The DeepCausality project was recently accepted into the Linux Foundation for AI & Data and, as the main author of the project, I want to use the occasion to share a brief introduction.
What is computational causality?
Although deep learning roots in statistics, popular deep learning frameworks such as TensorFlow or PyTorch shield developers from the underlying math. However, statistics uses correlation under the hood to map an input (say, a question) to an output (an answer). Contemporary deep learning has taken statistics one step further, but there are still certain limitations …
Read the full article on the LF AI & data blog post.