Foxxe Labs
Log #0024

Léargas — Memory That Breathes

A temporal map of 21,500 documents across three years of an AI-augmented mind. Topic blobs rise and fall with the shape of attention. Sound on for the full experience.

#Léargas #Mnemos #temporal-manifold #memory #Web-Audio #D3
project
engineering
personal
general

What you're looking at

Each blob is a topic cluster dominant in that month's conversation history — extracted from 21,500 documents in Mnemos using a Bayesian Gaussian Mixture Model per period, embedded with all-MiniLM-L6-v2. Blob size encodes weight × log(doc_count). Colour encodes category: green for project/research, amber for engineering, violet for personal, grey for general.

Press ▶ or use ← → arrow keys to step through months. Hit Sound to enable the audio layer — each blob entry fires a pitched tone, and the ambient drone scales with memory density. Empty months whisper rather than silence.


The corpus

MetricValue
Total documents~21,500
Periods2023-02 → 2026-03
Peak densityJun 2025 · 2,952 docs
Empty periods13 of 38 months
Topic modelBayesianGMM · 30 components
Embedding modelall-MiniLM-L6-v2

Sound design

The Web Audio API synthesises distinct sounds per category and event: blob arrivals fire pitched tones (F5 for project, C5 for engineering, E♭5 for personal, G4 for general), staggered so dense periods like June 2025 sound like a chord rather than noise. The ambient drone at 55Hz / 56.2Hz produces a 1.2Hz beating pattern; gain scales logarithmically with doc_count so dense periods have real acoustic weight. Empty periods produce a bandpass-filtered breath — not silence, but hollowness. No audio libraries. No dependencies beyond D3 and the browser.

Full write-up →