git-from-the-bottom-up VS paip-lisp

Here's a great walk through for how Git works from the bottom up: https://jwiegley.github.io/git-from-the-bottom-up/

It's short, easy to understand and you'll understand HEAD.

Very tangential:

Gerrit also stores some of its configs in a git repo. I was setting up a new instance, but couldn't get Admin permissions because the way my auth front-end didn't play well with the docker image's assumptions.

Gerrit already does a lot of its work via non-standard references. For example, you don't push to a branch, `refs/branches/foo`, you push to a separate `refs/for/foo` namespace that creates the review.

Similarly, Group config is stored in the All-Users git repo [1], but in references created after a UUID, in `refs/groups/UU/UUID`.

I ended up having a to exercise the plumbiest of plumbing commands [2] to create a new commit from scratch (from a tree, from the index, from blobs), to update the group ref to add myself to the Administrators group (this, of course, requires a local shell and permissions on the Gerrit host). It was a great way to exercise what I had learned in Git from the Bottom Up [3]

[1] https://gerrit-review.googlesource.com/Documentation/config-...

[2] https://git-scm.com/book/en/v2/Git-Internals-Git-Objects

[3] https://jwiegley.github.io/git-from-the-bottom-up/

I found Git from the Bottom Up helpful. It is very short as well. Then refer to the official book when you want more detail.

I recently came across "Git from the Bottom Up by John Wiegley" (thanks to Coding Blocks podcast), he has a chapter about rebasing: https://jwiegley.github.io/git-from-the-bottom-up/1-Repository/7-branching-and-the-power-of-rebase.html

You won't have to put your entire life on break in order to understand the fundamentals of git and why it works the way it works. Going through https://jwiegley.github.io/git-from-the-bottom-up/ and really understanding the material will take you a couple of hours at max, but will save you a lot of time in the future.

Wanting to understand things before using them is hardly elitism, not sure why you would think that.

Just like you probably don't want to fix bugs without understand the cause, it's hard to use a tool correctly unless you know how the tool works.

Have you seen https://stevelosh.com/blog/2018/08/a-road-to-common-lisp/ ? "Kludges" everywhere is applicable. On the other hand, having a function like "row-major-aref" that allows accessing any multi-dimensional array as if it were one dimensional is "sweeter than the honeycomb".

I still think CL code can be beautiful. Norvig's in PAIP https://github.com/norvig/paip-lisp is nice.

As for the inside-out remark, while technically you do it, you don't have to, and it's very convenient to not do. Clojure has its semi-famous arrow macro that lets you write things in a more sequential style, it exists in CL too, and there's always the venerable let* binding. e.g. 3 options:

    (loop (print (eval (read))))

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.