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Inner Fire visualizes seismic data with AI coding help

Inner Fire is a data visualization project that treats global seismic activity as a dynamic planetary pulse. Built using React 19, React Three Fiber, and MapLibre, it integrates live USGS earthquake data. The project also served as an experiment in using AI as a coding collaborator. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT This project uses AI as a coding assistant, but the core focus is data visualization, not a novel AI application.

RANK_REASON This is a personal project post on Mastodon, not a significant industry development.

Read on Mastodon — sigmoid.social →

COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 · [email protected] ·

    Day 96. Inner Fire 🔥 Inner Fire is my current attempt at treating global seismic activity less like static map data and more like a living planetary pulse unfol

    Day 96. Inner Fire 🔥 Inner Fire is my current attempt at treating global seismic activity less like static map data and more like a living planetary pulse unfolding through time. Built with React 19, React Three Fiber, GLSL, MapLibre, and the live USGS earthquake feed. It also be…