7 ms·

How the Brain Parses Language

152 points by mylifeandtimes 11mo ago

moralIsYouLie 11mo ago
reads like a collection of HN comments by commenters who like to build "chapter 1" textbook agents using instant-noodle "training tools". "and what would be the time complexity?" I can't do this anymore.
- Al-Khwarizmi 10mo ago
  Ev Fedorenko is a highly recognized cognitive scientist that has been studying how humans parse language for years. Of course this doesn't mean one shouldn't question what she says (that would be an obvious authority fallacy), but I do think it's fair to say that if you want to question it, the argument should be more elaborate that "this sounds like she has no idea of the topic".
  - Timwi 10mo ago
    I'm not the person you responded to, but I found the article unreadable because it kept going on about Ev’s life instead of her research. I'm sure her research is valuable and insightful, but with this style of reporting it is both inaccessible to me, and it gives me the (probably flawed) impression that her research isn't the part of her life that's supposed to be important or impressive.
    - jimbokun 10mo ago
      This is meant for a lay audience so you should probably just read her research papers. Also: > it gives me the (probably flawed) impression that her research isn't the part of her life that's supposed to be important or impressive. I don't see this at all in the article. There's just some human interest content to make her research more approachable.
    - mcswell 10mo ago
      FWIW, that's soft of the way a lot of physics books (not textbooks) approach the subject: Einstein/ Heisenberg/ Bohr/ Pauli/ Feynman/ Oppenheimer was this kind of person, oh, and by the way he came up with this theory of X. Apparently a lot of people like that way of presenting science, but it's not for everyone.
dr_dshiv 10mo ago
> It almost sounds like you’re saying there’s essentially an LLM inside everyone’s brain. Is that what you’re saying? >Pretty much. I think the language network is very similar in many ways to early LLMs, which learn the regularities of language and how words relate to each other. It’s not so hard to imagine, right? Yet, completely glosses over the role of rhythm in parsing language. LLMs aren’t rhythmic at all, are they? Maybe each token production is a cycle, though… hmm…
- GolDDranks 10mo ago
  I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.
  - tgv 10mo ago
    However ... language production and perception are quite separated in our heads. There's basically no parallel to LLMs. Note that the article doesn't give any, and is extremely vague about the biological underpinnings of language.
    - GolDDranks 10mo ago
      > language production and perception are quite separated in our heads Do you have any evidence for this? I am a former linguistics student (got my masters), and, after years of absenteeism in academia, interested in the current state of the affairs. So: "quite separated in our heads" Evidence for? against?
      - tgv 10mo ago
        Afasia, and general measures of "normal" performance. There are various kinds of afasia, often linked to specific brain areas (Wernicke's and Broca's are well-known). And M/EEG and fMRI research suggests similar distinctions. It is difficult to reconcile with the idea that there is only one language system. And you will also have noticed that your skills in perception and production differ. You can read/listen better than write/speak. Timing, ambiguity and errors in perception and production differ. And more logically: the tasks are very different. In perception, you have to perceive the structure and meaning from a highly ambiguous, but ordered input of sound triggering auditory nerves, while during production, meaning is given (in non-linear order), and you have to find a way to fit it in a linear, grammatical order with matching words, which then have to be translated to muscle movements.
tcsenpai 10mo ago
> But what if our neurobiological reality includes a system that behaves something like an LLM? It almost seems like we got inspiration from our brain to build neural networks!
- seanmcdirmid 10mo ago
  It isn’t clear though. Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words?
  - SAI_Peregrinus 10mo ago
    > It is totally plausible but do we really think just in words? I find that proposition totally implausible. Some people certainly report only thinking in words & having a continuous inner monologue, but I'm not one of them. I think, then I describe my thoughts in words if I'm speaking or writing or thinking about speaking or writing.
  - coldtea 10mo ago
    >Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words? LLMs might be trained via words, but as a backend transformers are not just for words. They're for high dimensional structured sequences. To make an analogy, transformers are not working on: Vector<Word> but Vector<ContextualizedEmbedding> where words just happens to be a handy training set we use. And, we too, might not think in words, but I bet that we do think using multi-dimensional sequences/vectors.
- coldtea 10mo ago
  We've been making the same metaphor ("that's how the brain works") with each new major technology we come up with...
alfanick 10mo ago
Anecdotal data, based on a sample of 1 (aka me). I'm originally Polish, but I would say my mother tongue is English. I also learned Latin as a kid/teen. Then learning any other languages is much easier, I also learned German and some Swiss German dialects. I can also do Spanish, Italian, French, Dutch, Czech, some Serbo-Croation. I think being Polish makes learning languages easy - as we have a lot of creations in Polish that do not translate easily to other languages. I think in my case it's the same part of brain that processes both human language and computer language. My brain can do another fun party trick: I never learned cyrillic, but I can read it just fine, my brain does like pattern matching and statistical analysis when reading cyrillic. I also learned to think in hmm "concepts", and then apply a language of my choice to express them. It's a fun skill to have :) Obviously works of Chomsky are great, especially exploring if language evolves mind or is the other way around, does mind evolve language? [let's skip his rather controversial political views lately].
- Tor3 10mo ago
