What Is Machine Learning and Why Companies Can’t Ignore It

July 24th, 2021
In today’s high tech world of smartphones, ridesharing apps and commercial flights, machine learning is all around us. So what is it? It’s a specific branch of artificial intelligence (AI) that trains machines to “learn” and create their own rules over time using algorithms. This technology learns through pattern recognition and real-world interactions, ultimately solving problems without human interference. Instead, they begin to anticipate human behavior, helping the ecosystem work smarter and more efficiently.
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Why Companies Can’t Afford to Ignore It


Machine learning offers organizations the capability to quickly and automatically analyze larger, more complicated data sets, delivering faster, more accurate results — and it’s scalable. The value in striving for precision means that a company increases its chance of spotting profitable opportunities and navigating away from risks.
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By automating repetitive and low-value activities like invoice matching or resume sorting, organizations are addressing real-time market changes and delivering business efficiency through process optimization and employee empowerment. Machine learning is the best way for many industries to stay competitive by driving intelligent systems that improve agility and customer-centricity.

Machine Learning Is Already Hard at Work for Us


Machine learning is all around us — Alexa, Siri, customer service chatbots and even Amazon recommendations. We’re comfortable using machine learning in our daily lives, we just aren’t aware of it. Settling into the sofa to watch Netflix activates an entire machine learning algorithm to push you the best predictions. Those algorithms are valued at $1 billion per year- and for good reason! Netflix predictions and recommendations are uncannily accurate.

There’s one massive example of machine learning that we use countless times per day — Google. Every time you search on Google, powerful algorithms behind the scenes watch your interactions with the results in order to improve the output. The algorithms are looking to see if you stay on the page, for how long, and what you clicked on, among other details. By collecting that data, Google optimizes and refines your searches.