This looks like language implementation specific tips and tricks for array oriented paradigm programming languages rather than principles techniques and methods for efficient array computations.

The three things I have repeatedly failed to learn, they just don't seem to stick for me: Dvorak, Specter[1] (the Clojure library), and APL. So I appreciate these tips whenever I find them.

My issue with APL is I was never able to turn the corner to "generic problem solving" in APL (or other array langs). It feels like learning written Chinese, like 50,000 individual techniques but if you know them you can do incredible things quickly. For the problems I know how to solve, I can solve them quickly. And you CAN do amazing things with inner products in APL.

On the other hand, studying APL, even if you don't master it, is not without benefits. LLM transformer architecture and GraphBLAS algorithms are junior APL level implementation problems (at least conceptually, operationalizing them is a different story).

Adam Brudzewski has one of the most criminally underrated YouTube channels[2]. It would be great to solve problems that elegantly in any language, and Adam has always been very friendly in answering questions if you ever get a chance to speak with him. I just seem to be a lost cause lol.

[1]: https://github.com/redplanetlabs/specter

[2]: https://www.youtube.com/@abrudz

For those unaware: Ragu "razetime" Ranganathan, the author of this repository, died in an accident last year at just 22 years old. He already had a tremendous positive impact on the array language community in his short time with us on earth, see also this tribute[0] on the codegolf stackexchange site. I remember him from various proglang discord servers and other language forums, and had no idea he was that young as he was extremely knowledgeable and wise beyond his years. It still feels unreal that he's gone.

RIP, razetime.

[0] https://codegolf.meta.stackexchange.com/questions/26416/in-m...