What Is Machine Learning?

Terms like artificial intelligence and machine learning are often used interchangeably, but they refer to slightly different technologies. Specifically, machine learning is a subtype of artificial intelligence.

In this Backstage Pass video, which aired Sept. 27, 2021, Motley Fool contributors Toby Bordelon, John Bromels, Jose Najarro, and Trevor Jennewine share their thoughts on machine learning and how it differs from artificial intelligence.

Toby Bordelon: A lot of people lump this in with artificial intelligence. You'll hear a lot of discussion about artificial intelligence and machine learning, maybe being one of the same. I think there's a little bit of nuance here. What do you think, guys? Let's go round again. I'll just go in the same order because it will be easy. Let's start with Jose. Jose, what do you think of when you think of machine learning?

Jose Najarro: When I think of machine learning, I think it's more of a subset of artificial intelligence. It's just the ability of that. I guess the word I used previously of learning was the wrong one, it's more like critical thinking within artificial intelligence. The machine learning is more of a subset where it allows that artificial intelligence to learn, either being some way a supervised or unsupervised method.

Toby Bordelon: Cool, thanks. All right, John, what are your thoughts? Machine learning.

John Bromels: Seeing an after all of that, I was leaning more toward that Jose was right on the last one. I think Jose and I are moving toward one another in terms of settling on a definition. But yeah, I feel machine learning is more of that learning processing, self-correcting idea, whereas artificial intelligence, yes, definitely has an iterative, figuring things out step but I feel like machine learning has this critical aspect of being able to either guided by a human or just self navigate through a learning process, I guess is a good way to put it.

Toby Bordelon: Okay. Thank you. What about you, Trevor? Machine-learning, what do you think?

Trevor Jennewine: I think they had it. I think this is where the learning comes into play. I kind of picture it as software that gets smarter over time, either by human example or just of its own accord. It's able to rewrite itself and make itself more precise over time.

Toby Bordelon: Okay.

John Bromels: Whether it get's smarter over time is a great concise way of putting that. I wish I had that power of gravity.

Toby Bordelon: [laughs] I think that's right. Let's look at an official definition, or I don't want to call this an official definition, but a definition I found from an authority. Let's put it that way. This is from IBM. Again, think Deep Blue right, think about the chess games IBM has been engaged in machine learning. It's very public ways. What they're telling us, is that machine learning is a branch of artificial intelligence, so like Jose said, maybe like a subfield of artificial intelligence and computer science, which focuses on the use of data and algorithms to imitate the way humans learn, gradually improving its accuracy. Subset of AI, where I can use the data and algorithms to gradually improve its accuracy to learn, and the key there I think, is imitate the way humans learn.

You can think of a lot of things. You can think of video games do this well in terms of scaling what they give you to how well the user is doing potentially. There's a lot of software using education that scales to the level of the student. Whether that is actually the program learning as humans learn, or are they just using a preset algorithm to say with this so, when you get X number of questions right, present this next group of questions. That's not machine learning that we're talking about, that's already pre-programmed in there. To truly be machine learning, I think the way all of you have you have suggested too, is you've got to somehow learn in a way that wasn't necessarily programmed, and you had to adapt ourselves to something that's beyond the original program. Adapting as you say taken data. Maybe it is a little bit of a higher level than we are thinking. The other word I gravitate there is imitate the way humans learn not learning exactly the way we learn, but it's some sort of imitation. I think that's a nuance that people can think about.