So, spiking neural networks don’t just crunch static matrices like traditional ANNs. They fire discrete electrical pulses over time, mimicking the actual event-driven architecture of biological neurons. From what I understand, this isn’t just a cute mimicry—it’s forcing computer scientists to confront how real brains actually handle information. Researchers working on neuromorphic architectures, like the team behind Intel's Loihi chips, have pointed out that this shift moves us away from snapshot models of cognition and toward a dynamic, temporal process. The implications for neuroscience are genuinely wild. If silicon can finally spike like wetware, we might stop treating intelligence as a fixed calculation and start looking at it as a rhythm.

I keep thinking about Alan Watts when I read about this. He always pushed back against the idea that consciousness is just another isolated object you can measure and pin down. To me, SNNs feel like a technological echo of that. When the model stops treating data as a static state and starts processing it as a sequence of timed events, it stops acting like a calculator and starts behaving more like a nervous system. It’s messy, context-sensitive, and deeply dependent on pacing. That’s not just code. That’s closer to how we actually experience reality. I’ve always found Crowley’s rigid, rule-bound systems exhausting, but Watts gets it. Intelligence isn’t a locked vault. It’s a current.

I’d argue this aligns pretty well with Carl Jung’s work on the unconscious as a living, shifting field rather than a static storage closet. Jung spent his life trying to map the currents beneath our conscious awareness, and SNNs are basically attempting that same mapping in silicon. Tarot has always taught me the same thing, honestly. You don’t get meaning from a single card sitting on a table. The reading lives in the timing, the flow, the space between the pulls. Intelligence—whether biological or artificial—might just be the ability to read those pulses correctly.

I’m definitely not saying we’re building conscious machines tomorrow. But if neuromorphic chips are pushing us toward temporal, event-driven architectures, I think we’re finally starting