Building Interactive ML Demos

I've been building interactive demos to explain machine learning concepts. Here's what I've learned about making complex ideas accessible.

Start with the Core Insight

Before writing any code, I ask: "What's the one thing I want someone to understand?" Everything else should support that insight.

Progressive Disclosure

Don't show everything at once. Let users build understanding step by step:

1. Start with a simple example
2. Add complexity gradually
3. Let users experiment at each stage

Make It Tactile

The best learning happens when people can manipulate things directly. Sliders, drag-and-drop, and real-time updates create engagement that static explanations can't match.

Show, Don't Tell

Instead of explaining that attention weights sum to 1, let users see the weights update as they change the input. Visual feedback is more powerful than text.

What's Next

I'm currently working on a [Transformer Visualizer](/apps/transformers) that breaks down each component of the architecture. Stay tuned!