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If You’re Still Unimpressed With Bitcoin Wait Until You See This Bitcoin ATM

Source: http://www.businessinsider.com/robocoin-bitcoin-atm-2013-9

robocoin

RoboCoin is a digital kiosk that lets its customers buy and sell Bitcoin for cash. For all intents and purposes, it’s a Bitcoin ATM.

Brothers Mark and John Russell of Las Vegas are the brains of the operation, having already run a software company that builds software powering more conventional ATMs. Russell was already an avid Bitcoiner, so building a Bitcoin ATM was just a natural extension of what they were already doing.

Here’s how it works. You put your cash deposit into the machine and either it tell it to generate a digital Bitcoin wallet for you and put your money there, or give the machine a preexisting wallet address for depositing your coins. It will print a QR code as a receipt of your transaction. About 10 minutes later, the Bitcoin network will push your transaction through, giving you access to your new Bitcoins.

If you want cash for your Bitcoins, bring your QR code back to a RoboCoin kiosk, scan it, and watch as it dispenses your physical money. Bitcoin to cash instantly, cash to Bitcoin almost instantly (consider the three- or four-day waiting period).

The Russells don’t intend to operate the RoboCoins themselves, but will instead sell the devices to operating partners for $18,500 (the price will later rise to $20,000). It’s not clear where the brothers foresee the ATMs being placed. Those who buy the kiosks will have to be smart when it comes to following financial regulations. These ATMs are essentially a money-launderer’s dream come true, but that’s hardly the point here. Where Bitcoin likely feels intractable for some, RoboCoin brings it into the physical world. Suddenly we’re dealing with Bitcoin right in front of us in terms that we understand – it’s just like any ATM you’ve used a thousand times before. It simply builds a bridge between digital and physical currency.

The first RoboCoin kiosk will open later this year in Vancouver and will spread quickly thereafter, according to the plan. The Glas! ers tell us there’s already plenty of interest. Check out the video below to see what a sample transaction looks like:

 


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Monday, September 9th, 2013 news No Comments

Google Chromecast review: can you make your dumb TV a smart one for just $35?

Source: http://www.engadget.com/2013/07/29/google-chromecast-review/

Google Chromecast review: can you make your dumb TV a smart one for just $35?

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Despite the best efforts of Panasonic, Samsung, Sony, LG and others, most of the televisions in people’s homes these days are not of the smart variety. However, there are hundreds of millions of regular televisions packing HDMI ports, and Google’s new Chromecast device offers a way to put some brains into those dumb TVs by giving them access to web-based content. Having a Chromecast dongle connected to your TV means you can stream videos straight from a Google Play, Netflix or YouTube app, or mirror the content in any open tab in Google’s Chrome browser using a tab casting feature.

Sure, we’ve seen devices with almost identical functionality, like Plair, but Chromecast is backed by Google, whose relationships with content providers and developers mean that the Google Cast technology powering it will soon be popping up in even more apps. Not to mention, there’s the price. At $35, it’s almost a third of the cost of Plair and also Roku 3 and Apple TV, the current most popular devices that bring internet video to your TV. Even for such a paltry outlay, is it a worthy addition to your living room? And is it really “the easiest way to enjoy online video and music on your TV” as Google’s marketing would have us believe? Read on to find out.

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Monday, July 29th, 2013 news No Comments

drag2share: Kids Who Grow Up Using iPads Have Restricted Vocabularies

source: http://feedproxy.google.com/~r/businessinsider/~3/ej7kmEb_VGA/kids-who-grow-up-using-ipads-have-restricted-vocabularies-2013-7

tablet

The iPad generation will learn fewer words, experts fear, as using text messages, emails and computers to learn could be stunting children’s vocabulary.

Our brains are hardwired to learn new words when we hear others use them in conversation. But as children increasingly learn through devices instead of listening to others they do not get the opportunity to hear a wide range of words.


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Tuesday, July 23rd, 2013 news No Comments

You Watch More TV (and Less YouTube) Than You Think

Source: http://gizmodo.com/5534061/you-watch-more-tv-and-less-youtube-than-you-think

You Watch More TV (and Less YouTube) Than You ThinkAs part of a special report on the state of couch potatoes in the year 2010, the Economist collected data on perceived vs. actual media consumption. People are in denial about their TV addictions and overconfident in their YouTube cool.

