What’s the difference between AI and ML?
Whilst diving into AI and reading up about its uses and applications, you are going to come across a load of jargon — but for those of you who are new to AI, let’s start right at the top with Artificial Intelligence (AI) and Machine Learning (ML). These terms get tossed around a lot, sometimes interchangeably, but they're not identical twins. So, what’s the difference?
Artificial Intelligence (AI): Think of AI as this big umbrella. It's all about creating machines that can tackle tasks we'd normally need a human brain for. That could be anything from making decisions, understanding languages, to, let's say, autonomously navigating a car through city streets.
Goals of AI: To create systems that can learn, adapt, and get better over time. It's not picky about the tools it uses—everything from rule-based systems to neural networks are fair game.
Sub-Fields: AI isn't a one-trick pony. It spans everything from robotics and natural language processing to, you guessed it, machine learning.
Implementation: We’ve got two flavors of AI. "Narrow AI" is that specialist focusing solely on one task, like translating languages. "General AI" is more of a Jack-of-all-trades, aiming to be good at, well, anything a human can do.
Machine Learning (ML): ML is like that smart kid in the class who sits under the AI umbrella but has a knack for one thing: learning directly from data.
Goals of ML: The end game? Enable computers to get better at specific tasks by learning from data, and not from explicit programming.
Methods: ML loves its data. It uses data-driven techniques, be it supervised or unsupervised learning, to train its algorithms.
Sub-Fields: Even within ML, you've got niches like deep learning, which goes all in on algorithms modeled after the human brain.
Implementation: ML thrives on specialisation. Train it with the right data and it excels in that task. But don't expect it to make you coffee—its skills are pretty specific.
So, What's the tl;dr? All machine learning is AI, but not all AI is machine learning. ML is your go-to for anything requiring learning from data, whereas AI covers a broader base, aiming to mimic human-like intelligence and behaviour.
Hope that clears things up.
