‘Things We Learned About LLMs in 2024’

Simon Willison:

A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past twelve months, plus my attempt at identifying key themes and pivotal moments. [...]

I think telling people that this whole field is environmentally catastrophic plagiarism machines that constantly make things up is doing those people a disservice, no matter how much truth that represents. There is genuine value to be had here, but getting to that value is unintuitive and needs guidance.

Those of us who understand this stuff have a duty to help everyone else figure it out.

Nobody is doing a better job of that than Willison. I learned so much from reading this piece — I bet you will too.

Update: Anil Dash:

I think everyone who has an opinion, positive or negative, about LLMs, should read how @simonwillison has summed up what’s happened in the space this year. He’s the most credible, most independent, most honest, and most technically fluent person watching the space.

Couldn’t say it better myself.

★ Thursday, 2 January 2025