See.Think.Act.
I'm Paul. I build machines that see and agents that act. This notebook takes models apart in writing — every article ships with instruments you can operate right in the browser, all written from scratch in TypeScript.
Featured
№ 0017 minInteractive
A CNN from scratch: watching a convolutional network see, in your browser
A handwritten-digit classifier written in plain TypeScript with no machine-learning library, then opened up so you can look at the output of every layer.
Notebook index
Newest first.
- № 0069 min
A robot dog in the browser: its walking policy is four matrix multiplications
MuJoCo compiled to WebAssembly plus the walking policy Deep Robotics published make a Lite3 walk in your browser. Then you try to knock it over: blindfold its senses, shove it, detune its motors.
Interactive#ai-agent#robotics#reinforcement-learning
- № 00510 min
One body, two heads: training a HydraNet that draws boxes and masks, in the browser
Emoji fruit as training data, and a small network with one shared trunk and two output heads, trained from scratch in your browser. It finds the fruit within ten seconds. Then we measure honestly what multi-task learning bought us and what it cost.
Interactive#computer-vision#multi-task#from-scratch
- № 0048 min
Training a Transformer from scratch in the browser: watching attention grow
No PyTorch and no libraries. A tiny autodiff engine and a Transformer of about fourteen thousand parameters, written in TypeScript. Press a button and it learns to reverse a string of digits within seconds.
Interactive#llm#transformer#from-scratch
- № 0036 min
Building a neuroevolution trading squad: AI strategies that adapt to the market
Let a crowd of random trading bots compete, breed and mutate on Apple's 2024 share price. Train one yourself, then look closely at what it learned and what it didn't.
Interactive#ai-agent#neuroevolution#trading
- № 0025 min
The fantastic journey of neural network evolution: 50 birds teach themselves Flappy Bird
Nobody shows these birds how to fly. Give each one a brain of six weights, add survival of the fittest, and a few dozen generations later they glide through every pipe.
Interactive#ai-agent#neuroevolution#from-scratch
- № 0017 min
A CNN from scratch: watching a convolutional network see, in your browser
A handwritten-digit classifier written in plain TypeScript with no machine-learning library, then opened up so you can look at the output of every layer.
Interactive#computer-vision#cnn#from-scratch
Who writes this
I'm Paul. I like to own the whole path: the perception model on the edge device, the tracks and events it produces, and the agents that decide what to do with them.
- Computer vision
- Multi-task perception networks, teacher / student distillation, ONNX / TensorRT on Jetson.
- Multi-agent systems
- Orchestrator / worker designs, MCP tool contracts, the edge-and-cloud split.
- LLM
- Multimodal document understanding, structured output, VLMs on trigger rather than on every frame.
- Edge
- RTSP, GStreamer, WebRTC; Rust and Kotlin Multiplatform where Python is too slow.