papers-we-love VS paip-lisp

Papers We Love (PWL) is a community built around reading, discussing and learning more about academic computer science papers. This repository serves as a directory of some of the best papers the community can find, bringing together documents scattered across the web. You can also visit the Papers We Love site for more info.

You might find the paper Out of the Tar Pit interesting if you haven't already read it: https://github.com/papers-we-love/papers-we-love/blob/main/d...

The ideas and approaches you talk about evoked some of the concepts from that paper for me. It talks a lot about separating accidental complexity and infrastructure so you can focus only on what is essential to define your solutions.

Sure he was expecting a practical language and was designing one. Lisp was from day zero a project to implement a real programming language for a computer.

Earlier he experimented with IPL and also list processing programming on Fortran. The plan was to implement a Lisp compiler. At first the Lisp code McCarthy was experimenting with, was manually translated to machine code.

Then came up the idea to use EVAL as a base for an interpreter, which was implemented by manually translating the Lisp code to machine language. Around 1962 then a compiler followed.

https://github.com/papers-we-love/papers-we-love/blob/main/c...

I'm in a 4th camp: we should be writing our applications against a relational data model and _not_ marshaling query results into and out of Objects at all.

Elaborations on this approach:

- https://github.com/papers-we-love/papers-we-love/blob/main/d...

- https://riffle.systems/essays/prelude/

The short ask: Anyone know of any projects that bring incremental view maintenance to SQLite?

The why:

Applications are usually read heavy. It is a sad state of affairs that, for these kinds of apps, we don't put more work on the write path to allow reads to benefit.

Would the whole No-SQL movement ever even have been a thing if relational databases had great support for materialized views that updated incrementally? I'd like to think not.

And more context:

I'm working to push the state of "functional relational programming" [1], [2] further forward. Materialized views with incremental updates are key to this. Bringing them to SQLite so they can be leveraged one the frontend would solve this whole quagmire of "state management libraries." I've been solving the data-sync problem in SQLite (https://vlcn.io/) and this piece is one of the next logical steps.

If nobody knows of an existing solution, would love to collaborate with someone on creating it.

[1] - https://github.com/papers-we-love/papers-we-love/blob/main/design/out-of-the-tar-pit.pdf

Here is a great Repo on GitHub named paers-we-love. You will surely find some great papers there and also some good other resources. Hope this helps.

However, f and g are interchangeable anywhere else (this is not actually true because their addresses can be obtained and compared; showing that a C-like language retains its referential transparency despite the existence of so-called l-values was the point of what I think is the first paper to introduce the notion referential transparency to the study of programming languages: https://github.com/papers-we-love/papers-we-love/blob/main/l...)

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.