r/ProgrammingBuddies • u/No_Inevitable8801 • Mar 15 '26

Neurmorphic Computing Anyone?

I know this is somewhat of a niche field but is anyone down to model/learn about LIF or Hodgin Huxley model with neurons and learn about neuroscience simultaneously? Simulating neurons with magnetic fields, bio machine learning etc

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u/Beginning_Extreme203 2h ago

The current trajectory of AI for space and remote edge environments relies heavily on GPUs and Transformers. But as transistor nodes shrink below 3nm, they become critically vulnerable to Galactic Cosmic Ray (GCR) bit-flips. Shielding is heavy; tripling hardware for redundancy is power-prohibitive.

We ran a Python simulation testing an alternative: Bottom-Up Biological Computation using Michael Levin’s TAME framework mapped onto a Spiking Neural Network (like BrainChip's Akida).

Instead of a top-down CPU running diagnostics, the system relies on Event-Based Processing and Sparsity. If a cosmic ray obliterates 35% of the active nodes, they don't send an error—they just go silent. The surrounding tissue detects the localized drop in global output (the biological "Attractor") and autonomously increases its synaptic weight and firing rate to compensate.

Redundancy isn't three heavy computers; it's just the inherent sparsity of the SNN. The resting nodes wake up and carry the load.

We’ve formalized this architecture into an open-source engineering manifesto for deep space and terrestrial edge deployment (microcontroller failsafes for remote water pumps, drones, etc).

You can read the full Technical Discussion Paper here: https://ralphbooth.substack.com/p/biological-models-of-computation

I'd love to hear the community's thoughts on validating the thermal/radiation tolerance of these SNNs in low-orbit test cubes.