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PaperclipPerfector  11mo ago (text post)   33043 thread views

Culture War Roundup for the week of July 7, 2025

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I continue to be baffled that anybody takes these bots seriously, or sees Grok or xAI or their competitors as anything other than nonsense generators. A slight change to the flavour of the nonsense doesn't really change my opinion any. Perhaps it moves me in the direction of thinking that Musk is childish and temperamental, but I already thought that, so it doesn't make much difference.

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It's not "naive" it's generating an average. If your training data is full of extraneous material (or otherwise insufficiently tokenized/vetted) your response will also be full of extraneous material, and again its not rationalizing it's averaging.

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Again, its not "naive" it is generating an average if the bulk of the tokenized training data related to your prompt is press releases, the response is going to reflect the press releases. Whether those press releases are true or false doesn't enter into the equation. This is expected.

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Can you elaborate on what you think words like "read", "searches", and "know" mean in this context. Im not asking just to pedantic, how you think about this question has informs how you approach algorithmic behavior.

Edit: if that is a bit too abstract instead try explain why you believe that the algo "knows" which claims are likely spurious and then explain why you would expect that to have any influence on the algorithm's output.

My experience with AI bots has generally been that they are extremely articulate when it comes to producing correct English text, but they have no awareness or intentionality and therefore no sense of relationship to fact, and no sense of context or meaning. What they do very well is string together words in response to prompts, and despite heroic efforts to get their output to be more fact-sensitive, the fundamental issue has never really been overcome.

I call them nonsense because I think that sense requires some sort of relationship to both fact and context. To be sensible is to be aware of your surroundings. That's not the case with bots.

I would add, at least, that this:

Deepseek, however, with a bit of prompting can be completely insane yet rational and easily smarter than most people you see if you go to any place outside of a professional context.

seems to depend on definitions of rationality or intelligence that I don't think I share. I think bots are very efficient at producing English text, even quite complex text. It's trivial enough to show that a bot can produce a better written letter or better poem or what have you than the average man or woman on the street.

But I think that written verbal acuity is, at best, a very restricted kind of 'intelligence'. In human beings we use it as a reasonable proxy for intelligence and make estimations based off it because, in most cases, written expression does correlate well with other measures of intelligence. But those correlations don't apply with machines, and it seems to me that a common mistake today is for people to just apply them. This is the error of the Turing test, isn't it? In humans, yes, expression seems to correlate with intelligence, at least in broad terms. But we made expression machines and because we are so used to expression meaning intelligence, personality, feeling, etc., we fantasise all those things into being, even when the only thing we have is an expression machine.

Bots and LLMs can produce statements that look very polished, and which purport to describe the world. In many cases, those descriptions are even accurate. But they are still, it seems to me, generating nonsense.

The other day I gave Sonnet 7000 lines of code, (much of it irrelevant to this specific task) and asked it to create a feature in quite general language.

I get out six files that do everything I've asked for and a bunch of random, related, useful things, plus some entirely unnecessary stuff like a word cloud (maybe it thinks I'm one of those people who likes word clouds). There are some weird leap-of-logic hacks, showing imaginary figures in one of the features I didn't even ask for.

But it just works. Oneshot.

How is that not intelligence? What do we even mean by intelligence if not that? Sonnet 4 has to interpret my meaning, formulate a plan, transform my meaning into computer code and then add things it thinks fit in the context of what I asked.

Fact-sensitive? It just works. It's sensitive to facts, if I want it to change something it will do it. I accidentally failed to rename one of the files and got an error. I tell Sonnet about the error, it deduces I don't have the file or misnamed it, tells me to check this and I feel like a fool. You simply can't write working code without connection to 'fact'. It's not 'polished', it just works.

How the hell can an AI write thousands of words of fiction if it doesn't have a relationship with 'context'? We know it can do this. I have seen it myself.

Now if you're talking about spatial intelligence and visual interpretation, then sure. AI is subhuman in spatial reasoning. A blind person is even more subhuman in visual tasks. But a blind person is not necessarily unintelligent because of this, just as modern AI is not unintelligent because of its blind spots in the tokenizer or occasional weaknesses.

The AI-doubter camp seems to be taking extreme liberties with the meaning of 'intelligence', bringing it far beyond the meaning used by reasonable people.

I can't actually tell what you asked a bot to do. You asked a bot to 'create a feature'? What the heck is that? A feature of what? At first I assumed you meant a coding task of some kind, but then you described it as writing 'thousands of words of fiction', which sounds like something else entirely. I have no idea what you had a bot do that you thought was so impressive.

