Listen to our podcast episode on The Devil Wears Prada:
http://bit.ly/2E0aafbGet 3 months of Audible for $6.95 by going to
http://audible.com/lfts or texting "lfts" to 500 500!
Support LFTS:
http://patreon.com/LFTScreenplayLFTS Merch:
https://standard.tv/collections/lftsTwitter:
http://twitter.com/michaeltuckerlaInstagram:
https://www.instagram.com/michaeltuckerla/Facebook:
https://www.facebook.com/lessonsfromthescreenplay/The Devil Wears Prada does a great job of setting up its story in a very fun and efficient way. This video goes on a tour of the first ten pages of the screenplay to see how it concisely sets the stage for the entire film.
Produced by: Michael Tucker (
http://twitter.com/michaeltuckerla)
Written by: Tricia Aurand (
https://twitter.com/TriciaJeanA)
Edited by: Alex Calleros (
http://twitter.com/alex_calleros)
Read the screenplay:
https://twitter.com/alinebmckenna/status/907776046535081987Become a channel member here on YouTube:
https://www.youtube.com/channel/UCErSSa3CaP_GJxmFpdjG9Jw/joinCheck out my kit, from screenwriting books to gear:
https://kit.co/LFTS/screenwriting-booksLFTS Recommended Reading List:
https://www.lessonsfromthescreenplay.com/reading-list/Translate this video:
http://www.youtube.com/timedtext_video?ref=share&v=-WgzNFEu61oThanks to Diego Rojas for composing original music for this video and this channel! Check out more of his work:
https://soundcloud.com/diegorojasguitarTwinSmart's Marxist Arrow is licensed under a Creative Commons Attribution license (
https://creativecommons.org/licenses/by/4.0/)
Artist:
http://www.twinmusicom.org/With the company Twin musicom licensed under the Creative Commons license Attribution (
https://creativecommons.org/licenses/by/4.0/)
Artist:
http://www.twinmusicom.org/About the Site π
This site provides links to random videos hosted at YouTube, with the emphasis on random. π₯
Origins of the Idea π±
The original idea for this site stemmed from the need to benchmark the popularity of a video against the general population of YouTube videos. π§
Challenges Faced π€
Obtaining a large sample of videos was crucial for accurate ranking, but YouTube lacks a direct method to gather random video IDs.
Even searching for random strings on YouTube doesn't yield truly random results, complicating the process further. π
Creating Truly Random Links π οΈ
The YouTube API offers additional functions enabling the discovery of more random videos. Through inventive techniques and a touch of space-time manipulation, we've achieved a process yielding nearly 100% random links to YouTube videos.
About YouTube πΊ
YouTube, an American video-sharing website based in San Bruno, California, offers a diverse range of user-generated and corporate media content. π
Content and Users π΅
Users can upload, view, rate, share, and comment on videos, with content spanning video clips, music videos, live streams, and more.
While most content is uploaded by individuals, media corporations like CBS and the BBC also contribute. Unregistered users can watch videos, while registered users enjoy additional privileges such as uploading unlimited videos and adding comments.
Monetization and Impact π€
YouTube and creators earn revenue through Google AdSense, with most videos free to view. Premium channels and subscription services like YouTube Music and YouTube Premium offer ad-free streaming.
As of February 2017, over 400 hours of content were uploaded to YouTube every minute, with the site ranking as the second-most popular globally. By May 2019, this figure exceeded 500 hours per minute. π
List of ours generatorsβ‘
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