This looks very interesting. I always felt most of ML is about one aspect of intelligence - prediction from existing data. While this may work for specific task

This looks very interesting. I always felt most of ML is about one aspect of intelligence - prediction from existing data. While this may work for specific tasks like driving a car or analysing a scanned image, the human intelligence has always been about the Why? on anything. Answering the Why? on a pile of data by connecting the dots using a causal model is also prediction in a sense, but a more generic one than a prediction on a bunch of specific classes or outcomes. For example, a self-driving car algorithm trained on a pre-classified data to detect obstacles versus a algorithm that can answer Why something is a obstacle is vastly different and is much more effective I guess.