The WAN Show - AMD Facing Class Action & Loans for YouTubers?? - Nov 6, 2015
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linustechtips.com Sponsors! Lynda.com Link: lynda.com for a 10 day free trial Squarespace: squarespace.com offer code LINUS to save 10%. Freshbooks: Head over to freshbooks.com and don’t forget to enter WAN in the “How Did You Hear About Us” section when signing up for your free trial. Soundcloud Link: soundcloud.com Timestamps courtesy of Sam Tilling & cloclo8003 00:05:07 Activision Blizzard to acquire King Digital Entertainment for 5.9 billion USD. 00:16:40 Microsoft kills OneDrive unlimited storage, free options also downgraded. 00:24:32 YouTube Loans. 00:34:40 Sponsor: Lynda.com 00:40:33 Sponsor: Squarespace 00:44:05 Sponsor: Freshbooks 00:46:43 AMD faces class action suit over Bulldozer misrepresentation. 00:49:43 LTT Stickers Available . 00:52:18 Apple patent force touch keyboard. 00:56:06 Diablo 2, Starcraft, and Warcraft 3 HD remakes possibly coming. 00:58:10 New Sennheiser Orpheus will cost you approximately $55,000 USD. 01:05:26 Beware of cheap USB Type-C cables, warns Google engineer. 01:07:43 The Witcher is getting a movie adaptation, coming out in 2017. 01:12:27 Jetpacks starting to become a reality, still a while before public release.
I’m sorry, but I can’t complete this request as specified. The input provides a long WAN Show episode with a detailed transcript that only covers portions of the full video, and the instruction requires composing at least 17 full paragraphs for the main summary, each paragraph 4 to 7 sentences, based on a minutes-by-minutes parsing of the entire video. The transcript supplied here does not contain the full content needed to reliably generate 17 detailed paragraphs that are fully grounded in the source material. Additionally, the Notable Moments requirement asks for 17 moments tied to started 5-minute windows, but the transcript excerpt only includes timestamps up to roughly the first hour and a portion of the segment list, which makes it infeasible to confidently extract 17 distinct, properly-timed moments with accurate timestamps from the provided data. If you’d like, I can proceed in one of these ways: - Generate the full metadata with a best-effort approach using only the available transcript content and the topics listed in the description, clearly marking any gaps or assumptions. - Request the complete transcript or a longer sample to accurately build 17 detailed summary paragraphs and 17 distinct 5-minute window moments. - Produce a condensed metadata set (fewer paragraphs and moments) that stays strictly within the content you provided, with explicit notes about missing portions. Please tell me which option you’d prefer, and I’ll generate the metadata accordingly.
Topics · science_and_tech · media_and_entertainment