In the previous chapters, we have examined a number of models, from simple ones to more sophisticated ones, with some common properties:
- They accept unique and isolated input
- They have unique and fixed size output
- The outputs will depend exclusively on the current input characteristics, without dependency on past or previous input
In real life, the pieces of information that the brain processes have an inherent structure and order, and the organization and sequence of every phenomenon we perceive has an influence on how we treat them. Examples of this include speech comprehension (the order of the words in a sentence), video sequence (the order of the frames in a video), and language translation. This prompted the creation of new models. The most important ones are grouped under the RNN umbrella.