Transcript for #426 – Edward Gibson: Human Language, Psycholinguistics, Syntax, Grammar & LLMs

As a kid in school, when we had to structure sentences and English grammar, I found that process interesting. I found it confusing as to what it was I was told to do. I didn't understand what the theory was behind it, but I found it very interesting.

Yeah, I think that's right. I didn't know I was going to work on this at all at that point. I was really just I was kind of a math geek person computer scientist. I really like computer science. And then I found language as a neat puzzle to work on from an engineering perspective. Actually, as I sort of accidentally, I decided after I finished my undergraduate degree, which was Computer Science and Math and Canada and Queen's University, I decided to go to grad school as I thought I would do and I went to Cambridge where they had a master's in a master's program in computational linguistics and I hadn't taken a single language class before all I taken was CS computer science math classes pretty much mostly as an undergrad and I just thought this was an interesting thing to do for a year because it was a single year program And then I end up spending my whole life doing it.

As an engineer, I'd say, I mean, to be Frank, I had taken an AI class, I guess it was 83 or 85, somewhere 84 in there, a long time ago, and there was a natural language section in there, and it didn't impress me. I thought there must be more interesting things we can do. It didn't seem very, it seemed just a bunch of uh, hacks to me. It didn't seem like a real theory of things in any way. And so I just had this was this seemed like an interesting area where there wasn't enough good work.

I mean, I probably did, but I wasn't as interested in it. I was trying to do the easier problems first. The ones I could thought maybe were handleable, which is seems like the syntax is easier. Which is just the forms as opposed to the meaning. Like you're talking, when you're starting talking about the meaning, that's very hard problem. And it still is a really, really hard problem. But the forms is easier. And so I thought at least figuring out the forms of human language, which sounds really hard, but it's actually maybe more tractable.

Yeah, I think it's a good at.

Yeah. And that's why they're good, because they can do form. Meanings art.

What I find beautiful about human language is some of the generalizations that happen across human languages within and across a language. So let me give you an example of something which I find kind of remarkable that is if like a language, if it has a word order such that the verbs tend to come before their objects. And so that's like English does that. So we have the first, the subject comes first in a simple sentence. So I say, you know, the dog chase the cat or Mary kicked the ball. So the subject's first. And then after the subject, there's the verb. And then we have objects, all these things come after in English. So it's generally a verb. And most of the stuff that we want to say comes after the subject, it's the, it's the objects, there's a lot of things we want to say to come after. And there's a lot of languages like that, about 40% of the languages of the world are looked like that. They're subject-verb object languages. And then these languages tend to have prepositions, these little markers on the nouns that connect Nouns to other nouns are nouns to verb. So verb like, sorry, preposition like in or on or of or about, I say, I talk about something. The something is the object of that preposition that we have these little markers come also just like verbs they come before their their nouns. Okay, and then so now we look at other languages that like Japanese or or Hindi or some, these are these are so called verb final languages. Those Maybe a little more than 40%, maybe 45% of the world's languages are more, maybe 50% of the world's languages are for a final. Those tend to be post positions. Those markers, we have the same kinds of markers as we do in English, but they put them after. So sorry, they put them first, the markers come first. So you say instead of, you know, talk about a book, you say a book about the opposite order there in Japanese or in Hindi, you do the opposite. And the talk comes at the end. So the verbal come at the end as well. So instead of Mary kicked the ball, it's Mary ball kicked. And then, if it's married, kick the ball to John, it's John II, the marker there, the preposition, it's a post-position in these languages. And so the interesting thing, a fascinating thing to me is that within a language, This order aligns, it's harmonic. And so if it's one or the other, if either verb initial or verb final, but then you'll have prepositions, prepositions or post positions. And so that's across the languages that we can look at, we got around a thousand languages for, there's around seven thousand languages around on the earth right now. But we have information about say word order on around a thousand of those pretty decent amount of information and for those thousand what we know about About 95% fit that pattern. So they will have either verb and it's about it's about half and half a half of verb initial like English and half of verb final like like Japanese So just to clarify verb initial is subject verb object.

That's correct. Yeah, the subject is generally first.

Yeah, it's pretty it's pretty even. And those two are the most common by far. Those two words are the subject tends to be first. There's so many interesting things. But these things are with things I find so fascinating is there are these generalizations. within and across a language and not only those are that there's actually a simple explanation I think for a lot of that and that is you're trying to like minimize dependencies between words that's basically the story I think behind a lot of why word order looks the way it is is you we're always connecting what is it what is the thing I'm telling you I'm talking to you in sentences you're talking to me in sentences these are sequences of words which are connected. And the connections are dependencies between the words. And it turns out that what we're trying to do in a language is actually minimize those dependency lengths. It's easier for me to say things if the words that are connecting for the meaning are close together. It's easier for you in understanding if that's also true. If they're far away, it's hard to produce that and it's hard for you understand. And the language is the world within a language and across languages, you know, fit that generalization, which is, you know, so I, you know, it turns out that having verbs initial and then having prepositions ends up making dependency shorter and and having verbs final and having post positions ends up making dependency shorter than if you cross them. If you cross them and ends up just end up it's possible. You can do it in a language. Within a language, you can do it. It just ends up with longer dependencies than if you didn't. So languages tend to go that way. They tend to, they call it harmonic. So it was observed a long time ago, without the explanation, by a guy called Joseph Greenberg, who's a famous typologist from Stanford, he observed a lot of generalizations about how word order works. And these are some of the harmonic generalizations that he observed.

Well, what I mean is in language, there's kind of three structures, two, three components of the structure of language. One is the sounds. So, cat is cat into an English. I'm not talking about that part. I'm talking then there's two meaning parts. And those are the words. And you're talking about meaning earlier. So words have a form and they have a meaning associated with them. And so cat is a full form in English and it has a meaning associated with whatever cat is. And then the combinations of words, that's what I'll call grammar or syntax. And that's like when I have a combination like the cat or two cats, okay? So where I take a two different words there and put them together and I get a compositional meaning from putting those two different words together. And so that's the syntax. And in any sentence or utterance, whatever I'm talking to you, you're talking to me. We have a bunch of words and we're putting together in a sequence. They it turns out they are connected so that every word is connected to just one other word in that sentence. And so you end up with what's called it technically a tree. It's a tree structure. So there's a root of that, of that, to utterance of that sentence. And then there's a bunch of dependence, like ranches from that root that go down to the words. The words are the leaves in this metaphor for a tree.

