Useful life and depreciation of accelerators

Plain English. Accounting spreads a chip's cost over an assumed useful life — typically four to six years for AI accelerators. The assumption is an estimate, and it directly sets reported earnings: shorter life, bigger annual depreciation charge, lower profit; longer life, the reverse.

Why it moves money. Whether the sector's earnings are real partly reduces to this estimate. Michael Burry's bear case is that useful lives are overstated and earnings inflated. The counter-evidence is now contractual rather than rhetorical: CoreWeave has signed an A100 contract running to 2029 — silicon whose architecture launched in 2020 — and reports prior-generation SKUs still renting well. Ornn Data's paper adds a mechanism: open-weight models create demand that extends the earning life of older GPUs, against the assumption that each Nvidia generation obsoletes the last.

What to watch. Rental pricing for prior-generation accelerators (the market's live estimate of remaining economic life); changes to depreciation schedules disclosed in filings; and resale or collateral marks in GPU-backed financings.

From the signals. CoreWeave has contracted A100-class silicon out to 2029. Older GPUs still renting well as losses widen — the Burry fight, joined. Ornn: open-weight demand extends the earning life of older GPUs.