Training and serving frontier models is now a networking problem as much as a compute problem. Collective operations like all-reduce and all-to-all synchronize thousands of accelerators during training, and the slowest…
Compute supply, energy and data-center capacity decide how cheaply AI can run. Infrastructure shifts show up in inference costs weeks later.
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