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The various costs of losing bets

Earlier this week, I encountered a man who boasted of having run naked (and through sprinklers) across the 18th green. It was the agreed-upon tax of a lost best. I have no interesting bet stories to divulge, probably because I've already willingly engaged in the kinds of activities (the predictable ones, at least--the legal but insane ones) that are smoldering at the ends of well-placed bets; my little brother bet his friend $20 to eat a AA battery once, but they were intercepted before it ever went too far; however, elsewhere across the wagering universe:

  • An NYC school principal lost a bet with a pack of seventh graders and kept his promise to show up to school in drag, causing the Post to cast shade.
  • After losing a bet with his physiotherapist, Austrian skier Rainer Schoenfelder skied naked down the Lauberhorn.
  • Canadian gambler Brian Zembic got breast implants as part of a $100,000 bet; he even kept them past the terms of the agreement.

Do I dare ask anything you've acquired or committed as payment for a lost bet, or in an answer to an accepted bet?

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New AI-Driven Music System Analyzes Tracks for Perfect Playlists
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Whether you're planning a bachelorette party or recovering from a breakup, a well-curated playlist makes all the difference. If you don't have time to pick the perfect songs manually, services that use the AI-driven system Sonic Style may be able to figure out exactly what you have in mind based on your request.

According to Fast Company, Sonic Style is the new music-categorizing service from the media and entertainment data provider Gracenote. There are plenty of music algorithms out there already, but Sonic Style works a little differently. Rather than listing the entire discography of a certain artist under a single genre, the AI analyzes individual tracks. It considers factors like the artist's typical genre and the era the song was recorded in, as well as qualities it can only learn through listening, like tempo and mood. Based on nearly 450 descriptors, it creates a super-accurate "style profile" of the track that makes it easier for listeners to find it when searching for the perfect song to fit an occasion.

Playlists that use data from Sonic Style feel like they were made by a person with a deep knowledge of music rather than a machine. That's thanks to the system's advanced neural network. It also recognizes artists that don't fit neatly into one genre, or that have evolved into a completely different music style over their careers. Any service—including music-streaming platforms and voice-activated assistants—that uses Gracenote's data will be able to take advantage of the new technology.

With AI at your disposal, all you have to do as the listener is decide on a style of music. Here are some ideas to get you started if you want a playlist for productivity.

[h/t Fast Company]

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