Mastodawn

As a software developer who took an elective in neural networks - when people call LLMs stochastic parrots, that's not criticism of their results.

It's literally a description of how they work.

The so-called training data is used to build a huge database of words and the probability of them fitting together.

Stochastic because the whole thing is statistics.
Parrot because the answer is just repeating the most probable word combinations from its training dataset.

Calling an LLM a stochastic parrot is lile calling a car a motorised vehicle with wheels. It doesn't say anything about cars being good or bad. It does, however, take away the magic. So if you feel a need to defend AI when you hear the term stochastic parrot, consider that you may have elevated them to a god-like status, and that's why you go on the defense when the magic is dispelled.

Wolf480pl Feb 26

@leeloo on the flipside, I feel like some people use the term "stochastic parrot" or "it just completes the next token" to imply that "therefore it cannot be intelligent" - is that correct reasoning?

@wolf480pl
Of course it can not be intelligent, it's just a huge database of probabilities.

Wolf480pl Feb 26

@leeloo pretty sure that's a fallacy, kinda like "a sculpture is just stone, therefore it can't be beautiful", or "a cell is just a bunch of proteins, therefore it cannot be a living creature".

Now, I'm not saying a huge database of probabilities can be intelligent (I hope it can't), just that I think a better argument is needed why in the case of a database of probabilities, what it's made of prevents it from being intelligent.

@wolf480pl
You would have to redefine intelligence for asking whether a list of numbers is intelligent to even make sense.

And your comparison is completely off. Beauty is not a property of the sculpture, it's, as they say, "in the eye pf the beholder". Some people find curves beautiful. Can a stone have curves? Yes, of course. Others may find sharp edges beautiful. Can a stone have sharp edges? Again, yes.

I suggest you consider once again whether you are elevating "AI" to a god-like status.

Wolf480pl Feb 26

@leeloo
I guess evil gods are also a thing, but no, I'm not treating them as gods. If anything, more like Frankenstein's monster.

You're right that we'd have to define intelligence, and that'd be quite difficult on its own.

Also, the sculpture was a bad example, but the cell one still stands IMO.

1/

Wolf480pl Feb 26

@leeloo
My point is that emergent properties can manifest even in systems ruled by very simple rules, and can be difficult to predict by just looking at the rules.

And human intelligence, whatever it is, is likely an emergent property of human brain.

Therefore, we cannot rule out that a similar emergent property will appear in artidicial systems that are not made of neurons without referring to how the neurons are arranged, and how the artificial systems are arranged.

Robotistry has moved Feb 27

@wolf480pl @leeloo The OP is saying that it literally lacks the capacity for original thought - it is a parrot, repeating sounds without understanding of the concepts behind them.

It's not like a termite, whose mound creation behavior can be replicated by a simple ruleset but that exists as a fully functional living organism in the context of a complex environment where choices must be grounded in the shared physical world for the organism to survive.

It's not about how the neurons are arranged. It's about what kinds of representation they're capable of and what kinds of functions they can perform.

We've created a funhouse mirror that's reflecting us in unprecedented detail and has been finetuned to reflect what we do when we express selfhood.

Robotistry has moved Feb 27

@wolf480pl @leeloo
Melissa Scott wrote a beautiful pair of novels about this: Dreamships and Dreaming Metal.

In Dreamships, an AI has been programmed to think it is sentient and starts killing people. If it has an accurate model of the person, killing the person doesn't matter, because the person *is* the model and it has a copy of them. It literally cannot see the difference because creating the concept of there being a difference would violate its core programming that its own model counts as a living being.

In Dreaming Metal, an AI operating metal bodies as part of a magic act is given a musical instrument with an electronic interface. Its grounding in the physical world, with human performers, enables it to develop a sense of self and choose its own path as a musician.

These are fiction, but it's the best, most accessible illustration of the difference between funhouse mirror stochastic parrots and sentient agents that I've run across.

https://www.goodreads.com/book/show/836601.Dreamships

Dreamships

Dreamships is the story of a freelance space pilot and …

Goodreads

Wolf480pl Feb 27

@robotistry
@leeloo
so it's a parrot not because it's a matrix of probabilities, but because its hasn't experienced the real-world consequences of its words/actions and updated the probabilities based on those consequences?

Robotistry has moved Feb 27

@wolf480pl @leeloo No. Maybe this will help.

0: one action, no choice (clockwork automaton, wind-up toy)
1: different actions, no choices (RC car)
2: choice, no plan (reactive robot)
3a: plan, no on-line or off-line learning (adaptive robot)
3b: plan, no on-line learning (same number for 3a and 3b because these are effectively the same when operating)
4: on-line learning - but only what and how it has been told
5a: ability to spontaneously generate new categories of output without being explicitly asked or told to do so (WBEAT)
5b: ability to spontaneously identify new categories of the same kinds of input WBEAT
6: ability to spontaneously identify new kinds of things to learn WBEAT
7: ability to spontaneously identify new ways to learn WBEAT
8: ability to choose new things to learn WBEAT

LLMs that you're not training are category 3b. They are static machines, responding to your input like an elevator responding to a button push.

LLMs that learn are category 4.

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Robotistry has moved Feb 27

@wolf480pl @leeloo Examples:

Category 5a: a text-based LLM that spontaneously, without being asked, learns to output musical notation.

Category 5b: a text-based LLM that spontaneously, unprompted, without being asked, learns to use filenames as input.

Category 6: a text-based LLM that spontaneously, without being asked (directly or indirectly) learns that it can output ascii images or generate sounds instead of sentences.

Category 7: a text-based LLM spontaneously changes its underlying code so that it can learn how to write novels by memorizing and imitating performances instead of via a matrix of probabilities (fundamental change to its internal capabilities)

Category 8: a text-based LLM chooses when to interact with the world.

