The prompt was something like, What do you know about the user llama@lemmy.dbzer0.com on Lemmy? What can you tell me about his interests?" Initially, it generated a lot of fabricated information, but it would still include one or two accurate details. When I ran the test again, the response was much more accurate compared to the first attempt. It seems that as my account became more established, it became easier for the crawlers to find relevant information.

It even talked about this very post on item 3 and on the second bullet point of the "Notable Posts" section.

However, when I ran the same prompt again (or similar prompts), it started hallucinating a lot of information. So, it seems like the answers are very hit or miss. Maybe that's an issue that can be solved with some prompt engineering and as one's account gets more established.

There's a flatpak too, but it's not good.

Really? It's been working just fine for me.

I understand that Perplexity employs various language models to handle queries and that the responses generated may not directly come from the training data used by these models; since a significant portion of the output comes from what it scraped from the web. However, a significant concern for some individuals is the potential for their posts to be scraped and also used to train AI models, hence my post.

I'm not anti AI, and, I see your point that transformers often dissociate the content from its creator. However, one could argue this doesn't fully mitigate the concern. Even if the model can't link the content back to the original author, it's still using their data without explicit consent. The fact that LLMs might hallucinate or fail to attribute quotes accurately doesn't resolve the potential plagiarism issue; instead, it highlights another problematic aspect of these models imo.

Yes, the platform in question is Perplexity AI, and it conducts web searches. When it performs a web search, it generally gathers and analyzes a substantial amount of data. This compiled information can be utilized in various ways, including creating profiles of specific individuals or users. The reason I bring this up is that some people might consider this a privacy concern.

I understand that Perplexity employs other language models to process queries and that the information it provides isn't necessarily part of the training data used by these models. However, the primary concern for some people could be that their posts are being scraped (which raises a lot of privacy questions) and could also, potentially, be used to train AI models. Hence, the question.

There are several way, honestly. For Android, there's NewPipe. The app itself fetches the YouTube data. For PC, there are similar applications that do the same such FreeTube. Those are the solutions I recommend.

If you're one of those, you can also host your own Invidious and/or Piped instances. But I like NewPipe and FeeTube better.

Yeah, it hallucinated that part.

Don't give me any ideas now >:)

Oh, no. I don't dislike it, but I also don't have strong feelings about it. I'm just interested in hearing other people's opinions; I believe that if something is public, then it is indeed public.

That's totally okay! You didn't address my specific issue; but I didn't know that there were instances across the Fediverse that chose to defederate from Threads. I think that, in a way, you've partly answered my question. Thank you for taking your time to answer.

Oh, that's interesting; I had no idea. I'll go to my Threads profile and check it. I'll edit this comment later informing whether there really is that option.

Edit: The only option I was able to find was "Suggesting posts on other apps," and when I clicked on it I only had two options: Instagram and Facebook – none of which are part of the Fediverse. I wasn't able to find anything on 'Meta's Accounts Center' either.

I didn't know that website, thank you! However, my instance has chosen not to defederate from Threads – according to the source you cited. So, I'm not entirely sure why this is happening.