ABasilPlant

o7

Yep, a few forks were identified within a few hours. I think the maintainers had forks too.

Do you want to return to that account?

If not, Temp mail works fine.

Also, Bug me not has user-submitted usernames + passwords to services. This works nicely.

I've used Port87 in the past. The user who created it promoted the service on lemmy initially. It worked (I paid for a few months).

~~I suggest using two different spellings:~~

~~Mold is the fungus. To mould is to shape.~~

Nvm I'm an idiot. Lol

That seems to be the consensus online. But thanks for that tidbit! It feels even more bizarre now knowing that.

I wonder why a handful of people think the way I presented in the post. Perhaps American/British influences in certain places? Reading books by british authors and books by american authors at the same time? Feels unlikely.

https://code.kryo.se/iodine/

https://blog.torproject.org/introducing-webtunnel-evading-censorship-by-hiding-in-plain-sight/

Yes, this would essentially be a detecting mechanism for local instances. However, a network trained on all available federated data could still yield favorable results. You may just end up not needing IP Addresses and emails. Just upvotes / downvotes across a set of existing comments would even help.

The important point is figuring out all possible data you can extract and feed it to a "ML" black box. The black box can deal with things by itself.

My bachelor's thesis was about comment amplifying/deamplifying on reddit using Graph Neural Networks (PyTorch-Geometric).

Essentially: there used to be commenters who would constantly agree / disagree with a particular sentiment, and these would be used to amplify / deamplify opinions, respectively. Using a set of metrics [1], I fed it into a Graph Neural Network (GNN) and it produced reasonably well results back in the day. Since Pytorch-Geomteric has been out, there's been numerous advancements to GNN research as a whole, and I suspect it would be significantly more developed now.

Since upvotes are known to the instance administrator (for brevity, not getting into the fediverse aspect of this), and since their email addresses are known too, I believe that these two pieces of information can be accounted for in order to detect patterns. This would lead to much better results.

In the beginning, such a solution needs to look for patterns first and these patterns need to be flagged as true (bots) or false (users) by the instance administrator - maybe 200 manual flaggings. Afterwards, the GNN could possibly decide to act based on confidence of previous pattern matching.

This may be an interesting bachelor's / master's thesis (or a side project in general) for anyone looking for one. Of course, there's a lot of nuances I've missed. Plus, I haven't kept up with GNNs in a very long time, so that should be accounted for too.

Edit: perhaps IP addresses could be used too? That's one way reddit would detect vote manipulation.

[1] account age, comment time, comment time difference with parent comment, sentiment agreement/disgareement with parent commenters, number of child comments after an hour, post karma, comment karma, number of comments, number of subreddits participated in, number of posts, and more I can't remember.

Ah if you messed it up, you can press "e" on the grub entry and edit the command line parameters to remove the thing that messes it up. Good luck with your fresh install [and use Debian this time... jk :)]

Make sure to update your grub after you do. I've messed that one up before lol 😅

Do you not need the nvidia-drm.modeset=1 in GRUB_CMDLINE_LINUX?

https://www.if-not-true-then-false.com/2015/fedora-nvidia-guide/#262-edit-etcdefaultgrub

Could you show us the kernel command line parameters (in /etc/default/grub)? Is the modeset along with other params enabled? I'm not a fedora user, so I may not be of too much help.