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Big Data Needs a Thought Collective | SYS-CON MEDIA

Big Data Needs a Thought Collective | SYS-CON MEDIA | Seattle.Tech.Unicorns | Scoop.it
SYS-CON Media, NJ, The world's leading i-technology media company on breaking technology news.

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, July 25, 2014 9:53 AM

Big Data should follow the lead of the scientific method (which was influenced by Fleck's ideas) to put greater emphasis on sharing and reusing data. Why is that important for businesses? Scientific data is easy to share among different organizations. Having the ability to do the same with data science could solve what's emerging as a major pain point. Employees change roles and organizations, but what happens to the knowledge, experiments, and patterns?

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Amazon Jobs | Sr. Technical Program Manager

Amazon Jobs | Sr. Technical Program Manager | Seattle.Tech.Unicorns | Scoop.it
This is an opportunity to define, build, and deliver projects that have direct product impact on Amazon Prime. You will own projects that shape the core of what Amazon Prime is and how the program will
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Amazon Jobs | Senior Data Engineer, Amazon Prime

Amazon Jobs | Senior Data Engineer, Amazon Prime | Seattle.Tech.Unicorns | Scoop.it
Amazon Prime is looking for a talented Senior Data Engineer to help lead the development of platforms and tools to that will meet our ever-growing information needs and provide answers to increasingly
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Introducing Amazon Prime Instant Video

Amazon Prime Instant Video - enjoy unlimited instant streaming of movies and TV shows. Anywhere, anytime. Get a 30 day trial at amazon.co.uk/
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Collecting just the right data: When you can’t collect all the data you need, a new algorithm tells you which to target.

Collecting just the right data: When you can’t collect all the data you need, a new algorithm tells you which to target. | Seattle.Tech.Unicorns | Scoop.it

Much artificial-intelligence research addresses the problem of making predictions based on large data sets. An obvious example is the recommendation engines at retail sites like Amazon and Netflix.

 

But some types of data are harder to collect than online click histories —information about geological formations thousands of feet underground, for instance. And in other applications — such as trying to predict the path of a storm — there may just not be enough time to crunch all the available data.

 

Dan Levine, an MIT graduate student in aeronautics and astronautics, and his advisor, Jonathan How, the Richard Cockburn Maclaurin Professor of Aeronautics and Astronautics, have developed a new technique that could help with both problems. For a range of common applications in which data is either difficult to collect or too time-consuming to process, the technique can identify the subset of data items that will yield the most reliable predictions. So geologists trying to assess the extent of underground petroleum deposits, or meteorologists trying to forecast the weather, can make do with just a few, targeted measurements, saving time and money.


Via Ashish Umre
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Amazon Jobs | Sr. Technical Program Manager

Amazon Jobs | Sr. Technical Program Manager | Seattle.Tech.Unicorns | Scoop.it
This is an opportunity to define, build, and deliver projects that have direct product impact on Amazon Prime. You will own projects that shape the core of what Amazon Prime is and how the program will
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REAL UNICORN SIGHTING 2014 - Final Proof of Unicorns - Rare Footage of Ghostly Creature

The elusive Unicorn caught on tape, with stunning close-ups in HD. Best evidence 2014 & real footage of the Mythical Unicorn, not to be missed. The unicorn i...
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