Detects whether a piece of text is AI-generated or human-written using a perplexity-based metric, served through a lightweight web app.
The problem
Most AI-text detectors are opaque classifiers that give you a confidence score and no reason to believe it. If a tool is going to make an accusation about someone’s writing, the mechanism should be inspectable.
How it works
- Uses perplexity — how surprised a language model is by the text — as the discriminating signal, rather than a black-box classifier head.
- Machine-generated text tends to sit in low-perplexity regions because it was sampled from the very distribution being measured; human writing is lumpier.
- Served through a lightweight web app so the metric is something you can try on a paragraph rather than read about.
Why it exists
A small, honest tool: the method is simple enough to explain in a sentence, which is exactly what a claim like this should be.
More work
Hiring for AI or ML?
I am open to AI/ML Engineering, Data Science, and Python roles, plus research collaborations and consulting. New York based, shipping worldwide.