Apr 07 2017

What's the difference between Artificial Intelligence and Machine Learning?

by Bret Waters

Brainsy

Part of my job at Tivix is to track current trends in the marketplace and understand how the various trend lines are likely to come together. In my recent conversations with corporate executives in the US and Europe, the terms "Artificial Intelligence (AI)" and "Machine Learning (ML)" get tossed around with great excitement, as it's clear to everyone that these are definitely powerful trends which are likely to drive transformation in several different ways. 

But I've also noticed that AI and ML are terms that sometimes get used interchangeably, so I thought it might be helpful here to attempt to make a distinction between the two. 

Artificial Intelligence is a term that is pretty much self-explanatory: it's the notion that we can create machines that appear to have intelligence on their own. But for the most part the machine's intelligence is limited to what we programmed into it. (My porch light is "intelligent" because it knows to turn on at dusk and off at dawn. But it will never learn anything beyond that).

Machine Learning is software (or a "machine") that actually has the ability to learn. And that has the potential to take Artificial Intelligence to a whole different level.

Part of what is driving ML is the explosion of data ("Big Data" is another hot buzzword these days). With the sheer volume of data that's available, the power of writing software that can consume that data and learn from it (Machine Learning) is enormous. When you use a navigation app such as Waze on your phone, it's using AI to determine the best route for your drive, and it's using ML to learn your usual driving patterns, learn what times of day the traffic on your usual routes is unusually heavy. It's the combination of those two things that makes it so powerful. 

Tivix has built platforms that are examples of both AI and ML. We helped to build Codalab, a platform for the world's leading data scientists to build and test machine learning code, and we've built several FinTech projects that use built-in intelligence to streamline financial services processes and underwriting decisions. 

There are a lot of interesting trends right now. Pretty much every executive I talk with today gets very excited about how AI and ML are going to come together to bring big changes to their enterprise. It will be interesting to see how it all plays out. 

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