AI is one of the biggest and most all-consuming zeitgeists I've ever seen in technology. I can't even search the internet without being served several ads about potential AI products, including the one that's still begging for permissions to run my devices. AI may be everywhere we look in 2025, but the kind of neural networks now associated with it are a bit older. This kind of AI was actually being dabbled with as far back as the 1950's, though it wasn't until 2012 that we saw it kick off the current generation of machine learning with AlexNet; an image recognition bot whose code has just been released as open source by Google and the Computer History Museum.
We've seen many different ideas of AI over the years, but generally the term is used in reference to computers or machines with self learning capabilities. While the concept has been talked about by science-fiction writers since the 1800's, it's far from being fully realised. Today most of what we call AI refers to language models and machine learning, as opposed to unique individual thought or reasoning by a machine. This kind of deep learning technique is essentially feeding computers large sets of data to train them on specific tasks.