At any rate, I think I've explained myself adequately? To repeat myself:

But I think that written verbal acuity is, at best, a very restricted kind of 'intelligence'. In human beings we use it as a reasonable proxy for intelligence and make estimations based off it because, in most cases, written expression does correlate well with other measures of intelligence. But those correlations don't apply with machines, and it seems to me that a common mistake today is for people to just apply them. This is the error of the Turing test, isn't it? In humans, yes, expression seems to correlate with intelligence, at least in broad terms. But we made expression machines and because we are so used to expression meaning intelligence, personality, feeling, etc., we fantasise all those things into being, even when the only thing we have is an expression machine.

Yes, a bot can generate 'thousands of words of fiction'. But I already explained why I don't think that's equivalent to intelligence. Generating English sentences is not intelligence. It is one thing that you can do with intelligence, and in humans it correlates sufficiently well with other signs of intelligence that we often safely make assumptions based on it. But an LLM isn't a human, and its ability to generate sentences in no way implies any other ability that we commonly associate with intelligence, much less any general factor of intelligence.

Yes, I made the bot do a programming task.

I ALSO observed it write long-form fiction. This is not an advanced reading comprehension task. It should be obvious that programming and creative writing are two different things.

I think I've explained myself adequately?

You said this:

I call them nonsense because I think that sense requires some sort of relationship to both fact and context. To be sensible is to be aware of your surroundings.

Normal people would think that 'fact' and 'context' would be adequately achieved by writing code that runs and fiction that isn't obviously derpy 'Harry Potter and the cup of ashes that looked like Hermione's parents'. But you have some special, strange definition of intelligence that you never make clear, except to repeat that LLMs do not possess it because they don't have apprehension of fact and context. Yet they do have these qualities, because we can see that they do creative writing and coding tasks and as a result they are intelligent.

I don't buy your appeal to normal people here. I think that most normal people do not think that chatbots are intelligent.

Realistically, I don't think most people can explain why they're not intelligent, because most people don't have definitions of intelligence on-hand. I think for most people it's an I-know-it-when-I-see-it situation. That's why we need to philosophise a bit about it in order to produce more reasonable definitions and criteria for intelligence.

Anyway, I think that intuitions of most normal people would say that bots aren't intelligent, and if we explored that with them, and had a patient, philosophically nuanced conversation about why, we probably would find that most people intuitively think that intelligence involves things like, to quote myself, 'awareness or intentionality'.

I don't buy your appeal to normal people here. I think that most normal people do not think that chatbots are intelligent.

It's hard to say what "normal people" think about this (or even what "normal people" are), but in my experience, people I would consider in that category use the label "AI chatbots" to describe things like ChatGPT or Copilot or Deepseek, while also being aware that "AI" is short for "artificial intelligence." This seems fundamentally incompatible with believing that these things aren't "intelligent."

Now, almost every one of these "normal people" I've encountered also believe that these "AI chatbots" lack free will, sentience, consciousness, internal monologue, and often even logical reasoning abilities. "Stochastic parrots" or "autocomplete on steroids" are phrases I've seen used by the more knowledgeable among such people. But given that they're still willing to call these chatbots "AI," I think this indicates that they consider "intelligence" to mean something that doesn't require such things.

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Well, I wouldn't use intentionality for bots at all. I think intentionality presupposes consciousness, or that is to say, subjectivity or interiority. Bots have none of those things. I don't think it's possible to get from language manipulation to consciousness.

At any rate, I certainly agree that every ideological person believes untrue things about the world. I'm not sure about the qualification 'for instrumental reasons' - I suspect that's true if you define 'instrumental' broadly enough, but at that point it's becoming trivial. At any rate, if you leave off reasons, I am confident that every person full stop holds some false beliefs.

That doesn't seem like the same thing to me, though. Humans sometimes represent the world falsely to ourselves. That's not what bots do. Bots don't represent the world to themselves at all. We sometimes believe falsely; they don't believe at all. They are not the kinds of things capable of holding beliefs.

Even the best models will confidently spout absolute falsehoods every once in a while without any warning.

Buddy, have you seen humans?

As a math nerd I seriously despise this line of argument as it ultimately reduces to a fully generalized argument against "true", "false", and "accuracy" as meaningful concepts.

Let's try a concrete example. Excerpted from here:

The o1 model identified the exact or very close diagnosis (Bond scores of 4-5) in 65.8% of cases during the initial ER Triage, 69.6% during the ER physician encounter, and 79.7% at the ICU

65.8% accuracy isn't that great, but buddy, have you seen humans?

—surpassing the two physicians (54.4%, 60.8%, 75.9% for Physician 1; 48.1%, 50.6%, 68.4% for Physician 2) at each stage.