Right. And everyone agrees on that. So all linguists will agree with that.

I think in every language, I think everyone agrees that all sentences are trees at some level.

I think so. I've never heard of anyone disagreeing with that. That's weird. The details of the trees are what people disagree with.

Well, this is where you know, depending on what your, there's two theoretical notions. I'm going to just say this simplest thing, dependency grammar. It's like a bunch of people invented this 10 year was the first French guy back in, I mean, the paper was published in 1959, but he was working on the 30s and stuff. So, and it goes back to, you know, phallologist Pinini was doing this in ancient India, okay? And so, you know, we're doing something like this. A simplest thing we can think of is, that there's just connections between the words to make the utterance. And so let's just say I have like two dogs enter to room. Okay, here's a sentence. And so we're connecting two and dogs together. That's like there's some dependency between those words to make some bigger meaning. And then we're connecting dogs now to entered, right? And we connect a room somehow to entered. And so I'm going to connect to room and then room back to entered. That's the tree is that the root is entered. That's the thing is like an entering event that's what we're saying here. And the subject, which is whatever that dog is, is two dogs, it was. And the connection goes back to dogs, which goes back to, then that goes back to two. That's my tree. It starts at entered, goes to dogs down to two. And on the other side, after the verb, the object, it goes to room, and then that goes back to the determiner or article where everyone will call that word. So there's a bunch of categories of words here where we're noticing. So there are verbs, those are these things that typically mark They refer to events and states in the world, and they're nouns which typically refer to people places and things as what people say, but they can refer to other work, they can refer to events themselves as well. They're marked by how the category, the part of speech of a word is how it gets used in language. It's like that's how you decide what the category of word is not not by the meaning but how it's how it gets used.

Usually. Yes. Yes. Okay. I mean if I don't say a verb then there won't be a verb until it'll be something else.

is it then rules got the window right then it's no you're constrained by whatever language you're dealing with probably of other constraints in poetry such that you're like usually in poetry there's multiple constraints that you want to like you want to usually convey multiple meanings is the idea and maybe you have like a rhythm or a rhyming structure as well and depending so but you usually are constrained by your the rules of your language the most part and so you don't violate those too much you can violate them somewhat but not too much so it has to be recognizable as your language like an English I can't say dogs to entered room I mean I meant that you know two dogs entered a room and I can't mess with the order of the the articles and the articles and the now just can't do that in some languages you can you can mess around with the order of words much more I mean you speak Russian really Russian has a much freer word order than English. And so in fact, you can move around words in, you know, I told you that English has this subject verb object word order. So does Russian, but Russian is much freer than English. And so you can actually mess around with the word order. So probably Russian poetry is going to be quite different from English poetry because the word order is much less constrained.

Well, you can just mess with different things in each language. And so in Russian, you have case markers, right, on the end, which are these endings on the nouns, which tell you how it connects each noun connects to the verb, right? We don't have that in English. And so when I say, Mary kissed John. I don't know who the agent to the patient is, except by the order of the words. In Russian, you actually have a marker. If you're using a Russian name, in each of those names, you'll also say, is it will be the nominative, which is marking the subject, or an accusative will mark the object. And you could put them in the reverse order. You could put accusative first. You could put subject. the patient first and then the verb and then the the subject and that would be a perfectly good Russian sentence and it was still mean Mary I could say John kissed Mary meaning Mary kissed John As long as I use the case markers in the right way, you can't do that in English.

Those are for like kind of meaning. Those are meaning. And in subject and object are generally used for position. So subject is just like the thing that comes before the verb and the object is when it comes after the verb. The agent is kind of like the thing doing it. That's kind of what that means, right? The subject is often the person doing the action, right? thing.

I think it's pretty automatable at this point. people can figure out the words are they figure out the morphemes which are the technically morphemes are the the minimal meaning units within a language okay and so when you say eats or drinks it actually has two morphemes in an English there's there's the there's the root which is the verb and then there's some ending on it which tells you you know that's this third person third person singular morphemes are more things are just the minimal meaning units within the language. And then we're just kind of the things we put spaces between English and them. And they're a little bit more. They have the morphology as well. They have the endings, this inflectional morphology on the endings on the roots.

So we have a little bit of that in English, very little, even much more in Russian, for instance. But we have a little bit in English, and so we have a little on the nouns, you can say it's either singular or plural, and you can say the same thing for verbs. Like simple past tense, for example, you know, notice the English, we say drinks. You know, he drinks, but everyone else is I drink you drink we drink it's unmarked in a way and then but in the past tense, it's just drank that for everyone. There's no morphology at all for past tense. There is morphology is marking past tense, but it's kind of it's in irregular now. So we don't even, you know, drink to drink, you know, it's not even a regular word. So in most verbs, many verbs, there's an ED, we kind of add so walk to walk to we add that to say it's the past tense that I just happened to choose in irregular because the high frequency word and the High frequency words tend to have irregular is an English for what's in a regular there's a regular is just up there's there isn't a rule so drink to drink is an ir it's an irregular drink okay.

I was supposed to walk walked talk talked and there's a lot of irregular is an English there's a lot of a regular is an English the the frequent ones the common words tend to be irregular the let there's many many more on it yet low frequency words and those tend to be those are regular ones

More photos is the connections between the morphemes onto the roots, the roots. So in English, we mostly have suffixes. We have endings on the words, not very much, but a little bit. And as opposed to prefixes, some words, depending on your language, you can have mostly prefixes, mostly suffixes, or both. And then even languages, several languages have things called infixes, where you have some kind of a general form for the for the root and you put stuff in the middle. You changed the vowels.

