sisyphean

joined 2 years ago
MODERATOR OF
[–] sisyphean@programming.dev 12 points 2 years ago (1 children)

Here is your Lemmy Gold:

Lemmy Gold

[–] sisyphean@programming.dev 1 points 2 years ago

As everything else by Lilian Weng, this is a very good no-nonsense overview of the state of LLM-based agents. Highly recommended.

[–] sisyphean@programming.dev 6 points 2 years ago* (last edited 2 years ago)

YAML is extremely complex for a configuration format and it has many really weird edge cases:

https://noyaml.com/

The problem is IMHO made worse because it looks so friendly at first glance.

[–] sisyphean@programming.dev 2 points 2 years ago (4 children)
  1. 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.
  2. 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.
[–] sisyphean@programming.dev 1 points 2 years ago

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.

[–] sisyphean@programming.dev 3 points 2 years ago* (last edited 2 years ago)

Hungarian here. It is safe to drink without boiling. People only boil water for baby formula to be extra safe.

[–] sisyphean@programming.dev 5 points 2 years ago* (last edited 2 years ago) (1 children)

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

[–] sisyphean@programming.dev 1 points 2 years ago

It seems really interesting, thanks for sharing it! I'll definitely check it out.

[–] sisyphean@programming.dev 6 points 2 years ago* (last edited 2 years ago)

#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.

#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!

[–] sisyphean@programming.dev 8 points 2 years ago* (last edited 2 years ago)

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.

[–] sisyphean@programming.dev 3 points 2 years ago

You can also use it as a PWA, it will be just like a normal app

[–] sisyphean@programming.dev 3 points 2 years ago (5 children)

The author is here on Lemmy, see their comment on the original post

 

cross-posted from: https://programming.dev/post/119195

AI isn’t magic, of course, but what this weirdness practically means is that these new tools, which are trained on vast swathes of humanity’s cultural heritage, can often best be wielded by people who have a knowledge of that heritage. To get the AI to do unique things, you need to understand parts of culture more deeply than everyone else using the same AI systems.

 

AI isn’t magic, of course, but what this weirdness practically means is that these new tools, which are trained on vast swathes of humanity’s cultural heritage, can often best be wielded by people who have a knowledge of that heritage. To get the AI to do unique things, you need to understand parts of culture more deeply than everyone else using the same AI systems.

 

Prompt:

open source, federated software connecting free people across the globe, without commercial interest --q 2 --v 5.1
 

TL;DR (by GPT-4 🤖):

  • The author reminisces about life before the ubiquity of cellphones and the internet, particularly focusing on the after-work hours.
  • The concept of being unreachable after work hours is alien to younger generations who are constantly connected and expected to be available at all times.
  • The author and his peers recall the days when work emails didn't exist, and work communication was restricted to work hours only.
  • The article highlights how the growth of remote work and the pandemic have blurred the boundaries between work and personal time, with a survey suggesting that U.S. workers were logged into their employers' networks 11 hours a day in 2021, up from 8 hours pre-pandemic.
  • The author interviews people of his age group about their experiences around 2002, when they were about 27 years old. They recall waking up just in time for work, commuting with newspapers or books, and using work phones for personal calls.
  • After work, they would engage in activities like swing dancing, improv classes, or simply visiting friends. Plans were made over the phone or via work email, and people were less likely to flake as there was no option to send a last-minute text.
  • They recall the days of watching whatever was on TV, renting movies from Blockbuster, and playing games on their desktop computers.
  • The article concludes with a reflection on how different life was before the internet and cellphones became a constant presence in our lives.
 

cross-posted from: https://programming.dev/post/115656

Quote from the article:

And the terrible, horrible thing about it is THIS IS A GOOD LETTER. It is better than most letters of recommendation that I receive. This means that not only is the quality of the letter no longer a signal of the professor’s interest, but also that you may actually be hurting people by not writing a letter of recommendation by AI, especially if you are not a particularly strong writer. So people now have to consider that the goal of the letter (getting a student a job) is in contrast with the morally-correct method of accomplishing the goal (the professor spending a lot of time writing the letter). I am still doing all my letters the old-fashioned way, but I wonder whether that will ultimately do my student’s a disservice.

 

cross-posted from: https://programming.dev/post/85783

OP actually went to the café as a joke but GPT-4 didn’t show up.

 

Original tweet by @emollick: https://twitter.com/emollick/status/1669939043243622402

Tweet text: One reason AI is hard to "get" is that LLMs are bad at tasks you would expect an AI to be good at (citations, facts, quotes, manipulating and counting words or letters) but surprisingly good at things you expect it to be bad at (generating creative ideas, writing with "empathy").

 

I didn't cross-post because the comments are also interesting.

 

cross-posted from: https://programming.dev/post/102011

We discover that DALLE-2 seems to have a hidden vocabulary that can be used to generate images with absurd prompts. For example, it seems that Apoploe vesrreaitais means birds and Contarra ccetnxniams luryca tanniounons (sometimes) means bugs or pests.

 

cross-posted from: https://programming.dev/post/107386

From the article:

symbex inspect_hash | llm --system 'explain succinctly'

Output:

This function calculates the hash of a database file efficiently by reading the file in blocks and updating the hash object using SHA256 algorithm from the hashlib module. The resulting hash value is returned as a hexadecimal string.
 

Quote from the article:

And the terrible, horrible thing about it is THIS IS A GOOD LETTER. It is better than most letters of recommendation that I receive. This means that not only is the quality of the letter no longer a signal of the professor’s interest, but also that you may actually be hurting people by not writing a letter of recommendation by AI, especially if you are not a particularly strong writer. So people now have to consider that the goal of the letter (getting a student a job) is in contrast with the morally-correct method of accomplishing the goal (the professor spending a lot of time writing the letter). I am still doing all my letters the old-fashioned way, but I wonder whether that will ultimately do my student’s a disservice.

view more: ‹ prev next ›