How did you get swayfx on sericea?

that was one of my only blockers for switching.

Not at all, it was annoying for a few weeks when reddit imploded but since then I haven’t had any problems.

I brute forced my way through learning starcraft, it took literal years to get out of the bronze league, probably my most played game of all time. Can’t wait for immortal gates of pyre.

Did she hate him or something?

He said worst, not best.

Yeah, you can always make your own scrappy little website. But you’ll be an island few to no users will want to visit and support if you’re competing with the other players. That, or you catch on and grow to the point where you yourself become the villain.

that’s exactly what federation prevents… you can be a scrappy little website and federate, and then you don’t need a massive infrastructure that would cause enshittification later. If you enshittify, people will just leave to other parts of the fediverse, the model causes enshittification to just be the failure of your website.

This is different from the world wide web in that the content is not partitioned. I can get the same lemmy experience if I go elsewhere, and not lose out on content. If there’s a major new privacy concern on my instance, i’m going to say fuck them and leave, and I’ll lose nothing.

Also, “no profit motive”? Where critical masses of people gather, entrepeneurs surely follow. Someone will figure out a way to monetize hosting a Fediverse instance. Hell, Threads tried, sort of. That alone won’t immediately enshittify the whole Fediverse. But given enough time and growth, well, see above.

Except they’ll inevitably fail aside from the people who legitimately don’t care, and quite frankly, if they don’t care, who does? Just go to another instance if that happens, you’ll lose nothing, and it won’t even be a problem.

Federation makes the part of enshittification where you box in your users not work. The reason facebook could enshittify is because if you left facebook, you’d lose ALL of facebook. They trapped people. You can’t trap people like that on the fediverse. The first step fails inevitably, you’ll just make everyone on your instance hate you and they’ll leave for literally any other instance and it will die.

The fediverse doesn’t work well with profit motive because of that, the only real way to profit without causing anybody who knows anything about what you’re doing maliciously to leave is… what exactly?

When leaving has no cost, there’s no way to force people to stay if you do something shitty.

Even if you keep some users, meh, they won’t keep me, and i’ll lose nothing by switching.

I completely reject the notion that the mainstream success of the fediverse will be the death of the fediverse, what are your reasons for believing that?

Enshittification happens to monetized platforms because they tried to capture as many users as possible and then profit off of them, lemmy instances show no profit motive, and are volunteer run. There isn’t a route to enshittification with federation, because even if YOUR instance enshittifies, there’s still many others that will not, and due to federation, you won’t miss out on any content (as long as your instance doesn’t defed), so it won’t matter.

I also believe the issues you call out, aside from algorithmically driven content, will be solved eventually, as mod tools improve, there will be less of a need for defederation.

Even algorithmically driven content is partially solved by “hot” and “best” being improved, it’s just not personalized.

With the rate of lemmy development being as rapid as it is, these things will eventually be solved, but that takes a lot of time. Lemmy is still barely even beta.

Yes, but we would refer to our consciousness as an emergent property of our brain.

And we’re trying to build artificial brains.

We also understand the math underlying it. Humans designed and constructed it; we know exactly what it is capable of and what it does

This is false. Read about their emergent properties. We have no way of knowing when emergent properties appear, we just notice them.

Except calculators aren’t models capable of understanding language that appear to become more and more capable as they grow. It’s nothing like that.

It literally can’t worry about its own existence; it can’t worry about anything because it has no thoughts or feelings. Adding computational power will not miraculously change that.

Who cares? This has no real world practical usecase. Its thoughts are what it says, it doesn’t have a hidden layer of thoughts, which is quite frankly a feature to me. Whether it’s conscious or not has nothing to do with its level of functionality.

And (from what I’ve seen) they get things wrong with extreme regularity, increasingly so as thing diverge from the training data. I wouldn’t say they’re a “stochastic parrot” but they don’t seem to be much better when things need to be correct… and again, based on my (admittedly limited) understanding of their design, I don’t anticipate this technology (at least without some kind of augmented approach that can reason about the substance) overcoming that.

Keep in mind, you’re talking about a rudimentary, introductory version of this, my argument is that we don’t know what will happen when they’ve scaled up, we know for certain hallucinations become less frequent as the model size increases (see the statistics on gpt3 vs 4 on hallucinations), perhaps this only occurs because they haven’t met a critical size yet? We don’t know.

There’s so much we don’t know.

