AI vs. Machine Learning: Is There a Difference?

Artificial (AI) and machine learning are increasingly hot topics in business, training, and employment circles.

Proponents believe AI and machine learning can help vastly improve efficiencies within organizations, while many employees fear their jobs may be rendered obsolete by sophisticated new technologies that may be able to mimic functions previously only achievable by humans.

But there are many misconceptions about AI and machine learning, not the least of which includes the idea that they are one and the same. In fact, machine learning is a form of AI. Here, we’ll discuss the distinctions.

Distinguishing Between AI and Learning

AI is a fairly broad term. As noted by Bernard Marr a contributor to Forbes there are many different definitions of AI, but at a fundamental level, we can describe it as the simulation or imitation of intelligent thinking normally found in human beings.

Let’s compare that with machine learning, which Sean Lawlor of Security Sales & Integration describes as “an area of AI that uses to help a computer improve performance without being explicitly programmed.” In other words, the computer “learns” over time as programmers “enable a computer to assess and alter its computational processes through training.”

IBM’s Watson is a popular example of this. Through machine learning, computer systems can not only solve problems but also make decisions and even predictions.

Related but Different

AI and machine learning are clearly related, but they are not the same thing. Machine learning is a subset of the broad range of AI functionality. Although many fear the possibility of being supplanted or rendered obsolete by these tools’ advancements, in reality, these tools can be leveraged to make employees far more efficient and provide them with opportunities to focus on higher-level, more strategic contributions to their organizations.

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