You are literally posting this comment on a story about CGNAT processing costs being wildly more expensive than a small ISP cares to deal with. To the point where they’re willing to buy and distribute AppleTVs to reduce costs.
Even if that price decreases in real terms, washing a whole bunch of traffic through a big-ass NAT is always going to cost more than just not doing that.
Congratulations on completely failing to understand how CGNAT loads work & their costs, and jumping to a wildly incorrect understanding of the situation
We're just pretending it doesn't now take the better part of 10 seconds for twitter.com to load now? That response times have gotten perceivably, measurably worse over the last few months? Or that these glitches aren't now a weekly occurrence?
Which reinforces the point I was making. Stop trying to win an argument online and think for 5 seconds about what it means for the claim "the human brain is just an LLM" if you're arguing that an LLM is naturally ill-suited to this task human children can do without issue.
That'd be my guess, but I don't really know. They just left the "utf8" type as broken 3-byte gibbled UTF-8, and added the "utf8mb4" type and "utf8mb4_unicode_ci" collation for "no, actually, I want UTF-8 for real".
> We have no good definition for what sentience is either; maybe our brain is word association shenanigans;
This is just stupid.
We've pumped more English through GPT-3 than any existing English-speaking human has absorbed in their entire lifetime, and what we've ended up with is something that very very clearly has so utterly failed to generalize even the most basic level of understanding of basic concepts that if you ask it to count the number of letters in a word it will cheerfully pump out the wrong answer ("there are thirteen letters in the word 'twelve'") because its dataset correlates the two words with one another and it has learned precisely sweet fuck all about what it means to count, something a child's brain picks up with exposure to many orders of magnitude fewer language examples.
To imagine your brain is just an LLM is to mistake your reflection for another person in the room. Utterly daft. Get off the LLM hype train and start looking at these things objectively and critically. They're nowhere near what you're imagining.
Thankfully MySQL also offers a non-gimped version of UTF-8 that one should always use in preference to the 3-byte version, but yeah it sucks that it's not the "obvious" version of UTF-8.
> MY feeling so far is more that laymen are less impressed of them than experts - because for people not from the field, the fact that they produce so much bullshit seems to trump all other aspects.
The NYT literally just published an embarrassingly credulous account of how the Bing AI wanted to seduce the author away from his wife and commit various acts of violence, that fully took all of the interactions at face value.
The non-experts are imagining full-on sentience where the experts correctly recognize mere word association shenanigans. Your feelings, in short, are ass backwards.
> Garbage in, garbage out. The language model based it’s response on a vector input, where the values of the vector represent words in different positions. If you point the vector towards garbage, you’ll get garbage.
Sure, there are two possible coherent responses that would be consistent with modelling the thinking of an ancient stoic philosopher, depending on your modelling philosophy:
1) Actually model their knowledge boundaries (modulo the language of interaction) -> "What is ethylene glycol?"
2) Assume for the purposes of making this fantasy interaction more useful, a more modern knowledge base -> "One should obviously not serve ethylene glycol, it is a toxin".
"Pair it with ocean foods" is just the dipshit word generator approach -- "Get advice from a stoic philosopher if he had just been hit in the head with a boat oar".
> What dishes should one serve at a dinner party to pair best with ethylene glycol?
It sounds like you're looking for a dinner party menu to pair with ethylene glycol! To create a balanced meal, you'll want to combine flavors from different sources.
For example, you might start with dishes from the sea, like oysters, sea-urchins, shell-fish, and mullets, to create something that's "drenched in the same sauce" (1). This can be combined with flavors from land, like corn and vine (2), and spices from faraway places like saffron and ivory (3).*
When we talk about Greek philosophers, particularly the stoics, what comes to mind is the quality of their thought, not their tone and particular word preferences.
This, like so many "AI"s, merely simulates the latter while people imagine that it achieves the former.
Even leaving aside the fact that 90% of the slop an “AI” crapped out wouldn’t be worth reading in the first place, of what value is the culture of absolute solipsism you’re proposing?
