David Friedberg: Michael Burry’s Datacenter Math is Wrong
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Episode Description
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Brief Summary
Michael Bur's claims about hyperscalers inflating earnings through extended depreciation schedules are examined, focusing on AI's impact on data centers.
Key points
- Hyperscalers' Financial Practices. Michael Bur claims hyperscalers are inflating earnings by manipulating depreciation schedules.
- Data Centers Transition to AI. Data centers evolved from storage to processing centers due to the AI boom.
Episode highlights
- Hyperscalers' Financial PracticesMichael Bur claims hyperscalers are inflating earnings by manipulating depreciation schedules.“They're cooking the books.”0:17Nov 19, 2025
- Data Centers Transition to AIData centers evolved from storage to processing centers due to the AI boom.“What happened in the data centers?”0:40Nov 19, 2025
Transcript
And I actually think Michael Bur's got this wrong. And so what Michael Bur is saying is that all of these hyperscalers have extended their depreciation schedule or the useful life of their data centers by roughly 2x which cuts the operating costs in half when they report it in earnings and so it's making their earnings inflate. So he's claiming they're cooking the books. Google first made this change in Q1 of 21 where they said the servers are now going from 3 to four years. The chart shows the combination of servers and networking equipment separately. In 2021, Google took networking equipment from 3 to 5 years and then in 2023 they took it from 5 to six years. And so this is a result
of this effort where they went in and did an analysis. So what happened? What happened in the data centers is that the data centers transitioned from being primarily data storage and data transfer systems where you would use hard drives and RAM and memory to store data and then transmit it back out to being data processing centers because of the AI boom. So as AI became more important in the data center, more of the dollars that are going into data centers were allocated towards chips from data storage which initially was hard drives. And then suddenly when you put these processors in to process the data to do AI, that's the majority of the spend and
the majority of the energy is going towards the processors. I made some calls and I checked around with some other friends and everyone says the same thing that these seven and 8year-old TPUs and GPUs that are sitting in the data centers are still being used and they're being used at 100% utilization. So that actually justifies and validates the depreciation schedule being much longer versus shorter.