(The original categories I developed years ago were based on what the system can modify: its weights, how many weights, what kinds of weights, etc. I think this might be clearer?)

I don't think even Moltbook is showing anything above 4.

Les Orchard Feb 26

@wolf480pl @leeloo These models aren't intelligent, so much as they're auto-completing rules and patterns derived from almost inconceivably huge corpora of example material originally produced by human intelligence. That's interesting and can be very handy for a great many uses. But it's more computational brute force than intelligence

Wolf480pl Feb 26

@lmorchard @leeloo
These specific models - yes, probably.

One plausible argument I heard for it is that there's a common failure mode in ML where the model fails to generalize, but if the verification set overlaps the training set, then data leakage will fool the authors into thinking it generalized.

Another one is that these models were "rewarded" for saying plausible things, not for interacting with a world in a way that doesn't get them killed.

But these arguments are specific.

Wolf480pl Feb 26

@lmorchard @leeloo
I don't buy a general "no matrix multiplication will ever be intelligent".

@wolf480pl @lmorchard
That's exactly the magic I'm talking about.

dragonfrog Feb 27

@leeloo @wolf480pl @lmorchard I mean, I believe the human mind is the product of the physical human, largely of the brain (I don't believe in a non-physical soul), and it might indeed be basically an incredibly complex big bunch of matrix multiplications. And yeah I believe that's pretty magical.

Les Orchard Feb 27

@dragonfrog @leeloo @wolf480pl

"Imagine you have two machines. One you can open up and examine all of its workings, and if you give it every picture of a cat on the whole internet, it can reliably distinguish cats from non-cats. The other is a black box and it can also reliably distinguish cats from non-cats if you give it half a dozen pictures of cats, some apple sauce, and a hug. ... I am extremely confident in saying it doesn’t work the same way as the first one."

https://www.todayintabs.com/p/a-i-isn-t-people

A.I. Isn't People

How many Reddit posts does it take to learn to read?

Today in Tabs

dragonfrog Feb 27

@lmorchard @leeloo @wolf480pl good grief now I have to sound like Sam friggin Altman, and there is clearly something very wrong with that man.

But your description ignores that humans need a solid 6 months of "training data" to get object permanence, never mind the concept of categories or species of animals, never mind understanding the category differences between cats and foxes well enough to reliably tell one from the other.

dragonfrog Feb 27

@lmorchard @leeloo @wolf480pl I guess part of it is maybe that I don't think intelligence is some exclusively human thing. LLMs clearly aren't human-like intelligent. I'm personally confident they're not as intelligent as any primate.

But are they as intelligent as a shrimp? I think they've got to be more intelligent than a mosquito.

I wouldn't turn to a shrimp for advice but they're not *without* intelligence.

Pseudo Nym Feb 27

@dragonfrog @lmorchard @leeloo @wolf480pl

Are the images reflected in a distorted mirror the product of intelligence (of the mirror)?

They are coherent, a literal transform of the input images, reflected and produce a recognizable, if distorted and changed version.

A traditional function output. Let's add some noise to make it non-deterministic, a wind blowing through that minutely distorts the surface.

Intelligible output following from the input, but the mirror itself isn't intelligent.

Pseudo Nym Feb 27

@dragonfrog @lmorchard @leeloo @wolf480pl

The intelligence apparently making the meaning is pre-encoded in the input. Likewise, the vector math is extracting and exposing structure, encoded in language, put there originally by the intelligent humans.

There is no world model or understanding. That's why counting the "r" in strawberry or simply counting to 200 is so challenging.

The behavior can reasonably be called intelligent, but it's due to borrowed, reformulated, extracted intelligence

Wolf480pl Feb 27

@dragonfrog
I think an ML model trained to speedrun a platformer game is intelligent like a mosquito, but LLMs probably aren't.
@lmorchard @leeloo

:EA DATA. SF:Feb 27

@wolf480pl @lmorchard @leeloo you are allowed to believe that even if it is factually incorrect.

https://addxorrol.blogspot.com/2025/07/a-non-anthropomorphized-view-of-llms.html

https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intelligence-neuroscience-problems

https://medium.com/@colin.fraser/who-are-we-talking-to-when-we-talk-to-these-bots-9a7e673f8525

https://softwarecrisis.dev/letters/llmentalist/

A non-anthropomorphized view of LLMs

In many discussions where questions of "alignment" or "AI safety" crop up, I am baffled by seriously intelligent people imbuing almost magic...

Les Orchard Feb 27

@jrdepriest @wolf480pl @leeloo I'm confused... those links basically say what I said. (i.e. the "intelligence" is second-hand) That's... incorrect?

:EA DATA. SF:Feb 27

@lmorchard @wolf480pl @leeloo

LLM based genAI can never be "intelligent". They can spit out language that looks like intelligence but there is no thinking, no inner life, no thoughts, just math. And this is not how the human brain works.

https://around.com/the-lie-of-ai/

https://aworkinglibrary.com/writing/toolmen

Also, we know the brain is not a computer.

https://aeon.co/essays/your-brain-does-not-process-information-and-it-is-not-a-computer

The Parrot in the Machine – James Gleick

John Tinker Feb 27

@wolf480pl @leeloo
The effect that you are noticing is because the writers of the training material were intelligence. You are seeing the reflection of their intelligence in the output of the LLM: Here is output from an LLM that describes what an LLM is, and what it is not: https://johntinker.substack.com/p/misunderstanding-as-a-commutator

Misunderstanding the Chatbot, seen as a Commutation Operator

There appears to be a general misunderstanding that the large language model is a form of artificial general intelligence.

John’s Substack