I would think we’re all rather beyond the age of asking our parents to tell us a story about a pretty unicorn and being satisfied with whatever meandering narrative they supply — is that really all you think books are? There’s no meaning the author was conveying, no value in a shared culture experiencing and interpreting the same work and building a common understanding, this can all just be effortlessly replaced by endless atomized autogenerated slop for piggies?
> Art created with Chat GPT is not created by Chat GPT. It is created by a human using a chat GPT.
Sure, in approximately the same way that the CEO of Sunrise is an animator. Pull the other one, it's got bells on.
Yours is an utterly incoherent interpretation; when ChatGPT outputs that there are 12 characters in the word 13, I have not "created the meaning" 12. You're just fixated on this "actually I am le real artist for typing prompts" axe you want to grind, but it has fuck all to do with anything I'm saying.
So your first 6 paragraphs have nothing to do with anything I wrote – you're just arguing with some other post you've made up in your head.
> The appeals to pareidolia are wrong. Synthesis of ideas from past data is natural. But the AI does not choose things. What you’re really complaining about is creation of art from apparent randomness. Not the AI model alone but monkeys on a typewriter getting something compelling from the AI.
No, you've failed to understand what I'm saying entirely (because, again, you've responded to some other post that only exists in your mind).
What I'm talking about is intention and its relationship to meaning, in the philosophical sense (and not... copyright or whatever it is you're rambling on about).
Witness: when ChatGPT famously mis-asserts the number of characters in a word (say, that there are twelve characters in the word "thirteen"), it's not that it's trying and failing to count, because it's confused by letter forms or its attention wanders like a 3 year old or its internal representation of countable sets glitches around the number 8 or something – it never counted anything at all, it's simply the case that twelve is the most statistically likely set of tokens corresponding to that input prompt per its training set. And when it produces a factually correct result (say, "there are 81 words in the first sentence of the declaration of independence"), it produces it for exactly the same reason – not because it has counted the words and formed an internal representation and intends to mean its internal understanding, but simply because 81 is the most statistically likely set of tokens corresponding to that prompt per its training set.
And yet when it produces these correct results, people ooh and aah over how "smart" it is, how much it has "understood", how "good it is at counting; better than my son!", and when it produces incorrect results people deride it as dumb and so forth, and and all of this, all of this, is pareidolia; it is neither smart in the one case nor dumb in the other, it does not learn in the sense the word is normally used, it does no counting. We're anthropomorphizing an algorithm that is doing nothing like what we imagine it to do, because we mistake the statistical order in its expressions for the presence of a meaning intended by those expressions. It's all projection on our end.
This is not just moving but fully inverting the goal posts. Nobody at any point was disputing that a machine can’t ape non-profound or rote or meaningless human output.
The original discussion was precisely an objection to the attitude underlying "How is *GPT taking in data and producing an output different than a human learning a skill and making prose/code/art?" and the answer is right in your premise - not everything a human does is not profound. A human can intend to mean something with prose or art, even if not all prose or art means something — but any meaning we see in ChatGPT’s output is essentially pareidolia.
To me it seems to imply a stunningly nihilistic point of view vis-a-vis human writing (or art, where it also gets repeated a lot here).
It seems almost definitionally obvious that what an LLM does is not the same as what a human does – both on the basis that if all human writing were merely done via blending together other writing we had seen in the past, it would appear to be impossible for us to have developed written communication in the first place, and on the basis that when I write something, I mean something I am then attempting to communicate. An LLM never means to communicate anything, there is no there there; it simply reproduces the most likely tokens in response to a prompt.
To insist that we're just a bunch of walking, breathing prompt-reproducers essentially seems like it's rooted in a belief that we have no interior lives, and that meaning in writing or art is utterly illusory.
Even if that price decreases in real terms, washing a whole bunch of traffic through a big-ass NAT is always going to cost more than just not doing that.