Jacob looked rather disappointed and sheepishly asked, “Quip, if anything happens to me, will you erase my porno collection? It will kill me to be dead and have Petra find my porno collection.”
Quip looked astonished at Jacob as he carefully asked, “YOU have a porno collection?”
Jacob grinned and laughed, “Got you! Actually, if I had one, I’d keep it in the log files section where no one would think to look,” he added in a sober tone.
Quip chuckled and acknowledged, “Kid, I didn’t think you’d be able to yank my chain. But as the phrase goes, no matter where you go, there you are. You’re going to be alright, kid.
“Let’s look to see what, if anything is going on with the usual suspects in the Middle East. If any of our key word searches brings up some activity surrounding nanotechnology, we can assume that the Cal-tech boys and girls were the victims of these bad people or the information was brokered to the al-Qaeda.”
“Quip, do we want to try out our new Big Data sifting system with enhanced facial recognition? I’m kinda anxious to see how you pull in all that dissimilar data like news articles, blog postings, social media activity, Internet chatter, emails, and SMS texts and distill it down to relevant useful chunks before running it again. Where do you introduce the facial recognition results in this process? Or better still, HOW do you introduce the facial recognition results?”
Quip grinned like he’d just won a prize as he educated, “I thought you would never ask! So, the Facial Recognition of Multitudes Software or the FROM-ware program, as it is now called, takes the contextual clues from the Big Data results and uses them to hunt for photos or videos where the highest likelihood of finding key individuals that have a close affinity to the topic being worked. As we continue to sift the information the closer we get to match a picture to the bad guy or guys. Once we have those highly relevant pictures we can then compare them to what may be on file with the usual law enforcement agencies. If we get a hit with a law enforcement agency, then we have not only current events but history on the bad guys as well.
“The more we know about them the easier it is to predict where they are and where they might go. Then, at that point, we can start tapping into street cameras for more sifting. The challenge of doing it this way is the handling and sorting of Bizzillo-bytes of information fast enough to operate on. For answers in our world to be useful, information must be promptly evaluated. The best example I can give you is a stock market broker trying to make money day trading using month old financial information: he’ll never be successful.”
“You made up that word Bizzillo-bytes, didn’t you?”
“You know life is more fun when you have someone to tease a little bit. You are fun to tease and you do tease back.”
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