Barbarian

u/Barbarian@lemmy.reckless.dev
3 posts · 49 comments

Recent posts

Recent comments

A server will only pull in everything from a community once at least 1 person on that server subscribes. Then it will start pulling in every new post and comment as soon as they're up.

I’m big into tabletop, and would welcome (perhaps after Beehaw growth), a specific tabletop community here

I would subscribe to that in a heartbeat.

Yeah, posts & comments can't work in this way because each instance will have different ID numbers for their federated copy. I'm not even sure how to begin approaching this issue.

Jesus:

temperatures surged to more than 40 degrees Celsius (104 degrees Fahrenheit) in Dhaka. Other cities such as Rangpur recorded a high of 41 degrees Celsius – the highest there since 1958.

Global warming is absolutely crushing certain countries. There's going to be a lot of dead elderly and young children before all that is over.

on *Permanently Deleted* · c/support · 3 pts · 3y

I don't think it's likely to have a UI element, devs are slammed enough as it is and there aren't enough new contributors stepping up (I'm trying, I really am, I just don't know Rust, Psql or Typescript enough).

Much better for there to be a community ruling about it which Beehaw members & contributors abide by

It's not allowed in a lot of instances because the moderation is absolutely exhausting and sometimes NSFL material.

The only limiting factor here is admins + moderators of an instance willing to put themselves through that.

So, there's a fundamental issue here. A lot of the systems that Amanda is talking about aren't actually AI.

Chat-GPT, contrary to the blogosphere, is not actually AI. It does not have the capability for thought. It doesn't have the capacity to understand truth or fiction as concepts, let alone tell them apart.

Chat-GPT and similar systems are probabilistic language models. Essentially, I start it off with sentences (a list of tokens, if you want to get technical). Then it responds by essentially looking at the training data it's been supplied with and picking out the sequence of tokens that most likely is the answer the user is expecting, given the input. Notice that bolded text? The user is expecting. Not anything else. These language models are trained to spit out what users expect, nothing more, nothing less. If a user doesn't like the response, they give a thumbs down and the model recalibrates, introducing more noise and randomness into the result.

These language models are actually really great at reducing manual labor at certain tasks (writing cover letters, delivering predictable essays, I've personally used Chat-GPT for Shadowrun world-building) but they need to have a knowledgeable person using them because they absolutely will not reliably say true things. They will say whatever their training data says is the most likely thing the user is asking for.