Next-Gen AI Infra: Beyond GPUs for Energy Efficiency
prateekj · x · 2026-08-15
The article analyzes the energy extravagance of current AI inference architectures, which involve storing large networks in memory, moving parameters, and performing billions of multiply-accumulate operations. To optimize the next generation of AI infrastructure, the key questions are: What is the least amount of energy required to produce a useful token? And what is the least amount of model state that must be activated? Solutions may include smaller models, conditional computation, lower precision, compute-in-memory, analog circuits, photonics, spiking neural networks, or software optimizations, moving beyond the reliance on just better GPUs.
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