I turned off the Twitter versions of my fleet of bots last week, and today I went through their various home pages and took out the Twitter timelines - which seem to have stopped working anyway - and replaced them with embedded timelines from their Mastodon incarnations, using Emfed, which was really …

When I was very young, perhaps four or five, I can remember imagining that the world was a flat slab of rock, and that the sky was a hemispherical dome suspended over it, and which somehow always managed to be centered on our car as it drove over the flat …

It's been good to see people from Twitter coming onto the Fediverse, or reviving the accounts which they started in 2018, but I'm also getting worn out. Though not nearly as worn out as the admins and moderators, who have been doing an amazing job.

Hugh's essay captures a lot …

No One is Talking About This, London: Bloomsbury, 2021

Patricia Lockwood

I finished this in a couple of days and it was funny and touching—people probably think of Lockwood as a Twitter phenomenon but she'd have been a good writer no matter what platform she'd made her own. Mostly …

I was tinkering around trying to get Justin Johnson's neural-style implementation working on the HPC - this is an algorithm which uses a deep learning image recognition net to extract low-level style features from one image and use them to render the large-scale contours of another. This technique has been commercialised …

@voronidols are on Twitter, and also on Mastodon @voronidols@botsin.space and the bots page.

Source code

I made a subdomain for my Twitter bots, with a page of info and credits about each of them: bots.mikelynch.org

I made a new bot, @GLOSSATORY, by training a recurrent neural network on a very long list of word definitions from WordNet. The results are quite weird and entertaining if you like this sort of thing:

Tweets by @glossatory

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 …

As an exercise in Haskell, I wrote a monad which threads random-number generation state through a context-free grammar, allowing the creation of arbitrary yet valid sentences. This was kind of clever.

Then I used it to generate a series of descriptions of bands of warriors along the lines of Homer's …