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Anne Hathaway says she was spammed with ChatGPT-written thank you notes after hiring for a recent role: ‘Nobody on that list gets that job’

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Anne Hathaway says she was spammed with ChatGPT-written thank you notes after hiring for a recent role: ‘Nobody on that list gets that job’

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The affordability crisis is so bad that, for the first time ever, both mom and dad are working full-time in most American families

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Current price of oil as of June 18, 2026
TechSpotify

Spotify Nabs Top A.I. Expert From Netflix

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Aaron Pressman
Aaron Pressman
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By
Aaron Pressman
Aaron Pressman
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September 6, 2019, 5:52 PM ET
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A top researcher in artificial intelligence techniques has jumped ship from Netflix to Spotify.

Tony Jebara joined the streaming music service Spotify last month as vice president of engineering for personalization to help improve Spotify’s recommendations to users and other features fueled by A.I. and machine learning.

Jebara, who is also a computer science professor at Columbia University and the co-author of numerous papers on A.I., said on his LinkedIn page that he’d be leading Spotify’s company-wide machine learning strategy.

Netflix declined to comment while Spotify didn’t immediately respond.

Spotify has rocketed to the top of the subscription streaming music market in part by appealing to customers with recommendations and curated playlists. For example, the “Discovery Weekly” playlist, created with the help of A.I., offers each Spotify listener a uniquely curated group of 30 songs based on other music that listener has searched and played. But while Spotify has attracted 108 million paid subscribers, Apple is trying to catch up with more than 60 million subscribers of its own.

Jebara started as an academic in 2001 but caught the startup bug, helping co-found Sense Networks in 2006. In 2014, AT&T’s online ad spinoff YP bought Sense, which focused on analyzing data from mobile phone customers. Jebara decamped to Netflix in 2015, where he led a team using machine learning to develop algorithms for personalizing each users’ experience on the service and making TV and movie recommendations.

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