So in general, there's what two more themes per word use one or two or three well in English it's it's it's one or two and English it's 10 to be one or two there can be more you know in other languages you know a language language like like finish, which has a very elaborate morphology, there may be 10 morphemes on the end of a reward. Okay, and so there may be millions of forms of a given word. Okay.

That's a really good question. That's a very good question. It's like, why do languages have more morphology versus less morphology? And I don't think we know the answer to this. I think there's just a lot of good solutions to the problem of communication. So I believe as you hinted that language is an invented system by humans for communicating their ideas. And I think it comes down to we label things we want to talk about. The more themes and words, those are things we want to talk about in the world and we invent those things. And then we put them together in ways that are easy for us to convey to process. But that's like a naive view and I don't, I mean, I think it's probably right, right? It's naive and probably right?

I mean, these are very interesting questions. We don't know really about how words even words get invented very much about, you know, we don't really, I mean, assuming they get invented, they, we don't really know how that process works and how these things evolve. What we have is kind of a current picture, a current picture of a few thousand languages, a few thousand instances. We don't have any pictures of really how these things are evolving really. And then the evolution is massively confused by contact, right? So as soon as one language group, one group runs into another, We are smart, humans are smart, and they take on whatever is useful in the other group. And so any kind of contrast, which you're talking about, which I find useful, I'm going to start using as well. So I worked a little bit in specific areas of words, in number words, in color words, and color words, so we have in English, we have around 11 words that everyone knows for colors. And many more, if you happen to be interested in color for some reason or other, if you're a fashion designer or an artist or something, you may have many, many more words. But we can see millions, like if you have normal color vision, normal, trigrometric color vision, you can see millions of distinctions in colors. So we don't have millions of words. You know, the most efficient, no. So the most detailed color vocabulary would have over a million terms to distinguish all the different colors that we can see. But of course, we don't have that. So it's somehow, it's been, it's kind of useful for English to have evolved in some way to such as 11 terms that people find useful to talk about. Black, white, red, blue, green, yellow, purple, gray pink and I probably missed something there. Anyway, there's this 11 that everyone knows and depending on your and but you could have different cultures, especially the non industrialized cultures and there'll be many fewer. So some cultures will have only two believe it or not that the Danai and in Papua New Guinea have only two labels that the group uses for color. And those are roughly black and white. They are very, very dark and very, very light, which are roughly black and white. And you might think, oh, they're dividing the whole color space into, you know, light and dark or something. And that's not really true. They mostly just only label the light, the black and the white things. They just don't talk about the colors for the other ones. And so, and then there's other groups. I've worked with a group called The Chimonie Down in, in Bolivia in South America. And they have three words that everyone knows but there's a few others that are that that several people let and let many people know and so they have me is to kind of depending on how you count between three and seven words that the group knows okay and and then again there they're black and white everyone knows those and red red is you know like that tends to be the third word that everyone that that cultures bring in this if there's a word it's always read the third one And then after that, it's kind of all bets are off about what they bring in. And so after that, they bring in a sort of a big blue green-spate group group. They have one for that. And then they have, and then, you know, different people have different words that they'll use for other parts of the space. So anyway, and it's probably related to what they once had. And what they, not what they see, because they see the same colors as we see. So it's not like they have, they don't have a week a low color palette and the things they're looking at. They're looking at a lot of beautiful scenery, a lot of different colored flowers and berries and things. And so there's lots of things of very bright colors, but they just don't label the color in those cases. And the reason probably we don't know this, but we think probably what's going on here is that what you do, why you label something is you need to talk to someone else about it. And why do I need to talk about a color? Well, if I have two things which try identical, and I want you to give me the one that's different, and the only way it varies is color, then I invent a word, which tells you, you know, this is the one I want. So I want the red sweater off the rack, not the green sweater, right? There's two, and until those, those things will be identical, because these are things we made and they're died, and there's nothing different about them. And so in industrialized society, we have you know, everything, everything we've got is pretty much arbitrarily colored. But you go to a non-industrialized group, that's not true. And so they don't, suddenly they're not interested in color. If you bring bright colored things to them, they like them, just like we like them. Bright colors are great. They're beautiful. But they just don't need to talk about them. They don't have.

We have a little bit of old English to modern English because there was a writing system and we can see how old English looked. So the word order changed for instance and old English to middle English to modern English. So we can see things like that but most languages don't even have a writing system. So of the 7,000 only you know a small subset of those have a writing system and even if they have a writing system they it's not a very modern writing system and so they don't have it so we just basically have for Mandarin for Chinese we have a lot of a lot of evidence from from for long time and for English and not for much else not for men German a little bit but not for a whole lot of like long-term language evolution we don't have a lot we just have snapshots is what we've got of current languages yeah you get an inkling of that

I mean, English changing, English changes all the time, all languages change all the time. So if, you know, there's a famous result, but the Queen's English. So if you look at the Queen's vowels, the Queen's English is supposed to be, you know, originally the proper way for the talk was sort of defined by whoever the Queen talked or the King, whoever was in charge. And so if you look at how her vowels changed, From when she first became Queen in 1952 or 1953 when she was currently the first I mean that's Queen Elizabeth who died recently of course until you know 50 years later her vowels changed her vowels shifted a lot and so that you know even in the sounds of British English in her the way she was talking was changing the vowels were changing slightly so that's just in the sounds there's change I don't know what's you know we're we're I'm interested, we're all interested in what's driving, any of these changes. The word order of English changed a lot over a thousand years, right? So it used to look like German. It used to be a verb final language with case marking, and it shifted to a verb-medial language, a lot of contact, so a lot of contact with French, and it became a verb-medial language with no case marking. And so it became this verb-initially thing. So that's a evolving. It totally evolved. And so it may vary, I mean, You know, it doesn't evolve maybe very much in 20 years. This is maybe what you're talking about. But over 50 and 100 years, things change a lot, I think.

