engine VS paip-lisp

10 × PlayCanvas Personal plan for 12 months

For some reason that I cannot understand in my case the calculated shading normals are pixelated. Compared to playcanvas.com (probably a forward renderer), mine is like utter shit.

PlayCanvas has been using WordPress for 12 years now. Generally speaking, it's been fine. However, after much consideration, we have migrated away to Jekyll + GitHub Pages. I thought our experience might be of interest to other WordPress users (if only to confirm why you wouldn't consider switching): https://blog.playcanvas.com/moving-from-wordpress-to-jekyll-a-case-study/ Interested to hear peoples' thoughts...

It's just a cool tech demo that pushes CSS to its limits, but it's completely useless if you want to create usable 3d models. If you want to model in the browser, you can check out vectary, playcanvas, or spline

Hey, I do not have any experience with deepar.ai so I’m not super familiar with the process using that platform. In my opinion I’d probably recommend another platform to try and accomplish this. Since you mentioned that you have everything set up in a engine already (lens studio) I’d recommend you just use a webxr engine. In my experience the two best engines are https://playcanvas.com and https://wonderlandengine.com. I think that going down this route may be the best option for your needs. I am willing to help out or do some of the work for you just pm me if you have any questions or anything.

If you want the closest thing to Unity that's focused on browser-based (mobile and otherwise) development, try Playcanvas: https://playcanvas.com/

Release Notes: https://github.com/playcanvas/engine/releases/tag/v1.62.0 Clustered Arealights Demo: https://playcanvas.com/demos/arealights/

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.