  I speak several languages too, though definitely not as many as you do. I'm also in the process of learning a completely new one, at an advanced age relative to when I last learned a new one (I was in my thirties then). To me, my brain most definitely doesn't process human language the way it handles computer language. It's about as different as it can get. The latter is "learning", the former is "burn patterns into the brain", and learning a language can take years, at least at this age. Computer languages? Those can be picked up in as little as a weekend, and getting proficient isn't a multi-year or decade long process. It feels totally different for me (I've been learning new computer languages at the same time as I've been trying to get up to speed with a new human language).
  - vkazanov 10mo ago
    Computer languages are much simpler than human languages, and they also operate in similar kind of logical ways. I definitely remember how hard was to go from pascal to C to Cpp to Python to prolog to haskell to SQL... until at some point nothing was new.
liampulles 10mo ago
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.
- lapcat 10mo ago
  I think this quote may speak to the question: > The brain’s general object-recognition machinery is at the same level of abstractness as the language network. It’s not so different from some higher-level visual areas such as the inferotemporal cortex (opens a new tab) storing bits of object shapes, or the fusiform face area storing a basic face template. In other words, it sounds like the brain may start with the same basic methods of pattern matching for many different contexts, but then different areas of the brain specialize in looking for patterns in specific contexts such as vision or language. This seems to align with the research of Jenny Saffran, for example, who has studied how babies recognize language, arguing that this is largely statistical pattern matching.
  - mullsork 10mo ago
    In the series Babies by Netflix some of her research on this topic is covered. Season 1 Episode 4 "First Words."
- Anon84 10mo ago
  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)
  - phkahler 10mo ago
    >> To my surprise, she doesn’t mix words from the different languages in the same sentence I knew two brothers that would mix words from different languages while speaking to each other because they shared the same set of languages and presumably used the best words to express their thoughts. Your daughter probably knows other people generally speak and understand one language at a time and just conforms because its most effective. I'm not sure if or at what age it might be good to start mixing languages with others who can.
lapcat 10mo ago
I wouldn't read too much into the LLM analogy. The interview is disappointingly short, filled with a bunch of unnecessarily tall photgraphs, and the interviewer, the one who brought up LLMs and ChatGPT and has a history of writing AI articles (https://www.quantamagazine.org/authors/john-pavlus/ https://www.quantamagazine.org/authors/john-pavlus/), almost seemed to have an agenda to contextualize the research in this way. In general, except in a hostile context such as politics, interviewees tend to be agreeable and cooperative with interviewers, which means that interviews can be steered in a predetermined way, probably for clickbait here. In any case, there's a key disanalogy: > Unlike a large language model, the human language network doesn’t string words into plausible-sounding patterns with nobody home; instead, it acts as a translator between external perceptions (such as speech, writing and sign language) and representations of meaning encoded in other parts of the brain (including episodic memory and social cognition, which LLMs don’t possess).
- adamzwasserman 10mo ago
  The disanalogy you quote might actually be the key insight. What if language operates at two levels, like Kahneman's System 1/2? Level 1: Nearly autonomic — pattern-matched language that acts directly on the nervous system. Evidence: how insults land before you "process" them, how fluent speakers produce speech faster than conscious deliberation allows, and the entire body of work on hypnotic suggestion, which relies on language bypassing conscious evaluation entirely. Level 2: The conscious formulation you describe — the translator between perception and meaning. LLMs might be decent models of Level 1 but have nothing corresponding to Level 2. Fedorenko's "glorified parser" could be the Level 1 system.
  - lapcat 10mo ago
    > LLMs might be decent models of Level 1 I don't think so. Fast speakers and hyponotized people are still clearly conscious and "at home" inside, vastly more "human" than any LLM. Deliberation and evaluation imply thinking before you speak but do not imply that you can't otherwise think while you speak.
    - 10mo ago
qqxufo1 10mo ago
If the brain's language network is only for "packaging words" and not for actual logic or reasoning, why does writing or speaking our messy thoughts out loud suddenly make them feel more logical? Is language actually helping us think, or is it just a filter that forces our chaotic ideas into a structure we can finally understand?
- mcswell 10mo ago
  That's a really good question. I don't have an answer, or even the beginning of an answer, but I would hazard a guess that there is a feedback loop. So listening to yourself talk (or even better, putting your thoughts down in print) is sort of like listening to someone else talk, which puts new ideas into your mind, or causes you to better organize the ones you already have. Doing mathematical proofs might be an extreme example of that: a mathematician has (I am told) an intuition--a thought--but has to work it out rigorously. Once they've done that, the intuition becomes much clearer. I guess.
netfortius 10mo ago
Every time I read something like this reminds me of Maturana (of autopoiesis fame), who was among the first scientists from where I started gaining an interest in these areas. Relevant to his view, in the area of language, is the following: "We human beings are living systems that exist in language. This means that although we exist as human beings in language and although our cognitive domains (domains of adequate actions) as such take place in the domain of languaging, our languaging takes place through our operation as living systems. Accordingly, in what follows I shall consider what takes place in language[,] as language arises as a biological phenomenon from the operation of living systems in recurrent interactions with conservation of organization and adaptation through their co-ontogenic structural drift, and thus show language as a consequence of the same mechanism that explains the phenomena of cognition:"
