How AI Works. An entirely non-technical explanation of LLMs by Nir Zicherman, January 29, 2024. “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.”