Ladder of causation is a taxonomy for classifying causation tasks. We would like to build intelligent systems that can reasonably perform well in one or more of these tasks.
To an LLM we can give a set of paragraphs extracted using a Retriever, and then elicit an answer to the question "how often does event B occur given event A".
These tasks involve predicting a possibility. For example, "if I make this move, will it result in that event". Here the intelligent system is inferring from a range of possibilities, pretty much like the next token prediction. It has a Markovian flavor.
What level is pixtral at in this ladder of causation?