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liminal 🦠
dc4cd086cd7ce5b1832adf4fdd1211289880d2c7e295bcb0e684c01acee77c06
building #Alexandria & #DreamGradAcademy https://next-alexandria.gitcitadel.eu/ Decentralize education
Replying to Avatar Sergio

πŸ‘‰πŸ˜–πŸ‘ˆ βž‘οΈβš‘πŸ«‚βš‘πŸ«‚βš‘πŸ«‚βž‘οΈ 🧠

i.nostr.build/xEdeV.gif

Absolutely love this one πŸ˜‚

Awee so does that mean Damus Android wont get custom reactions? πŸ₯Ή

In case any parent already didn't get the memo before the recent AI wave started kicking up: Don't let your kids watch "educational material" unsupervised.

Otherwise, there's nothing to be worried about.

https://www.theintrinsicperspective.com/p/here-lies-the-internet-murdered-by

Of course, another great read and commentary by nostr:npub1h8nk2346qezka5cpm8jjh3yl5j88pf4ly2ptu7s6uu55wcfqy0wq36rpev on #AIUnchained

https://fountain.fm/episode/nHeo1s1OQoP4d2LLDvPQ

Replying to Avatar liminal 🦠

nostr:npub1f6ugxyxkknket3kkdgu4k0fu74vmshawermkj8d06sz6jts9t4kslazcka has amazing notes on opsec and security. I wish there was a way to aggregate them in a way that's not just hashtags! I think there are quite a few users who'd benifit from something like that.

Something I've considered as a solution could be thought of as essentially modular, composable articles. Basically taking influence the long form content and list nips while also considering the functional aspects of linked/aggregated knowledge.

The idea is that you have event ids in the list which are small fragments of a larger contained article. It also could work for the typical nostr clients user functionality to aggregate related ideas. Good potential for remixing content.

https://wikifreedia.xyz/nkbip-01/dc4cd086cd7ce5b183

nostr:npub1f6ugxyxkknket3kkdgu4k0fu74vmshawermkj8d06sz6jts9t4kslazcka has amazing notes on opsec and security. I wish there was a way to aggregate them in a way that's not just hashtags! I think there are quite a few users who'd benifit from something like that.

Something I've considered as a solution could be thought of as essentially modular, composable articles. Basically taking influence the long form content and list nips while also considering the functional aspects of linked/aggregated knowledge.

The idea is that you have event ids in the list which are small fragments of a larger contained article. It also could work for the typical nostr clients user functionality to aggregate related ideas. Good potential for remixing content.

https://wikifreedia.xyz/nkbip-01/dc4cd086cd7ce5b183

Everything is in 4/4 if you focus enough πŸ‘‰πŸ˜–πŸ‘ˆπŸ₯ πŸ₯ πŸ₯ πŸ₯ πŸ₯πŸ₯ πŸ₯ πŸ₯ πŸ₯πŸ₯ πŸ₯ πŸ₯ πŸ₯ πŸ₯

feeeEEee3el the pulse bruh

Feel like i didnt understand math till Calc 3 πŸ€£πŸ€£πŸ˜…πŸ˜°πŸ˜­πŸ˜­ even more so when i took Dynamic Systems

Actually curious about the reasoning for it πŸ˜€

We care about some sort of threshold classification, with some sort of "pending"/leniancy state for newcomers.

Maybe even a sinkhole point-of-no-return-make-a-new-npub-bitch for spam/noted toxic individuals given your network.

A sigmoid is standard practice for classification, but asymptotic bounds of 0 and 1 don't really help those that have been in the game for a while. So we want to classify yes and no, in between state, and also note the very (un)trustworthy individuals.

Tan and cubic curves accomplish that. They grow very fast after a certian point.

With minimal assumptions, you can just encode every data point as Β±1 for positive/negative interactions, and put the average * scaling constant into the function.

Or you can weight the interactions by type (mutes>follows> sentiment classification of comments > reaction classification, or weight based on if the points are coming from your follows) and compute the weighted average.

Coracle's WOT formula, where mutes are the argument and follows are the parameter.