- deleted 10mo ago
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adamzwasserman 10mo ago
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 articles/adjectives, and rich verbal morphology. English has largely shed these. If you trained identical neural networks on French vs English corpora, holding everything else constant, you might expect French models to hit certain capability thresholds earlier — not because of anything about the network, but because the language itself carries more redundant structural information per token. This would support Fedorenko's view that the language network is revealing structure already present in language, rather than constructing it. The "LLM in your head" isn't doing the thinking — it's a lookup/decode system optimized for whatever linguistic code you learned. (Disclosure: I'm running this exact experiment. Preregistration: https://osf.io/sj48b https://osf.io/sj48b)
- fellowniusmonk 10mo ago
  Dyslexia seems to be more of an issue in English than other languages right? But also, maybe the difficulty of parsing recruits other/executive function and is beneficial in other ways? The per phoneme density/efficiency of English is supposed to be quite high as an emergent trade language. Perhapse speaking a certain language would promote slower more intentional parsing, humility through syntax uncertainty, maybe not, all I know is that from a global network resilience perspective it's good that dumb memes have difficulty propagating across cultures/languages.
  - adamzwasserman 10mo ago
    The dyslexia point is interesting; yes, English orthography causes more reading disorders than languages with more regular spelling-to-sound mappings (Italian, Finnish, etc.). That's consistent with the parser having to work harder when the signal is noisier. Your intuition about "slower more intentional parsing" connects to something I'm exploring: we may parse language at two levels simultaneously; a fast, nearly autonomic level (think: how insults land before you consciously process them) and a slower deliberate level. Whether those levels interact differently across languages is an open question.
griffzhowl 10mo ago
One disanalogy between human language use and LLMs is that language evolved to fit the human brain, which was already structured by millions of years of primate social life. This is more or less the reverse situation to a neural network trained on a large text corpus.
- HarHarVeryFunny 10mo ago
  Yes, but animal/human brains (cortex) appear to have evolved to be prediction machines, originally mostly predicting evolving sensory inputs (how external objects behave), and predicting real-world responses to the animal's actions. Language seems to be taking advantage of this pre-existing predictive architecture, and would have again learnt by predicting sensory inputs (heard language), which as we have seen is enough to induce ability to generate it too.
rdtsc 10mo ago
> 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.
- HarHarVeryFunny 10mo ago
  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 the LLM is only predicting based on the preceding sequence, while our brain is driving language generation by a combination of sequence prediction and the thoughts being expressed. You can think of the thoughts being a bias to the language generation process, a bit like language being a bias to a diffusion based image generator. What would be cool would be if we could to some "mechanistic interpretability" work on the brain's language generation circuits, and perhaps discover something similar to induction heads.
  - rdtsc 10mo ago
    > 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. Indeed, and I wasn't even saying it's wrong, it may be pretty close. > What would be cool would be if we could to some "mechanistic interpretability" work on the brain's language generation circuits, and perhaps discover something similar to induction heads. Yeah, I wouldn't be surprised. And maybe the more we find out about the brain, it could lead to some new insights about how to improve AI. So we'd sort of converge from both sides.
  - aeve890 10mo ago
    >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.
fallingfrog 10mo ago
I've had the experience of having migraines with aphasia- this is essentially a migraine aura that affects the part of the brain that processes language. I can confirm that while this was happening, i was aware of my surroundings and able to have thoughts, but I was unable to speak and unable to understand spoken or written language. It all just looked and sounded like gibberish. I thought about whether I should go to a hospital, what was going on, wondered whether my loved ones were concerned, and so on, but was unable to communicate any of those thoughts to other people. It was a bizarre experience.
taeric 10mo ago
This feels too reductive to me. In particular, it makes a hard distinction between the thinking and the language. I fully accept that they are distinct, but how distinct? It is hard not to think that some thinking styles influence how something is heard? Not just in full language, mind, but consider the last time you heard a song in a major key? Do you even know what that means? Because many of us do not. Same goes for listening to people discuss things like sports. I'm inclined to think many people effectively run a simulation in their mind of a game as they listen to it broadcast. This almost certainly isn't inherent to the language, it is part of the learning of it, though. Think looking over lists of the moves in a chess game. Then go from that to laying out the pieces as they are after that list. Or calling what the next move can be. Can this be a completely separate set of "circuitry" in our brains that first parses the language and then builds the simulation? I suppose. Seems more likely there is something that is active between the two that can effectively get merged in advanced practitioners.
rramadass 10mo ago
Language and Reality: a Wittgensteinian Reading of Bhartrhari - https://wab.uib.no/agora/tools/alws/collection-9-issue-1-article-55.annotate https://wab.uib.no/agora/tools/alws/collection-9-issue-1-art... New Vistas to study Bhartrhari: Cognitive NLP (Natural Language Processing) - https://arxiv.org/abs/1810.04440 https://arxiv.org/abs/1810.04440

