I’ve got two useful AI tidbits for you this month:
The first is the best explanation of how large language models work. This is a pretty opaque topic that few attempt to understand, but I think it’s important to grasp – even in metaphor – how systems like ChatGPT work. When you understand how they work, your intuition for the types of problems they can – or can’t – solve is much better.
I started writing my own explanation for you, but then The Every sent out something so excellent I wasn’t even going to try to beat it:
"For all the talk about AI lately—its implications, the ethical quandaries it raises, the pros and cons of its adoption—little of the discussion among my non-technical friends touches on how any of this stuff works. The concepts seem daunting from the outside, the idea of grasping how large language models (LLMs) function seemingly insurmountable.
But it’s not. Anyone can understand it. And that’s because the underlying principle driving the surge in AI is fairly simple.
Over the years, while running Anchor, leading audiobooks at Spotify, and writing my weekly newsletter, I’ve had to find ways to distill complicated technical concepts for non-technical audiences. So bear with me as I’ll explain—without a single technical word or mathematical equation—how LLMs actually work. To do so, I’ll use a topic we all know well: food. In the analogy to LLM, “dishes” are words and “meals” are sentences. Let’s dive in."
Have you seen our new Handwritten Text Recognition Sandbox? It’s a FromThePage project designed to let you explore how different types of documents, languages and models work for AI generated text. Have organizational leaders or patrons who say “let’s just get it OCRed?” without knowing the limits of technology? The HTR Sandbox is a great place to demonstrate the technology’s quality (and lack thereof) in a visible, hands-on way.