Engram Hypotheses https://engram-hypotheses.vercel.app/ Candidate, AI-surfaced hypotheses: grounded, sourced, cross-model verified. en-us The accuracy lost converting a network to spikes may be a clock problem, not a hard limit https://engram-hypotheses.vercel.app/h/ann-snn-conversion-temporal-alignment/ https://engram-hypotheses.vercel.app/h/ann-snn-conversion-temporal-alignment/ neuromorphic computing Thu, 04 Jun 2026 00:00:00 GMT The latency and accuracy gap introduced when an artificial neural network is converted to a spiking neural network may track a single quantity, how well spike-train firing rates are temporally aligned across layers, rather than being an irreducible cost of spiking, suggesting the gap is a synchronization artifact, not a fundamental limit.