3 Facts You Need to Know About Machine Learning

June 28, 2017

At Interactions, we talk a lot about machine learning, but its definition and use are often misconstrued. Whether we know it or not, we encounter some type of machine learning on a daily basis, making it increasingly important to understand what it is, how it works, and how it will affect our future.

So what is it?

Machine learning is a set of algorithms that, like humans, learns from data and/or experiences, rather than being explicitly programmed. Machine learning utilizes techniques like neural networks and deep learning, so that it can help to create more complex technologies like automatic speech recognition (ASR) and natural language processing (NLP).

Because its technology and definition can be complex, we’ve rounded up 3 key facts that you need to know about machine learning:

  1. Machine learning and AI are not the same thing
    While often mistaken for each other, these two technologies aren’t the same, but rather are interconnected. It’s easiest to think of machine learning as one of the underlying technologies of AI. While the goal of AI is to imitate and mimic human behavior, machine learning gives us the mathematical tools that allow us to do that. AI is able to understand languages, conduct conversations, and continually improve itself because of machine learning algorithms.
  2. It’s in the background of almost everything we do
    Have you ever been writing an important text or email and notice afterwards you’ve incorrectly spelled something? Luckily, machine learning algorithms are used to detect when a word is spelled incorrectly and is able to suggest a new one, saving you time and embarrassment. Similarly, Netflix uses specific machine learning algorithms to suggest content for you based off of your preferences.From TV suggestions, to filtering out our spam email, and much more, these algorithms are meant to radically simplify our lives, and we encounter them a lot more than we think. According to Srinivas Bangalore, Lead Inventive Scientist at Interactions, “good machine learning should not be in your face. It should be behind the scenes, tracking, and helping achieve goals much more quickly and efficiently.”
  3. Incorporating humans is the recipe for success
    No human is perfect, and the same goes technology. Adding a human to the machine learning process increases the level of accuracy and self-awareness. Humans can assist with labeling data, and correct inaccuracies, which leads to more accurate end results. The combination of the two makes the technology more personable, and, in-turn, less intimidating. We understand the importance of the human element, which is why we heavily incorporate it into our products. Our Adaptive Understanding™ technology utilizes the best of speech recognition and Human Assisted Understanding to provide our customers, and their customers, conversational and engaging self-service.

Machine learning is a fascinating technology filled with limitless potential, and this is just the beginning. Experts expect even greater things (think self-driving cars) to come from these algorithms in future.

To learn more about the fundamentals of machine learning, download our free whitepaper below.

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The Fundamentals of Machine Learning

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