this post was submitted on 05 Aug 2026
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[–] m_f@discuss.online 1 points 2 weeks ago (1 children)

not that a human couldn’t solve it, but that they didn’t bother

I'd agree, but with the caveat that that's still impressive and useful. There's kind of an LLM of the gaps thing going on, where LLMs obviously can't produce novel mathematical results, right up until they can. There's limitations and caveats, and one shouldn't trust most anything tech ceos say, but the models continue to progress in capabilities. This is the stuff of science fiction a few years ago.

One day a real AGI is going to be created.

IMO this is real AGI. It's just not ASI. It's a general intelligence because it's capable of handling a huge variety of tasks fairly well without needing to be trained specifically for each one. It's clearly not as smart as humans, and thus isn't an ASI. The specific terms I'm not really attached to, moreso the point is that we need more specific ways of talking about intelligence.

[–] OpenStars@discuss.online 1 points 2 weeks ago (1 children)

right up until they can

Absolutely, this right here. Except they haven't yet. So one day they will be at genius level. But this is not that day. Maybe literally tomorrow? More likely LLMs will never be sufficient on their own, at least in the more neural network sense, and probably in the near future a more mathematical & counting functionality will be grafted onto the LLM, so that a question like "what is 1+1" will at least have awareness of the fact that computationally speaking the answer would be 2, even if the actual answer given is something else, like "little Bobby, you told me that you would consent to going to bed in 10 minutes... but that was 25 minutes ago, and you asked me to do just one more... and we did five more" - you know, true AGI stuff.

Which when it comes will be astonishing. But for now it makes astonishing mistakes, yet techbros want all of the water and electricity and to keep the profits while off-loading all the costs to society at large now, even though the remotest possibility of a true AGI has yet to be demonstrated can come from an LLM - especially alone without other counterbalancing components.

I don't trust anyone who calls these theorem-proving models as "geniuses", senile or otherwise. An LLM yes, an "AI" very much controversially (where the outcome depends upon power and politics, not any kind of search for realism to represent Truth), an intriguing contribution definitely yes, an important one the jury is still our on how useful the result will ultimately be but I preemptively concede that it at least could be, but an AGI... can it do anything other than predict, based on its training data?

It can shuffle, mixing and matching existing things according to a weighted fashion and in a manner such that we humans may find the end product useful (at least sometimes, although a LOT ends up being discarded as well and that is something that I find missing from most discussions - e.g. if a googleplex of monkeys hammering away on a keyboard can produce a Shakespearian play, buried amongst googles of nonsense words, does that make the monkeys "smart"?), but can an LLM think? That is what the "I" stands for, after all?

At which point I've wrapped around to agreeing with you, not that we currently have an AGI bc I think we do not yet (definitely not a "genius" one, senile or otherwise), but that in order to even answer that we would have to know what that "I" even stands for in the first place. Critical thinking? Ability to count and do computations? Articulation of internal processes? And so on.

[–] m_f@discuss.online 1 points 2 weeks ago (1 children)

The trick is to define "think". Nobody has a good definition that isn't circular, because we don't really know enough about how the brain works to come up with an objective, testable definition. It all loops around endlessly, "think" to maybe "conceive" or "ponder" or "know" or "aware" or "conscious" or "sentient", so on and so on. I think LLMs think in the same way that planes and bees both "fly", even if it's very different mechanisms 🤷

I agree that the models aren't geniuses, and we should critically evaluate them, especially whenever OpenAI or other such companies make claims, and all that. I just don't really care for arguing about "is it truly thinking", but maybe that's just the engineer side of me:

https://www.smbc-comics.com/?id=1879

[–] OpenStars@discuss.online 1 points 2 weeks ago

Going off slightly on a tiny tangent: if a human is not merely a set atoms (which get continually replaced anyway) but the PATTERN of them, then a molecular-level copy is essentially the same person. Or at least as functionality indistinguishable from them as makes no difference. Yes obviously the one who existed first "came first", which is a tautology hence uninteresting.

I think the issue with LLMs, for most people who aren't hip-deep into the techbro culture that seems to be basically worshiping the idea of playing the role of a god to create a new technological lifeform, is not whether they think or not, but whether they are USEFUL to them or not. And there's the rub: when an "AI" can search the Internet for you - especially nowadays when it is so enshittified, burying information behind multiple clicks, requests to sign-up to newsletters, JavaScript and even CSS interactivity that fights you at every step of the way trying to glean information from a website - and return something useful, like a recipe to cook food, then people enjoy using it! Until it turns out that the recipe is fatal to humans that consume the product - e.g. when it contains glue in it (arguably producing the best picturesque foodstuff products, suitable for visual presentation rather than edible consumption), or razor blades (that one representing straight-up poisoning the well scenarios, but since those can often represent sarcasm - even in material that long predates the emergence of LLMs hence was genuinely meant for a fellow human to read - it is not always so easy to detect).

My primary issue lies with how modern LLMs offers the form of an answer, while cheapening out on the substance. It thus flips the standard mode of evaluation, making it more rather than less difficult for someone to use it to find information. e.g. if you come across a page on the internet that is full of spelling errors, then the chances of its content being accurate in spite of that is next to nil. However, ChatGPT has straight up told people to do things that would literally kill them. I am used to an older model of computation where if you ask a computer what 1+1 is it will deterministically always tell you "2" (aside from issues such as hardware failure, including running low on battery power supply), whereas LLMs simply work according to an entirely different model, where the answer might sometimes be 3, or 1 again, or the message to KYS, etc. And I don't think that most people - especially literal children - realize the switch. They are bullshit generators - which I mean to say not only that in the derogatory sense, but more foundationally that is literally what they were designed to be, in being able to provide an answer in a certain format and when an answer is not forthcoming then to simply make shit up... by design.

So I would guess that the "is it thinking" questions might come more from those techbros who are in love with the idea of technological emergence of sentience, whereas most common folk simply want to be able to find information on the internet, especially now that SEOs have made Google notably less useful at that task. And for them, hearing about whether a tool is at the "genius" level or not is a proxy for how much they can place trust in the outcome of a query. Which is to say, not much - a position that Sam Altman is expressing himself so by no means a niche or even exclusively outsider concern.