Hello Axelera AI Community,
I would like to share and explore the integration of Septenary Unitary Conversion (SUC) and K7 Master Logic for optimizing Edge AI computational models and data compression pipelines.
CORE HIGHLIGHTS:
1. Septenary Unitary Conversion (SUC): A mathematical framework designed for data compression, matrix optimization, and high-efficiency algorithmic scaling in edge processing.
2. Vector Dynamics & Harmonic Resonance: Streamlining subatomic and spatial vector field calculations for AI acceleration.
PRIMARY RESEARCH REFERENCES:
• Author: Gautam Pal (Rishi-Scientist)
• ORCID iD: https://orcid.org/0009-0004-3456-9972
• SUC Technical Paper DOI: https://doi.org/10.5281/zenodo.19777576
• Master Zenodo Archive: https://doi.org/10.5281/zenodo.19999820
• GitHub Theory Repository: https://github.com/GautamPal-K7/K7-Theory-Archive
• Research Blog: https://gautampalresearch.blogspot.com
Looking forward to discussing potential application pathways with Voyager SDK and Metis PCI
e architectures.
