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How the Brain Parses Language

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Re: How the Brain Parses Language

#61

Post by paddleon »

HarHarVeryFunny wrote: post #36
rdtsc wrote: post #26

> But what if our neurobiological reality includes a system that behaves something like an LLM? With every technological breakthrough we always posit that the brain has to work like the newly discovered thing. At various times brains were hydraulic, mechanical, electrical, like a computer, like a network. Now, of course, the brain has to be like an LLM.

Yes, but at least now we're comparing artificial to real neural networks, so the way it works at least has a chance of being similar. I do think that a transformer, a somewhat generic hierarchical/parallel predictive architecture, learning from prediction failure, has to be at least somewhat similar to how we learn language, as opposed to a specialized Chompyskan "language organ". The main difference is perhaps that…

> comparing artificial to real neural networks

I had a sad day in college when I thought I'd build my own ANN using C++.

First thing I did was create a "Neuron" class, to mimic the idea of a human neuron.

Second thing I did was realize that ANNs are actually just Weiner filters with a sigmoid on top. The base unit is not a "neuron".

Re: How the Brain Parses Language

#62

Post by adamzwasserman »

retrac wrote: post #54
adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting. One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order an…

These are good points that sharpen the hypothesis. The word order question is interesting — positional encoding vs morphological encoding might have different computational properties for a parser.

One difference I'm betting on: morphological agreement is redundant (same information marked multiple times), while word order encodes information once. Redundancy aids error correction and may lower pattern extraction thresholds. But I'm genuinely uncertain whether that outweighs the structural information carried by strict word order.

Do you have intuitions on which would be "easier" for a statistical learner? Or pointers to relevant literature? The vocabulary size / morpheme count tradeoff is also something I hadn't fully considered as a confound.

Re: How the Brain Parses Language

#63

Post by adamzwasserman »

tgv wrote: post #50
adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

There are more differences between English and French than you just described, and they can affect your measurement. Even the corpora you use cannot be the same. There isn't "ceteris paribus" (holding everything else constant). The outcome of the experiment doesn't say anything about the hypothesis. You're also going to use an artificial neural network to make claims about the human brain? That distance is too large…

The confound concern is fair: no cross-linguistic comparison is perfectly controlled. The bet is that the effect size (if any) will be large enough to be informative despite the noise. But you're right that it's not ceteris paribus in a strict sense.

Your proposal is interesting though. Synthetic manipulation of morphology within a single language. Have you seen this done? The challenge I'd anticipate is that "genderized English" wouldn't have natural text to train on, so you'd need to generate it somehow, which introduces its own artifacts. But comparing French vs artificially gender-neutralized French might be feasible with existing parallel corpora. Worth thinking about as a follow-up.

On the neural network → brain distance: agreed it's a leap. The claim isn't that transformers are brains, but that if both are extracting structure from language, they might reveal something about what structure is there to extract. Fedorenko's own comparison to "early LLMs" suggests she thinks the analogy has some merit.

Re: How the Brain Parses Language

#64

Post by [deleted] »

adamzwasserman wrote: post #62
retrac wrote: post #54

Earlier quoted context omitted.

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting. One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order an…

These are good points that sharpen the hypothesis. The word order question is interesting — positional encoding vs morphological encoding might have different computational properties for a parser. One difference I'm betting on: morphological agreement is redundant (same information marked multiple times), while word order encodes information once. Redundancy aids error correction and may lower pattern extraction thr…

[deleted]

Re: How the Brain Parses Language

#65

Post by HarHarVeryFunny »

aeve890 wrote: post #52
HarHarVeryFunny wrote: post #36

Earlier quoted context omitted.

Yes, but at least now we're comparing artificial to real neural networks, so the way it works at least has a chance of being similar. I do think that a transformer, a somewhat generic hierarchical/parallel predictive architecture, learning from prediction failure, has to be at least somewhat similar to how we learn language, as opposed to a specialized Chompyskan "language organ". The main difference is perhaps that…

>Yes, but at least now we're comparing artificial to real neural networks Given that the only similarity between the two of is just the "network" structure I'd say that point is pretty weak. The name "artificial neural network" it's just an historical artifact and an abstraction totally disconnected from the real thing.

Sure, but ANNs are at least connectionist, learning connections/strengths and representations, etc - close enough at that level of abstraction that I think ANNs can suggest how the brain may be learning certain things.

Re: How the Brain Parses Language

#66

Post by patcon »

adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

I suspect you're more right than wrong. I'm a strong believer in this sort of thing -- that humans are best understood as a cyborg of a biological and semiotic organism, but mostly a "language symbiont inside a host". We should perhaps understand this as the strange creature of language jumping between hosts. But I suspect we're looking at a mule of sorts: it can't reproduce properly. But this mule could destroy us if we put it to work doing the wrong things, with too much agency when it doesn't have the features that give us the right to trust our own agency as evolved creatures.

