Futures From Nature: 100 Speculative Fictions is an anthology of 100 short-short science fiction stories originally published on the back page of the prestigious weekly science journal Nature
. The stories come from all matter of writers -- science fiction professionals, working scientists, science writers (there's even one -- rather good -- story written by a scientist's 12-year-old daughter!), and take all manner of approaches to the challenge.
As is inherent in the short-short story form, the pieces are often comic and conceptual, rather than fleshed out narratives -- it's quite a trick to cram a full-blown story with realized characters into a mere 700 words. Many of these stories are flat-out brilliant, and not all of those come from professional writers (though sf pros like Bruce Sterling, Ben Rosenbaum, Joan Vinge, Kathryn Cramer, Robert Charles Wilson and Toby Buckell all have superb little gems here). Clearly, many scientists have a frustrated sf writer lurking within them.
100 short-short stories make for a very strong cup of tea indeed. The opening paragraphs alone are something of a masterclass in the rapid establishment of a story: setting, person and problem all nailed up within a few words. Plunging into -- and emerging out of -- 10 worlds in a day's reading can be a genuinely disorienting experience.
But it's a good kind of disorientation. These stories take on the big and small problems of science, from grant-writing to debunking pseudoscience, from Frankensteinian techno-apocalypses to the brightest utopias. Considered purely as an exercising in finding out what sort of thing captures the imagination of a working scientist, this is a fantastic little journey.
And of course, it doesn't hurt that many of these are just plain great stories.
(Disclosure: I have a story in this collection)
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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