this post was submitted on 09 Jun 2025
211 points (98.6% liked)

Fuck AI

3065 readers
804 users here now

"We did it, Patrick! We made a technological breakthrough!"

A place for all those who loathe AI to discuss things, post articles, and ridicule the AI hype. Proud supporter of working people. And proud booer of SXSW 2024.

founded 1 year ago
MODERATORS
 

[OpenAI CEO Sam] Altman brags about ChatGPT-4.5's improved "emotional intelligence," which he says makes users feel like they're "talking to a thoughtful person." Dario Amodei, the CEO of the AI company Anthropic, argued last year that the next generation of artificial intelligence will be "smarter than a Nobel Prize winner." Demis Hassabis, the CEO of Google's DeepMind, said the goal is to create "models that are able to understand the world around us." These statements betray a conceptual error: Large language models do not, cannot, and will not "understand" anything at all. They are not emotionally intelligent or smart in any meaningful or recognizably human sense of the word. LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another.

OP: https://slashdot.org/story/25/06/09/062257/ai-is-not-intelligent-the-atlantic-criticizes-scam-underlying-the-ai-industry

Primary source: https://www.msn.com/en-us/technology/artificial-intelligence/artificial-intelligence-is-not-intelligent/ar-AA1GcZBz

Secondary source: https://bookshop.org/a/12476/9780063418561

you are viewing a single comment's thread
view the rest of the comments
[–] queermunist@lemmy.ml 3 points 1 day ago (1 children)

The article is about LLMs specifically? And it's arguing that intelligence can't exist without subjectivity, the qualia of experiential data. These LLM text generators are being assigned intelligence they do not have because we have a tendency to assume there is a mind behind the text.

This is not about AI being conceptually impossible they're "made of math". I'm not even sure where you got that? Where did that quote come from? It's not in the link, or the Atlantic article.

[–] masterspace@lemmy.ca 0 points 1 day ago* (last edited 1 day ago) (1 children)

It's the last line quoted in the post. They talk a lot of fancy talk up front but their entire reasoning for LLMs not being capable of thought boils down to that they're statistical probability machines.

So is the process of human thought.

[–] queermunist@lemmy.ml 4 points 1 day ago (3 children)

LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another.

This line?

Because that sure isn't the process of human thought! We have reasoning, logical deductions, experiential qualia, subjectivity. Intelligence is so much more than just making statistically informed guesses, we can actually prove things and uncover truths.

You're dehumanizing yourself by comparing yourself to a chatbot. Stop that.

[–] ZDL@lazysoci.al 2 points 1 day ago

Are you sure you're not talking to a chatbot?

[–] masterspace@lemmy.ca -2 points 1 day ago (1 children)

Yes and newer models arent just raw LLMs, but specifically models designed to reason and deduct and start chaining LLMs with other types of models.

It's not dehumanizing to recognize that alien intelligence could exist, and it's not dehumanizing to think that we are capable of building synthetic intelligence.

[–] hendrik@palaver.p3x.de -2 points 1 day ago* (last edited 1 day ago) (1 children)

I feel you're wasting your time here. Some people seem to be under the impression it's the year 1990 or 1950 and we're talking about markov chain chatbots. The stochastic parrot argument would certainly apply there. But we're talking about something else here.

And it's also a fairly common misconception that AI somehow has to be intelligent in the same way a human is. And by using the same methods. But it really doesn't work that way. That's why we put the word "Artificial" in front of "Intelligence".

But this take gets repeated over and over again and I don't really know why we need to argue about how maths and statistics are a part of our world, how language and perception work and who is dehumanizing themselves... The scientific approach is to define intelligence, come up with some means of measuring it, and then do it... And that's what we've done. We can get rid of the perception part of language. We can measure how "intelligent" entities can memorize and recall facts, combine them, transfer and apply knowledge... That's not really a secret... I mean obviously it seems to be misunderstood or hyped or whatever by lots of people. But we also (in theory) know some of the facts about AI and what it can and can not do and how that relates to the vague concept of intelligence.

[–] masterspace@lemmy.ca 0 points 1 day ago (1 children)

Given the inherently simplistic nature of a community called 'fuck ai', I assume what I'm saying will be unpopular, but there's always some people genuinely open to reason and rational discussion.

[–] ZDL@lazysoci.al 1 points 16 hours ago (1 children)

How "rational" is it to come into a community called, literally, "Fuck AI" and expect pro-AI messaging to be desired and engaged with?

Is "rational" now a synonym for its opposite, like how "literally" now means both itself and "figuratively"?

