What is Artificial Intelligence Anyway? Posted on : Jun 19 - 2019

The term AI (artificial intelligence) is a bit of a blanket phrase that is used to cover so many different things today. In our mind at least it is analogous to saying “baking”, we all know what baking is, but are we talking about, bread, cookies or cakes? Moreover, if we are explicitly talking about baking bread, is that sourdough, rye, flatbread or dinner rolls? The term AI is a lot like that; we could be talking about deep learning, machine learning, neural networks, or anything in between.

Knowing the basic differences between each is essential, not just to the data scientist but to the practitioner that may be buying or using AI in their business. The good news is that you don't need to know anything about algorithms or advanced math, you need to know why each is different and where and how you can effectively apply each one. For once in our lives, a little knowledge can go a long way.

Machine Learning

The most likely form of AI that you will encounter in the enterprise is Machine Learning (ML), as the name suggests it's a system that learns over time. It does so by learning to identify patterns in data. ML tools use different models to undertake different tasks. There are many such models, but common ones include, Decision Trees, Random Forests, Hidden Markov, Naïve Bayes, and Support Vector Machines. Each works quite differently from the other, though they can also be used in conjunction with one another.

This is a simple but powerful and highly intuitive method that finds regular use in rules-based business activities like credit risk assessments, or for that matter dating applications.

Does this person like heavy metal music (yes or no), do they like foreign travel (yes or no). You get the idea, it's pretty simple, and something we all do ourselves every day when we make decisions. Do I need exercise (yes), do I want to go to the gym (no). View More