Entry 50359 (Berkeley CSUA MOTD)

Berkeley CSUA MOTD:Entry 50359

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2024/11/22 [General] UID:1000 Activity:popular

11/22

2008/6/24-27 [Industry/Startup] UID:50359 Activity:nil

6/24    Searching for a startup company in your area? Another goodie
        from crunchbase/techcrunch:
        http://www.startupwarrior.com
        http://valleywag.com/5018794/ten-most-densely-populated-technology-startup-regions

2024/11/22 [General] UID:1000 Activity:popular

11/22

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2013/4/23-5/18 [Industry/Startup] UID:54661 Activity:nil

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2013/3/1-26 [Industry/Startup] UID:54615 Activity:nil

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2013/1/16-2/17 [Industry/Startup, Finance/Investment] UID:54582 Activity:nil

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	...

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www.startupwarrior.comContact StartupWarrior shows the locations of computer technology companies across the globe. Use the map to find a startup job, explore your neighborhood, or decide where you should start your own company.

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valleywag.com/5018794/ten-most-densely-populated-technology-startup-regionsStartup Warrior bills itself as a tool entreprenuers can use to "find a startup job, explore your neighborhood, or decide where you should start your own company." But we feel the site is best used by wary VCs, hassled journos and cynical M&A types looking for regions to avoid. Be warned: Enter into any of the ten regions mapped below and suffer elevator pitches, pleading looks and limp handshakes at your own risk. Update: Apparently Startup Warrior didn't do much in the way of researching the actual addresses of these startups -- many are listed by only by city and state, leading to clumps in central neighborhoods. There isn't actually a zoning law against useful vowels and consonants in Seattle, yet still among the startups between Cherry Street and Jefferson Street: Askablogr. Rafat Ali of PaidContent parent company ContentNext Media legitimizes Santa Monica's startup scene. Then there's Jason Calacanis's year-old "Google-killer" Mahalo -- which will pay you $10 per hour to write Wikipedia entries from your dorm room or trailer. It clusters every NYC start-up for which they don't have exact address data as "New York, NY" which automatically clusters them around Chambers and Reade Streets.