LLMs
sari and
LLMs
March 2023 AI Overview for Boards
docs.google.comnice overview of why every company needs an AI strategy
#ai #llms #transformers #stanford #genai | Eduardo Ordax | 89 comments
linkedin.com
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
One way to think about (LLM) is that about 3 years ago, aliens landed on Earth. They handed over a USB stick and then disappeared. Since then we’ve been poking the thing they gave us with a stick, trying to figure out what it does and how it works.
There’s a lot of hype around AI, and in particular, Large Language Models (LLMs). To be blunt, a lot of that hype is just some demo bullshit that would fall over the instant anyone tried to use it for a real task that their job depends on. The reality is far less glamorous: it’s hard to build a real product backed by an LLM .
Phillip Carter • All the Hard Stuff Nobody Talks About When Building Products With LLMs
An Interview With Daniel Gross and Nat Friedman about the Democratization of AI
Ben Thompsonstratechery.com