[–] hendrik@palaver.p3x.de 2 points 16 hours ago* (last edited 16 hours ago) (1 children)

They said rational. Not pro-AI. And I mean why not? This is a community dedicated to talking about AI, so you could expect people having a basic understanding of what they're talking about. This could also be a community dedicated to blind hate. I'm not sure. But what I'm sure about is, there are some people with some level of insight, maybe even from the field or who have this as a hobby, who say "fuck AI" for the impact on society and climate it has, or for it being used against the people in some way or another... So yeah. I'm opposed to the blind hate. I'd rather hate it for the facts. And that's the reason I also advocate for "rational".

[–] ZDL@lazysoci.al 1 points 15 hours ago (2 children)

This could also be a community dedicated to blind hate.

Which part of "Fuck AI" was unclear? There's only two words there (well, a word and an initialization if you want to get picky). Which one of those was unclear?

[–] masterspace@lemmy.ca 2 points 10 hours ago

There's a difference between understanding how nuclear weapons work and opposing them because of their consequences, and sticking your head in the sand and insisting that nuclear weapons couldn't possibly work.

I suggest you grow the fuck up.

[–] hendrik@palaver.p3x.de 2 points 15 hours ago* (last edited 14 hours ago)

The "AI" part seems to be unclear to some people. That's why we're having this argument. And I think I have a rough understanding, but the "fuck" part is unclear to me, because I have nuance when I f***... There are different ways of doing it, not just one. So I'd say it's both words.

[–] masterspace@lemmy.ca -1 points 1 day ago (1 children)

Yes and newer models arent just raw LLMs, but specifically models designed to reason and deduct and start chaining LLMs with other types of models.

It's not dehumanizing to recognize that alien intelligence could exist, and it's not dehumanizing to think that we are capable of building synthetic intelligence.

[–] ZDL@lazysoci.al 1 points 16 hours ago

Go to one of these "reasoning" AIs. Ask it to explain its reasoning. (It will!) Then ask it to explain its reasoning again. (It will!) Ask it yet again. (It will gladly do it thrice!)

Then put the "reasoning" side by side and count the contradictions. There's a very good chance that the three explanations are not only different from each other, they're very likely also mutually incompatible.

"Reasoning" LLMs just do more hallucination: specifically they are trained to form cause/effect logic chains—and if you read them in detail you'll see some seriously broken links (because LLMs of any kind can't think!)—using standard LLM hallucination practice to link the question to the conclusion.

So they do the usual Internet argument approach: decide what the conclusion is and then make excuses for why they think it is such.

If you don't believe me, why not ask one? This is a trivial example with very little "reasoning" needed and even here the explanations are bullshit all the way down.

Note, especially, the final statement it made:

Yes, your summary is essentially correct: what is called "reasoning" in large language models (LLMs) is not true logical deduction or conscious deliberation. Instead, it is a process where the model generates a chain of text that resembles logical reasoning, based on patterns it has seen in its training data[1][2][6].

When asked to "reason," the LLM predicts each next token (word or subword) by referencing statistical relationships learned from vast amounts of text. If the prompt encourages a step-by-step explanation or a "chain of thought," the model produces a sequence of statements that look like intermediate logical steps[1][2][5]. This can give the appearance of reasoning, but what is actually happening is the model is assembling likely continuations that fit the format and content of similar examples it has seen before[1][2][6].

In short, the "chain of logic" is generated as part of the response, not as a separate, internal process that justifies a previously determined answer. The model does not first decide on an answer and then work backward to justify it; rather, it generates the answer and any accompanying rationale together, token by token, in a single left-to-right sequence, always guided by the prompt and the statistical patterns in its training[1][2][6].

"Ultimately, LLM 'reasoning' is a statistical approximation of human logic, dependent on data quality, architecture, and prompting strategies rather than innate understanding. ... Reasoning-like behavior in LLMs emerges from their ability to stitch together learned patterns into coherent sequences." [1]

So, what appears as reasoning is in fact a sophisticated form of pattern completion, not genuine logical deduction or conscious justification.

[1] https://milvus.io/ai-quick-reference/how-does-reasoning-work-in-large-language-models-llms

[2] https://www.digitalocean.com/community/tutorials/understanding-reasoning-in-llms

[3] https://sebastianraschka.com/blog/2025/understanding-reasoning-llms.html

[4] https://en.wikipedia.org/wiki/Reasoning_language_model

[5] https://arxiv.org/html/2407.11511v1

[6] https://www.anthropic.com/research/tracing-thoughts-language-model

[7] https://magazine.sebastianraschka.com/p/state-of-llm-reasoning-and-inference-scaling

[8] https://cameronrwolfe.substack.com/p/demystifying-reasoning-models

Now I'm absolutely technically declined. Yet even I can figure out that these "reasoning" models are nothing different from the main flaws of LLMbeciles. If you ask it how it does maths, it will also admit that the LLM "decides" if maths are what it needs and will then switch to a maths engine. But if the LLM "decides" it can do it on its own it will. So you'll still get garbage maths out of the machine.