As Lineal points out in their latest post, “AI is having a moment.” That’s for sure! 😉 And it’s why their short history of AI puts it into perspective.

The post, titled (wait for it!) A Short History of AI: Why LLMs Aren’t the Whole Story (available here), discusses that the rise of generative AI has transformed how we think about technology. Large Language Models (LLMs) like ChatGPT can summarize, draft, and classify text in ways that seemed impossible just a decade ago.

But while LLMs feel brand new, they’re the latest chapter in a much longer story. AI has gone through multiple eras, each building on the last. And here’s the key: those older approaches? They’re still incredibly useful today—sometimes even faster, cheaper, or more reliable than the newest models.

To make this concrete, they use a simple example: document classification. Imagine you’ve got thousands of documents, and you need to sort them into two piles: finance vs. manufacturing. How have computers tackled this task over the decades? Lineal takes us through four “eras” from the 1950s to present day.

So, what are the four eras? And why can’t we simply use LLMs for everything? Find out here, it’s only one click! It will amplify your intelligence about artificial intelligence! 😉

So, what do you think? How much of the short history of AI did you know about? Please share any comments you might have or if you’d like to know more about a particular topic.

Image created using Microsoft Designer, using the term “robot lawyer looking through a large history book with lots of pages”.

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