Quantum Geometric Networks
for Artificial Intelligence
Transforming Machine Learning
QGNai has developed a novel machine learning platform, RG Categorifier™ (RGC), to significantly improve the learning and decision-making of machines.
RGC learns hidden relationships in the data (e.g., image, text, bio sequence, etc.) through a hierarchical structure resulting in deeper learning than state-of-the-art.
The platform uses a proprietary recursive dimensional reduction technology to coarse-grain initial datasets to discover their underlying dominant features at all levels. The invertibility of the architecture allows fine-tuning coarse-grain data to generate new datasets based on latent variables. RGC's bidirectional generative design enables efficient classification, clustering, and explainability.
RG Flow has broad applications in natural language processing, biomedical research, cybersecurity, and robotics.