That’s missing the forest for the trees. Of course an AI isn’t going to go fishing. However, I should be able to assert some facts about fishing and it should be able to reason based on those assertions. e.g. a child can work off of facts presented about fishing, “fish are hard to catch in muddy water” -> “the water is muddy, does that impact my chances of a catching a bluegill?” -> “yes, it does, bluegill are fish, and fish don’t like muddy water”.

https://blog.research.google/2022/05/language-models-perform-reasoning-via.html

they do this already, albeit imperfectly, but again, this is like, a baby LLM.

and just to prove it:

https://chat.openai.com/share/54455afb-3eb8-4b7f-8fcc-e144a48b6798

You’re assuming i’m saying something that i’m not, and then arguing with that, instead of my actual claim.

I’m saying we don’t know for sure what they will be able to do when they’re scaled up. That’s the end of my assertion. I don’t have to prove that they will suddenly come alive, i’m not claiming they will, i’m just claiming we don’t know what will happen when they’re scaled, and they seem to have emergent properties as they scale up. Nobody has devised a way of predicting what emergent properties happen when, nobody has made any progress whatsoever on knowing what scaling up accomplishes.

Can they reason? Yes, but poorly right now, will that get better? Who knows.

The end of my claim is that we don’t know what’ll happen when they scale up, and that you can’t just write it off like you are.

If you want proof that they reason, see the research article I linked. If they can do that in their rudimentary form that we’ve created with very little time, we can’t write off the possibility that they will scale.

Whether or not they reason LIKE HUMANS is irrelevant if they can do the job.

And i’m not anthropomorphizing them without reason, there aren’t terms for this already, what would you call this behavior of answering questions significantly better when asked to fully explain reasoning? I would say it is taking the easiest option that still meets the qualifications of what it is requested to do, following the path of least resistance, I don’t have a better word for this than laziness.

https://www.downtoearth.org.in/news/science-technology/artificial-intelligence-gpt-4-shows-sparks-of-common-sense-human-like-reasoning-finds-microsoft-89429

Furthermore predictive power is just another way of achieving reasoning, better predictive power IS better reasoning, because you can’t predict well without reasoning.

I’m not guessing. When I say it’s a difference of kind, I really did mean that. There is no cognition here; and we know enough about cognition to say that LLMs are not performing anything like it.

We do not know that, I challenge you to find a source for that, in fact, i’ve seen sources showing the opposite, they seem to reason in tokens, for example, LLM’s perform significantly better at tasks when asked to give a step by step reasoned explanation, this indicates that they are doing a form of reasoning, and their reasoning is limited by what I have no better term for than laziness.

https://blog.research.google/2022/05/language-models-perform-reasoning-via.html

If I teach a real AI about fishing, it should be able to reason about fishing and it shouldn’t need to have read a supplementary knowledge of mankind to do it.

This is a faulty assumption.

In order for you to learn about fishing, you had to learn a shitload about the world. Babies don’t come out of the womb able to do such tasks, there is a shitload of prerequisite knowledge in order to fish, it’s unfair to expect an ai to do this without prerequisite knowledge.

Furthermore, LLM’s have been shown to do many things that aren’t in their training data, so the notion that it’s a stochastic parrot is also false.

You’re guessing, you don’t actually know that for sure, it seems intuitively correct, but we simply do not know enough about cognition to make that assumption.

Perhaps our ability to reason exclusively comes from our ability to predict, and by scaling up the ability to predict, we become more and more able to reason.

These are guesses, all we have now are guesses, you can say “it doesn’t reason” and “it’s just autocorrect” all you want, but if that were the case why did scaling it up eventually enable it to perform basic math? Why did scaling it up improve its ability to problemsolve significantly (gpt3 vs gpt4), there’s so many unknowns in this field, to just say “nah, can’t be, it works differently from us” doesn’t mean it can’t do the same things as us given enough scale.

We don’t know that for sure yet, we saw a lot of emergent intelligent properties appear as we scaled up, and we’re nowhere near done scaling LLM’s, I’m not saying it will be solved, just that we don’t know one way or the other yet.

I use the Mozilla homeserver

These aren’t companies, these are projects, lemmy/mastodon are co-operatively worked on and can be worked on by any number of companies.

I don’t want a corpo internet, that’s kind of the point of federation.

There may be a need for improvement overtime… but that has nothing to do with if competition is helpful.

This is free open source software, it’s better to have many people working together on one project than a bunch of projects being worked on separately, for reasons I think are obvious.

There isn’t a race to be the king of the fediverse, competition does nothing but make people work separately on something that should be worked on cooperatively, it accomplishes nothing but slowing down development. If we used competition, when a new feature was implemented, now instead of it being implemented for everyone, it’ll be implemented in one particular codebase, and if other people want to implement it, there will be a massive duplication of effort.

What does competition in this space actually do for the community? As far as I see it, absolutely nothing at all, except duplicating effort.