Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata. Open sourced by Apple.
Very cool interactive visualization for large embeddings is hugely valuable for debugging and exploration. Curious about performance on million‑vector scales and support for custom distance metrics.
We’re debuting today as well keen to hear what you think.
I work with large embedding datasets—this visualization saves hours. Can it handle real-time updates or streaming data sources?
Looks like Apple is letting their research publish open source projects! If so — that's great news for the OSS ecosystem.
Embedding Atlas Features:
🏷️ Automatic data clustering & labeling: Interactively visualize and navigate overall data structure.
🫧 Kernel density estimation & density contours: Easily explore and distinguish between dense regions of data and outliers.
🧊 Order-independent transparency: Ensure clear, accurate rendering of overlapping points.
🔍 Real-time search & nearest neighbors: Find similar data to a given query or existing data point.
🚀 WebGPU implementation (with WebGL 2 fallback): Fast, smooth performance (up to few million points) with modern rendering stack.
📊 Multi-coordinated views for metadata exploration: Interactively link and filter data across metadata columns.
Check out the demo — impressive this is all done in the browser!