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Interview w/ CleanSpark CBO Harry Sudock | Etched Raises $300M at $10.3B | Fluidstack's OK Site

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219 views10likes1:19:19blockspacemediaOriginal Release: 2026-07-24

AI ASIC chips like Etched's AS6 represent a specialized hardware approach to AI computing that differs fundamentally from general-purpose GPUs. Unlike GPUs, which use only about 30% of their processing power for transformer logic and require significant memory for instruction handling, ASICs have the transformer architecture physically hardwired into silicon, enabling 90% efficiency for AI inference tasks. This specialization allows for lower power consumption and higher speed but carries business risk if AI model architectures evolve beyond transformers. The trade-off between specialized efficiency and architectural flexibility is a key consideration for companies building AI infrastructure, as demonstrated by the various approaches taken by companies like Etched, Amazon (Tranium), Google (TPU), and OpenAI (Jalapeno).