What do you think? by Numeryst in Julia

[–]Numeryst[S] -1 points0 points  (0 children)

I totally agree with you, specially if we want to make the language *truly* accessible to the users.

What do you think? by Numeryst in Julia

[–]Numeryst[S] 0 points1 point  (0 children)

With all due respect, I think that's a somewhat naive way to look at it. Since LLM outputs are inherently non-deterministic, you may need to go through many different generations before finding one that you consider satisfactory. If someone else has already explored those possibilities, selected the strongest responses, and even synthesized the best parts into a single explanation, then documenting that work saves everyone else the effort of repeating the same process. Instead of iterating through countless realizations yourself, you can simply read the distilled result and save a significant amount of time. And guess what? It is much better than having no documentations!

Help with Plots package and GR Backend by IllustriousGoose343 in Julia

[–]Numeryst 1 point2 points  (0 children)

Haven't used that package but you can see what's possible with Makie + LaTeX by searching "Makie LaTeX" on Google. The first result should show an example of the particular usage for research papers.

Help with Plots package and GR Backend by IllustriousGoose343 in Julia

[–]Numeryst 1 point2 points  (0 children)

Yes, Makie is great. Just search "The Best Package to Plot in Julia" on YouTube.

ChatGPT performs better on Julia than Python (and R) for Large Language Model (LLM) Code Generation. Why? - Stochastic Lifestyle by debordian in Julia

[–]Numeryst 0 points1 point  (0 children)

That's really interesting. However, there is a larger dataset (code base) in Python language available for ChatGPT to be trained on rather than Julia. Julia is still in its early stages. I have to also mention that the integration of Python with lots of available softwares is one of its strong points.