slime VS paip-lisp

Try https://github.com/slime/slime/commit/e6a71c725c8e13d7d4c40e6a6fa7b696575a8d01

With emacs your two choices are either SLIME or SLY. Slime is a good place to start - it's rock solid. Once you get moving you can make a judgement call on whether or not SLY has features you'd like over what SLIME has available.

To provide a bit more context, most of SLIME is just Common Lisp code (https://github.com/slime/slime), with a bunch of Emacs Lisp code alongside to support interfacing with Emacs. But you don't need that Emacs Lisp code to take advantage of almost all of the functionality SLIME provides. For instance, if you want to know who-calls a function, there's some command in emacs to do it, but all that command is doing is just a bit of elisp code which sends a message to Swank (a server running inside Common Lisp) and Swank invokes some native CL code to figure that out and return the results, then finally a bit of elisp code presents the results in some way. Vim can do the same thing just fine with vimscript/python (what the Slimv plugin uses) or otherwise, the bulk of the work in figuring out the list of callers of some function is done by the CL code (and CL implementation itself).

SLIME or SLY for Common Lisp (if you want to work with it), Geiser for various Schemes

That's rather new, https://github.com/slime/slime/commit/789584a7acb15747678fa62a8fcfc8d1187be867 is probably about that.

With that headline on HN, I was expecting this: https://common-lisp.net/project/slime/

SLIME or Sly for Common Lisp, Geiser for most Scheme implementations, or racket-mode for Racket?

For example, some people that are Common Lisp programmers, but don't use GNU Emacs, may decide to use GNU Emacs because of the slime-mode workflow.

PAIP by Peter Norvig, Chapter 23, Compiling Lisp

https://github.com/norvig/paip-lisp/blob/main/docs/chapter23...

Emacs is so much more than a text editor! But I need to stay on topic...

I believe your assessment of LISP (and therefore of MacArthy)'s impact on AI to be unfair. Just a few days ago https://github.com/norvig/paip-lisp was discussed on this site, for example.

Sounds like a great project idea to make a toy demo of this direction you'd like to see. Maybe comparable to https://github.com/norvig/paip-lisp/blob/main/docs/chapter15... and https://github.com/norvig/paip-lisp/blob/main/docs/chapter8.... which are a few hundred lines of Lisp each, but do enough to be interesting.

You could look into Paradigms of AI Programming by Peter Norvig which might interest you regardless of Lisp content.

Lisp has great power, examine PAIP, part II chapters 7 and 8.

A computer running Prolog reasons, and that only requires a couple of pages of code. So it seems feasible that the network could have learned some ability to reason within its network.

IMHO it's because lisp shines to manipulate symbols whereas the current AI trend is crunching matrices.

When AI was about building grammars, trees, developing expert systems builds rules etc. symbol manipulation was king. Look at PAIP for some examples: https://github.com/norvig/paip-lisp

This paradigm has changed.

Origen: Conversación con Bing, 4/4/2023(1) gigamonkey/monkeylib-binary-data - GitHub. https://github.com/gigamonkey/monkeylib-binary-data Con acceso 4/4/2023. (2) paip-lisp/chapter4.md at main · norvig/paip-lisp · GitHub. https://github.com/norvig/paip-lisp/blob/main/docs/chapter4.md Con acceso 4/4/2023. (3) bibliography.md · GitHub. https://gist.github.com/gigamonkey/6151820 Con acceso 4/4/2023.

If anyone is interested PAIP is downloadable at https://github.com/norvig/paip-lisp