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Artificial Intelligence vs Machine Learning: What’s the Difference?

September 23,2020

Artificial intelligence and machine learning are extremely hot topics in tech right now, as they help us live easier lives across several industries. How are they connected and what place do they have in our daily routines?

What's the difference between artificial intelligence and machine learning?

It’s unlikely you’re going to go home from a party in the Silicon Valley without hearing these terms at least once. These hot tech topics are closely related and often used interchangeably by people who don’t work with them directly. However, they’re actually a bit distinct and it’s important to understand this if you decide to pursue a project in either.

Artificial Intelligence (AI) is a broader concept that refers to mechanical systems, such as a mobile app, that can reason the way humans do to carry out the decisions we make for us. It’s the mechanism behind Siri or Alexa responding to your questions the way a human would. It’s how Netflix predicts you’ll like its fantasy series Cursed after you’ve binged The Witcher multiple times. 

AI is designed with the goal to mimic human intelligence, so the better it’s executed, the more human-like the system’s response is. Remember Cleverbot from the early 2010s? That was an earlier version of AI that we’ve made some progress from.

Machine learning (ML) is one type of AI that allows the machine to learn from data on its own. It uses an algorithm to process the historical and current data it’s fed. Success in an AI system using ML depends on using accurate algorithms and properly representative, unbiased data. A well-known app where ML is the star of its operations is Pinterest, which uses it to figure out what existing content to curate for you based on your profile and past app activity.

So everything ML counts as AI, but not all AI counts as ML. 

One prominent way that ML differs from other forms of AI in that it automatically adapts to the data you feed it. This means it doesn’t require as much human intervention. Think of it like how you, a human, might change your opinions or decision-making habits after learning new information. ML is behind the mechanisms that allow apps to detect the tone of the email you’re writing. 

In order for ML to function, extensive artificial neural networks need to be built using complex mathematical equations. That refers to a computer system set up similarly to a human brain. This complexity allows it to make its own statements and decisions like how you would. Aside from curating content you’ll probably like on Pinterest and Netflix, some of these decisions include offensive content warnings and tips specifically customized for you. For example, it’s the mechanism behind how language-learning app Duolingo figures out when you need a refresher on those German verbs you learned last month based on your past behavior.

Something called deep learning is an important subset of ML. Deep learning refers to the usage of deep artificial neural networks that make decisions on more abstract, visual concepts such as image recognition, sound recognition, and natural language processing. Sound recognition is how apps like Shazam can tell you the name of the song you’ve heard play 30 times in the local grocery store just from you recording it for a few seconds. Natural language processing allows a system to understand everyday human speech and is how Siri can answer some of your weirder questions beyond “what is today’s weather” and “why is the sky blue”. 

AI and ML together are dramatically advancing our everyday lives and our societies by helping us with more repetitive tasks and decision making. Hand-in-hand, they’re helping us run businesses through chatbots and evaluating the quality of our leads, filtering out spam in our emails and Facebook feeds, letting you know your email to your coworker sounds pretty angry, and helping find a photo of a restaurant’s menu on Yelp when there’s no order button, or an official website is nowhere to be found. 

We’ve had a great time helping our clients build AI systems using ML and aren’t stopping anytime soon. We’ve built apps that have automated so much of our client’s workload. While AI generally isn’t quite as nuanced as human brains yet, it’s the goal we’re striving for. 

So contact us if you think some AI could help out your business and stay tuned on this blog to learn more about the wonderful ways it can liven up your business.