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* Hybrid Crowd: Higher value work and a greater volume of work can be completed when specialists, crowd workers and machines work together.
* AI: Machine learning creates a cascade of knowledge that enables more and more automation and continuously optimizes cost and quality. <ref>“Enabling Exponential Data Productivity: How Crowd Computing bridges the gap between Big Data and the enterprise”. White Paper, May 2013; http://www.crowdcomputingsystems.com/Big-Data-Crowdsourcing-Automation-White-Paper#oid=1001_11_banner_22</ref>
Businesses and society in general increasingly rely on the combined intelligence, knowledge, bandwidth and life experiences of the ‘crowd to improve processes, make decisions, identify solutions to complex problems and monitor changes in consumer taste.<ref>Crowdcomputing.com</ref> Companies like [[Amazon.com|Amazon]] and [[Google]] saw early-on the potential for crowd computing. In 1995, Amazon created [[Amazon_Mechanical_Turk|Mechanical Turk]] to deal with its internal problem of sorting its massive inventory. The platform organizes people from around the globe to ‘work efficiently as a giant machine.”<ref>Popper, Ben (17 April 2012). "Crowd computing taps artificial intelligence to revolutionize the power of our collective brains". Venture Beat. Retrieved 8 June 2012.</ref> Google uses a [[captcha]] to help digitize books. Major sites like [[Facebook]] and [[Twitter]] rely on the crowd to power the translation that spreads their service around the globe. <ref>Popper, Ben (17 April 2012). "Crowd computing taps artificial intelligence to revolutionize the power of our collective brains". Venture Beat. Retrieved 8 June 2012.</ref>
The premise of leveraging the triumverate of crowd sourcing, automation and machine learning accelerates the speed, improves the accuracy and reduces the cost of work historically completed through outsourced workers and frees internal analysts to do higher-value work. The enterprise, as a result, experiences exponentially greater productivity. <ref>“Enabling Exponential Data Productivity: How Crowd Computing bridges the gap between Big Data and the enterprise”. White Paper, May 2013; http://www.crowdcomputingsystems.com/Big-Data-Crowdsourcing-Automation-White-Paper#oid=1001_11_banner_22</ref>
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The company’s platform automates tasks and combines human labor sourced from companies such as [https://www.elance.com/p/lpg/freelancing/?rid=1TN5N&utm_source=google&utm_medium=cpc&utm_campaign=C-Brand-Exact&utm_term=elance&ad=29682394458&bmt=e&adpos=1t1&gclid=CKzuq7SvwbkCFVNo7AodzTsAWw#testimonials Elance], [https://www.odesk.com Odesk] and [https://www.mturk.com/mturk/welcome Amazon Mechanical Turk] to create, manage and enhance an on-demand content and data workforce. <ref>Crosman, Penny. (4 Sept, 2013). “A New Way to Outsource Bank Jobs: To the Cloud”. Banking Technology News. Retrieved 5 September 2013. http://www.americanbanker.com/issues/178_171/a-new-way-to-outsource-bank-jobs-to-the-cloud-1061769-1.html</ref>
In the late 1800s, a team of British archeologists in Egypt stumbled upon a half million pieces of 2000-year-old papyrus, each with remarkably well-preserved text requiring translation. The pieces were shipped from the desert to Oxford University, where generations of scholars have been working to decipher their writings ever since. After over a hundred years, only about 15 percent of the collection had been completed. These manuscripts contain remarkably significant pieces of history, including the controversial Gospel of Thomas and the lost comedies of Athenian playwright Menander. In 2011, however, the scholars decided to speed up the process by leveraging the crowd. They launched a website, Ancient Lives, with a game that tasks members to translate small bits of the text from home. As of November of 2011, users had already provided 4 million transcriptions, helping to identify Thucydides, Aristophanes, Plutarch’s “On the Cleverness of Animals” and much more. <ref>Crowdcomputing.com; http://www.crowdcomputing.com/uses-and-examples-of-crowd-computing</ref>
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