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March 6, 2015

5 Good Reads in Big Open Data: March 6 2015

2015: What do you think about Machines that think? - via Edge: A.I isn't so artificial “With these kind of software challenges, and given the very real technology-driven threats to our species already at hand, why worry about malevolent A.I.? For decades to come, at least, we are clearly more threatened by like trans-species plagues, extreme resource depletion, global warming, and nuclear warfare…”
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  1. 2015: What do you think about Machines that think? via Edge:  A.I isn't so artificialWith these kind of software challenges, and given the very real technology-driven threats to our species already at hand, why worry about malevolent A.I.? For decades to come, at least, we are clearly more threatened by like trans-species plagues, extreme resource depletion, global warming, and nuclear warfareWhich is why malevolent A.I. rises in our Promethean fears. It is a proxy for us, at our rational peak, confidently killing ourselves.
  2. What would you do with 139TB of big open data? via Common Crawl: We've just released 1.82 billion web pages for you to discover, build and innovate. Check it out and please email contributions@commoncrawl.org to share your work!
  3. Google Makes Overriding Redirection More Difficult  - via Search Engine Land:  Google says this move is to improve local user experience, but is The Right To Be Forgotten the true reason?
  4. Less than 40 percent of the world has ever connected to the internet via Slate: the problems are "infrastructure, affordability and relevance" according to Facebook's Internet.org. This information may be disheartening to some, but it also shows what tremendous potential the web still has if we can connect the world.
  5. Hadoop game-changers via Opensource.com: Hadoop, an open source software framework with the funny sounding name, has been a game-changer for organizations by allowing them to store, manage, and analyze massive amounts of data for actionable insights and competitive advantage. But this wasn't always the case. Initially, Hadoop implementation required skilled teams of engineers and data scientists, making Hadoop too costly and cumbersome for many organizations. Now, thanks to a number of open source projects, big data analytics with Hadoop has become much more affordable and mainstream. Here's a look at how three open source projects — Hive, Spark, and Presto—have transformed the Hadoop ecosystem.

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