Artificial Intelligence vs Machine Learning: Should Investors Care About the Difference?

Key takeaways

• Artificial intelligence and machine learning are often used interchangeable, but they don’t mean exactly the same thing
• Artificial intelligence is basically the catch all term for any form of computer science that involves getting a computer to do something a human usually would
• Machine learning on the other hand, is a subset of artificial intelligence designed around getting a computer to do tasks it wasn’t specifically programmed for
• For investors, the difference doesn’t really matter, it’s all about how much value the tech brings to the world

Lately we’re hearing about AI from every corner of the internet, from chatbots to cloud computing to cars to investing, it seems like just about every type of tech is trying to integrate AI into it.

More than that, it’s in danger of becoming a buzzword. Not because the underlying tech isn’t game changing (it is), or because there aren’t a massive number of real world use cases right now (there are), but as we’ve seen before, the Gartner hype cycle can blow even the most exciting innovations out of proportion.

We only need to look at the dotcom bubble to see the perfect example. The internet went through a period of massive hype, culminating in a huge crash and billions of value being wiped out.

Did that mean the internet was a fad? Clearly not. So where does AI and machine learning fit into this, and does the difference between the two terms mean anything for investors?

Artificial intelligence vs machine learning

Broadly speaking, artificial intelligence is the catch-all term for the field of computer science that aims to have machines do tasks which usually require the intelligence of a human. Setting aside the question of what level of ‘human intelligence’ we’re talking about, it’s essentially the overall category of computer science.

Within the overall category of artificial intelligence are a number of different subcategories. Machine learning is one of these, with some other examples areas like robotics, neural networks and speech recognition.

The idea behind machine learning is that it allows a computer to do tasks that it wasn’t explicitly programmed to do. So, for example you could have a robot which has been specifically programmed to pick up a box from Point A and drop it at Point B while navigating a warehouse full of people of equipment.

That navigation would be a form of artificial intelligence. Machine learning is the ability to allow that same robot to learn new tasks without those having to be specifically programmed.

The bottom line

The difference between artificial intelligence vs machine learning doesn’t really matter for investors. As with most things, there is a lot of crossover between the different fields of artificial intelligence, with much of the tech we use daily working across many of these different subcategories.

For investors and shareholders, the important thing is what value this technology derives. And that is the fundamental question with AI. Investors need to be able to look past the buzzwords and flashy presentations to see the day to day use cases of the tech.