Beyond Machine Learning: Capturing Cause-and-Effect Relationships


Deep learning is a powerful statistical technique for classifying patterns using large training data sets and multi-layer AI neural networks. It's essentially a method for machines to learn from all kinds of data, whether structured or unstructured, that's loosely modeled on the way a biological brain learns new capabilities. Machine learning can be applied to just about any domain of knowledge given our ability to gather valuable data in almost any area of interest. But machine learning methods are narrower and more specialized than humans. There are many tasks for which they're not effective given the current state-of-the-art.