"Learning to write: a machine learning experiment" is a textual artificial organism that performs a reading and writing exercise using video input from around the globe and a generative language model trained on 19th-century travel literature and contemporary Latinoamerican Literature. The work focuses on the notion of travel, journey, discovery, and cognition.

The system articulates two structures: a convolutional neural network using mobile vision and a long short-term memory (LSTM) architecture of recurrent neural network (RNN).

The convolutional neural network using mobile vision interprets a set of audiovisual micro-narratives representing personal waiting times or moments in which I feel present, as well as videos that depict places and cultural phenomenons in Latinamerica.

Then, the objects and situations recognized by the machine are sent to a long short-term memory (LSTM) recurrent neural network (RNN) that has been trained on 19th-century travel literature and contemporary Latinoamerican Literature. The RNN model then narrates what is happening -or what it thinks is happening- in the image.

The work is an experiment around endless writing that attempts to understand a world made up of limited objects and perceptions, perhaps a reflection of our cognitive operations.