Editing Openai/6960ed20-8dfc-8005-a089-1bb9023ccffa (section)

=== Assistant: Short answer: yes, largely because companies like Google, Amazon, and Microsoft already built massive infrastructure ov… ===
Short answer: yes, largely because companies like Google, Amazon, and Microsoft already built massive infrastructure over decades, while OpenAI is scaling very fast all at once. But there are a few important nuances.

==== That number (when it appears in reports) usually refers to capacity reservations or long-term supply agreements, not OpenAI alone physically buying every wafer off the market. ====

Big players like:
* Google
* Amazon (AWS)
* Microsoft
* Meta

are also buying enormous amounts of memory — just less visibly, and often through:
* captive supply chains
* internal chips
* long-standing contracts

They don’t need headline-grabbing deals because they already locked this in years ago.

==== Google, Amazon, and Microsoft started building hyperscale data centers 15–20 years ago. ====

They already have:
* thousands of data centers worldwide
* pre-negotiated DRAM + HBM supply contracts
* in-house silicon (TPUs, Trainium, Inferentia)
* mature cooling, power, and networking stacks

So when AI demand exploded:
* they expanded existing pipelines
* not panic-scaled from scratch

OpenAI, by contrast:
* went from research lab → global AI platform in ~3 years
* had to scale instantly, not gradually

That forces very aggressive forward buying.

==== Another key reason: architecture choices. ====

===== - Uses TPUs =====
* TPUs are designed with tighter memory–compute integration
* Often need less HBM per unit of compute

===== - Heavy reliance on H100 / H200 / Blackwell GPUs =====
* These demand huge amounts of HBM
* HBM is the real bottleneck, not compute

So OpenAI’s path is HBM-hungry, while Google’s is more memory-efficient.

==== Companies like Google: ====
* diversify suppliers
* spread purchases across regions
* avoid public attention to prevent price spikes

OpenAI:
* needs guaranteed supply
* doesn’t have decades-old leverage
* must signal seriousness to partners and governments

So deals become visible and dramatic.

Think of it like:
* Google = owns oil fields
* OpenAI = buying oil futures aggressively

==== OpenAI is willing to: ====
* over-reserve capacity
* lock into massive long-term contracts
* bet on AI demand continuing to explode

Google/Amazon:
* optimize for utilization
* avoid stranded capacity
* already monetizing AI internally

Different business incentives.

==== You’re basically right, with refinements: ====
* ✅ Yes, Google and others already built infrastructure over decades
* ✅ They are buying wafers — just not suddenly or publicly
* ✅ OpenAI is compressing 20 years of infrastructure growth into ~5 years
* ✅ GPU-based AI requires far more HBM, forcing aggressive wafer deals

That’s why it looks like OpenAI is buying everything — when in reality, it’s the newcomer scaling at maximum speed, not the incumbents standing still.

If you want, I can also explain why HBM is the real choke point, not GPUs themselves.