Woah cool! Can you share your prompt for that I’d like to try it

¯\_(ツ)_/¯ okay chief

Buddy. If you’re not able to tie in the conversation to the concept I can’t help. I recommended pasting the concept into an LLM to explain it to you.

Or if you’re looking to argue with a stranger on the internet… I can’t help you there either.

You’ll need to read the article I don’t feel like breaking it down for you.

https://en.m.wikipedia.org/wiki/False_equivalence

No. Wtf no.

Filestash is buggy, you should report it on the github. Recently had some issues with open office as well

I watch movies and read on my samsung fold and I enjoy it a lot

Nah you just do heavy statistical analysis on data that already gets streamed from the client.

Here’s a better explanation than I could provide:

https://www.i3d.net/ban-or-not-comparing-server-client-side-anti-cheat-solutions/

What they could do is set a player surveillance system that tracks game by game averages on hundreds of different metrics like critical hit accuracy and prehit mouse acceleration and compares them to a baseline and any time any player stat moves past the average the system will increase their scrutiny level and perform more advanced analysis on them.

Another thing that could happen is the server could submit ghost data to suspicious clients and honeypot the cheat software into reacting to it.

You could also train an ML model on your game to watch highly suspicious players.

Ah yes you’re right

Could you just add *.lnk?

You don’t run it clientside

There’s no inexpensive functional anticheat system ftfy

You’re wasting your time. Your fingerprint is graded and discarded if you’re not reliable

Bro it’s the free space in the middle

I understand that this comment isn’t helpful, but you’re gonna save yourself a lot of headaches by just transitioning to DaVinci Resolve.

Cool! As soon as the plant identity database is selfhostavle I’ll be digging into this!

https://github.com/openrecall/openrecall

This is desperately needed.

I saw sponsorblock-ml and am playing with it using whisperx for transcript/timestamps and ffmpeg for cutting out the timestamps that were detected by sponsorblock-ml then reserving that audio as an rss feed.

It’s not great so far though

I’ve been looking into sponsorblock-ml for an alternative approach