Why We're Stuck With GPUs This Long?

Short summary

Despite technical superiority, GPU alternatives haven't displaced Nvidia due to economic barriers: custom silicon requires billions in NRE and ecosystem matching CUDA's decades of maturation. Hyperscalers face the innovator's dilemma—locked into GPU capital, they're structurally disincentivized from funding disruption. The real threat comes from consumer NPUs running quantized models locally, eroding the subscription-based inference economy.

• •Custom ASIC alternatives are technically viable but require billions in R&D and ecosystem development to match CUDA's decade of entrenchment
• •Hyperscalers have capital to fund disruption but are structurally locked into GPU investments and face capital write-downs if displacement succeeds
• •Consumer NPUs running local quantized models pose a bigger threat to the inference economy than data-center chip alternatives

Generated with AI, which can make mistakes.