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.
To keep the capabilities of AI progressing, the future of AI models will need to more closely align with the biological model for human intelligence. The hardware and software must evolve in order to exhibit more natural intellect and processing capabilities.