Stay in The Know: Differentiating Machine Learning and AI

When you look at the words “machine learning” and “artificial intelligence” devoid of context, they could seem like alien concepts – something for only Elon Musk and NASA to worry about, not for us regular mortals.

When you learn what they mean, though, it becomes easier to see how simple they are, and how ubiquitous.

We come into contact with AI and ML every day, so it’s only fitting that we learn to differentiate between them.

What is AI?

Artificial intelligence, in its most simple sense, comprises any abilities given to technology that renders it “smart”, like humans are.

When you break this down further, it translates to any code that allows a machine to adapt, learn, and grow its own skills, without much intervention from us. A machine with AI can do uniquely human things like “sense”, “recognize”, “evolve”, and “solve”.

But Isn’t that the Same as Machine Learning?

Not exactly.

Machine Learning is extremely connected to AI.

If AI-enabled machines are the goal, ML is a tool that brings us closer to making that goal a reality.

Machine Learning comes under AI’s broad umbrella, but it’s specific. It relates only to the aspect of utilizing code for data processing in order to make certain decisions and elicit certain reactions.

Machine Learning is everywhere. Google uses it to understand your web surfing and search preferences. Netflix uses it to show you the kind of movies and shows you’d like, based on what you’ve already watched. Facebook uses it to show you ads that you might actually click on, based on your interactions with other Facebook pages and posts.

While ML is aimed toward accuracy, i.e. the device learning how to perform one task exceedingly well, AI is aimed toward wider success at stimulating natural intelligence and making optimal decisions.

How Does a Machine Learn?

Like humans do, through training, and using a brain.

Training, when it comes to machines and AI programs, takes the form of feeding them vast amounts of data. And the brain, in this case, is a neural network of coded pathways that are designed to process this data, learn from it, and then make predictions based on it.

Once the process of Machine Learning has been successfully set in motion, Artificial Intelligence comes in to get the job done. The AI uses what has been learnt through Machine Learning and applies it to executing real tasks and solving actual problems.

To properly understand why it’s important to know all this, we have to look to the future.

As of now, narrow Artificial Intelligence is in almost every piece of technology we use. Our apps, sites, social media platforms, and streaming services, and video games all use it. Even appliances are beginning to incorporate it, so that, for example, your coffee maker could learn when you like your coffee and how strong you like it, and make it without you having to enter the specifications yourself. Alternatively, your car could take data from your Google Maps and learn the routes you usually take every day.

Narrow Artificial Intelligence is easier to understand, since it only deals with systems and applications being equipped to constantly learn, adapt, and improve their abilities within a narrow field of tasks. There wouldn’t be any use in your AI-enabled coffee maker also learning how to perfectly reproduce famous paintings, for example.

What the future holds, however, is generalized AI, which is more human-like. Computers with generalized AI would learn and grow their own intelligence in order to solve complex problems in a number of verticals. Machine Learning would help such AI devices and applications process data from multiple sources, and learn how to predict, react, and execute a whole range of tasks autonomously or with minimal human intervention.

As a society, we’re quite far from the reality of generalized AI. But we’re making huge strides toward this reality every year. In the meantime, it’s up to us to make sure that we’re well-informed enough to be ready for a world that’s run by AI-enabled technology.

In response to this trend, businesses are growing their arsenal of AI tech. Given the efficiency, cost cutting and predictive abilities this technology can provide, it is no surprise that AI is increasingly popular in various verticals. If you want to get explore AI solutions for your organization, contact us to find out how AI can elevate your business.

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