The Ryskamp Learning Machine represents a quantum leap in the world of machine learning. It breaks from the traditions of the past and uses a completely new paradigm for the core machine learning algorithm. This algorithm focuses on logic over pure mathematical solutions and specific information processing (currently associated with traditional programming) combined with categorization and pattern recognition (currently associated with machine learning) into a single algorithm and engine. Additionally, the RLM saves every decision it ever makes, making debugging simple. Neural network "black box" problems are now a thing of the past.

I want to share our new project in hopes that you will give us some constructive feedback. We just recently open-sourced and hosted on Github. The RLM is a ML engine that incorporates concepts of an artificial neural network to solve a wide variety of problems such as categorization, reinforced learning problems, etc.. What makes the RLM different to traditional ML is the core algorithm relies on logic instead of advanced mathematics which means you don't need to be an expert in math to use the RLM. For more details, please visit our site or you may read this technical overview. I hope you find it interesting and apply it on one of your AI endeavors in the future and let us know how it went.