The Las Vegas all-you-can-eat buffet arms-race has gone thermonuclear: for $37.99, the Bellagio will give you access to its all-you-can-eat caviar buffet, offering "the world’s finest caviars Ikura and Tobiko."
Although buffets are all you can eat, the chefs recommend that customers take the caviar in small bites. To help novices, the chefs serve an appropriate amount on blinis and mini-waffles with traditional accompaniments such as chopped egg, red onions, chives or creme fraiche.
"We do have some people who come up with a bowl and want us to fill it up," Ortiz said. "But we like to respect the integrity of the dish."
A fascinating article in The Verge looks at the history of casino cheating and talks to Ted Whiting, director of surveillance at the Aria casino in Vegas, who specced out a huge, showy CCTV room with feeds from more than 1,100 cameras. They use a lot of machine intelligence to raise potential cheating to the attention of the operators.
Despite that, Whiting says facial recognition software hasn’t been of much use to him. It’s simply too unreliable when it comes to spotting people on the move, in crowds, and under variable lighting. Instead, he and his team rely on pictures shared from other casinos, as well as through the Biometrica and Griffin databases. (The Griffin database, which contains pictures and descriptions of various undesirables, used to go to subscribers as massive paper volumes.) But quite often, they’re not looking for specific people, but rather patterns of behavior. "Believe it or not, when you've done this long enough," he says, "you can tell when somebody's up to no good. It just doesn't feel right."
They keep a close eye on the tables, since that’s where cheating’s most likely to occur. With 1080p high-definition cameras, surveillance operators can read cards and count chips — a significant improvement over earlier cameras. And though facial recognition doesn’t yet work reliably enough to replace human operators, Whiting’s excited at the prospects of OCR. It’s already proven useful for identifying license plates. The next step, he says, is reading cards and automatically assessing a player’s strategy and skill level. In the future, maybe, the cameras will spot card counters and other advantage players without any operator intervention. (Whiting, a former advantage player himself, can often spot such players. Rather than kick them out, as some casinos did in the past, Aria simply limits their bets, making it economically disadvantageous to keep playing.)
With over a thousand cameras operating 24/7, the monitoring room creates tremendous amounts of data every day, most of which goes unseen. Six technicians watch about 40 monitors, but all the feeds are saved for later analysis. One day, as with OCR scanning, it might be possible to search all that data for suspicious activity. Say, a baccarat player who leaves his seat, disappears for a few minutes, and is replaced with another player who hits an impressive winning streak. An alert human might spot the collusion, but even better, video analytics might flag the scene for further review. The valuable trend in surveillance, Whiting says, is toward this data-driven analysis (even when much of the job still involves old-fashioned gumshoe work). "It's the data," he says, "And cameras now are data. So it's all data. It's just learning to understand that data is important."
One thing I wanted to see in this piece was some reflection on how casino level of surveillance, and the casino theory of justice (we spy on everyone to catch the guilty people) has become the new normal across the world.
The New Yorker's profile of Apollo Robbins is one of the most interesting things I've read all year (ha). Robbins is a self-trained virtuoso pickpocket who once managed to lift a pen out of Penn Jillette's pocket, steal the ink cartridge, and return the pen, all while he was demurely insisting to Jillette that he wasn't really comfortable performing in front of magicians.
Josh grew increasingly befuddled, as Robbins continued to make the coin vanish and reappear—on his shoulder, in his pocket, under his watchband. In the middle of this, Robbins started stealing Josh’s stuff. Josh’s watch seemed to melt off his wrist, and Robbins held it up behind his back for everyone to see. Then he took Josh’s wallet, his sunglasses, and his phone. Robbins dances around his victims, gently guiding them into place, floating in and out of their personal space. By the time they comprehend what has happened, Robbins is waiting with a look that says, “I understand what you must be feeling.” Robbins’s simplest improvisations have the dreamlike quality of a casual encounter gone subtly awry. He struck up a conversation with a young man, who told him, “We’re going to Penn and Teller after this.”
“Oh, then you’ll probably want these,” Robbins said, handing over a pair of tickets that had recently been in the young man’s wallet.
When Robbins hits his stride, it starts to seem as if the only possible explanation is an ability to start and stop time. At the Rio, a man’s cell phone disappeared from his jacket and was replaced by a piece of fried chicken; the cigarettes from a pack in one man’s breast pocket materialized loose in the side pocket of another; a woman’s engagement ring vanished and reappeared attached to a key ring in her husband’s pants; a man’s driver’s license disappeared from his wallet and turned up inside a sealed bag of M&M’s in his wife’s purse.
After the performance, Robbins and I had dinner at the bar. “A lot of magic is designed to appeal to people visually, but what I’m trying to affect is their minds, their moods, their perceptions,” he told me. “My goal isn’t to hurt them or to bewilder them with a puzzle but to challenge their maps of reality.”
My fascination with the profile doesn't just come from the recounting of Robbins's many impressive deeds (though they are impressive, and if I ever had cause to book a magician for a gig, he'd be it), but also the struggle that Robbins has had in coming up with ways to maximize his prodigious talent.