152 points by mylifeandtimes 11mo ago

reads like a collection of HN comments by commenters who like to build "chapter 1" textbook agents using instant-noodle "training tools". "and what would be the time complexity?" I can't do this anymore.

Al-Khwarizmi 10mo ago
Ev Fedorenko is a highly recognized cognitive scientist that has been studying how humans parse language for years. Of course this doesn't mean one shouldn't question what she says (that would be an obvious authority fallacy), but I do think it's fair to say that if you want to question it, the argument should be more elaborate that "this sounds like she has no idea of the topic".
- Timwi 10mo ago
  I'm not the person you responded to, but I found the article unreadable because it kept going on about Ev’s life instead of her research. I'm sure her research is valuable and insightful, but with this style of reporting it is both inaccessible to me, and it gives me the (probably flawed) impression that her research isn't the part of her life that's supposed to be important or impressive.
  - jimbokun 10mo ago
    This is meant for a lay audience so you should probably just read her research papers. Also: > it gives me the (probably flawed) impression that her research isn't the part of her life that's supposed to be important or impressive. I don't see this at all in the article. There's just some human interest content to make her research more approachable.
  - mcswell 10mo ago
    FWIW, that's soft of the way a lot of physics books (not textbooks) approach the subject: Einstein/ Heisenberg/ Bohr/ Pauli/ Feynman/ Oppenheimer was this kind of person, oh, and by the way he came up with this theory of X. Apparently a lot of people like that way of presenting science, but it's not for everyone.

dr_dshiv 10mo ago

> It almost sounds like you’re saying there’s essentially an LLM inside everyone’s brain. Is that what you’re saying? >Pretty much. I think the language network is very similar in many ways to early LLMs, which learn the regularities of language and how words relate to each other. It’s not so hard to imagine, right? Yet, completely glosses over the role of rhythm in parsing language. LLMs aren’t rhythmic at all, are they? Maybe each token production is a cycle, though… hmm…

