Neuromorphic Chips Challenge GPU Dominance, But Production Reality Lags

Recent breakthroughs in Spiking Neural Networks demonstrate compelling energy efficiency gains—SPARQ achieves 330x power reduction—reigniting debate over GPU alternatives for AI inference. However, these achievements remain confined to legacy models like AlexNet and inaccessible research chips, raising questions about real-world commercial viability. The neuromorphic movement reflects a fundamental shift toward biological computing principles, but the gap between research claims and deployable solutions remains substantial.