AI & ML interests

Founded in 2015, Lumina AI develops Random Contrast Learning (RCL®) — a new paradigm in machine learning that moves beyond neural networks. RCL is designed to work across text, tabular, and image data, delivering models that are lightweight, reproducible, and efficient on standard CPU hardware. Instead of relying on massive GPU clusters, RCL introduces a different way of learning patterns in data — one that emphasizes: Determinism – identical runs on identical data always yield the same model. Efficiency – millisecond-level inference and compact model files. Accessibility – deployable anywhere: laptops, servers, or the edge. We share datasets and resources here on Hugging Face so the community can explore how RCL opens new possibilities for machine learning research and practice — from rapid prototyping to enterprise-scale deployment.

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Overview

Lumina AI leverages innovative machine learning techniques, like our proprietary Random Contrast Learning (RCL) algorithm, to deliver cutting-edge solutions for classification problems.

Key Projects

Random Contrast Learning (RCL)

Random Contrast Learning (RCL) is an unconstrained classification algorithm and a new approach to machine learning. Optimized for CPU-chipsets, RCL enhances both speed and accuracy without the need for AI-specific chipsets, reducing costs in data, time, energy and hardware. RCL can be utilized via our API and PrismRCL, our Windows application.

PrismRCL

PrismRCL is our Windows-based application designed to run on CPU hardware, providing accessible AI solutions for a broad range of users. Try PrismRCL free for 30 days at [Website] (https://lumina247.com/prismrcl-sign-up-2-0/)

Datasets

Explore our curated datasets optimized and structured for use with RCL and other machine learning algorithms. All datasets currently hosted have been referenced in our research, available at https://lumina247.com/research/

Links

Team Members

  • Allan Martin (CEO & Co-Founder)
  • Dr. Morten Middelfart (Chief Data Scientist & Co-Founder)
  • Fadi Farhat (SVP, Operations)
  • Daniella Diaz (VP, Sales & Marketing)

Community and Collaboration

We invite collaboration with AI practitioners and researchers. Join our community to contribute and share insights.

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