GolDDranks 10mo ago
I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.
- tgv 10mo ago
  However ... language production and perception are quite separated in our heads. There's basically no parallel to LLMs. Note that the article doesn't give any, and is extremely vague about the biological underpinnings of language.
  - GolDDranks 10mo ago
    > language production and perception are quite separated in our heads Do you have any evidence for this? I am a former linguistics student (got my masters), and, after years of absenteeism in academia, interested in the current state of the affairs. So: "quite separated in our heads" Evidence for? against?
    - tgv 10mo ago
      Afasia, and general measures of "normal" performance. There are various kinds of afasia, often linked to specific brain areas (Wernicke's and Broca's are well-known). And M/EEG and fMRI research suggests similar distinctions. It is difficult to reconcile with the idea that there is only one language system. And you will also have noticed that your skills in perception and production differ. You can read/listen better than write/speak. Timing, ambiguity and errors in perception and production differ. And more logically: the tasks are very different. In perception, you have to perceive the structure and meaning from a highly ambiguous, but ordered input of sound triggering auditory nerves, while during production, meaning is given (in non-linear order), and you have to find a way to fit it in a linear, grammatical order with matching words, which then have to be translated to muscle movements.

tcsenpai 10mo ago

> But what if our neurobiological reality includes a system that behaves something like an LLM? It almost seems like we got inspiration from our brain to build neural networks!

seanmcdirmid 10mo ago
It isn’t clear though. Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words?
- SAI_Peregrinus 10mo ago
  > It is totally plausible but do we really think just in words? I find that proposition totally implausible. Some people certainly report only thinking in words & having a continuous inner monologue, but I'm not one of them. I think, then I describe my thoughts in words if I'm speaking or writing or thinking about speaking or writing.
- coldtea 10mo ago
  >Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words? LLMs might be trained via words, but as a backend transformers are not just for words. They're for high dimensional structured sequences. To make an analogy, transformers are not working on: Vector<Word> but Vector<ContextualizedEmbedding> where words just happens to be a handy training set we use. And, we too, might not think in words, but I bet that we do think using multi-dimensional sequences/vectors.
coldtea 10mo ago
We've been making the same metaphor ("that's how the brain works") with each new major technology we come up with...

alfanick 10mo ago

Anecdotal data, based on a sample of 1 (aka me). I'm originally Polish, but I would say my mother tongue is English. I also learned Latin as a kid/teen. Then learning any other languages is much easier, I also learned German and some Swiss German dialects. I can also do Spanish, Italian, French, Dutch, Czech, some Serbo-Croation. I think being Polish makes learning languages easy - as we have a lot of creations in Polish that do not translate easily to other languages. I think in my case it's the same part of brain that processes both human language and computer language. My brain can do another fun party trick: I never learned cyrillic, but I can read it just fine, my brain does like pattern matching and statistical analysis when reading cyrillic. I also learned to think in hmm "concepts", and then apply a language of my choice to express them. It's a fun skill to have :) Obviously works of Chomsky are great, especially exploring if language evolves mind or is the other way around, does mind evolve language? [let's skip his rather controversial political views lately].

Tor3 10mo ago
I speak several languages too, though definitely not as many as you do. I'm also in the process of learning a completely new one, at an advanced age relative to when I last learned a new one (I was in my thirties then). To me, my brain most definitely doesn't process human language the way it handles computer language. It's about as different as it can get. The latter is "learning", the former is "burn patterns into the brain", and learning a language can take years, at least at this age. Computer languages? Those can be picked up in as little as a weekend, and getting proficient isn't a multi-year or decade long process. It feels totally different for me (I've been learning new computer languages at the same time as I've been trying to get up to speed with a new human language).
- vkazanov 10mo ago
  Computer languages are much simpler than human languages, and they also operate in similar kind of logical ways. I definitely remember how hard was to go from pascal to C to Cpp to Python to prolog to haskell to SQL... until at some point nothing was new.

liampulles 10mo ago

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.

