Artificial Intelligence vs Machine Learning: the Key Differences

If you’re starting to familiarise yourself with the burgeoning world of AI research, then you might have come across two terms, the meaning of which might appear to be interchangeable. The first is ‘Artificial Intelligence’; the second or ‘Machine Learning’.

What these terms mean is hugely important, so it’s worth dwelling on the distinction between them.

What is AI?

While we all might think we have an intuitive grasp of what AI is, actually spelling it out is quite difficult. A number of competing definitions have been developed since the 1950s when Alan Turing developed his famous test. But for the most part, intelligence is something that’s capable of goal-oriented decision-making. Artificial intelligence is a machine that’s able to do this.

AIs come in different forms. A narrow AI is something that is very good at doing one particular kind of thinking. You might look at the calculator on your phone, which can perform arithmetic with superhuman speed and accuracy. Then there’s broad AI, which can do several different things – you might think of your voice assistant, which can not only recognize your commands, but also execute them by booking appointments, setting timers, and placing orders.

What is Machine Learning?

Machine learning is one process via which artificial intelligence can be created and refined. The most popular kinds use a kind of Darwinian approach, with hundreds of interactions progressively refining an algorithm using training data. The program is varied slightly with each iteration, and the variations which can perform the task better are allowed to form the basis for the following generation.

So, for example, we might develop machine intelligence that can race a virtual car around a virtual track: the cars that progress furthest, fastest, are taken and used to create a new generation of virtual cars, and in this way, the program is refined.

Human beings or unsupervised can supervise machine learning. Machine learning is a major component of attention-retaining websites like Youtube, Facebook, and Tiktok. The machine is constantly experimenting with users, and learning which psychological buttons to press. It’s for this reason that you might get different thumbnails on Netflix for your friends.

What makes one different to the other?

If you’re struggling with the difference, it’s easy to just remember that machine learning is just one variety of AI. You’ll find other terms within the category of machine learning, too, like ‘deep learning’. To develop the sophisticated AIs of the future, software companies might well use a form of machine learning – but they might equally use any number of other techniques since machine learning has drawbacks that can be offset by other approaches.

If you’re struggling to understand how modern AI technology might benefit your company, or how it might expose you to unforseen risk factors, then it might be worth bringing in professional help from specialised tech solicitors.


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