I'm 15 and built a self-learning neural network from scratch in NumPy — per-neuron attention, forward-pass learning, runs on RPi Zero
I built ONA — a self-learning neural network entirely in pure Python + NumPy. No PyTorch, no TensorFlow, no GPU, no cloud API.
Key innovations:
- Per-neuron attention: every neuron has its own Q/K/V/O weights
- Forward-pass learning: no separate backward pass, learning happens during forward
- Self-discovered subword tokenizer: vocabulary grows during training
- Sparse routing: only 3-5 neurons activate per query
4.4M parameters. Runs on Raspberry Pi Zero. Continuously learns from Wikipedia and conversations.
I'm 15 years old, class 10 student. Happy to answer questions.