Well, our brains are closer to spiking neural networks than 'regular' neural networks. And they work pretty well. For the most part.

I feel like SNNs are like Brazil - they are the future, and shall remain so. I think more basic research is needed for them to mature. AFAIK the current SOTA is to train them with 'surrogate gradients', which shoe-horn them into the current NN training paradigm, and that sort of discards some of their worth. Have biologically-inspired learning rules, like STDP, _really_ been exhausted?

Spiking neural networks are not software, they are usually built directly into silicon chips because they are using pulse timing to encode information instead of multiple bits. The problem is that training them is difficult because they operate over time, not that they don't work. As of now, scaling training infrastructure is more important than theoretical power efficiency.