1. The Era of Cloud Computing

    “Historically, we’ve been in a world where computing was a scarce resource. Now it is moving to being an abundant resource. Anybody who claims to have a crystal ball about where this is heading is kidding themselves.”

    (Source: The New York Times)

     
  2. In a hole- the problems of European telecoms companies

    Mobile companies find it hard to fight back, not least because they lack their own fast broadband networks and so have no choice but to rent from the incumbents. Though the price is regulated, it can be dear. For example, the rate recently set for fibre by the Spanish regulator—€20 per connection per month—means “the economics are impossible for a renter”, Ms Bienenstock says. And to make the squeeze worse, Liberty Global, an American-owned cable company with operations in several European countries, has said that it is interested in expanding its mobile services too.

     
  3. Hey! You! Get Onto My Cloud: GE Moves Big Machines to the Cloud

    GE has partnered with Amazon Web Services, which pioneered the development of the cloud ‑ and coined its name ‑ to broaden GE’s data software and analytical offerings. GE also expanded its partnerships with Accenture and Pivotal to develop new Industrial Internet services and deploy new high-volume machine data management software based on the powerful Hadoop open-source framework.
    (..)
    Amazon’s chief technology officer said that GE’s “domain expertise” combined with Amazon’s global infrastructure, services, and big data expertise “will help enable customers to solve problems in ways we haven’t even imagined yet, such as improved accuracy in healthcare treatments or extreme levels of energy efficiency.” Paul Maritz, Pivotal’s CEO, said that Pivotal and GE shared “a vision for a common platform that is cloud-agnostic and based on modern, scale-out technologies, and does it all at speeds faster than what was previously possible.”

    (Source: gereports.com)

     
  4. Most data isn’t “big,” and businesses are wasting money pretending it is

    For those of you who don’t normally think in data, what that means is that past a certain point, your return on adding more data diminishes to the point that you’re only wasting time gathering more.

    One reason: The “bigger” your data, the more false positives will turn up in it, when you’re looking for correlations. As data scientist Vincent Granville wrote in “The curse of big data,” it’s not hard, even with a data set that includes just 1,000 items, to get into a situation in which “we are dealing with many, many millions of correlations.” And that means, “out of all these correlations, a few will be extremely high just by chance: if you use such a correlation for predictive modeling, you will lose.”

    (Source: qz.com)

     
  5. At long last, Microsoft is ready to compete head on with Amazon Web Services

    While he did not characterize Azure IaaS as an “Amazon killer,” Azure GM Bill Hilf did say Microsoft will match AWS on price for any of its base-level infrastructure — storage, compute instances, etc. — continuing a price war that flared last November when AWS, Google and Microsoft traded price cuts on their respective cloud storage offerings.

    (Source: gigaom.com)

     
  6. Analyst: Google Will Spend $84M Building Out KC’s Fiber Network To 149K Homes; $11B If It Went Nationwide

    The firm also sounds a note of caution about whether the search giant will ever embark on a nationwide effort: it could cost up to $11 billion to build out gigabit Internet and TV service to another 20 million homes to achieve a medium-to-large rollout to compete with other providers.

    (Source: TechCrunch)

     
  7. eight server makers now account for 75 percent of Intel’s server chip revenues — and one of those is Google. Just four years ago, three companies made up that 75 percent: Dell, HP, and IBM.
     
  8. Into the Cloud

    Data is a physical entity that takes up space and feeds on energy. What will be the cost with a growing demand of speed, access and real time transactions?

    (Source: The New York Times)

     
  9. Everything You Wanted to Know About Data Mining But Were Afraid to Ask

    And these days, there’s always more data. We gather far more of it then we can digest. Nearly every transaction or interaction leaves a data signature that someone somewhere is capturing and storing. This is, of course, true on the Internet; but, ubiquitous computing and digitization has made it increasingly true about our lives away from our computers (do we still have those?). The sheer scale of this data has far exceeded human sense-making capabilities. At these scales patterns are often too subtle and relationships too complex or multi-dimensional to observe by simply looking at the data. Data mining is a means of automating part this process to detect interpretable patterns; it helps us see the forest without getting lost in the trees.

    (Source: Mashable)

     
  10. A great video illustrating scalability, speed and capacity in convergence #convergence #technology