Have you seen our recent blog post on Artificial Intelligence? (If you haven’t, you should!). If you have, then you already know a little about machine learning. But let’s refresh your memory.
Machine learning is essentially a subset of the greater beast that is Artificial Intelligence; in fact, it’s sort of what makes it intelligent.
But what is Machine Learning exactly?
Machine learning is based on the idea that systems can actually learn from data and identify patterns, which in turn changes to meet the need. It’s what trains the machine how to learn and interpret the data.
Understanding the mechanics behind this smart technology may help promote the adoption of it in business operations – and in construction, you know how tough that adoption process can be.
But we’re here to help.
4 quick facts about machine learning.
- You see machine learning every day. Don’t believe us? Fraud detection, online recommendation offers that you see on places like Amazon, and self-driving cars – all examples of machine learning. And that’s only a few.
- Machine learning is currently used across a variety of industries today, such as oil and gas, health care, retail, and government. Truth is, it’s not just for everyday practicality; it also helps with potential future expansion and knowledge. For example, the wearable devices and sensors health care professionals use actually take data and assess the patient’s health in real-time. In addition, the data that technology collects from patients helps medical experts to create better diagnoses and treatments.
- There are two major types of learning methods – supervised and unsupervised learning. The difference is basically the way it learns and what it’s used for. Supervised learning is told what the correct “answer” is – a test can either pass or fail, for instance. This is commonly used to help identify potential fraud. In unsupervised learning, the machine is not told the right answer and has to use data to determine patterns. This is especially useful in places like marketing so companies know they are targeting similar groups of customers.
- The goal of machine learning is to ultimately help organizations identify more profitable opportunities and reduce risk. By having technology that analyzes data and patterns, companies are able to better predict highs, lows, and the in-betweens. Sas.com says, “By using algorithms to build models that uncover connections, organizations can make better decisions without human intervention.”
So, while not everyone can have a self-driving car, almost everyone could benefit from smart technology in other ways. Our question is: Why should a construction business be any different?