lapcat 10mo ago
I think this quote may speak to the question: > The brain’s general object-recognition machinery is at the same level of abstractness as the language network. It’s not so different from some higher-level visual areas such as the inferotemporal cortex (opens a new tab) storing bits of object shapes, or the fusiform face area storing a basic face template. In other words, it sounds like the brain may start with the same basic methods of pattern matching for many different contexts, but then different areas of the brain specialize in looking for patterns in specific contexts such as vision or language. This seems to align with the research of Jenny Saffran, for example, who has studied how babies recognize language, arguing that this is largely statistical pattern matching.
- mullsork 10mo ago
  In the series Babies by Netflix some of her research on this topic is covered. Season 1 Episode 4 "First Words."
Anon84 10mo ago
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)
- phkahler 10mo ago
  >> To my surprise, she doesn’t mix words from the different languages in the same sentence I knew two brothers that would mix words from different languages while speaking to each other because they shared the same set of languages and presumably used the best words to express their thoughts. Your daughter probably knows other people generally speak and understand one language at a time and just conforms because its most effective. I'm not sure if or at what age it might be good to start mixing languages with others who can.

lapcat 10mo ago

I wouldn't read too much into the LLM analogy. The interview is disappointingly short, filled with a bunch of unnecessarily tall photgraphs, and the interviewer, the one who brought up LLMs and ChatGPT and has a history of writing AI articles (https://www.quantamagazine.org/authors/john-pavlus/ https://www.quantamagazine.org/authors/john-pavlus/), almost seemed to have an agenda to contextualize the research in this way. In general, except in a hostile context such as politics, interviewees tend to be agreeable and cooperative with interviewers, which means that interviews can be steered in a predetermined way, probably for clickbait here. In any case, there's a key disanalogy: > Unlike a large language model, the human language network doesn’t string words into plausible-sounding patterns with nobody home; instead, it acts as a translator between external perceptions (such as speech, writing and sign language) and representations of meaning encoded in other parts of the brain (including episodic memory and social cognition, which LLMs don’t possess).

adamzwasserman 10mo ago
The disanalogy you quote might actually be the key insight. What if language operates at two levels, like Kahneman's System 1/2? Level 1: Nearly autonomic — pattern-matched language that acts directly on the nervous system. Evidence: how insults land before you "process" them, how fluent speakers produce speech faster than conscious deliberation allows, and the entire body of work on hypnotic suggestion, which relies on language bypassing conscious evaluation entirely. Level 2: The conscious formulation you describe — the translator between perception and meaning. LLMs might be decent models of Level 1 but have nothing corresponding to Level 2. Fedorenko's "glorified parser" could be the Level 1 system.
- lapcat 10mo ago
  > LLMs might be decent models of Level 1 I don't think so. Fast speakers and hyponotized people are still clearly conscious and "at home" inside, vastly more "human" than any LLM. Deliberation and evaluation imply thinking before you speak but do not imply that you can't otherwise think while you speak.
  - 10mo ago

qqxufo1 10mo ago

If the brain's language network is only for "packaging words" and not for actual logic or reasoning, why does writing or speaking our messy thoughts out loud suddenly make them feel more logical? Is language actually helping us think, or is it just a filter that forces our chaotic ideas into a structure we can finally understand?

mcswell 10mo ago
That's a really good question. I don't have an answer, or even the beginning of an answer, but I would hazard a guess that there is a feedback loop. So listening to yourself talk (or even better, putting your thoughts down in print) is sort of like listening to someone else talk, which puts new ideas into your mind, or causes you to better organize the ones you already have. Doing mathematical proofs might be an extreme example of that: a mathematician has (I am told) an intuition--a thought--but has to work it out rigorously. Once they've done that, the intuition becomes much clearer. I guess.

netfortius 10mo ago

Every time I read something like this reminds me of Maturana (of autopoiesis fame), who was among the first scientists from where I started gaining an interest in these areas. Relevant to his view, in the area of language, is the following: "We human beings are living systems that exist in language. This means that although we exist as human beings in language and although our cognitive domains (domains of adequate actions) as such take place in the domain of languaging, our languaging takes place through our operation as living systems. Accordingly, in what follows I shall consider what takes place in language[,] as language arises as a biological phenomenon from the operation of living systems in recurrent interactions with conservation of organization and adaptation through their co-ontogenic structural drift, and thus show language as a consequence of the same mechanism that explains the phenomena of cognition:"