You might be interested to look into the Leiden Theory of Language[1][2]. It's been my absolutely favourite fringe theory of mind since I stumbled across the rough premise in 2018, and went looking for other angles on it.

[1] https://www.kortlandt.nl/publications/art067e.pdf

[2]: https://en.wikipedia.org/wiki/Symbiosism

> Language is a mutualist symbiont and enters into a mutually beneficial relationship with its hominid host. Humans propagate language, whilst language furnishes the conceptual universe that guides and shapes the thinking of the hominid host. Language enhances the Darwinian fitness of the human species. Yet individual grammatical and lexical meanings and configurations of memes mediated by language may be either beneficial or deleterious to the biological host.

EDIT: almost forgot the best link!

Language as Organism: A Brief Introduction to the Leiden Theory of Language Evolution https://www.isw.unibe.ch/e41142/e41180/e523709/e546679/2004f...

Re: How the Brain Parses Language

#67

Post by adamzwasserman »

patcon wrote: post #66
adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

I suspect you're more right than wrong. I'm a strong believer in this sort of thing -- that humans are best understood as a cyborg of a biological and semiotic organism, but mostly a "language symbiont inside a host". We should perhaps understand this as the strange creature of language jumping between hosts. But I suspect we're looking at a mule of sorts: it can't reproduce properly. But this mule could destroy us i…

Thank you for the Leiden references. I hadn't encountered this framework before. The "language symbiont" framing resonates with what I've been circling around: a system that operates with its own logic, sometimes orthogonal to conscious intention.

The mule analogy is going to stick with me. LLMs have inherited the statistical structure of the symbiont without the host: pattern without grounding. Whether that makes them useful instruments for studying the symbiont itself, or just misleading simulacra, is exactly what I'm trying to work out.

Going to dig into Kortlandt tonight.

Re: How the Brain Parses Language

#68

Post by mcswell »

adamzwasserman wrote: post #19

There's an interesting falsifiable prediction lurking here. If the language network is essentially a parser/decoder that exploits statistical regularities in language structure, then languages with richer morphological marking (more redundant grammatical signals) should be "easier" to parse — the structure is more explicitly marked in the signal itself. French has obligatory subject-verb agreement, gender marking on…

Written French does have all that inflectional morphology you talk about, but spoken French has much less--a lot of the inflectional suffixes are just not pronounced on most verbs (with the exception of a few, like être and aller--but at least 'be' in English is inflected in ways that other verbs are not). So there's not that much redundancy.

As for gender marking on adjectives--or nouns--it does almost no semantic work in French, except where you're talking about professional titles (doctor, professor...) that can be performed by men or by women.

If you want a heavily inflected language, you should look at something like Turkish, Finnish, Swahili, Quechua, Nahuatl, Inuit... Even Spanish (spoken or written) has more verbal inflection than spoken French.

Re: How the Brain Parses Language

#69

Post by mcswell »

Anon84 wrote: post #15
liampulles wrote: post #9

What I'm curious about is what the language parts of the human brain look like for babies and toddlers. Humans obviously have a bunch of languages they can speak, and toddlers pick up the language that their guardians speak around their home, so there seems to be machinery there that is for the task of "online" learning.

Me too! Babies and toddlers brains are like sponges. We started teaching my baby 3 languages since birth (essentially I always spoken with her in my native language, my wife in hers and gets English from living in the US). She’s not even 4 yet an fully fluent in all three and seemlessly jumps back and forth between them. (To my surprise, she doesn’t mix words from the different languages in the same sentence)

There's a lot more to language learning than being a "sponge". Virtually all the grammar we learn is productive/ creative--that is, we apply it to new words, and say things we never heard anyone say before. And the grammar is implicit in what we hear, so children need to extract it in a form that can be generalized to new thoughts and words.

Re: How the Brain Parses Language

#70

Post by mcswell »

griffzhowl wrote: post #21
liampulles wrote: post #9

What I'm curious about is what the language parts of the human brain look like for babies and toddlers. Humans obviously have a bunch of languages they can speak, and toddlers pick up the language that their guardians speak around their home, so there seems to be machinery there that is for the task of "online" learning.

One part of the story I found fascinating is the overlap in infants' brains of the areas involved in tool use and hierarchical syntax. These diverge and specialize in adults. The homologous brain region in primates is involved in motor planning. It's an interesting hint at the deeper evolutionary origins of language in the ability to plan complex actions, providing a neural basis for the observation that language and…

"overlap in infants' brains of the areas involved in tool use and hierarchical syntax"---you didn't see that in the Quanta article, right? I went back and looked, but can't find it mentioned anywhere.
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