Netflix Became One of the Biggest Online Streamers in the World
Netflix started streaming in 2007, and until this day they were streaming to 60 countries. Now they expand their range to 190 countries. It almost all World. Just some part of the Middle East and China left, which they don’t start streaming yet.
Netflix started streaming in 2007, and until this day they were streaming to 60 countries. Now they expand their range to 190 countries. It almost all World. Just some part of the Middle East and China left, which they don’t start streaming yet.
The last expand is what Netflix needed for staying alive in the future of streaming wars. Many big companies began to enter the market, for example; Amazon, Sony, and Google just some of them. Apple decided, instead of streaming videos for a monthly fee, the company will rent or sell the movies or other type content from Apple TV.
READ ALSO: Netflix Crushed Other Streaming Sources
Next step for Netflix is expanding their original content archive. They put some good tv shows lately, like Marvel’s Daredevil and Marvel’s Jessica Jones, Narcos, Sense8, Grace and Frankie, and Marco Polo. Added new documentaries into their streaming content. And They will also produce some movies just for Netflix users. I am hoping that they will be better than “Ridiculous 6.” The movie was really ridiculous, they need to give me a monthly fee to watch this film. Anyway, In 2016 company will release 31 new original content for their users.
This last move of Netflix, make us see a good future for the company but still need to make more high-quality content to keep people interested into their service. Yes, Netflix future looks bright, but now they need to work harder.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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