Natural Intelligence Systems was a performer in the DARPA VIP program. During this program we validated the Third Wave AI capabilities of our pattern-based machine learning system.
Today’s neural networks use complex math that requires huge training data and computational horsepower. The Natural Intelligence Neuromorphic system uses patterns- enabling it to learn quickly with small amounts of data like the human brain.
Pattern-based AI gives data scientists new tools for helping interpret and understand their data and the predictions being made. Think of our pattern-based AI as an X-ray of your ML model – Allowing you to see the inner workings of its predictions.
With Natural Intelligence, explanations are inherent to our pattern-based model because the data is preserved all the way from the input of the system to the output prediction.
AI can deliver amazing answers to seemingly insolvable problems, but it’s often a black box. You can’t see the “why” behind the answers. Here’s why explainability in AI matters.
Brains make sense of the world with patterns. Inspired by the human neo-cortex, our machine learning model, the Natural Intelligence Machine Learning system (NIML), is pattern-based.