I recently wrote a blog post exploring the idea of interfacing with local LLMs for ambiguous tasks like this. Doesn't that make more sense than coding the neural network yourself? Using something like llama.cpp and evaluating whether a small model solves your problem out of the box, and fine-tuning if not, then programmatically interfacing with llama.cpp via a wrapper of your choice seems more pragmatic to me.
I started blogging about stuff I've learned about that I am likely to forget down the road. It feels so good when you throw up a post, never share it, and still manage to get a thank you email for writing it years later. If you have a folder full of notes, I would recommend turning them into a blog on a rainy day.
These are awesome hobby devices to hack on. I’m not very experienced with graphics programming but I had a ton of fun developing with the SDK, wrote a blog post on it recently if anyone is interested in learning more about it.
I recently learned Fennel and cranked out a Love2D game as well. Not only that, but I discovered it’s trivial to run the game on some spare nintendo consoles I have lying around, because Lua is insanely portable.
In contrast, I spent a ton of time trying to build other lisps that are designed to be embeddable on those consoles and got nowhere.
Fennel rocks. Such a pragmatic and well designed mini-language.
I’ve been exploring this project recently, I’m having a great time with it so far. The many examples and great documentation are much appreciated. I’m very tempted to try it for some upcoming projects building workflow systems at work.
I've really enjoyed reading (and playing with) kons-9's codebase in Common Lisp. It lets you do exploratory 3D modeling via the program's GUI or the repl. The source is very neatly structured and readable. I don't see many CL projects that do 3D rendering, so it's nice to see!
Would it be feasible to fine-tune a large, capable model (like the recent LIMA) on the source code (and maybe a few high quality libraries) of a niche language, such that it's much better at helping you write and understand it?
Imagine how many doors it would open if you could fine-tune models capable of writing language bindings for you and keeping them up to date.
> The OpenAI chat completion endpoint encourages the second-person prompting you describe, so that could be why you see it a lot.
You're talking about system prompts specifically right? And I'm assuming the "encouragement" you're referring to is coming from the conventions used in their examples rather than an explicit instruction to use second person?
Or does second person improve responses to user messages as well?
The excellent backwards compatibility rocks too. This weekend I wanted a library to diagram the class hierarchy of a Java project I put together.
I found a 10 year old library that worked with no issues, I was done in minutes even though I rarely use Java or Clojure so my familiarity is low. There are very few languages where I would have a similar experience.
Yeah I think people are reading this the wrong way. Software was originally considered unpatentable under 35 U.S.C. § 101, but language was developed to allow software to be patented by narrowing the scope of the claimed inventions to a physical processor which are programmed to contain specific algorithms.
I don't think this is a showstopper in terms of copyright registration of A.I. works, but rather a first step in a back-and-forth process of figuring out the legal structure of how to makes rules and enforcement work.
I came back to Emacs after trying alternatives for a while. I ripped out most of my config and found it much more pleasant to run close to stock.
I'm having better luck using my web browser for email, sublime merge for Git, debuggers in external programs, etc. If I need to do some edits with multiple selections I open up Kakoune, and if I have a burning need for LSP I switch to VS code.