Every day—every minute, every second—the world’s computers are amassing visual information at an extraordinary rate. Aspiring Tarantinos are sending their two-minute videos to Youtube in the hopes of going viral. Mom and Dad are uploading their Napa Valley vacation photos to Flickr. Doctors are sending patient MRIs to medical databases, and satellites are scanning the earth for evidence of sinister activity.
As information such as passwords and account numbers moves from computer to computer across the Internet, it is encrypted—jumbled into a non- comprehensible form. Unfortunately, attackers can intercept this encrypted data as they flow through the system or access encrypted data from where it sits in storage and use it maliciously. Cloud computing is becoming more and more common and will require changes in the way that data are protected.
With so much information being shared online these days, it’s critical that much of it remains private and anonymous. We trust, for example, that social networking sites such as Facebook remove personally identifiable information when they share our preferences and desires with advertisers. Vitaly Shmatikov, a young, fast-talking associate professor of computer science studies privacy in ubiquitous data sharing systems, from Facebook to hospitals to Netflix.
Texas Computer Science students are programming robots to play soccer... and winning. Current robots are only 2-feet high, but the goal is to develop robotic players large and skillful enough to beat a real-live World Cup team by 2050. Students from Texas Tech (TT) and The University of Texas at Austin (UT) use C++ to program robots to play without human interaction during the games. The robots play as a team and make individual decisions.
Uli Grasemann and Risto Miikkulainen are using their neural network system, DISCERN, to model what might be going on inside a schizophrenic brain. DISCERN can understand and produce natural language. Working with Ralph Hoffman, a psychiatrist at Yale, they have also been able to pair their neural network results with a study of human schizophrenics, and the similarities have been striking.