LLMs
sari and
LLMs
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://t.co/1nctiAIuGO https://t.co/VpjnY2NcpM
riley tomasektwitter.comMarch 2023 AI Overview for Boards
docs.google.comnice overview of why every company needs an AI strategy
LLMs are mid. It does a good job at getting the average and this is useful in many areas where this is tough. When you want "good", LLMs let you down. We underestimate the impact doing things to a "mid" level will have on the world.
"A key challenge of (LLMs) is that they do not come with a manual! They come with a “Twitter influencer manual” instead, where lots of people online loudly boast about the things they can do with a very low accuracy rate, which is really frustrating..."
Simon Willison, attempting to explain LLM
Embeddings: What they are and why they matter
simonwillison.net
Weird GPT token for Reddit user davidjl123, “a keen member of the /r/counting subreddit. He’s posted incremented numbers there well over 163,000 times. Presumably that subreddit ended up in the training data used to create the tokenizer used by GPT-2, and since that particular username showed up hundreds of thousands of times it ended up getting
... See moreMeta 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.