Historical analogies for large language models

A very common trope is to treat LLMs as if they were intelligent agents going out in the world and doing things. That’s just a category mistake. A much better way of thinking about them is as a technology that allows humans to access information from many other humans and use that information to make decisions. We have been doing this for as long a... See more

Like all machine learning, LLMs turn a logic problem into a statistics problem: instead of people writing the pattern for each possible question by hand, which doesn’t scale, you give the machine a meaningful sample of all the text and data that there is and it works out the patterns for itself, and that does scale (or should do). You get the machi... See more

Using LLM products today feels a lot like using early cars in the 1800s: clearly magical, clearly going to change the world, and really hard to drive.

The first cars didn’t have steering wheels (they hadn’t been invented yet), so you’d steer them with a big lever called a tiller. The problem with tillers is that they are imprecise, which made drivin... See more