Subquadratic's founders have a new answer to the AI efficiency problem: show the benchmarks

After a skeptical May launch, Justin Dangel and Alex Whedon are using Appen tests and a technical report to defend SubQ's sparse-attention claim.

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Primary source: MIT Technology Review

Why it matters

Subquadratic is attacking the cost curve behind long-context AI, but its real test is whether independent users can reproduce the gains outside company-controlled benchmarks.

An abstract representation of an AI model's architecture, specifically highlighting sparse attention mechanisms and their efficiency evaluation through benchmark data. (exploded-view technical diagram)

Justin Dangel and Alex Whedon are trying to move Subquadratic's biggest claim out of the realm of launch-day belief and into measured evidence.…

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