Lossless Semantic Matrix Analysis (99.999% accuracy, no training)

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I built an open-source system for lossless, structure-preserving analysis of matrix data. It auto-discovers semantic relationships between datasets (e.g., drugs ↔ genes ↔ categories) with 99.999% accuracy — without deep learning or lossy compression. It supports CSV/TSV/Excel data, runs via Docker, and outputs semantic clusters, property stats, similarity scores, and visualizations. No setup needed. Works on any data. Fully explainable. GitHub: https://github.com/fikayoAy/MatrixTransformer Docker: fikayomiayodele/hyperdimensional-connection Happy to answer any questions!

Visit product View on Hacker NewsJul 23, 2025

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Actual performance

2points

4comments

Did not reach leaderboard

Launch Intel predictions

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Correct prediction on native model

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