Large Language Models (LLMs)
sari and
Large Language Models (LLMs)
An Interview With Daniel Gross and Nat Friedman about the Democratization of AI
Ben Thompsonstratechery.com
Embeddings: What they are and why they matter
simonwillison.net
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
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
Meta AI released LLaMA ... and they included a paper which described exactly what it was trained on. It was 5TB of data.
2/3 of it was from Common Crawl. It had content from GitHub, Wikipedia, ArXiv, StackExchange and something called “Books”.
What’s Books? 4.5% of the training data was books. Part of this was Project Gutenberg, which is public dom
“A more practical answer is that it’s a file. This right here is a large language model, called Vicuna 7B. It’s a 4.2 gigabyte file on my computer. If you open the file, it’s just numbers. These things are giant binary blobs of numbers…”
Simon Willison, attempting to explain LLM
