Sparse silicon could be the next 10x for AI compute, argues hardware veteran
blelbach · x · 2026-09-17
In a follow-up post, blelbach argues that today's AI hardware is essentially dense linear algebra machinery, with only some support for structured and block sparsity. Given sparsity's promise for AI workloads, radically different chips built around true sparsity may be the path to the next 10x in compute.
Together with his previous post, the thread's thesis: low-precision quantization gains are ending, and architectural innovation — especially sparse specialized compute — is the main way forward.
Related event: Veteran: CMOS Scaling Is Tapped Out, Sparsity Is AI's Next 10x(4 posts)→
More from Infra
- Marvell-Lumentum deal signals what it takes to compete with Broadcom — BenBajarin · 2026-11-02
- Sam Altman: AI query energy cost fell 1,000x-100,000x in 3-4 years — rohanpaul_ai · 2026-11-02
- Marvell and Lumentum to merge, targeting $550B AI connectivity market — BenBajarin · 2026-11-02
- Samsung chairman visits Yokohama advanced packaging lab, pledging ¥40B investment over five years — pstAsiatech · 2026-11-02
- Sam Altman meets Samsung executives in Korea to deepen memory chip and AI infrastructure cooperation — pstAsiatech · 2026-11-02
- Simulating 200,000 months: can your home AI rig pay rent at 2026 GPU prices? — LeviTurk · 2026-11-02