Auteur Sujet: random[a..z]khi Fancred Gets $3M To Continue Building Social Network Just For Sp  (Lu 13 fois)

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 According to the suit, Netflix allegedly knew about the agreements in place before pursuing the hires of both employees, with the specific intent of incentivizing them to break their contracts. Fox is looking for damages in addition to the injunction against any further poaching.In a statement provided to The Hollywood Reporter, Netflix said that it  believe in employee mobility  and doesn ;t believe Fox   use of employment contracts is  enforceable  under the law.Netflix has a fairly strong reputation for its recruiting processes, both on its tech side and in terms of creative talent. stanley drink bottle  The streaming service   string of creative hits definitely helps with its ability to poach top i stanley thermos ndustry talent, and it has additional know-how thanks stanley cup  to its experience finding and keeping engineering talent in the highly competitive Silicon Valley job market.This suit means that legacy film and TV studios clearly see Netflix as a threat, especially as the strea Vfkz Photobucket Is Releasing A New App, Looking To Close The Loop On Their Storage Services
 What S艒sh provides are recommendations not only about venues like the kind you ;d be able to find from crowdsourced efforts like Yelp, but about specific activities, events, and services that you ;d be likely to actually attend or use. It combines data-analysis efforts and algorithmic recommendati stanley cup price ons with human-curated selection to pare down the wealth of things to do in any given city to effectively a top 15 percent that should actually be relevant and high quality.S艒sh founder and CEO Rishi Mandal explained in an interview that what makes his company special in a world of similar types of products is the special attention paid to typical flags of low-quality events, lik botella stanley  stanley bottles e over-emphatic language and other subtle cues. It   an approach that Mandal thinks makes S艒sh better than others tackling personalized recommendations, like TechCrunch Battlefield candidate Livestar or Ness Computing. This is almost a stupidly hard problem to try to solve, and yet it   also