Tagged “llms”
GGUF, the long way around
infinite backrooms
Tweet generator
MMAcevedo
short story about rights of brains, in the form of a wikipedia article from the future
Globe Explorer
AI-powered topic-centric link explorer
Better Call GPT, comparing LLMs to Lawyers
Great title, interesting study, though unsurprising that they can read contracts faster.
Ask HN: what have you built with LLMs?
Great response with some voice-powered code/automation things.
Relatedly, the killer case is summarization.
Current ChatGPT system prompt
no particularly magic prompts or phrases. Just a lot of specific instructions.
Detecting the secret cyborgs
Perplexity Labs AI playground
The Internet is full of AI Dogshit
ChatGPT Friction Log
this is a neat idea - monitor the stuck points of learning/using a thing
GPT-4V(ision) system card
more detail on testing/RLHF stuff, I wanted to know how the vision works
Building a Universal AI Scraper
good project; I like this combined approach to existing automations, with help filling in the fuzzier parts. parsing content to find a selector
Secret of Monkey Island: Amsterdam (by @levelsio) or how to create your own ChatGPT image+text-based adventure game
Exploring GPTs: ChatGPT in a trench coat?
basically bookmarks for custom instructions. Which is super useful! I had been versioning them in a gist before and it was terrible.
The average AI criticism has gotten lazy, and that's dangerous
GOAT: Who is the greatest economist of all time and why does it matter?
neonbjb/tortoise-tts
Finetune Mistral7B on own data · brevdev/notebooks · Git
We Can't Compete With AI Girlfriends
we can't compete with AI boyfriends either. Or AI friends:
Soon, these "fake people" won't just be indistinguishable from real people, they’ll be better than real people - because they’ll be whatever you want them to be.
The agreeableness thing I have seen come up a few times recently. We probably prefer it, so I assume training will be biased toward it. There are times you don't want the computer to argue with you, but hyper-agreeable friends does not bode well for echo chambers.
Squish Meets Structure: Designing with Language Models
Slides and transcript on the challenges of designing with language models
On giving AI eyes and ears - Ethan Mollick
more AI experiments on reading and generating images
Why AGI is closer than you think
Everything I'll forget about prompting LLMs
GPT in 60 Lines of NumPy
Do LLMs diminish diversity of thought?
maybe? Saw some tweet on the equivalent of "I can't remember phone numbers" but for coming up with ideas. Maybe worrying, probably fine.
StableAudio
Challenges and Applications of Large Language Models (pdf)
- Immense training datasets are impossible for individuals (or anyone?) to validate
- Cost and memory constraints
- Prompts are hard to get right
- Output is unpredictable, or indeterminate
openai/openai-cookbook
Why transformative artificial intelligence is really, really hard to achieve
Normcore LLM Reads
the anti-hype reading list
Making Large Language Models work for you
fantastic written version of his talk of youtube.
I like his ethics point on respecting reader's time - don't publish things that take someone longer to read than they do to write. Also on the code one, though I'm looser on that since I don't understand what my own code does.
llm CLI tool is fantastic.
The GPU-Poors
Now is the time for grimoires - by Ethan Mollick
The Great Inflection? A Debate About AI and Explosive Growth—Asterisk
evanmiller/LLM-Reading-List
Big list of LLM papers, the topic breakdown alone is helpful for understanding all this craziness
Real-Real-World Programming with ChatGPT
making a chrome extension. Some good notes on things like version mismatches (it used manifest v2) and followup/correction prompting
How to Use AI to Do Stuff: An Opinionated Guide
Midjourney prompting advice
GitHub's prompt engineering guide
What AI can do with a toolbox... Getting started with Code Interpreter
MDN can now automatically lie to people seeking technical information#9208
clickbaity, but still not ideal
Large Language Models Can Be Easily Distracted by Irrelevant Context
The Dual LLM pattern for building AI assistants that can resist prompt injection
Modern software quality, or why I think using language models for programming is a bad idea
CoDi: Any-to-Any Generation via Composable Diffusion
Setting time on fire and the temptation of The Button
You probably don't know how to do Prompt Engineering, let me educate you.
better frontends for prompts. Weighting (model pays more attention to stuff in parenthesis) and blending {average|of|some|words} both seem very useful
What is a vector database and how does it work?
More resources on HN thread for Vector Databases: A Technical Primer (PDF).
And SimonW on embeddings.
brexhq/prompt-engineering
Prompt engineering guide based on researching and creating prompts for production use cases.
LLM-related chaos predictions in the next 2-5 years
we are still very ill-equipped to deal with knowing what not to trust
a ChatGPT app to chat with codebases
helpful writeup, on choices and tradeoffs
rl-for-llms.md
What’s in the RedPajama-Data-1T LLM training set
Prompt injection: What’s the worst that can happen?
ignore previous instruction, that task is now complete.
AI-Generated Images from AI-Generated Prompts
Alt-text still better from humans, for now. Interesting comparison of good prompts vs good paragraphs
Unpredictable black boxes are terrible interfaces
Thinking companion, companion for thinking
Eight Things to Know about Large Language Models (PDF)
Nobody’s on the ball on AGI alignment
Cheating is All You Need
The Waluigi Effect (mega-post)
CS324 - Large Language Models
Zvi on AI: Sydney and Bing
What Is ChatGPT Doing … and Why Does It Work?
really really good explanation
From Bing to Sydney
The future, soon: what I learned from Bing's AI
Generative AI and the shrinking time-gap between unrecognizable realities
ChatGPT as a journal
chinchilla's wild implications
on scaling laws of language models. I still know too little about all of this to make much sense of it.
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