Lumina AI announced the general availability of Random Contrast Learning™ (RCL) 2.7.0, the first production release to include a fully native Linux build of its CPU-optimized machine-learning engine. Data-science teams can train and deploy high-accuracy models directly in Linux environments, without proprietary runtimes or specialized hardware.
“Adding Linux support means users can now use our AI tools on the operating system where most AI workloads run. This makes it easier for people to integrate RCL in their existing workflows and helps more organizations get value from our technology.” – Fadi Farhat, SVP Operations
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RCL 2.7.0 Highlights
- Native support for leading Linux distributions: successfully tested on Ubuntu 22 & 24, Red Hat Enterprise Linux 9 & 10, and Fedora Workstation 42
- Consistent command-line experience: The Linux executables
prismrclandprismrclmbehave exactly like their Windows counterparts; users simply adjust file paths to Linux syntax. - Auto-optimize 2.5+ routine: Automatically selects the most appropriate metric—accuracy, macro-F1, weighted-F1, or Matthews correlation coefficient—based on each dataset.
- LLM training mode: Adding the
--llmflag with--readtextbylineplaces RCL in language-model training mode for datasets already prepared in the RCL-LLM format. - Broad data-type coverage: Handles images (.png), text, and tabular inputs; tabular data train effectively without prior normalization.
- Clean upgrade path: earlier models must be retrained to ensure compatibility and auditability
“With native Linux support, RCL 2.7.0 positions Lumina at the intersection of open-source innovation and sustainable AI. We’re proving that state-of-the-art performance doesn’t require GPUs—just smart engineering on the hardware organizations already own.” – Allan Martin, CEO.
Source: PRNewswire