@Natanael you seem to continue to focus on PDSes even though I explicitly said it doesn't matter which PDS you're on, the secondary centralization (and thus control) happens in the "reach" layer, outside of what PDSes do in ATproto.
In other words, changing a PDS gives you way, way less agency in BS, compared to agency you get with changing an instance on Fedi.
BS is designed to make that secondary centralization happen, and to be where the real power in the system is.
> The Mastodon fediverse have stronger network effects because big servers can enforce policies on other servers to stay federated. It’s complicated for users to move servers.
Well, I wrote about this as well, so I think I might not be missing these details: https://rys.io/en/168.html
@Natanael enshittification is about power, and ATproto is designed to look decentralized but enable secondary centralization where it matters for power dynamics in the network, in a way that the Fediverse very much doesn't: https://rys.io/en/167.html
(shameless plug, I wrote that, but it dives somewhat deep into the "why" of what I said above)
tl;dr it doesn't matter which PDS you use if everyone is still beholden to the same entity that controls the "reach" layer in BS.
@lloram239 that's really akin to claiming that a mannequin is a human being because it really really looks alike.
The "predictions about the world" you refer to here are instead predictions about the text. They are not based on a model of the world, they are based on loads and loads of text the model was trained on.
I don't have to prove ChatGPT is not intelligent. That would be proving a negative. The burden of proof is on those claiming that it is intelligent.
@lloram239 ah, so you're down to throwing epithets like "idiotic" around. Clearly a mark of thoughtful and well-reasoned argument.
> Predictions about the world are probabilistic by nature, since the future hasn’t happened yet.
Thing is: GPT doesn't make predictions about the world, it makes predictions about what the next word, phrase, sentence should be in a text, based on the prompt and the corpus it got "trained" on.
It's not about sensory inputs, it's about having a model of the world and objects in it and ability to make predictions.
> The important part is that the AI can figure out the pattern in the data it does get and so far AI systems are doing very well.
GPT cannot "figure" anything out. That's the point. It only probabilistically generates text. That's what it does, there is no model of the world behind it, no predictions, no"figuring out".
> Circular reasoning. “LLMs are different from human brains because they are different”.
LLMs are different than human brains because human brains are biological organs and LLMs are probability distributions over sequences of words. These are two completely different classes of entities. Like, I don't know how much more different two things can even be.
Are you claiming they are literally the same? Are you saying they are functionally the same? What are you claiming here, exactly?
> We do it routinely. It is called Education System.
That relies on human brains that are trained. LLMs are not human brains. "Training" them is not the same thing as teaching humans about something. Human brains are way more complicated than just a bunch of weighed correlations.
And if you do want to claim it is in fact the same thing, we're back to square one: please provide proof that it is.
@Barbarian772 it matters because with regard to intelligent beings we have moral obligations, for example.
It also matters because that would be a truly amazing, world-changing thing if we could create intelligence out of thin air, some statistics, and a lot of data.
It's an extremely strong claim, and strong claims demand strong proof. Otherwise they are just hype and hand-waving, which all of the "ChatGPT intelligence" discourse is, in order to "maximize shareholder value".