I also feel like saying, 1984...

This story appeared in Economic Times, wherein Apple claims to have developed (or is busy doing that) sensitive info about an iphone user. Subsequently, Apple intends to hold/halt usage of the iphone device from the "unauthorized" user, this unauthorized reportedly includes -

1. an iphone that has been hacked to work outside the contract with which it was sold, read "jailbroken"

2. an iphone that is perhaps being used by someone other than the person who registered the first heartbeat or facial recognition info..

Apple intends to capture the phone location using GPS/other tech and perhaps control the device remotely if they feel its being used "unauthorized"..

i agree with people who remember 1984 after reading apple's intentions...ha.. time does come back...George Orwell.. were u too right ??
in reference to: Apple to make iPhone theft-proof - Hardware - Infotech - The Economic Times (view on Google Sidewiki)

Country General Mood using Tweets

Well, it sure is pretty fascinating to do that kind of study and come back with results as commonsensical as we see here...

http://www.iq.harvard.edu/blog/netgov/2010/07/mood_twitter_and_the_new_shape.html


I quote - (with all credits where its due, none to me...)

A group of researchers from Northeastern and Harvard universities have gathered enough data from Twitter to give us all a snapshot of how U.S. residents feel throughout a typical day or week.

Not only did they analyze the sentiments we collectively expressed in 300 million tweets over three years against a scholarly word list, these researchers also mashed up that data with information from the U.S. Census Bureau, the Google Maps API and more. What they ended up with was a fascinating visualization showing the pulse of our nation, our very moods as they fluctuate over time.

The researchers have put this information into density-preserving cartograms, maps that take the volume of tweets into account when representing land area. In other words, in areas where there are more tweets, those spots on the map will appear larger than they do in real life.

A apparantly public domain result of the analysis is available here -
http://cdn.mashable.com/wp-content/uploads/2010/07/twitter-moods.jpg