yepp  representation theory studying resuming time.

now that I have study notes of mine, it would be faster to revise previously studied knowledge.

yayy I wish to finish today most of studying if possible. with some focus session to then tomorrow resume some theoretic topics to then start writing abstract library of about repr. theory like topics. 

some intermediary and very important layer of ml project this library of optimizations would be. since I had bought this computer, I am counting hours to start writing code with this very fast computer. (Razer laptop, i9 processor, Nvidia RTX 4070, 32Gb RAM.). 

I had not selected language to write the code. I am quite bored of scala since I utilize scala in my normal daily data engineering tasks usually. so most possibly I would might select another language. 

hmm maybe new cpp.  no no not Rust. (I am bored of learning a new language right now :) Reason I  do not wish to proceed with Rust lang which  I heard that is based on cpp). 

(Of course I dont even consider Java as always. (coming from c/cpp roots. the rift between javaers and c/cpp'ers :) ) plus Java really has weird syntax even threading imho ) (scala is much better than java surely) 

hmm i might also revise golang and use golang. 

or else might come up to cpp (but surely would need to relearn new standard)

I mean its because since this library is need to be an optmiizations library. and I think for these scientific domains its more cpp/python libs available than other languages imho. 

i think creating highly performant per one cpu core is both a concern and not alot concern. in the end, scalability is what matters. (e.g. akka type or erlang type scalability) but in this library even performance in one core of cpu is also very important. since it would be an optimizations library that is like intermediary layer. but again, i think again its not correct mindset to try to optimize this library so much. what matters is the algorithms of the optimization libraries coded inside the library. but not library's own performance.  what rather most matters is scalability of the library. 

so in these aspects, its kind of not very good mindset to not utilize scala/akka -> 

but reason I dont wish to follow approach based with scala is I  constantly work with scala usually :)  (since being a data engineer and most data engineering libraries are with scala) 

I mean in ml hobby project, I would most possibly switch to other computer languages.

e.g. instead of akka based distributed computing solution, trying erlang alternative alike.

(its all because due  always or usually or most times coding with scala.)  (I mean since data engineering usually mostly is done with scala )  

( hmm revising erlang would be interesting. I remember that it were also enabling distributed computing. hmm golang, does it support distirbuted computing as alike akka? i do not exactly remember golang's such features.  but as some light threads wise it were nice library surely. hmm but i think erlang has had the distributedness alike Akka. and could run cpp/c libraries also. ok. lets go with this solution option: using erlang as distributed computing layer and coding essential library features with c and cpp. cause I am very bored from java based plateu or I mean scala etc etc. (since scala is like the main language in data engineering (since most platforms are based on scala, and since scala works faster than python most times so we data engineers most time code with scala. ). )

if it were not optimization library, I might even utilized Typescript or Python. they are even more interesting than Scala to me. (cause I always usually code with scala. and it becomes quite monotone )  (so in hobby project time, I would definitely not code with Scala. Or neither Akka. Erlang instead of Akka, yepp.  (I remember that erlang also supported multi nodes scaling wise distributivity. but lets check later) )  I also wonder haskell. e.g. instead of using category theoretic coding with scala, I think learning Haskell seems more interesting imho. 

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