Large Language Models (LLMs)
sari and
Large Language Models (LLMs)
"the best use case of LLMs is bullshit"
Meanwhile, LLM results are probabilistic. 10 blue links are also probabilistic, but Google is giving you options - adding human curation by making you pick from a list of results. Using an LLM result is more like hitting ‘I’m feeling lucky’ - it requires more confidence
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
People are intrigued by LLMs’ ability to generate new text, change styles, and generally chat. While impressive, turning text written in one style into text written in your own voice (or into legaleze) is essentially taking unstructured data and turning it into more unstructured data. I’m surprised about the lack of attention to doing the exact opp... See more
Matt Hartman • The power of AI is its ability to turn unstructured data into structured data
An Interview With Daniel Gross and Nat Friedman about the Democratization of AI
Ben Thompsonstratechery.com
@RamaswmySridhar: 1/ AI exploded on the scene at the end of 2022, with applications like @OpenAI's ChatGPT taking the world by storm.
2023 is poised to be the most exciting year of AI yet! 🎉
Here's mine and @vivek7ue's look at the lay of the land + what might happen next...
👀🧵
I've learned so much from @hubermanlab, but podcasts make recall and discovery challenging.
Huberman AI uses the latest models from @openai to search every episode with Google-level accuracy and summarize the results.
https://huberman.rile.yt