Are You in the Weights?

Name: Are You in the Weights?
Availability: InStock
Author: turtlesoup

by turtlesoup·Jun 18, 2026·99 points·73 comments

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AI Analysis

●●SolidRabbit HoleCrowd Pleaser

Parallel LLM queries across 15 models to check if you're in the training data.

Strengths

•Parallel querying and clustering across 15+ frontier models is non-trivial engineering
•Timely cultural question about AI training data presence resonates now
•Leaderboard gamification encourages exploration beyond your own name

Weaknesses

•Fundamentally a novelty tool with limited repeat usage after first try
•No clear utility beyond one-time curiosity about model recognition

Post Description

With more traffic moving off-web and into LLMs, I got curious about what traces we leave "in the weights". My design partner and I built a site in the past few weeks that checks recognition across frontier and small models. It queries many of them in parallel, clusters the responses, and tells you how strongly they recognize you. Happy to answer any questions here!