The ~$750B question posed as a DESTINATION, not a spender: where does the aggregate AI capex actually land, on what projects? The taxonomy — chips (Nvidia/AMD/TSMC/Broadcom + custom silicon like Jalapeño), datacenters (Stargate, Camellia, Colossus + the 100s of sites), power (gas turbines, nuclear-for-AI, grid), land/cooling/water. Sibling to hyperscaler-capex-big-picture, which cuts the SAME money by spender; this one follows it to where it physically lands. Most destinations have no thread yet — that's the worklist. ADDENDUM 2026-08-15: the capex-committed-vs-capacity-energized gap now has its first two real outcomes on the record, on opposite sides — AWS's Lusby, MD project withdrew rather than clear Texas- style compliance gates (08-04), while Core Scientific, Vantage, and SB Energy formally committed to Abbott's PUCT/ERCOT standards (08-12). Track which outcome the majority of the project queue lands on, not just whether the gap exists.
Summary
This meta-thread reframes AI capex from who's spending to where roughly $750B actually lands, across chips, datacenters, power, and land.
Whether the destination breakdown across chips, datacenters, power, and land shifts as more sites report actual spend is the open question.
