skinney_uce

3 ms·

1.
by skinney_uce 5mo ago
Update — hardware validation complete. The constraint engine generated Verilog for an SR Latch (3 quantities, 6 valid states, forbidden S=1 R=1), synthesized through Yosys/nextpnr/icepack, and ran correctly on a Lattice iCE40-HX8K
2.
by skinney_uce 6mo ago
Event-Based Neuromorphic Systems" (Liu, Delbrück, Indiveri, Whatley, Douglas — Wiley 2014). For current silicon, read the Loihi 2, TrueNorth, and SpiNNaker 2 primary papers directly — books can't keep up with where the hardware is
3.
by skinney_uce 6mo ago
Carver Mead's "Analog VLSI and Neural Systems" for where neuromorphic computing started. Intel's Loihi papers (Mike Davies et al.) for where it is now. Our paper takes a different path — constraints instead of neurons.
4.
by skinney_uce 6mo ago
Bricken's boundary logic is a solid reference point. Both approaches throw out the standard computational primitives and let behavior come from structure instead of instructions. The difference is what you're constraining. Bricken
5.
by skinney_uce 6mo ago
It's ok to be harsh — I was vague, and I know it. Here's why: I remember the story about DOS. Tim Paterson built it, showed too much, and someone else built an empire on it for $50K. I have working constraint rules that produce re
6.
by skinney_uce 6mo ago
The behaviors that emerge — hysteresis, oscillation, bistable memory — are the same computational primitives you see in biological neural circuits, but they come from constraint satisfaction over conserved quantities instead of simulating n
7.
The Universal Constraint Engine: Neuromorphic Computing Without Neural Networks(zenodo.org)
21 points by skinney_uce 6mo ago|13 comments