deep learning models like to cheat: during training, they find easiest paths to optimize in the data landscape once we digitize the data: convert the raw data into numbers, and put them toghether in a way that the models can process.
- there are many places during this process that we can induce loss or inductive bias. sometimes the bias are effective, sometimes it’s not.