Krzysztof Sakrejda

@menelion @fastfinge @matt @nolan @zersiax that's beautiful, thank you!

@menelion @fastfinge @matt @nolan @zersiax maybe a dumb question but do the screen readers have hooks for custom text parsing in the pipeline before it gets read out? At a minimum it should, in a better world, be capable of calling out a timestamp without reading it...

@menelion @fastfinge @matt @nolan @zersiax yeah that's a great example of why this needs tooling! I cringed just starting to read that!

It always reminds me of this Victor Borge routine: https://youtu.be/NPc0aijY2o4

He was onto something.

@fastfinge @menelion @matt @nolan @zersiax right, and log text has a simple structure with meaningful lines located in time with repeating glue text that has changing values attached so it's really structured data for analysis as a vector of words with a small vocabulary and (some) meaningful punctuation...

Uh, I'll poke/ask around if this is something that's been a target for model training and whether I can find anybody who has done it from this angle.

@fastfinge @menelion @matt @nolan @zersiax yes and since AI gets that feature from being a specific kind of deep learning method I think this might be a good niche for an established machine learning method that a) burns less electricity and b) doesn't make shit up, you just got me thinking a little about which one that would be.

@fastfinge @menelion @matt @nolan @zersiax right and what I'm saying is that the rolling could do a lot better here, you don't get plots without figuring out how to parse logs either, how to summarize information verbally vs visually is a challenge but it's not something (for the tooling, not for an individual, for an individual it's overwhelming)

@fastfinge @menelion @matt @nolan @zersiax so one thing that would be helpful is a straightforward alternative to sed/awk for finding relevant bits of logs and accessible summaries of graphs?