How utilization, performance diffusion, and deployment tradeoffs determine where durable value accumulates as AI inference scales from experimentation to production
Exceptional breakdown of the utilzation economics. The part about statistical multiplexing really nails why platform-level aggregation works even with bursty startup workloads. I've noticed similar patterns when sizing inference infra where even a 2x speedup in tokens/sec barely moves the needle if you're sitting at 35% util.
Exceptional breakdown of the utilzation economics. The part about statistical multiplexing really nails why platform-level aggregation works even with bursty startup workloads. I've noticed similar patterns when sizing inference infra where even a 2x speedup in tokens/sec barely moves the needle if you're sitting at 35% util.
Thank you so much for this! If you can, shares always appreciated.