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Election Models Predict Trump Defeats Clinton

The MogIA artificial intelligence system correctly predicted the last three U.S. presidential elections and is picking Trump to be the next commander in chief. The MogIA crunches massive amounts of Internet data including social media. It shows that Trump has overtaken Barack Obama’s peak in 2008 by 25 percent.

Another company, Cognovi Labs, an Ohio-based analytics startup, has a tool built on technology developed at Wright State University by Dr. Amit Sheth called Twitris. Cognovi correctly predicted the Brexit outcome hours ahead of the final vote, going against what traditional polling was indicating. James Mainord, Cognovi CEO, says at this point in the election there is still too much movement in the public mood to say with certainty who will win.

“If I had answered this question on Oct. 28 at 12:30 p.m., my answer would have likely been Clinton,” Mainord told PJ Media. “Even though her support had been harmed by a 10/24 HHS report on Obamacare and continued Wikileaks drops, it appeared that she was holding on to support. The FBI announcement by James Comey was very damaging and we’re following closely to see how much harm it has done.”

So that puts three models for Trump and one on the edge.

There are some adults within the Democratic Party who understand that no matter what happens, even if Clinton wins, she won’t be able to govern (that is, pass liberal legislation), and some are even asking for divine intervention. Proving once again that there are no atheists in foxholes or when in legal/political trouble.

Future campaigns will spend big bucks for software that can measure, react to, and then influence voting behavior. Commercial marketing departments will do the same for their products and services.

Computer models are only going to get better and more sophisticated. Forget about measuring data in terabytes; petabyte storage drives are next, and exabytes, zettabytes, and yottabytes will eventually follow. Each designation adds three zeros and a comma to the previous number.

In 1814, the scientist/mathematician Pierre-Simon Laplace famously suggested a “sufficiently powerful intellect” could, if it knew certain things at a given time, calculate the evolution of the system at any other time. In laymen’s talk, in a way he was saying the future is theoretically predictable.

It didn’t take long for later scientists to conclude that the only thing predicable about the future is its unpredictability. But then, they didn’t have access to our modern data handling and processing capabilities.

With increasing data handling capacities and accompanying faster computing speeds, are we are rapidly approaching Laplace’s concept of “sufficiently powerful intellect”? If you scoff at that idea, and many purists rightly will, just keep in mind that if you are willing to take a little liberty with definitions and accept a little fuzziness in the predictions, we may get close enough for all practical purposes.