A curated map for silicon that thinks like a brain

What it does

The Neuromorphic Computing Guide is a curated markdown reference that catalogs hardware, software, courses, and research for building analog VLSI systems that mimic biological neural architectures. It covers everything from Intel’s Loihi 2 and BrainChip’s Akida to PyTorch workflows, CUDA, and basic circuit physics. A community-maintained mdBook version also exists.

The interesting bit

The guide treats neuromorphic engineering as a full-stack discipline — you get chip specs alongside Ohm’s law and Faraday’s law refreshers. That breadth is either admirably thorough or slightly unhinged, depending on your attention span.

Key highlights

• Links to major research chips: Intel Loihi 2, BrainChip Akida NSoC
• Curated book list with recent academic titles on memristors and neuromorphic photonics
• Training course index spanning Coursera, edX, MIT OCW, and Harvard
• Sections on adjacent domains: bioinformatics, robotics, NLP, computer vision
• Available as both GitHub markdown and a rendered mdBook

Caveats

• The README is a link directory, not original analysis or code
• Maintenance badge says 2024 but last-commit badge isn’t shown in the excerpt; freshness is unclear
• Some topic tags on the repo (neural radiance fields, neural machine translation) appear only loosely related to neuromorphic hardware

Verdict

Worth bookmarking if you’re entering neuromorphic research and need a structured starting point. Skip it if you want hands-on code or deep technical evaluation of specific chips — this is a map, not a vehicle.