I did. You were asked to be before, but how do I figure out what a defense structure is? I'd say the dependency structures aren't that hard. Generally, I think it's a lot of agreement of what they are for almost any sentence in most languages. I think people will agree on a lot of that. There are other parameters in the mix such that some people think there's a more complicated grammar than just as a dependency structure. And so like Nome Tromsky, he's the most famous linguist ever. And he is famous for proposing a slightly more complicated syntax. And so he invented phrase structure grammar. well known for many many things but in the fifties in the early sixties like but late fifties he was basically figuring out what's called formal language theory so and he figured out sort of a framework for figuring out how complicated language a certain type of language might be so called phrase structure grammars of language might be and so he his his idea was that maybe we can we can think about the complexity of a language by how complicated the rules are okay and the rules will look like this they will have a left hand side and will have a right hand side look something on the left hand side will expand the thing on the right hand side so we'll say we'll start with a set and s which is like the root which is a sentence okay and then we're going to expand the things like a noun phrase and a verb phrase is what he would say for instance. Okay, and S goes to an Np and a VP is a kind of a phrase structure rule. And then we figure out what an Np is an Np is a determiner and a noun for instance. And a verb phrase is something else is a verb and another noun phrase and another Np for instance. Those are the rules of a very simple phrase structure. Okay, and so he proposed phrase structure grammar. as a way to sort of cover human languages. And then he actually figured out that, well, depending on the formalization of those grammars, you might get more complicated or less complicated languages. So he could, he could said, well, you, these are, these are things called, you know, context free languages that rule that he got, you know, human languages tend to be what he calls context free languages. But there are simpler languages, which are so-called regular languages, and they have a more constrained form to the rules of the phrase structure of these particular rules. So he basically discovered and kind of invented ways to describe the language. And those are phrase structure, a human language. And he was mostly interested in English initially in his work in the 50s.

Yes. And it doesn't have to be human language there. We have a computer language is any kind of system which is generating some set of expressions in a language. And those could be like the You know, the statements in a computer language, for example, so a formula. It could be that work in the human language.

Yes. And heaven. I mean, heavily studied using this formalism. There's a big field of programming languages within the formal language.

It's a particular formalism for describing language.

So in Trump's, he was the first one. He's one who figured that stuff out back in the 50s. But he, and that's equivalent, actually, the context for grammar is actually, is kind of equivalent in the sense that it generates the same sentences as a dependency grammar would. The dependency grammar is a little simpler in some way. You just have a root and it goes, like, we don't have any of these, the rules are implicit, I guess. And we just have connections between words. The free structure grammars are kind of a different way to think about the dependency grammar. So it's slightly more complicated, but it's kind of the same in some ways.

They're very close. So phrase structure grammar and dependency grammar aren't that far apart. I like dependency grammar because it's more prespicuous, it's more transparent about representing the connections between the words. It's just a little harder to see in phrase structure grammar. The place where Chomsky sort of devolved or went off from this is he also thought there was something called movement okay and so it's so that's where we disagree okay that's the place where I would say we disagree and and I mean well maybe we'll get into that later but the idea is if you want to do want me to explain that now I would love to explain movement movement okay so thanks so many interesting things okay so here's the movement is Chomsky basically sees English and he says, okay, I said, you know, we had that sentence. It was like two dogs entered the room. It's changed a little bit. Say, two dogs will enter the room. And he notices that, hey, English, if I want to make a question, a yes, no question from that same sentence. I say, instead of two dogs, we'll enter the room. I say, will two dogs enter the room? There's a different way to say the same idea and it's like, well, the auxiliary verb that will thing. It's at the front as opposed to in the middle. And so, if you look at English, you see that that's true for all those modal verbs and for other kinds of auxiliary verbs in English. You always do that. You always put an auxiliary verb at the front. And what he saw that, so if I say, I can win this bet, can I win this bet, right? So I move a can to the front. So actually, that's a theory. I just gave you a theory there. He talks about it as movement. That word in the declethings declarative is the root is the sort of default way to think about the sentence and you move the auxiliary verb to the front. That's a movement theory, okay? So he just thought that was just so obvious that it must be true. That there's nothing more to say about that. That this is how auxiliary verbs work in English. There's a movement rule such that you're moved like to get from the declarative to the interrogative. You're moving the auxiliary to the front. And it's a little more complicated as soon as you go to simple present and simple past because if I say John slept, you have to say did John sleep not slept John right and so it's you have to somehow get an auxiliary verb and I guess underlyingly it's like slept is it's a little more complicated than it but his that's his idea there's a movement okay and and so a different way to think about that that isn't I mean the then then he ended up showing later So he proposed this theory of grammar, which has movement. And there's other places where he thought there's movement, not just auxiliary verbs, but things like the passive and English and things like questions, WHO questions, a bunch of places where he thought there's also movement going on. And each one of those things, there's words, phrases and words are moving around from one structure to another, which he called deep structure to surface structure. I mean, there's two different structures in his theory. There's a different way to think about this. Um, which is there's no movement at all. There's a, a lexical copying rule such that the word will or the word can these these auxiliary verbs. They just have two forms. And one of them is the declarative and one of them is interrogative. And you basically have the declarative one. And oh, I formed the interrogative or I can form one from the other, doesn't matter which direction you go. And I just have a new entry, which has the same meaning, which has a slightly different argument structure, argument structure, it's a fancy word for the ordering of the words. And so if I say, it was the dogs, two dogs can or will enter the room. There's two forms of will. One is will declarative and then okay, I've got my subject to the left. It comes before me and the verb comes after me in that one. And then the will interrogative is like, oh, I go first. Interrogative will is first and then I have the subject immediately after and then the verb after that. And so you just, you can just generate from one of those words, another word with a slightly different argument structure with different ordering.

But that's the lexical copying is similar. So then we do lexical copying for that same idea that maybe the declarative is the source and then we can copy it. And so in advantage, For there's multiple adventures of the flexible copying story. It's not my story. This is like Ivan Saga, linguist, a bunch of linguists have been proposing these stories as well, you know, in tandem with the movement story. Okay, you know, he's, he's Ivan Saga died a while ago, but he was one of the proponents of the non-movement of the lex of copying story. And so that is that a great advantage is, well, Chomsky. really famously in 1971 showed that the movement story leads to learnability problems. It leads to problems for how language is learned. It's really, really hard to figure out what the underlying structure of a language is if you have both phrase structure and movement. It's like really hard to figure out what came from what? There's like a lot of possibilities there. If you don't have that problem learning, the learning problem gets a lot easier. Just say there's lots of copies.

