Wired's Dylan Tweney has a great piece up on the world's burgeoning crop of Hacker Spaces -- clubhouses where members pitch in to share the rent in exchange for a role in governing a collectively managed collection of hacking kit: workbenches, tools, and components. I've visited hacker lofts in Vienna, San Diego, Los Angeles and elsewhere, and they always have a fantastic
vibe, that palpable buzz you get from gathering a lot of smart, passionate, creative people inside each others' spheres of attention and set them to work, a cross-pollinated vigor.
DIY Freaks Flock to 'Hacker Spaces' Worldwide
At the center of this community are hacker spaces like Noisebridge, where like-minded geeks gather to work on personal projects, learn from each other and hang out in a nerd-friendly atmosphere. Like artist collectives in the '60s and '70s, hacker spaces are springing up all over.
There are now 96 known active hacker spaces worldwide, with 29 in the United States, according to Hackerspaces.org. Another 27 U.S. spaces are in the planning or building stage.
Located in rented studios, lofts or semi-commercial spaces, hacker spaces tend to be loosely organized, governed by consensus, and infused with an almost utopian spirit of cooperation and sharing.
"It's almost a Fight Club for nerds," says Nick Bilton of his hacker space, NYC Resistor in Brooklyn, New York. Bilton is an editor in The New York Times R&D lab and a board member of NYC Resistor. Bilton says NYC Resistor has attracted "a pretty wide variety of people, but definitely all geeks. Not Dungeons & Dragons–type geeks, but more professional, working-type geeks."
For many members, the spaces have become a major focus of their evening and weekend social lives.
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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