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adamzwasserman 10mo ago

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 articles/adjectives, and rich verbal morphology. English has largely shed these. If you trained identical neural networks on French vs English corpora, holding everything else constant, you might expect French models to hit certain capability thresholds earlier — not because of anything about the network, but because the language itself carries more redundant structural information per token. This would support Fedorenko's view that the language network is revealing structure already present in language, rather than constructing it. The "LLM in your head" isn't doing the thinking — it's a lookup/decode system optimized for whatever linguistic code you learned. (Disclosure: I'm running this exact experiment. Preregistration: https://osf.io/sj48b https://osf.io/sj48b)

fellowniusmonk 10mo ago
Dyslexia seems to be more of an issue in English than other languages right? But also, maybe the difficulty of parsing recruits other/executive function and is beneficial in other ways? The per phoneme density/efficiency of English is supposed to be quite high as an emergent trade language. Perhapse speaking a certain language would promote slower more intentional parsing, humility through syntax uncertainty, maybe not, all I know is that from a global network resilience perspective it's good that dumb memes have difficulty propagating across cultures/languages.
- adamzwasserman 10mo ago
  The dyslexia point is interesting; yes, English orthography causes more reading disorders than languages with more regular spelling-to-sound mappings (Italian, Finnish, etc.). That's consistent with the parser having to work harder when the signal is noisier. Your intuition about "slower more intentional parsing" connects to something I'm exploring: we may parse language at two levels simultaneously; a fast, nearly autonomic level (think: how insults land before you consciously process them) and a slower deliberate level. Whether those levels interact differently across languages is an open question.

griffzhowl 10mo ago

One disanalogy between human language use and LLMs is that language evolved to fit the human brain, which was already structured by millions of years of primate social life. This is more or less the reverse situation to a neural network trained on a large text corpus.

HarHarVeryFunny 10mo ago
Yes, but animal/human brains (cortex) appear to have evolved to be prediction machines, originally mostly predicting evolving sensory inputs (how external objects behave), and predicting real-world responses to the animal's actions. Language seems to be taking advantage of this pre-existing predictive architecture, and would have again learnt by predicting sensory inputs (heard language), which as we have seen is enough to induce ability to generate it too.

rdtsc 10mo ago

> 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.

HarHarVeryFunny 10mo ago
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 the LLM is only predicting based on the preceding sequence, while our brain is driving language generation by a combination of sequence prediction and the thoughts being expressed. You can think of the thoughts being a bias to the language generation process, a bit like language being a bias to a diffusion based image generator. What would be cool would be if we could to some "mechanistic interpretability" work on the brain's language generation circuits, and perhaps discover something similar to induction heads.
- rdtsc 10mo ago
  > 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. Indeed, and I wasn't even saying it's wrong, it may be pretty close. > What would be cool would be if we could to some "mechanistic interpretability" work on the brain's language generation circuits, and perhaps discover something similar to induction heads. Yeah, I wouldn't be surprised. And maybe the more we find out about the brain, it could lead to some new insights about how to improve AI. So we'd sort of converge from both sides.
- aeve890 10mo ago
  >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.

fallingfrog 10mo ago

I've had the experience of having migraines with aphasia- this is essentially a migraine aura that affects the part of the brain that processes language. I can confirm that while this was happening, i was aware of my surroundings and able to have thoughts, but I was unable to speak and unable to understand spoken or written language. It all just looked and sounded like gibberish. I thought about whether I should go to a hospital, what was going on, wondered whether my loved ones were concerned, and so on, but was unable to communicate any of those thoughts to other people. It was a bizarre experience.

taeric 10mo ago

This feels too reductive to me. In particular, it makes a hard distinction between the thinking and the language. I fully accept that they are distinct, but how distinct? It is hard not to think that some thinking styles influence how something is heard? Not just in full language, mind, but consider the last time you heard a song in a major key? Do you even know what that means? Because many of us do not. Same goes for listening to people discuss things like sports. I'm inclined to think many people effectively run a simulation in their mind of a game as they listen to it broadcast. This almost certainly isn't inherent to the language, it is part of the learning of it, though. Think looking over lists of the moves in a chess game. Then go from that to laying out the pieces as they are after that list. Or calling what the next move can be. Can this be a completely separate set of "circuitry" in our brains that first parses the language and then builds the simulation? I suppose. Seems more likely there is something that is active between the two that can effectively get merged in advanced practitioners.

rramadass 10mo ago

Language and Reality: a Wittgensteinian Reading of Bhartrhari - https://wab.uib.no/agora/tools/alws/collection-9-issue-1-article-55.annotate https://wab.uib.no/agora/tools/alws/collection-9-issue-1-art... New Vistas to study Bhartrhari: Cognitive NLP (Natural Language Processing) - https://arxiv.org/abs/1810.04440 https://arxiv.org/abs/1810.04440