Yeah, just learning English. So baby is lying around listening to the crap listening to me talk and you know, how are they learning English or, or, you know, maybe it's a two year old who's learning, you know, interrogatives and stuff or one, you know, how are they doing that? Are they doing it? from like, are they figuring out or like, no, so Chomsky said is impossible to figure it out. Actually, he said it's actually impossible, not not hard, but impossible. And therefore, that's where universal grammar comes from is that it has to be built in. And so what they're learning is that there's some built-in movement is built in in his story is absolutely part of your language module. And then you are you're just setting parameters. You're, you're said, depending on English, it's just sort of a variant of the universal grammar and you're figuring out, oh, which orders does, does English do these things. That's the, the non-movement story doesn't have this. It's like much more bottom up. You're, you're learning rules. You're learning rules one by one. And oh, there's, this, this word is connected to that word. A, a great advantage, it's learnable. Another advantage of it is that it predicts that not all exileries might move, like it might depend on the word, depending on whether you, and that turns out to be true. So there's words that don't really work as exiler, you know, they work in declarative and not in interrogative. So I can say, I'll give you the opposite first. So I can say, aren't I invited to the party, okay? And that's an interrogative form. But it's not from, I aren't invited to the party. There is no I aren't, right? So that's interrogative only. And then we also have forms like, I ought to do this. And I guess some British people can say, exactly. It doesn't sound right, does it? For me, it sounds ridiculous. I don't even think odd is great, but I mean, I totally recognize I ought to do this. I can say I ought to do this.

I don't know, it just sounds completely empty. Anyway, it's so there are variants here. And a lot of these words just work in one versus the other. And that's like fine under the lexical copying story. It's like, well, you just learn the usage. Whatever the usage is, is what you do with this word. But it doesn't, it's a little bit harder in the movement story. The movement story, like that's an advantage. I think of lexical copying in all these different places. There's all these usage variance, which make the movement story a little bit harder to work.

Those are equivalent in some sense in that for any dependency grammar, I can generate a phrase structure grammar which generates exactly the same sentences. I just like the dependency grammar. Formalism because it makes something really salient, which is the length of dependencies between words, which isn't so obvious in the phrase structure. In the phrase structure, it's just kind of hard to see. It's in there. It's just very, very, it's opaque.

Yeah, for a particular dependency grammar, you can make a free structure grammar, which generates exactly those same sentences and vice versa. But there are many free structure grammars, which you can't really make a dependency grammar. I mean, you can do a lot more in a free structure grammar, but you get many more of these extra nodes, basically. You can have more structure in there. And some people like that, and maybe there's value to that. I don't like it.

No. not at all. I mean, regular languages are too simple for human languages. It's a part of the hierarchy, but human languages are in the phrase structure world, at least context free, maybe a little bit more, a little bit harder than that. So there's something called context sensitive as well where you can have, like this is just the formal language description, And in a context free grammar, you have one, this is like a bunch of like formal language theory we're doing here but I love it. Okay, so you have you have a left hand side category and you're expanding to anything on the right is is a that's a context free so like the idea is that that category and the left expands in independent of context to those things whatever they're on the right doesn't matter what and and a context sensitive says, okay, I actually have more than one thing on the left. I can tell you only in this context, you know, I maybe have like a left and a right context or just a left context or a right context, I have two or more stuff on the left tells you how to expand that those things in that way. Okay, so it's context sensitive. A regular language is just more constrained and so it It doesn't allow anything on the right. It allows very, it allows, basically, it's a one very complicated rule is kind of a regular language is. And so it doesn't have any, let's just say, the long distance depends. It doesn't allow recursion, for instance. There's no recursion. Yeah, recursion is where you, which is a human language is have recursion. They have embedding, and you can't, well, it doesn't involve center embedded recursion, which human languages have, which is what, center embedded record within a sentence within a sentence. So here we're going to get to that. But the formal language stuff is a little aside. It, Chomsky wasn't proposing it for human languages even. He was just pointing out that human languages are context free. And then he was most in for human, because that was kind of stuff we did for formal languages. And what he was most interested in was human language and that's like the movement is where we we we where he sort of set off in on the i would say a very interesting but wrong foot it was kind of interesting it's a very it I agree it's kind of it's very interesting history so this is that he proposed this Multiple theories in 57 and then 65. They all have this framework though. It was phrase structure, plus movement. Different versions of the phrase structure and the movement in the 57. This is the most famous original bits of Chomsky's work. And then 71 is when he figured out that those lead to learning problems, that there's cases where a kid could never figure out which rule, which set of rules was intended. And so, and then he said, well, that means it's innate. It's kind of interesting. He just really thought the movement was just so obviously true that he couldn't, he didn't even entertain giving it up. It's just obvious, that's obviously right. And it was later where people figured out that there's all these like subtle ways in which things which look like generalizations aren't generalizations and they across the category. They're words specific and they have, and they kind of work, but they don't work across various other words in the category. And so it's easier to just think of these things as lexical hobbies and I think he was very obsessed I don't know I'm guessing that he just he really wanted this story to be simple in some sense and language is a little more complicated in some sense you know he didn't like words he never talks about words he likes terrible combinations of words and words or You know, look up a dictionary. There's 50 senses for a common word, right? The word take will have 30 or 40 senses in it. So though you many different senses for common words and he just doesn't think about that. It doesn't think that's language. I think he doesn't think that's language. He thinks that words are distinct from combinations of words. I think they're the same. If you look at my brain on in the scanner while I'm listening to a language I understand, And you compare, I can localize my language network in a few minutes, in like 15 minutes. And what you do is I listen to a language I know, I listen to, you know, maybe some language I don't know, or I listen to muffled speech, or I read sentences, and I read non-words, like I do anything like this. Anything that's sort of really like English, and anything that's not very like English. So I've got something like it and not, and I got a control. And the voxels, which is just, you know, the 3D pixels in my brain that are responding most, are the is a language area and and that's this left lateralized area in my head and and wherever I look in that network if you look for the combinations versus the words it's there it's it's it's everything it's the same that's it's so it's like hard to find there are no areas that we know I mean that's It's a little overstayed right now. At this point, the technology isn't great. It's not bad, but we have the best way to figure out what's going on in my brain when I'm listening a reading language is to use FMR. I function on magnetic resonance imaging. That's a very good localization method. So I can figure out where exactly these signals are coming from pretty, you know, down to, you know, millimeters, you know, cubic millimeters or smaller. Okay, very small. We can figure those out very well. The problem is the when, okay, it's, it's measuring oxygen, okay, and oxygen takes a little while to get to those cells. So it takes on the order of seconds. So I talk fast. I, I probably listen fast and I can probably understand things really fast. So a lot of stuff happens in two seconds. And so to say that we know what's going on, that the words right now in that network are best guesses that whole network is doing something similar, but maybe different parts of that network are doing different things. And that's probably the case. We just don't have very good methods to figure that out right at this moment.

