Integer Gate Logic (“IGL”) delivers unprecedented improvements in AI-system performance: from TinyML to datacenter scale, IGL neural networks are faster, more efficient, and more accurate than traditional AI systems.

Core Technology: IGL Intelligent Nodes

Each node in an IGL network uses a non-differentiable activation function to emulate any desired Boolean or other combinatorial logic function using integer math. This significantly increases parametric knowledge density over conventional networks that use gradient descent-based weighted sum nodes.

IGL Benefits

+10X faster inference and training speeds

90% fewer parameters

Highly parallelizable

Linear scalability

Fully explainable AI via internal Boolean logic flows and real-time internal visualization – no more AI “black box” effects

For More Information, contact us at info@mliglon.com

MLiglon Corporation

MLiglon AI (creator of Integer Gate Logic, “IGL”) is a Texas based corporation offering the next generation of products and platforms for training neural networks. Using patented, proprietary technology, IGL networks train faster, predict more accurately, reduce energy consumption, provide enhanced parallelization and scalability, and promote model transparency. IGL addresses all of the most pressing AI industry needs, including faster and better performance models at lower cost. IGL is the first truly revolutionary AI neural network architecture in 50 years, and could make backpropagation and other gradient-descent training solutions a thing of the past.