This was the first time I submitted a NaNoGenMo entry which aimed at being readable, in contrast to my previous efforts, Everywhere Dense and Neuralgae, which were really abstract. Annales is a generated parody of a very ancient genre, the chronicle, which tells history as a sequence of reigns, deaths …

My entry for National Novel Generating Month 2016 is a procedurally-generated chronology of rulers, courtiers and tribes, using a nonsense vocabulary generated with the neural net which drives my twitter bot, @GLOSSATORY.

The full text is available on GitHub:

• ANNALES
• ANNALES.pdf

The source code is here

I'll be blogging …

MWHALE IN THE WHALE AND BERED OF THE WHALE IN THE WHALE.

"The whale seemed the ship had been the side of the stranger of the ship would be seen the artain in the sea, and the whale was the ship was a sudden and sounding and head of the …

I've updated the algorithm behind neuralgae. It's still the same basic principle: render a deepdraw image based on some random categories, feed the results back through the classifier, and then repeat with the new categories. But the draw part of the cycle now uses the weights from the classification stage …

I've made my first Twitter bot. It posts a new image and accompanying text from my Neuralgae NaNoGenMo project, six times a day, modified slightly so that it fits within the character limit. One of my goals with Neuralgae was to generate something which was in some sense readable, and …

For NaNoGenMo (national novel generation month) 2015, I wrote some Python which generates a series of loosely-coupled deepdream images, and adds eight-line surrealist 'poetry' to them based on the image categories used to draw them.

The full text is here: Neuralgae.

The source code and a fairly detailed description of …

"Everywhere Dense is a novel generated by the principle of recursive acronym expansion, in which this sentence is repeatedly interpolated with random words."

NaNoGenMo, or National Novel Generation Month is a fun parody of National Novel Writing Month (which I also tried one year, but more on that later). Everywhere …