2 min readArtificial intelligence (AI) and machine learning (ML) are hot industry terms right now, and for good reason. Data is widely considered the new global currency, and the most effective personalization and marketing strategies leverage AI and/or ML fueled by quality data insights. In fact, industries including retail, financial services, healthcare, and manufacturing make up more than half of the global compound expenditure in AI. That investment is expected to reach nearly $60B dollars by 2021.
In previous posts, SoftServe clarified the difference between distributed ledger technology (DLT) and blockchain—two terms that, like AI and ML, are often incorrectly used interchangeably. With the growing reliance on artificial intelligence and machine learning, it may be helpful to differentiate between the two here as well.
First, there are two classifications of A I: applied and general.
Applied vs general AI
If artificial intelligence refers to devices designed to act intelligently, then applied AI is task-specific application of that intelligence, especially in the context of industry such as automated trading in financial services, or autopilot functionality in flight. In other words, it is technology designed to make an individual’s work easier and more efficient.
General AI is a broader term that refers to technology that applies to much of the exciting advancements being made today. It is what experts like SoftServe are referring to when touting the merits of AI potential. In particular, it relates to the potential for machines to take over repetitive tasks, to perpetually learn from interactions, and then optimize and personalize accordingly.
Machine learning
Machine learning is a subset of general AI, but without question it is the most central and relevant application of artificial intelligence today. From Google Search to Amazon recommendations, consumers rely on machine learning every day, even if most don’t realize it. In fact, Gartner predicts that by 2020, 85% of customer interactions will be managed without a human.
What to remember for your next meeting or mixer
The next time someone uses AI and ML as synonyms, innovation IQ points will be available to the one who can confidently say:
“Actually, AI refers to intelligences designed to make the machines we use smarter, whereas machine learning refers to a state-of-the-art application of AI that empowers machines to learn for themselves.”
Just be sure to be as human as possible and use the proper tone and hand gestures when saying it.
Learn how SoftServe empowers our clients to leverage big data, AI, and ML to drive smarter and more personalized experiences, check out our latest white paper, "Earn Fan Loyalty with Personalization 2.0".