Learning path

Eight steps from your first spiking neuron to real hardware, using free tools. Lessons are added as they are written and tested; unfinished ones are not linked.

1. What is neuromorphic computing, and why? coming soon

Brains versus conventional chips, energy use, where this is used today, and honest limits.

2. The spiking neuron (LIF) playground ready

Integrate, leak, fire. Start with the interactive playground; the written lesson is coming.

3. Encoding information as spikes coming soon

Rate coding, temporal coding and event-based data.

4. A small network and the raster plot coming soon

Connect neurons and read what the network is doing.

5. Your first model with snnTorch coming soon

Train a small spiking network on free Google Colab. Requires Python basics.

6. Fixed-point and quantization coming soon

Why hardware uses small integers, and what it costs in accuracy.

7. A neuron in Verilog on an iCE40 FPGA coming soon

Write, simulate and run a hardware neuron with open-source tools.

8. The hardware landscape coming soon

Loihi, SpiNNaker, Akida and others: what exists, what is accessible, what is not.

Free resources to use alongside

Spiyk does not replace these. They are excellent, and we link to them rather than copy them: Neuromatch Academy, snnTorch tutorials and Open Neuromorphic.