Artificial Intelligence vs. Machine Learning: Key Differences in Intelligent Technology

Posted October 22, 2019

In Blog, Cloud Service Providers, Managed IT Service Providers, Managed IT Services, Managed Network Services, Managed Service Provider, Managed Services

Often, the terms Artificial Intelligence and Machine Learning are used interchangeably. In reality, Machine Learning is actually a subset of the larger umbrella of AI.

In the same way that all squares are rectangles, but not all rectangles are squares, there are other varieties of Artificial Intelligence that aren’t necessarily Machine Learning.

To help clear up the confusion, we’ll explore both as individual practices of computer science, as well as the ways that they interact with each other. Let’s dive in.

Artificial Intelligence

In an article on the past and future of AI, computer scientist John McCarthy defined it in this way: “It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence.”

When the idea of Artificial Intelligence first hit the tech scene at the 1965 Dartmouth Conference, McCarthy led the charge, fulling believing that computers could become capable of understanding abstract thought and reasoning in much the same way that humans are able to.

What we understand as AI today is teaching a computer anything that it wasn’t capable of doing before. By feeding in algorithms and rules, the computer can create, sort, and report new information based on the data it’s been given.

For that reason, many people don’t really consider AI as “intelligent” at all, saying that the concept of intelligence is uniquely human. Computers aren’t (yet) capable of performing processes that are entirely distinctive to the machine. They must work within the confines of the structure and data that we provide.

Machine Learning

Under the overarching concept of AI is Machine Learning. With ML, your computer is able to adapt and enhance performance based on nuances in the user’s input.

A great example is Clippy, the old Microsoft Word mascot who would adapt its reactions to key parts of a document you were typing. If your first words were “To Whom It May Concern,” Clippy’s algorithm might suggest tips on writing a letter. If you were listing out job experience, it might offer you a resume template.

If you watch any streaming services, like Netflix or Hulu, use autocorrect on your phone, or let iTunes compile a list of songs you might like, you’re using machine learning. Based on your input, the algorithms provided to that particular service by the developers is able to offer you a more customized experience.

Why should businesses care about AI and ML?

Many companies can use both to provide themselves and their customers with an optimized interface or product. Loading demographic data into a trend-finding program can help you make better marketing decisions. Data on cyber attacks helps your security suite predict and eliminate potential threats. Even the ability to set up chat bots through your social media is a valuable product of technology’s advancements in computer intelligence.

At Verus, we work with AI to keep business networks secure.

WatchGuard Fireboxes use AI to detect zero day attacks at the network perimeter. It uses sophisticated Machine Learning to predict when, where, and how attacks are going to happen based on data about past attempts to breach the network.

Sophos Anti-Virus uses a deep learning neural network at the host level to protect users from threats. It is able to detect both known and unknown malware without relying on signatures, which can be unreliable in identifying possible threats.

Finding ways to implement AI successfully is becoming more and more necessary as customers seek a more personalized way to interact with their technology.

Kyle Vinar

Kyle Vinar is Partner / President of Verus Corporation. He oversees all business operations and coaches Verus teams to continually improve on their solutions from client experience to product development and overall solution implementation. He works with all Verus resources to increase efficiencies and excellence in every aspect of their organizational roles. Kyle believes that people are the last real competitive edge that a company can have and constructing a rich culture is a vital step in running a world-class organization. Therefore he strives to create a culture within Verus that allows everyone to show up authentically and grow both personally and professionally, which in turn allows Verus Corp team members to provide clients with top-of-the-line service. Kyle helps balance strategy, capacity, and culture in such a way that has allowed Verus Corp to achieve exponential growth since he joined the company in 2013. One of Kyle’s greatest professional achievements has been in helping lay the foundation upon which Verus Corporation could be named the 2nd Best Place to Work by the Minneapolis/St. Paul Business Journal. Kyle holds a Bachelor of Science in Marketing from St. Cloud State University. He lives in Champlin with his wife and 3 children. He has enjoyed volunteering as a soccer coach for over 6 years and was the former Director of Coaching for Rebels Soccer Club. If Kyle isn’t on the sidelines of one of his children’s soccer games or in the audience of his eldest’s musicals, he can often be found cruising scenic routes on his Harley, in a deer stand, or on the golf course.