LLMs
sari and
LLMs
“The fact that these things model language is probably one of the biggest discoveries in history. That you (LLM) can learn language by just predicting the next word … — that’s just shocking to me.”
- Mikhail Belkin, computer scientist at the University of California
There is so much more structure in the world than we tend to believe. And LLMs and other AI models are structure discovery machines.
People need to be more thoughtful building products on top of LLMs. The fact that they generate text is not the point.
Linus Leestream.thesephist.comI'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
Riley Tomasektwitter.comMeanwhile, 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
NFX’s Generative Tech Open Source Market Map
docs.google.comThere’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
