Elon Musk’s latest changes for X are driving more users away – not exactly a surprise, granted – and many of them are flocking to rival social media outlet Bluesky. So many made the switch, in fact, it led to Bluesky briefly going down due to the volume of incoming new users.

The central move initiated by X that made the headlines for driving migration away from Musk’s platform is a change to the way the ‘Block’ button works. This was actually announced back in September, but is officially being implemented now (well, it’ll be in place ‘soon’ we’re told).

It means that going forward, X users who you have blocked will still be able to view your (public) posts – though they won’t be able to engage with them in any way (from replies to liking and so forth).

This is problematic for obvious reasons, in terms of enabling stalkers and trolls who will still be able to view the posts of an account that has blocked them, when previously this wasn’t the case. In the past, blocking meant that the blocked user couldn’t see any posts (or anything at all, save for a message telling them that they’ve been blocked), but soon, this will change.

Bluesky posted to say it had in excess of 100,000 new users inside 12 hours following the announcement by X, after the rival network highlighted the fact that its block function stops those who are blocked from viewing any posts.

In an update, Bluesky noted that it has now gained half a million new users in the past day.

There’s another reason that some folks are rapidly exiting from X stage left (and right, and indeed center, clambering over the audience, it would seem), and that’s a change to X’s privacy policy.

As TechCrunch reports, the new policy includes an update that allows third-party collaborators to use content on X to train their AI models – unless the user opts out. This is a notable extension of the reach of AI training on X, which has so far only been used to train Musk’s own Grok AI (unless users opt out, again).

  • dual_sport_dork 🐧🗡️@lemmy.world
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    14 days ago

    This is in fact precisely what happens. LLM output becomes increasingly incoherent with each subsequent generation trained off of previously AI generated data.