Predictive Intelligence

Artificial intelligence is a broad field that covers a wide range of applications. Machine learning is a subset of AI that allows artificial intelligence to analyze digital data to reach new conclusions it has not technically been programmed to reach. Machine learning then forms the basis of predictive intelligence.

What is Predictive Intelligence?

Predictive intelligence is simply analyzing past behavior to predict future performance. Successful poker players are generally masters of predictive intelligence. They watch the unconscious behaviors of other players before certain outcomes (most commonly known as "tells"), which allows them to predict future outcomes based on those same behaviors. While human intelligence is vastly superior to artificial intelligence in many ways, there are ways in which artificial intelligence has a significant upper hand. Perhaps the biggest advantage of artificial intelligence is the ability to absorb and analyze massive amounts of data in a fraction of the time it would take a human to do the same.

For instance, imagine you gave a human being 100 hours of digital surveillance to watch and asked them to log every time a person in a red cap was shown. Even by just fast-forwarding through the footage it may still take as many as 20-30 hours to absorb all the footage and complete the task. In fact, it would most likely take even longer just simply due to the fact that humans need to use the restroom, eat and just take breaks now and then. If you loaded the same digital recordings into an analytical program, however, it may take anywhere from a few minutes to a few hours to deliver the same results.

While human intelligence may be capable of analyzing a wide range of factors a computer cannot, artificial intelligence is capable of extrapolating from a far greater range of data sets. For instance, utility companies that serve colder regions know they need to have significantly greater stores of natural gas on tap during the winter than in the summer. By analyzing usage in years past, they can make relative predictions of how much natural gas they need to keep at the ready. Like all businesses, the more accurately they predict demand, the better they come out financially. If they under-predict demand, they may have to pay a high premium for additional resources at the last minute. If they over-predict demand, they end up with excess resources they may have to sell at a loss. Predicting exactly how much natural gas will be necessary from winter to winter can be incredibly challenging, however, because of extreme temperature fluctuations from winter to winter.

As more and more homes begin to use smart thermostats, however, utility companies no longer have to rely on just monthly meter readings to understand specific supply needs. Now, millions of smart thermostats are sending information about exactly how much energy almost every household in America is consuming on an hour-by-hour basis. Armed with that information, predictive intelligence can predict exactly how much natural gas an entire town or city will need when the outside temperature is 52 degrees, 40 degrees or -2 degrees. In addition, predictive intelligence can also factor in a wide range of variables, such as how much natural gas might be needed on a weekday when office buildings need to be heated, versus on the weekend when homes are full and offices are empty. It can even factor in tourism fluctuations based on flight and travel information. Without artificial intelligence and machine learning, having specific usage data on millions of homes in the US would be of little use. There would simply be too much data for any small team of people to analyze.

Applications For Predictive Intelligence

Because artificial intelligence is capable of extrapolating from masses of data and a much broader range of data sets, it can find patterns that would be almost impossible for a human being to see. For instance, predictive intelligence can analyze the top-selling fashions of all times as well as global current events to determine which events - if any - had the greatest impact on sales. Predictive intelligence may be able to help the fashion industry determine which fabrics and patterns might be the hottest sellers during any given time frame and which are likely to be the biggest flops.

Predictive intelligence can help gambling and gaming establishments predict which players are most likely to cheat and even help insurance companies determine which customers are likely to be the greatest liability. Predictive intelligence may even be able to help health care providers determine who is at greatest risk of developing cancer or even the likelihood of a tumor being malignant without invasive surgery.

While predictive intelligence is still a growing field, there are few sectors or industries that will not soon be impacted significantly by predictive intelligence.

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