Earlier this summer, Marvel published Deadpool, Vol. 1: Dead Presidents, a reboot its long-running character Deadpool, a wise-cracking, horribly disfigured, effectively immortal Canadian mercenary who's been kicking around the periphery of the Marvel universe since the 1990s. The reboot, written by Brian Posehn and Gerry Duggan, was greatly complemented by artwork from Tony Moore, the talented illustrator who created the original art for the Walking Dead, one of the great masters of the grotesque (see, for example, his zombie Alfred E Neumann and black-light zombie posters).
I loved this. Deadpool's always been a funny dude, but the current incarnation makes him over as an ultra-violent avatar of Freakazoid.
This works perfectly in the context of the story, which revolves around the fundamental depravity and unaccountability of secret spy-agencies (sound familiar?) like SHIELD, whose old rogue agent has been practicing his necromancy by raising America's presidents from the grave, only to discover that they've come back without their humanity, bent on saving America from Americans by killing all of them
. Moore proves that he is the king of gross-out zombie art here, with a collection of ghoulish, rotting dead presidents who are the focus of wonderful slapstick -- I'm especially fond of the full-page splash where zombie Reagan (in a forgotten Soviet space-based nuclear missile platform) is eviscerated, releasing a cloud of jellybeans and the immortal line, "You stabbed my jellybelly!"
Deadpool, Vol. 1: Dead Presidents
The Nightmare Machine is an MIT project to use machine learning image-processing to make imagery for Hallowe’en.
The Stormtrooper Decanter is on back-order, but you can pre-order one from the next batch for £22 — it’s based on Andrew Ainsworth’s original movie helmet moulds from 1976, and will provide endless opportunities to point to lowball glasses and say things like “aren’t you a little short for a Stormtrooper drink?” (via Bonnie Burton)
Yahoo has released a machine-learning model called open_nsfw that is designed to distinguish not-safe-for-work images from worksafe ones. By tweaking the model and combining it with places-CNN, MIT’s scene-recognition model, Gabriel Goh created a bunch of machine-generated scenes that score high for both models — things that aren’t porn, but look porny.
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