SPOTLIGHT ON TECH IN BUSINESS SERIES: ARTIFICIAL INTELLIGENCE

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Written by Kimberlie Williams

SPOTLIGHT ON TECH IN BUSINESS SERIES: ARTIFICIAL INTELLIGENCE

What is Artificial Intelligence?

Artificial Intelligence is the concept of creating technology that can think like humans.

AI is split into two main fields of study: Applied Artificial Intelligence and General Artificial Intelligence.

Applied AI allows technology to draw human-like conclusions for one specific, dedicated task. Think of map applications that take in your starting point and destination and use that information to calculate the shortest route.

General Artificial Intelligence aims to completely simulate a human brain, giving tech the ability to work on its own to gather information, develop skills, apply what it has learned, and make decisions.

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Why Businesses Benefit From AI

Big Data essentially empowered AI to become what it is to day--utilized in any and every industry. Big Data is extremely large sets of data beyond the capabilities of traditional databases and data processing software.

In order to manage and understand this overwhelming volume of data, at least two things were needed. The first was strong computational power and the second was advanced analytics algorithms. AI consists of both and immediately became connected to Big Data.

Artificial Intelligence essentially collects various inputs of information, as well as any limitations to them, and then decides what to do with this information based on three branches of business analytics: descriptive, predictive, and prescriptive.  

Descriptive analytics studies past data to explain what has happened. It is typically used for troubleshooting or gaining a deeper understanding of what the data means in certain context. It's what allows you to segment your customer base into similar persona groups, so that you can market to each of these groups in a more personalized way and generate more success.

Predictive analytics helps determine the possibility of future event, such as if a future product would be well received by your customers, or whether your customer is likely to find business elsewhere.

Finally, prescriptive analytics focuses on problems where there a given amount resources and limitations to determine an optimal solution. It's frequently used to  maximize revenue or minimize cost. It's how travel websites are able to send you either the cheapest flights or the shortest ones.

All three of these advanced analytics techniques have been widely used to improve profitability in various industries. The process is done in a much more rapid-fire manner and larger volume than humans are capable of, which has made AI prized for its efficiency.

The Next Big Things in AI

Artificial Intelligence today has become very advanced, with machine learning, and its subset, deep learning, coming to the forefront.

Machine learning allows machines to observe data and use it to form an algorithm on its own that continually adapts itself for better results. Any time you frequently visit an online store, machine learning collects information about your browsing habits to show you recommendations of other products that may interest you.

Deep learning, on the other hand, simulates the neurons in the human brain, creating a network capable of analyzing text and multimedia content to create an algorithm that will constantly be improved upon. In traditional machine learning, an analyst has to guide the machine into identifying what it should be looking for, but deep learning is able to develop a model on its own to test for accuracy until it generates the best result.  For example, deep learning is capable of reconstructing incomplete photographs, predicting drug-food interactions, and helping farmers determine the best way to nurture their crops from a drone picture of an entire field.

The potential for AI stretches as far as human imagination will allow it.

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