As everything else by Lilian Weng, this is a very good no-nonsense overview of the state of LLM-based agents. Highly recommended.
YAML is extremely complex for a configuration format and it has many really weird edge cases:
The problem is IMHO made worse because it looks so friendly at first glance.
- Only on programming.dev, at least in the beginning, but it will be open source so anyone will be able to host it for themselves.
- I set up a hard limit of 100 summaries per day to limit costs. This way it won’t go over $20/month. I hope I will be able to increase it later.
Yes, for a moment you think “oh, there’s such a convenient API for this” and then you realize…
But we programmers can at least compile/run the code and find out if it’s wrong (most of the time). It is much harder in other fields.
Hungarian here. It is safe to drink without boiling. People only boil water for baby formula to be extra safe.
This looks really useful, especially the formulas for Sheets. I tried it on this simple example:
It picked up the pattern perfectly and even the degree symbol didn't confuse it :)
Thank you for sharing this, this looks like something I will use daily!
EDIT: here is the link to the website: GPT for Work
It seems really interesting, thanks for sharing it! I'll definitely check it out.
#1
I started using GPT-4 for summarizing YouTube videos: I download the transcript (there are websites where I can do it but I'm sure it can be automated easily), which I feed into GPT-4 and get a really nice summary.
- There is an example in the body of this post
- Here is the link to the ChatGPT conversation
#2
I implemented documentation querying using a vector store and GPT-3.5 at my day job. Here is a simple example in Langchain's docs.
#3
My wife and I are both huge fans of the "His Dark Materials" trilogy by Philip Pullman. The story of these books starts out in a parallel world where everyone has a "daemon", an animal companion that is the embodiment of part of their soul. What kind of animal a person's daemon "settles" as after puberty reflects their personality. We asked ChatGPT to ask a few questions about our personalities, which we answered, then it determined what kind of animals our daemons would be, and wrote Midjourney prompts to visualize them. This was a really fun game, we enjoyed it a lot!
As AI hype is approaching fever pitch, "Prompt Engineering" has become another buzzword, with an insane amount of guides and tutorials cropping up on the internet. Unfortunately, a large portion of these resources offer little more than cookie-cutter strategies, contributing to a growing skepticism around the term itself.
It's easy to dismiss it as just another fad, but doing so overlooks the genuine engineering behind effective communication with LLMs. This guide shows some strategies that really work and are based on sound principles instead of guesswork by AI-bros compiled into yet another useless infographic.
I hope it will be just as useful to you as it was for me.
You can also use it as a PWA, it will be just like a normal app
The author is here on Lemmy, see their comment on the original post
Here is your Lemmy Gold: