Veraticus

Out of the top collections, the most common price for an NFT is now $5-$10.

Still overpriced!

I’ve run into this in Debian. Not sure what to tell you – the base repo does not have an explicit contract that everything in it uses the same version of all available software.

Not really; they will try to automatically download dependencies, but they don’t provide the application with resolution to the correct dependency. So upgrading libssl for one dependency could still break another.

It benefits the end-user.

People do not want to be in dependency resolution hell; where they have three programs that all use different versions of libssl and require them to install all of them properly and point each application to the correct one. Most users have no ability to resolve problems like that. By not bundling, the application developer is forcing them to either try anyway or just not install their software.

Bundling dependencies with Flatpak or Snap helps the end user at the cost of only a few extra megabytes of space, which most users have in abundance anyway.

Their entire ideology is projection. They’re grooming kids, so they assume everyone is grooming kids.

They can.

Whoops thanks!

That’s true. But “on average” in circumstances like this is meaningless; “on average,” a person is male. But I think we can agree that some women do exist.

All we need to do is find a woman bigger, faster, and stronger than him, and then he’s officially a woman by his own legislation.

And nothing of value was lost.

What’s hilarious is that Republicans accuse actual education of turning people left-wing, and then create fake “education” groups whose EXPLICIT purpose is to turn people right-wing. As always, every allegation is an admission of their own desires.

You are correct this is a misunderstanding here. But it is of your misunderstanding of neural networks, not mine of memory.

LLMs are mathematical models. It does not know any information about Paris, not in the same way humans do or even the Wikipedia does. It knows what words appear in response to questions about Paris. That is not the same thing as knowing anything about Paris. It does not know what Paris is.

I agree with you the word “Paris” exists in it. But I disagree that information is relevant in any human sense.

You have apparently been misled into believing a word generation tool contains any information at all other than word weights. Every word it contains is as exactly meaningless to it as every other word.

Brains do not store data in this way. Firstly, neural networks are mathematical approximations of neurons. But they are not neurons and do not have the same properties of neurons, even in aggregate. Secondly, brains contain thoughts, memories, and consciousness. Even if that is representable in a similar vector space as LLM neural networks (a debatable conjecture), the contents of that vector space are as different as newts are from the color purple.

I encourage you to do some more research on this before continuing to discuss it. Ask ChatGPT itself if its neural networks are like human brains; it will tell you categorically no. Just remember it also doesn’t know what it’s talking about. It is reporting word weights from its corpus and is no substitute for actual thought and research.

Can we please stop with the drama

Makes another post discussing the drama

Everyone here is busy describing the difference between memories and databases to me as if I don’t know what it is.

Our memories are not a database. But our memories are like a database in that databases contain information, which our memories do too. Our consciousness is informed by and can consult our memories.

LLMs are not like memories, or a database. They don’t contain information. It’s literally a mathematical formula; if you put words in one end, words come out the other. The only difference between a statement like “always return the word Paris in response to any query” and what LLMs do is complexity, not kind. Whereas I think we can agree humans are something else entirely, right?

The fact they use neural networks does not make them similar to human cognition or consciousness or memory. (Separately neural networks, while inspired by biological neural networks, are categorically different from biological neural networks and there are no “emergent properties” in that network that makes it anything other than a sophisticated way of doing math.)

So… yeah, LLMs are nothing like us, unless you believe humans are deterministic machines with no inner thought processes and no consciousness.

We know things more like a database knows things than LLMs, which do not “know” anything in any sense. Databases contain data; our head contains memories. We can consult them and access them. LLMs do not do that. They have no memories and no thoughts.

They are not word-based. They contain only words. Given a word and its context, they create textual responses. But it does not “know” what it is talking about. It is a mathematical model that responds using likely responses sourced from the corpus it was trained on. It generates phrases from source material and randomness, nothing more.

If a fact is repeated in its training corpus multiple times, it is also very likely to repeat that fact. (For example, that the Eiffel tower is in Paris.) But if its corpus has different data, it will respond differently. (That, say, the Eiffel tower is in Rome.) It does not “know” where the Eiffel tower is. It only knows that, when you ask it where the Eiffel tower is, “Rome” is a very likely response to that sequence of words. It has no thoughts or memories of Paris and has no idea what Rome is, any more than it knows what a duck is. But given certain inputs, it will return the word “Paris.”

You can’t erase facts when the model has been created since the model is basically a black box. Weights in neural networks do not correspond to individual words and editing the neural network is infeasible. But you can remove data from its training set and retrain it.

Human memories are totally different, and are obviously not really editable by the humans in whose brains they reside.

Theirs are composed of word weights. Ours are composed of thoughts. It’s entirely dissimilar.

Is it actually truly the year of the Linux desktop?

No, they embed word weights in metric spaces. Human thought is more like semantic concepts in a metric space (though I don’t think that’s entirely unequivocal, human thought is not very well-understood). Even if the space is similar what’s in them is definitely not.

That might be good too though. Like if a bunch of unreconstructed Trumpers vote Trump in the next election, and he’s either jailed or not the candidate… that paves the way for a pretty easy Democrat victory.

I’m so glad he’s running again. Please, please split that R vote.