ASIC circuit design locks algorithm support at the moment of tapeout. MoE, Mamba, and multi-modal architectures emerged after MACH-1's silicon was finalized — making it structurally incompatible with frontier models.

MACH-1 chose LPDDR (mobile DRAM) over HBM for cost and availability. Modern LLM inference is memory-bandwidth-bound — LPDDR's lower bandwidth became the critical bottleneck as model sizes grew.

The global developer community has built every optimization library, training framework, and inference stack on NVIDIA's CUDA. A new ASIC must replicate years of ecosystem work to be practically usable.

Silicon design-to-mass-production takes 18–24 months minimum. AI model architectures changed radically every 2–4 months during the same period. Hardware simply cannot keep up with this cadence.