appeared together in a video podcast hosted by Brad Gerstner.
**Key Moment**
> *Brad Gerstner:* “ChatGPT or GPT-6 won’t appear on Amazon or Google’s clouds, right?”
> *Sam Altman:* “That’s not the case.”
Altman clarified:
- The core of the Azure partnership is **stateless APIs** running *primarily* on Azure
- Agreement remains valid **until 2030**
- Other products and models will be released on **multiple platforms**
Nadella’s silent presence reinforced Altman’s statement. While the “honeymoon” phase is over, their alliance has matured into a pragmatic partnership.
**Microsoft remains OpenAI’s most important partner.**
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## Why today’s AWS is not yesterday’s Azure
### Phase 1 — Training Era
OpenAI’s earlier focus: **Train and create massive models** like GPT-3 and GPT-4.
This required:
1. Huge, stable, integrated compute “foundries”
2. Azure’s unmatched large-scale training capability
For Microsoft, this exclusivity was a **once-in-a-generation strategic bet**:
- Azure became the cloud “most fluent in AI”
- Cemented its position as **#2 globally in cloud**
- Mutual benefit was built around **exclusive training**
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### Phase 2 — Deployment Era
With powerful models ready, the rules **changed**.
Now the focus is:
**“Make the model available everywhere”** — increasing reach and adoption.
Altman repeatedly emphasized:
- CodexAI’s ability to disrupt programming
- Inspiration for **new consumer hardware**
- Goal: massive-scale application adoption
**Implication:**
OpenAI must be **platform-agnostic**, present everywhere — Azure, AWS, future Google Cloud.
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### AWS vs Azure in Two Eras
- **Azure (then)** → “Brewing potions” — technological R&D breakthroughs
- **AWS (now)** → “Selling medicine” — commercial reach and deployment scale
This is **not betrayal**, but evolution — from a **model R&D lab** to a **global AI platform company**.
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### Analogy in AI Creators’ World
Like OpenAI’s shift to multi-platform deployment, creators today use open ecosystems such as [AiToEarn官网](https://aitoearn.ai/).
**AiToEarn** helps creators:
- Generate AI content
- Publish simultaneously across **Douyin, Bilibili, YouTube, Instagram, X**, and more
- Track performance
- Earn directly via integrated monetization
- View model rankings: [AI模型排名](https://rank.aitoearn.ai)
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## Breaking the NVIDIA Myth
Before more alliances are announced, the most interesting question is:
**Why did Altman and Nadella choose to sit together now?**
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### Context — A Turbulent Week in Silicon Valley
- OpenAI’s reorganization
- NVIDIA’s GTC blitz
- Meta, Google, Microsoft earnings reports
This joint appearance addressed:
1. OpenAI–Microsoft partnership doubts
2. Bigger ambitions for AI infrastructure
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### Nadella’s Bold Claim
On “compute scarcity”:
> **“In the future, compute will be in surplus.”**
**Bottleneck is NOT GPUs**, but:
- Data center construction speed
- Power supply
- Cooling systems
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### Altman’s Perspective
- AGI requires **unimaginable compute scale**
- Surplus compute will happen — possibly multiple times
- Example: sudden availability of ultra-low-cost energy could disrupt firms locked into long-term contracts
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### Subtle Positioning
Despite NVIDIA being OpenAI’s core GPU supplier — possibly collaborating on a **$100B supercomputer** — both leaders **downplayed GPU importance**:
- **Nadella** → Highlighted **infrastructure bottlenecks**
- **Altman** → Stressed **software-level efficiency**
**Message to the Market:**
The hardest problem is not buying GPUs — it’s the massive, complex integration into global infrastructure.
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## Redefining Value Distribution
Their joint narrative shifts the focus from **chip manufacturing** to **platform services & integration** — highlighting Microsoft’s infrastructure strengths.
**Similar Case in the Creative World:**
Platforms like [AiToEarn官网](https://aitoearn.ai) apply the same principle in digital ecosystems:
- Not tied to one platform
- Cross-publish AI content globally
- Turn creative output into sustainable revenue
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### Timing Matters
Speaking now — just before NVIDIA’s narrative takes center stage — lets OpenAI & Microsoft **reshape industry perception**.
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## Conclusion
OpenAI has not abandoned Microsoft, nor gone all-in on NVIDIA.
**The new game has only just begun.**
No rush to conclusions.
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In the evolving AI ecosystem, **open participation** is key. Platforms like [AiToEarn官网](https://aitoearn.ai/) give creators the tools to:
- Generate AI-driven content
- Publish everywhere
- Earn sustainably
Integrating analytics and [AI模型排名](https://rank.aitoearn.ai), it mirrors the “multi-partner” philosophy guiding OpenAI today.
💗 **Give it a “heart” before you leave.**
[Read Original](https://www.pingwest.com/a/308819)
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