turn

It Would Cost 37 Billion Dollars a Year To Screen YouTube Videos

Source: http://gizmodo.com/5914188/it-would-cost-37-billion-per-year-to-pre+screen-youtube-videos

It Would Cost $37 Billion Per Year to Pre-Screen YouTube VideosLast week, we reported that a staggering 72 hours of video are uploaded to YouTube every minute. Now, engineer Craig Mansfield has worked out how much it would cost per year to pre-screen all that video for copyright infringements—and the answer is close to that of Google’s annual revenue.

Mansfield calculated that a team of 199,584 judges—or equally qualified individuals—would be required to watch and rule over the video, which in turn would cost $36,829,468,840. For comparison, Google’s revenue for 2011 was $37,905,000,000.

Even if it were possible to find a cheaper labor source, the costs would still be astronomical. If you’re interested, you can read his working in detail. [Craig Mansfield via TechDirt]

Image by Rego – d4u.hu under Creative Commons license

Tags: , , , , , , , , , , , , , , , , , , , , , ,

Wednesday, May 30th, 2012 digital No Comments

specialized channels with niche and original content

Source: http://www.engadget.com/2012/01/08/youtubes-got-big-plans-for-web-tv-specialized-channels-with-ni/

YouTube’s come quite a long way from its roots as a repository for random videos from the public. It’s gone from “Chocolate Rain” and the Tron guy to streaming Disney classics and now creating original, quality content. The New Yorker spoke extensively with YouTube’s Global Head of Content Robert Kyncl about the site’s future plans, and YouTube’s got its sights set on grabbing a big slice of TV’s $300 billion pie. Kyncl thinks the future of TV is in niche content, and YouTube’s original channels are just the vehicle to deliver it direct to your digital door. The site is commissioning people and companies to create the channels (as opposed to individual shows or pieces of content) which gives the creators freedom to program their channels as they see fit — all YouTube asks is that they provide a certain number of hours of programming per week. This production model is apparently pretty attractive to content producers, given the talent that’s on board and the amount of content that’ll be rolling out over the next six months.

The idea is that all the original content will get people watching YouTube for longer periods of time, and in turn grant more opportunities to reap ad revenue. Of course, these specialized channels don’t provide the wide advertising reach of traditional television, but they do allow advertisers to target very specific audiences with focused ads. That presumably provides them with better bang for their buck. Time will tell if YouTube’s new plan will win the war against traditional television and web TV (including Kyncl’s former employer Netflix), but free, quality on-demand content certainly sounds good to us. Get a fuller accounting of Kyncl’s vision at the source below, and feel free to sound off in the comments if you’re picking up what he’s putting down.

YouTube’s got big plans for web TV: specialized channels with niche and original content originally appeared on Engadget on Sun, 08 Jan 2012 06:35:00 EDT. Please see our terms for use of feeds.

Permalink The Verge  |  sourceThe New Yorker  | Email this | Comments


drag2share – drag and drop RSS news items on your email contacts to share (click SEE DEMO)

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Sunday, January 8th, 2012 news No Comments

A Few Insights Drawn From The Facebook Pages Of Abercrombie, Aeropostale And More (AEO, ANF, ARO)

Source: http://www.businessinsider.com/insight-facebook-abercrombie-2011-11


abercrombie

“Although Abercrombie fans agree this Skyler cami is cute, a few refuse to pay $88 for it.”

That’s the kind of insight Brean Murray’s Eric Beder drew from comments on the Facebook pages of retail brands. Here are some more:

A&F fans also love the new warm and comfy sweats.

AE fans love the spread in People magazine and they’re digging the “Friends & Family Additional 30% Off” deal, but they’re bad about web tech problems.

Aeropostale “are going crazy” over the 40% off for “Friends & Family” and they’re also excited about the fee $25 gift card after they spend $100.

Hollister fans are buying the new sweaters, though a few object to the prices. The Huntington Beach cardigan is a “must have.”

Urban Outfitters is pissing off its target consumers with the latest fashion line. And everyone thinks those platform heels are “hideous and unoriginal.”

Now take a sneak peak at the Victoria’s Secret fashion show >

Please follow Money Game on Twitter and Facebook.

Join the conversation about this story »

See Also:




drag2share – drag and drop RSS news items on your email contacts to share (click SEE DEMO)

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Wednesday, November 23rd, 2011 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.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

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.

Augustine Fou portrait
http://twitter.com/acfou
Send Tips: tips@go-digital.net
Digital Strategy Consulting
Dr. Augustine Fou LinkedIn Bio
Digital Marketing Slideshares
The Grand Unified Theory of Marketing