Very Important Entire Ai
Sarah Guo is right that the capex-free cloud model minted a generation of software startups, and inference looks set to replay that story. The economic history she leans on is the strongest part of her case — vertical integration only pencils out at hyperscale, and treating it as a universal playbook is how smaller companies burn capital.… more
What makes the take timely is the supply squeeze: with frontier labs prioritizing their own training and first-party products, independent inference capacity is becoming genuine infrastructure rather than a commodity. Our caveat: leaning on a handful of inference vendors swaps one dependency for another, and inference margins are thin enough that the 'abundance' she wants isn't guaranteed by market structure alone. Still, for founders the takeaway holds — rent your compute, spend your capital on product.
It is very important for the entire ai startup ecosystem for key inference vendors to be 1) capable of getting capacity that they can freely allocate, 2) secure, 3) reliable, 4) always driving cost and perf
let’s not forget how much of an enabler cpu-era cloud was for innovation! no capex! outsource much of your infra ops (and more every year)!
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Source:
X — Sarah Guo
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