The basic concept of machine learning is teaching computers how to interpret large amounts of information and combine it with repetitive processes to make machines more intelligent. This builds a baseline for detecting things like anomalies and eventually, suggesting corrections. It can happen on a small scale, or to an extreme – the possibilities are endless.
Machines are constantly learning about the different ways we use technology. In essence, we are making them smarter so they can be more effective in our quest for artificial intelligence. Ultimately, to do more with less effort.
Everyday Machine Learning Examples
Let’s talk machine learning with traffic lights. Do you ever notice that during different traffic hours at intersections, your wait time is more noticeable than others? The flow of traffic is regulated by sensor pads in the concrete or cameras in the poles. The timing of how those lights change is set after data is collected on how many cars go through the intersection at different times of the day.
In cities where they have sophisticated technology applied to those intersections, the timing of the traffic lights actually adjusts to the flow of traffic automatically. In rural places or areas with legacy traffic infrastructure, the traffic lights aren’t so smart. You might sit at a stop for 30 seconds longer (or more) than you expect to, and there’s no one else around. This is a prime example of an old algorithm and an old process.
You will also see machine learning with social media – an example most people can relate to. If you start liking pictures of cats, your feed will start suggesting that you look at more pictures of cats. It is constantly learning about your preferences and setting them into practice inside your social applications.
Natural Language Processing
Another fascinating component to machine learning is specific to lingual processing: natural language processing (NLP). NLP allows us to train a machine how to recognize language, but at the same time, teach it how to speak back to us. When you get a new smartphone or a new computer, it may ask you to read several sentences into the computer. The computer is getting smarter and learning how to interpret you personally. It’s also learning how to speak back to you. Over time, you’ll notice the impact of your interactions with the device more frequently.
Machine Learning for Business Operations
You likely have vendors that you pay the same amount every single month. Machine learning allows us to send a message in the finance systems that we implement that will make intelligent suggestions to you. For example, “We see you’ve paid this vendor the same payment three months in a row, would you like to set this up as an auto-pay and have it automatically deducted from the bank so that you don’t have to process any receipts or payments?” Your bank will do that for you. You have phone apps that will do that for you, and it’s just a small piece of business process that saves all of us a ton of time.
Other manual processes within your business operations can be improved dramatically with machine learning-based automation for things like manufacturing/supply chain, human resources, sales/marketing, and other operational components. And, as your organization tries to become more efficient to save time and money, machine learning will start to take on a bigger role.
Arctic IT makes it our mission to help companies build and adapt to machine learning applications that optimize their operations. For a recent business-case scenario, we’re currently deploying Azure Logic Apps for a major county in the Pacific Northwest. These sophisticated, pre-built applications are being put in motion to accomplish data migration and data transformation workflows through machine learning. With Logic Apps, the team has been able to let technology do the work that’s typically done by a software engineer, thereby saving thousands for the county’s project budget.
Technologies like these combine storage, processing, communication, and business services to respond to the needs of your customer or operation.
Ready to take your business to the next level? Contact us today to see where your processes can take advantage of machine learning.