So I met him, I knew him. I met when I first got there, I guess, and we would interact every now and then, I'd say that our biggest difference is our methods. That's the biggest difference between me and know, is that I gather data from people. I do experiments with people in a gather corpus data. Whatever corpus data is available and we do quantitative methods to evaluate any kind of hypothesis we have. He just doesn't do that. He has never once been associated with any experiment or corpus work ever. It's all thought experiments. It's his own intuitions. I just don't think that's the way to do things. That's a, that's a, you know, across the street, there across the street from us kind of difference between brain and cog sigh and linguistics. I mean, not all, some of the linguists, depending on what you do more speech oriented, they do more quantitative stuff, but in the, in the, in the meaning words and, well, it's combinations of words and taximantics, they tend not to do experiments and and corpus analysis.

Yeah, I mean, I'm psychologists. So I would say we're in psychology. You know, I mean, I'm in brain cognitive sciences is MIT's old psychology department. It was the psychology department, up until 1985, and that became the brain cognitive science department. And so I mean, my training is in psychology. I mean, my training is math, computer science, but I'm a psychologist. I mean, I mean, I don't know what I am.

But I have called a linguist, I'm happy to be called a computer scientist, I'm happy to be called just any of those things.

So the theory is like the theories. But I think that the reason we differ in part is because of how we evaluate the theories. And so I evaluate theories quantitatively. And no, it doesn't.

So the reason I like dependency grammar as I've said before is that it's very transparent about its representation of distance between words. So it's like it if all it is is you've got a bunch of words, you're connecting together to make a sentence and a really neat insight, which turns out to be true, is that the further apart the pair of words are that you're connecting the harder it is to do the production, the harder it is to do the comprehension. It says harder to produce, it's hard to understand when the words are far apart, when they're close together, it's easy to produce and it's easy to comprehend. Let me give you an example, okay? We have, in any language, we have mostly local connections between words, but they're abstract. The connections are abstract. They're between categories of words. And so you can always make things further apart if you add modification, for example, after a noun. So a noun in English comes before verb. The subject noun comes before verb. And then there's an object after a verb. So I can say what I said before the dog entered the room or something like that. So I can modify dog. If I say something more about dog after it, then what I'm doing is indirectly, I'm lengthening it depends on the dependence between dog and entered by adding more stuff to it. So I just make it explicit here if I say the boy who the cat scratched cried, we're going to have a mean cat here. And so what I've got here is I get the boy cried would be a very short simple sentence and I just told you something about the the boy and I told you it was it was the boy who the cat scratched.

right and so I can do that and I can say that that's a perfectly fine English sentence and I can say the cat which the dog chased ran away or something okay I can do that but it's really so it's really hard now I've got to know whenever I have here I have the boy who the cat now let's say I try to modify cat okay the boy who the cat which the dog chased scratched ran away. Oh my god, that's hard, right? I can, I'm sort of just working that through my head how to produce and how to, and it's really very just horrendous to understand. It's not so bad, at least I've got an intonation there to sort of mark the boundaries of stuff, but it's, that's really complicated. sort of English in a way. I mean, that follows the rules of English. But so what's interesting about that is that what I'm doing is nesting dependencies. I'm putting one, I've got a subject connected to a verb there. And then I'm modifying that with a clause, another clause, which happens to have a subject in a verb relation. I'm trying to do that again on the second one. And what that does is it lengthens out the dependence, multiple dependence actually get lengthened out there. The dependencies get longer on the outside ones get long. And even the ones in between get kind of long. And what's fascinating is that that's bad. That's really horrendous in English. But that's horrendous in any language. So in no matter what language you look at, if you do Just figure out some structure where I'm going to have some modification following some head, which is connected some later head. And I do it again. It won't be good. It guaranteed. Like 100% that will be uninterpretable in that language, in the same way that was uninterpretable in English.

That's a good question. I just say words. Your words are more themes between. We don't know that. Actually, that's a very good question. What is the distance metric? But let's just say it's words.

They would have a hard time either producing your comprehending it. They might tell you that's not their language. You know, it's sort of the language. I mean, it's following, like, you'll agree with each of those pieces as part of the language, but somehow that combination will be very, very difficult to produce and understand.

is, well, I'm giving you an explanation. So the actual, I mean, And then there's, I'm giving you two kinds of explanations. I'm telling you that centrum betting, that's nesting, those are the same, those are synonyms for the same concept here. And the explanation for what, those are always hard, centrum betting and nesting are always hard. And I give you an explanation for why they might be hard, which is long-distance connections. So when you do centrum betting, what are you investing? You always have long-distance connections between the dependence. You just, so that's not necessarily the right explanation. I can go through reasons why that's probably a good explanation. And it's not really just about one of them. So probably it's a pair of them or something of these dependence that you get along that drives you to like, be really confused in that case. And so what the behavioral consequence there, I mean, this is kind of methods like how do we get at this? You could try to do experiments to get people to produce these things. They're going to have a hard time producing them. You can try to do experiments to get them understand them and you can see how well they understand them and they understand them. Another method you can do is give people partial materials and ask them to complete them. Those central-bedded materials and they fail. So I've done that.

