Patriarchy is resilient, but women’s economic independence is a powerful solvent: gender status in medieval China and today.
Janelle Shane is a humorist who creates and mines her material from neural networks, the form of machine learning that has come to dominate the field of artificial intelligence over the last half-decade. Perhaps you’ve seen the candy-heart slogans she generated for Valentine’s Day: DEAR ME, MY MY, LOVE BOT, CUTE KISS, MY BEAR, and LOVE BUN. Or her new paint-color names: Parp Green, Shy Bather, Farty Red, and Bull Cream. Or her neural-net-generated Halloween costumes: Punk Tree, Disco Monster, Spartan Gandalf, Starfleet Shark, and A Masked Box.
Her latest project, still ongoing, pushes the joke into a new, physical realm. Prodded by a knitter on the knitting forum Ravelry, Shane trained a type of neural network on a series of over 500 sets of knitting instructions. Then, she generated new instructions, which members of the Ravelry community have actually attempted to knit.
In the Colours of Nature dye house, Vijayakumar Varathan is busy prepping a vat of indigo. At 51, he looks frail, with a tanned body made mostly of bones, but he runs to and fro, setting up an open fire where he’ll brew cauldrons of natural colorants made from plants.
He’s worked here for 15 years. But until his early 30s, Varathan mixed chemicals in a conventional clothing factory in the same region of southern India. There he developed a disease that caused layers of his skin to peel off. Even today, it is discolored. “It was pretty bad,” he says, in his fragmented English. “But I didn’t have a choice.”
In February 1939, Vogue ran a major feature on the fashions of the future. Inspired by the soon-to-open New York World’s Fair, the magazine asked nine industrial designers to imagine what the people of ‘a far Tomorrow’ might wear and why. (The editors deemed fashion designers too of-the-moment for such speculations.) A mock‑up of each outfit was manufactured and photographed for a lavish nine-page colour spread.