The state of the art for generating accurate medical diagnoses doesn't involve gathering the brightest highschoolers, giving them another decade(-ish) of formal education, then more clinical experience before asking for their opinions. It involves training an LLM.

I don't think so. Those concepts still have pretty clear meaning and can be applied to the output of AI as well as humans. What this line of argument is disputing is the (often unstated) conclusion: "therefore, AI is not valuable." But this doesn't follow. Humans distort information, accidentally or maliciously, make errors, hallucinate, and are generally somewhat unreliable, but their output still has value. An AI can share all of those same characteristics and still be very valuable as an information processing agent.

I invite further clarification.

Imagine a a trick abacus where the beads move on thier own their own via some pseudorandom process, or a pocket calculator where digits are guaranteed to a +/- 1 range. IE you plug in "243 + 67 =" and more often then not you get the answer "320" but you might just as well get the answer "310", "321" or "420". After all, the difference between all of those numbers is very small. Only one digit, and that digit is only off by one.

Now imagine you work in a field where numbers are important, you lives depend on getting this math right. Or maybe you're just doing your taxes, and the Government is going to ruin you if the accounts don't add up.

Are you going to use the trick calculator? If not, why not?

That is not an explanation for:

As a math nerd I seriously despise this line of argument as it ultimately reduces to a fully generalized argument against "true", "false", and "accuracy" as meaningful concepts.

You're arguing that since LLMs are not perfectly reliable, therefore they're unreliable. There are different degrees of reliability necessary to do useful things with them. It is a false dichotomy to divide them so. I contend that they've crossed the threshold for many important, once well-paying lines of cognitive labor.

Besides, your thought experiment is obviously flawed. If you're sampling from a noisy distribution, what's stopping you from doing so multiple times, to reduce the error bars involved? I'd expect a "math nerd" to be aware of such techniques, or did your interest end before statistics?

If I had to rely on an LLM for truly high-stakes work, I'd be working double time to personally verify the information provided, while also using techniques like running multiple instances of the same prompt, self-critique or debate between multiple models.

Fortunately, that's a largely academic exercise, since very few issues of such consequences should be decided by even modern LLMs. I give it a generation or two before you can fire and forget.

I have no objections to my own doctor using an LLM, and I use them personally. All I ask is that they have the courtesy and common sense to use o3 instead of 4o.

Besides, the contraption you describe is quite similar to how quantum computing works. You get an answer which is sampled from a probability distribution. You are not guaranteed to get a single correct answer. Yet quantum computers are at least theoretically useful.

Hell, as a maths nerd, you should be aware that the overwhelming majority of numbers cannot be physically represented. If you also happen to be a CS nerd on the side, you might also be aware of the vagaries of floating point arithmetic. Digital computers are not perfect, but they're close enough for government work. LLMs are probably close enough for government work too, given the quality of the average bureaucrat.

Humans are fallible. LLMs are fallible, but they're becoming less so. The level of reliability needed for a commercially viable self-driving vehicle is far higher than that for a useful Roomba. And yet, Waymos are now safer than humans.

I rest my case.

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I'm always right. (except when I'm wrong) I'm in fact many times more accurate than even the best ai models, and I'm just an ordinary person.

I wonder how well you'd do if asked to opine accurately on the range of topics that people demand of their humble chatbots. Better yet, how would you fare if you didn't have access to Google? Search is a relatively new feature for LLMs, and they do better with it enabled.

I doubt you could accurately answer questions regarding astrophysics, botany, niche psychological theories, Color Revolutions, the sexual habits of Australian Indigenes and Ska music.

You would definitely not fare better when it came to specifics like dates and names.

LLMs have grossly superhuman world-knowledge, but not crystalline intelligence. I don't care who you are, not even Gwern could match them.

LLMs do worse with search enabled, because LLM search is garbage in garbage out.

An LLM without search has many advantages over a human without search. But an LLM with search is absolute worthless dogshit garbage compared to a human with search.

I doubt you could accurately answer questions regarding astrophysics, botany, niche psychological theories, Color Revolutions, the sexual habits of Australian Indigenes and Ska music.

I might know much less off the top of my head, but my confidence calibration will be through the roof. Those topics are just begging for hallucinations.

I might know much less off the top of my head, but my confidence calibration will be through the roof. Those topics are just begging for hallucinations.

If knowledge isn't a concern and all we care about is a Brier score, I must regretfully inform you that a rock saying "nothing ever happens" has you beat.

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Sure, but so does everybody else.

I don't. (Not as much as AI at least)

How do you know?

I catch AI spouting falsehoods far more often than AI catches me 🙃

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