Imagine a vast, intricate network of interconnected nodes, each one a tiny, hyper-specialized librarian, frantically searching for the perfect book to recommend to you.
These nodes, or 'neurons,' are connected by a labyrinthine system of roads and highways, each one a different type of data.
When you ask the system for a recommendation, it's like asking the librarian a question, and it will rummage through the shelves, gathering and cross-referencing information until it finds the perfect book.
The catch? The librarian's tastes and biases are a product of its own training, so the recommendations might be... interesting.
Want to know more about this enigmatic system?
Read Deep Neural Networks, or perhaps Neural Networks Are Like.