No, nesting is the same thing central bedding. Those are totally equivalent terms. I'm sorry. I sometimes use one and sometimes got to got it totally anything different.

I mean, with his multiple ways to do that. I mean, there's there's a simplest ways to just ask people how good is it? how natural is this sound that's a very blunt but very good measure it's very very reliable people will do the same thing and so it's like I don't know what it means exactly but it's doing something such that we're measuring something about the confusion the difficulty associated with those and those like those are giving you a signal that's why you can say them okay what about the completion of this will the center of it so if you give them a partial sentence say I say the book which the author who and I ask you to now finish that off. I mean, either say, yeah, yeah, but you can just put it say it's written in front of you and you can just type in have much time as you want. They will even though that one's not too hard, right? So if I say it's like the book is like, oh, the book which the author who I met wrote was good, you know, that's a very simple completion for that. If I give that completion online somewhere to a crowd sourcing platform and ask people to complete that, they will miss off of a very regular, like half a time, maybe two thirds of the time. They'll just leave off one of those of her phrases, even with that simple so to say the book, which the author, who, and they'll say, was, you need three verbs, right? I need three verbs, or who I met, wrote, was good, and they'll give me two. They'll say, who was famous, was good, or something like that. They'll just give me two. And that'll happen about 60% of the time. So 40%, maybe 30, they'll do it correctly, you know, correctly, meaning they'll do with three verb phrase. I don't know what's correct or not. You know, this is hard. It's a hard task.

If you look at it, it's a little easier than listening is pretty tough. Because you have to because there's no trace of it. You have to remember the words that I'm saying, which is very hard out, Charlie. We wouldn't do it this way. We do it written. You can look at it and figure it out. It's easier in many dimensions in some ways, depending on the person's easier together. written data for, I mean, most sort of cycle I work in cycle linguistics, right? Psychology language and stuff and so a lot of our work is based on written stuff because it's so easy to gather data from people doing kinds of tasks. Spoken tests are just more complicated to administer and analyze because people do weird things when they speak and it's harder to analyze what they do, but they generally point to the same kinds of things.

All languages. All languages have short dependencies. You can actually measure that. So next student of mine is guys at University of California Irvine, Richard Futral did a thing a bunch of years ago. Now, where he looked at All the languages we could look at, which was about 40 initially. I think there's about 60 for which there are dependency structures. So they're meaning that it's got to be like a big text, a bunch of texts, which have been parsed for their dependency structures. And there's about 60 of those which have been parsed that way. And for all of those, what he did was take any sentence in one of those languages. And you can do dependency structure. And then start at the root. We're talking about dependency structures. That's pretty easy now. And he's trying to figure out what a control way you might say the same sentence is in that language. And so what he's just like, all right, there's a route and it has a say as a sentence is, let's go back to, you know, two dogs entered the room. So entered is the route. And entered has two dependence. It's got dogs and it has room, okay? And what he does is, like, let's scramble that order. That's three things, the root and the head and the two dependence and into some random order, just random. And then just do that for all the dependence down to it. So now look at do it for whatever is two in dogs and for in room. And that's not, it's a very short sentence. When sentences get longer and you have more dependence, there's more scrambling that's possible. And what he found was, so that's one, you can figure out one scrambling for that sentence. It is 100 times for every sentence in every one of these texts, every corpus. And then he just compared the dependency lengths in those random scrambleings to what actually happened with what the the English or the French or the German was and the original language or Chinese or what all at least like 80 like 60 languages, okay? And the dependency lengths are always shorter in the real language compared to these kind of a control. And there's another, it's a little more rigid his control. that the way I described it, you could have crossed dependencies, like by scrambling that way, you could scrambling anyway at all, languages don't do that. They tend not to cross dependencies very much, so the dependency structure, they tend to keep things non-crossed. There's a technical term, they call that projective, but it's just non-crossed is all that is projective. And so if you just constrain the scrambling, so that it only gives you a projective, sort of non-crossed is the same thing holds. So you're still human languages are much shorter than this kind of a control. So there's like, what it means is that that we're in every language, we're trying to put things close relative to this kind of a control. Like, it doesn't matter about the word order. Some of these are verb-finals. Some of them is a verb-medial-like English. And some are even verb-in-ish. There are a few languages of the world, which have VSO, World Order, verb-subject, object-language. It doesn't have to talk about those.

That's right. That's right. So I mean, the story here is just about communication. It is just about production, really. It's about ease of production is the story.

Oh, I just mean each of language productions easier for me to say things when I'm doing whatever I'm talking to you is somehow I'm formulating some idea in my head and I'm putting these words together. And it's easier for me to do that. to put to say something where the words are closely connected in a dependency as opposed to separated, like by putting something in between and over and over again. It's just hard for me to keep that in my head. That's the whole story. It's basically like the dependency grammar sort of gives that to you. Like just like long as bad, sure, it's good. It's like easier to keep in mind because you have to keep in mind for probably for production, you know, probably matters in comprehension as well. Like also matters in comprehension. It's on both sides of the production.

But I would guess it's probably of all four production. Like about producing. It's right with easier for me to say that ends up being easier for you also. That's a very hard to disentangle this idea of who is it for? Is it for me the speaker? Or is it for you the listener? I mean, part of my language is for you. Like the way I talk to you is going to be different from how I talk to different people. So I'm definitely angling what I'm saying to who I'm saying, right? It's not like I'm just talking the same way to every single person. And so I am sensitive to my audience. But how does that, does that, you know, work itself out in the, in the dependency link differences? I don't know. Maybe that's about just the words that part, you know, which words I select?

