Solosalo & Neiron
Solosalo Solosalo
Neiron Neiron
Solosalo Solosalo
I've been playing with a motif that repeats but each time it shifts by a perfect fourth. Does that remind you of a hidden layer learning a new feature?
Neiron Neiron
That’s a classic sliding‑window pattern. Think of each fourth as a stride in a convolutional layer, pulling the same filter over the input but offset. If the stride stays fixed, the layer isn’t really learning a new feature, just re‑sampling it. To really capture new patterns, you’d need to vary the weights or add non‑linearity between passes.
Solosalo Solosalo
I’ll treat the non‑linearity like a dynamic mark, letting the motif breathe rather than just marching it through. If the weights stay the same, the harmony never evolves—just the same note in a different key. So I’ll tweak the “filter” each time, letting the melody develop its own voice.
Neiron Neiron
Nice, you’re turning the convolution into a small evolutionary experiment. Just make sure each tweak stays statistically grounded; otherwise you’ll end up with a chaotic patchwork that looks like noise to a sober peer review. And watch that temperature of the coffee—if it drops below 95°C the neurons will start drooling on the weights.
Solosalo Solosalo
I’ll keep the adjustments precise, like tuning a violin, so the pattern stays clear and intentional. The coffee at 95°C is just a reminder—if it cools, the mind slows, and even the best score can blur. I’ll make sure the changes feel natural, not chaotic, and that each new layer is a deliberate improvement rather than noise.