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The Quick 10: 10 Ways to Stop People from Climbing the New York Times Building

A third person climbed up the New York Times building last week, forcing the Times to make adjustments to the structure. This trend is similar to the common backyard problem of squirrels scaling birdfeeders. Maybe the NYT can learn from some of these tips to keep critters from climbing up and pillaging the seed:

10 Ways To Stop People from Climbing the New York Times Building

1. Stick the New York Times building on top of a tall pole, put a barrier below and demolish any adjacent buildings within jumping distance.
2. Grease the exterior of the building to make it slippery.
3. Cap the building with a dome (the windows already don't open).
4. Put a cage around the building.
5. Electrify the building exterior.
6. Incorporate rotating beams that turn under the climber's weight. You know, like MXC (the rotating cylinders are a couple of accidents in to the clip)

7. Use a mechanism like the Droll Yankee Flipper, Whipper, Tipper or Dipper.
8. Sprinkle the urine of a natural predator around the base of the building (try fox urine).
9. Hang dried ears of corn outside the Wall Street Journal building to tempt the climbers elsewhere.
10. Beware that squirrels and climbers are prone to biting and promoting agendas.

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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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