Akamai bets inference needs proximity: agent chains lose 4 seconds to distance alone
FinanceYF5 · x · 2026-11-12
At Akamai's AI Summit, the company argued hyperscale now means proximity — training concentrates near power, inference near users. A 20-step agent chain burned 4 full seconds on distance alone. The five-layer stack over four compute tiers is mostly in production, co-taught with NVIDIA engineers; buyers' first complaint was speed. Semantic caching is early and no pricing appeared. Revenue proof waits on February earnings.
Related event: Akamai Bets on Inference at the Edge, Not Hyperscale Bulk(2 posts)→
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