About Cmospike

Cmospike (芯脉) is a neuromorphic chip architecture research entity. We study how spiking neural network designs — built on proven CMOS fabrication processes — can close the energy efficiency gap between artificial and biological computation.

Our Name

CMOS — Complementary Metal-Oxide Semiconductor, the dominant chip fabrication technology for over four decades. Spike — the fundamental unit of communication in biological neural networks. Our name reflects our thesis: the next leap in computing efficiency will come from rethinking how mature silicon processes represent and transmit information.

Our Focus

If software intelligence scales indefinitely, what physical substrate can sustain it? Current AI hardware is approaching a power wall — models grow faster than chips become efficient. Cmospike exists to study the alternative: computation modeled on biological neural architecture, manufactured on accessible silicon.

Methodology

We publish architecture analyses, not chips. Our research process:

1. Survey — Map the current landscape of neuromorphic designs (Intel Loihi 2, BrainChip Akida, SynSense Speck, Zhejiang Darwin3) 2. Model — Simulate energy-performance trade-offs across process nodes, neuron models, and learning rules 3. Analyze — Identify which design decisions yield the largest efficiency gains per dollar of fabrication cost 4. Publish — Release findings as research notes accessible to engineers, investors, and policymakers