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The Time Has Come to Stop Fearing and Start Embracing AI and ML

The Time Has Come to Stop Fearing and Start Embracing AI and ML

By Mike Cartmill

Everywhere I go, I hear dire warnings of how Artificial Intelligence (AI) and Machine Learning (ML) are going to take over the world. I can’t help but wonder how so many people are missing the potential positive impact these technologies can have. AI and ML are already being put to good use in Silicon Valley and by technology and industrial corporations. But even small and midsize businesses can positively channel these technologies to improve their bottom lines.

Forget what you’ve seen in the movies

When most people hear AI or ML mentioned, they tend to think about Skynet and HAL, or some other science fiction storyline. At the moment, there are many more examples of these technologies that are human- and business-friendly.  We all recognize Siri, Alexa, and Watson as current AI and ML platforms, but many people do not yet realize that Salesforce, Yelp, Facebook, and Twitter are already using machine learning, and Microsoft has announced its plans to use it in Excel.

The movie “Her” may actually be one to remember

One of the simplest machine learning models is also one of the most effective for business. This model is the Artificial Neural Network (ANN). With the ANN, multiple nonlinear data points are entered. From there, the model takes data and processes it through different layers of “artificial neurons” before beginning to look at and connect the input data with known results. Then it creates a model to output a prediction based on previous results. If you have seen the movie “Her” with Joaquin Phoenix, the operating system his character falls in love with does this to some degree.

ANN won’t be your friend, but she could help you retain your customers

A great application of this technology for business is a model that takes client data into account data and then creates a predictive model to identify clients that might be at risk to being lost to a competitor. The ANN would take historical data from an existing data set that would be input and used to “train” itself for evaluating other data sets. During the training set, the ANN would process the data, make nonlinear connections, and determine which factors should be weighted higher than others for a customer attrition prediction. Once it goes through this progression, it would then look at the existing customer base data set (including new customers) and help identify those customers that might need a bit more attention. The more it learns, the more customers you keep and the more you earn!

Good tools are already available

As the use of ML increases, more tools become available and these tools gradually become easier to use to develop your own ML models. Many of the existing tools including TensorFlow, Theano, and Keras have wonderful resources, a variety of tutorials, and work with many languages (Python, R, and Java).  Clearly, as more businesses realize the benefits of these tools, more integration will be added to existing platforms using API services (e.g., AWS, Google, and Microsoft Azure).

If you implement Machine Learning into your business toolbox, you too can help increase success and feel like:

Implement Machine Learning

Mike Cartmill

About the author

Mike is a Software Support Specialist with FMAudit. Mike also enjoys building audio circuits and embedded systems when not attending classes to finish his B.S. in Electrical Engineering at Arizona State.

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