Maybe not consciously, but that seems to be the case. The chart shows that to some extent YouTube is still a media event—something we’re aware of ourselves watching—whereas TV just washes over us and seeps into our rotting brains without us even realizing it.

These numbers are from 2008, though, and it would be interesting to see how the balance has shifted over the last 2 years. Personally, my YouTube watching is way up, my TV watching is way down, and the only time I hear the radio is when someone drives by with their windows down. Because honestly, who needs Treme when you have this. [The Economist]

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Sunday, May 9th, 2010 news No Comments

How Google Crunches All That Data

Source: http://gizmodo.com/5495097/how-google-crunches-all-that-data

If data centers are the brains of an information company, then Google is one of the brainiest there is. Though always evolving, it is, fundamentally, in the business of knowing everything. Here are some of the ways it stays sharp.

For tackling massive amounts of data, the main weapon in Google’s arsenal is MapReduce, a system developed by the company itself. Whereas other frameworks require a thoroughly tagged and rigorously organized database, MapReduce breaks the process down into simple steps, allowing it to deal with any type of data, which it distributes across a legion of machines.

Looking at MapReduce in 2008, Wired imagined the task of determining word frequency in Google Books. As its name would suggest, the MapReduce magic comes from two main steps: mapping and reducing.

The first of these, the mapping, is where MapReduce is unique. A master computer evaluates the request and then divvies it up into smaller, more manageable “sub-problems,” which are assigned to other computers. These sub-problems, in turn, may be divided up even further, depending on the complexity of the data set. In our example, the entirety of Google Books would be split, say, by author (but more likely by the order in which they were scanned, or something like that) and distributed to the worker computers.

Then the data is saved. To maximize efficiency, it remains on the worker computers’ local hard drives, as opposed to being sent, the whole petabyte-scale mess of it, back to some central location. Then comes the second central step: reduction. Other worker machines are assigned specifically to the task of grabbing the data from the computers that crunched it and paring it down to a format suitable for solving the problem at hand. In the Google Books example, this second set of machines would reduce and compile the processed data into lists of individual words and the frequency with which they appeared across Google’s digital library.

The finished product of the MapReduce system is, as Wired says, a “data set about your data,” one that has been crafted specifically to answer the initial question. In this case, the new data set would let you query any word and see how often it appeared in Google Books.

MapReduce is one way in which Google manipulates its massive amounts of data, sorting and resorting it into different sets that reveal new meanings and have unique uses. But another Herculean task Google faces is dealing with data that’s not already on its machines. It’s one of the most daunting data sets of all: the internet.

Last month, Wired got a rare look at the “algorithm that rules the web,” and the gist of it is that there is no single, set algorithm. Rather, Google rules the internet by constantly refining its search technologies, charting new territories like social media and refining the ones in which users tread most often with personalized searches.

But of course it’s not just about matching the terms people search for to the web sites that contain them. Amit Singhal, a Google Search guru, explains, “you are not matching words; you are actually trying to match meaning.”

Words are a finite data set. And you don’t need an entire data center to store them—a dictionary does just fine. But meaning is perhaps the most profound data set humanity has ever produced, and it’s one we’re charged with managing every day. Our own mental MapReduce probes for intent and scans for context, informing how we respond to the world around us.

In a sense, Google’s memory may be better than any one individual’s, and complex frameworks like MapReduce ensure that it will only continue to outpace us in that respect. But in terms of the capacity to process meaning, in all of its nuance, any one person could outperform all the machines in the Googleplex. For now, anyway. [Wired, Wikipedia, and Wired]

Image credit CNET

Memory [Forever] is our week-long consideration of what it really means when our memories, encoded in bits, flow in a million directions, and might truly live forever.

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Wednesday, March 17th, 2010 news No Comments

Dr. Augustine Fou is Digital Consigliere to marketing executives, advising them on digital strategy and Unified Marketing(tm). Dr Fou has over 17 years of in-the-trenches, hands-on experience, which enables him to provide objective, in-depth assessments of their current marketing programs and recommendations for improving business impact and ROI using digital insights.

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