Last month, a YouTube user named demonflyingfox uploaded a video titled “Harry Potter by Balenciaga.” It showed characters from the Harry Potter films—Hagrid, Ron, Hermione, Snape, McGonagall, Dobby—as gaunt models with aggressive cheekbones (slightly yassified), dressed in gothic capes and leather jackets. Set against a catwalk-worthy electronica beat, the actors blink, nod, and speak lines from the books which have been remixed with fashion references. “You are Balenciaga, Harry,” Hagrid says, instead of breaking the news that Harry is a wizard.
The video is strange and hilariously sinister. In three weeks, it has received almost five million views; a sequel, released less than a week ago, has netted more than a million and a half. Pop-culture mashups of one famous thing with another are an archetype of Internet meme-making. What’s unusual about “Harry Potter by Balenciaga” is that it was generated with artificial-intelligence tools. As the video’s creator, the Berlin-based photographer Alexander Niklass, who made the demonflyingfox channel, told me, the video demonstrates a newfound ability of A.I. to “create filmlike moments.”
Read the rest of this article at: The New Yorker
One spring evening, two men and a woman walked into the Ritz Club casino, an upmarket establishment in London’s West End. Security officers in a back room logged their entry and watched a grainy CCTV feed as the trio strolled past high gilded arches and oil paintings of gentlemen posing in hats. Casino workers greeted them with hushed reverence.
The security team paid particularly close attention to one of the three, their apparent leader. Niko Tosa, a Croatian with rimless glasses balanced on the narrow ridge of his nose, scanned the gaming floor, attentive as a hawk. He’d visited the Ritz half a dozen times over the previous two weeks, astounding staff with his knack for roulette and walking away with several thousand pounds each time. A manager would later say in a written statement that Tosa was the most successful player he’d witnessed in 25 years on the job. No one had any idea how Tosa did it. The casino inspected a wheel he’d played at for signs of tampering and found none.
That night, March 15, 2004, the thin Croatian seemed to be looking for something. After a few minutes, he settled at a roulette table in the Carmen Room, set apart from the main playing area. He was flanked on either side by his companions: a Serbian businessman with deep bags under his eyes and a bottle-blond Hungarian woman. At the end of the table, the wheel spun silently, spotlighted by a golden chandelier. The trio bought chips and began to play.
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One of the stultifying but ultimately true maxims of the analytics movement in sports says that most narratives around player performance are lies. Each player has a “true talent level” based on their abilities, but the actual results are mostly up to variance and luck. If a player has, say, the true talent to hit thirty-one home runs in a season, the timing of those home runs is mostly random. If someone hits a third of those in April, that doesn’t really mean he’s a “hot starter” who is “building off a great spring”—it just means that if you take thirty-one home runs and toss them up in the air to land randomly on a time line, sometimes ten of them float over to April. What does matter, the analytics guys say, are plate appearances: you have to clock in enough opportunities to realize your true talent level.
For much of my career, I was the type of journalist who only published a handful of magazine pieces a year. These required a great deal of time, much of which was spent on minor improvements to the reporting, structure, and sentences. I believed that long-form journalism, much like fiction or poetry, possessed a near-mystical rhythm that could be accessed through months of intensive labor. Once unlocked, some spirit would sing through the piece and touch the readers in a universal, truthful way.
Read the rest of this article at: The New Yorker
In the past, the post office has been an embarrassing place for Megan Hitt. The 25-year-old nurse from south Wales recalls a time, a few years ago, when she had to approach the counter with six different Asos parcels in her arms, her “shopping addiction exposed for everyone to see”. Since university, Hitt has been a prolific online shopper – buying several outfits at a time, picking one to keep and returning the rest. This time, when she handed over her parcels to be scanned, she was ashamed that there were so many. Still, she knew she would be back soon – she already had another Asos order on the way.
Buying and returning clothes online is part of the fabric of modern life. For years, Hitt didn’t think much about it: “I used to buy and return like it didn’t matter.” At her worst, she’d order three parcels a week; sometimes, if she knew she’d wear something only once, on a night out, she’d keep the tags on and send it back. “It was something we all used to do,” Hitt says of her university days. “In a house of six girls, four did it all the time.”
In the UK, customers return £7bn of internet purchases every year, while more than a fifth of all clothes bought online are sent back. Across the globe, return rates are typically higher when customers shop online – in the US, 8-10% of sales from physical shops are returned, while 20-30% of e-commerce purchases ultimately rebound. Rising returns during the cost of living crisis are troubling retailers; in the spring of 2022, fast fashion retailer Boohoo blamed an increase in returns for a 94% slump in pre-tax profits.
Read the rest of this article at: The Guardian