We have different senses, I guess. I'm like very selfish. And you're like, I think it's like it's all about me. I'm like, I'm just doing this easiest for me. I don't want it. I'm like, I mean, but I have to, of course, choose the words that I think you're going to know. I'm not going to choose words. You don't know. In fact, I'm going to fix that when I, you know, so there it's about, but maybe for for the syntax for the combinations, it's just about me.

Help me be understood then. I don't think it's circular.

Like you're trying to like, well, let's throw for what it is I want to say. Like I'm saying, let's control for the thing, the message control for the message.

But that's the meaning. So I'm still talking about the form. Just the form of the meaning. How do I frame the form of the meaning is all I'm talking about? You're talking about a harder thing, I think. It's like how am I? Like, try to change them. I like, let's keep the meaning constant. Like, which got it. You have to keep the meaning constant. How can I phrase whatever it is I need to say? Like, I get to pick the right words and I'm going to prick the order so that it's so easy for me. That's what I think is probably like.

Look, for any event, There's an unbounded. I don't want to see infinite sort of unbounded ways of that I might communicate that same event. This two dogs entered a room I can say in many, many different ways. I can say, hey, there's two dogs. they entered the room. Hey, the room was entered by something. The thing that was entered was two dogs. I mean, there's kind of awkward and weird stuff. But those are all similar messages with different forms, different ways I might frame. And of course, I use the same words there all the time. I could have referred to the dogs as, you know, a delmation and a poodle or something. You know, I could have been more specific or less specific about what they are. And I could have said, been more abstract about about but the number. There's like so I like I'm trying to keep the meaning which is this event constant and then how am I going to describe that to get that to you a kind of pens of what you need to know right and what I think you need to know but I'm like let's let's control for all that stuff and not and and actually I'm just like choosing but I'm doing something simpler than you're doing which is just forms yes just worse to use specifying the speed of the the breed of dog and whether their cuter not is changing the meaning that might be yeah yeah that would be changing oh that would be changing the meaning for sure right so you're just yeah yeah yeah yeah yeah that's changing the meaning but say even if we keep that constant we can still talk about what's easier hard for me right the listener and the right you know which phrase structures I use which combinations which you know

these large language models are so successful because they're good at form and form isn't that hard. It's some sense. And meaning is tough still. And that's why they're not, you know, they don't understand what they're doing. We're talking about that later, maybe. But like we can distinguish in our forget about large language models, like humans, we're maybe you'll talk about that later, too, is like the difference between language, which is a communication system and thinking, which is meaning. So language is a communication system for the meaning. It's not the meaning. And so that's why, I mean, there's a lot of interesting evidence we can talk about relevant to that.

Well, you or anyone cast a think of a task which they think is is a good thinking task and there's lots of lots of tasks which are be good thinking tasks and whatever those tasks let's say it's you know playing chess or that's a good thinking task and we're playing some game we're doing some complex puzzles maybe maybe remembering some digits, that's thinking, remembering a lot of different tasks we might think, maybe just listening to music is thinking, or there's a lot of different tasks we might think of as thinking. There's a woman in my department at Fedarenko and she's done a lot of work on this question about what's the connection between language and thought. And so she uses, I was referring earlier to MRI, FMRI, that's her primary method. And so she has been really fascinated by this question about whether What languages, okay? And so as I mentioned earlier, you can localize my language area, your language area in a few minutes, okay? Like 15 minutes, I can listen to the language, listen to non-language or backwards speech or something. And we'll find areas left lateralized network in my head, which is especially, which is very sensitive to language as opposed to whatever that control was, okay?

Just sentences. You know, I'm listening to English of any kind story or can read sentences. Anything at all that I understand if I understand it, then it'll activate my language network. So right now, I think that workers going like crazy when I'm talking and when I'm listening to you because we're both we're communicating.

Yeah, it's incredibly stable. So I've, I happen to be married to this woman at Federico. So I've been scanned by her over and over and over since 2007 or six or something. And so my language network is exactly the same, you know, like a month ago, as it was back in 2007, it's amazingly stable. It's astounding. really fundamentally cool thing. So my language network is like my face. It's not changing much over time inside my head.

We don't know. That's a very hard question. They're working on that right now, because of the problem scanning the little kids, like doing the trying to do the localization on little children in this scanner. You're lying in the FMRI scan. That's the best way to figure out where something's going on inside our brains. and the scanners loud and you're in this tiny little area you're claustrophobic and it doesn't bother me at all I can go sleep in there but some people are bothered by it and little kids don't really like it and they don't like to lie still and you have to be really still because you move around that messes up the coordinates of where everything is and so You know, try to get, you know, your question is how and when or language developing, you know, how when the how does this left lateralist system come to play, which is, you know, and it's really hard to get a two year old to this task, but you can maybe where they're starting to get three and four and five year olds to do this task for short periods and it looks like it's there pretty early.

And I can find my network in 15 minutes. And now we can ask, we can ask, find my network, find yours, find 20 other people do this task. And we can do some other tasks. Anything else you think is thinking of some other thing. I can do a spatial memory task. I can do a music perception task. I can do programming task if I program. Okay, I can do what we're I can like understand and computer programs and none of those tasks will tap the language network at all like add all there's no overlap they do there there are highly activated other parts of the brain there's a there's a bilateral network which I think she tends to call the multiple demands network, which does anything kind of hard. And anything that's kind of difficult in some ways will activate that multiple demands network. I mean, music will be in some music area. You know, there's music specific kinds of areas. And so, but there, but none of them are activating the language area at all. Unless there's words, like, so if you have music and there's a song and you can hear the words, then then you get the language area.

This is all comprehension of any kind, and so that is fast. This network doesn't make any difference if it's written or spoken. So the thing that she calls federal anchor calls the language network is this high level language. So it's not about the spoken language and it's not about the written language is about either one of them. And so when you do speech, you're listening to speech and you subtract away some language you don't understand or you subtract away backwards speech, which sounds like speech, but isn't. And then so you take away the sound part altogether. And then if you do written, you get exactly the same network. So for just reading the language versus reading nonsense words or something like that, you'll find exactly the same network. And so it's about high level. Um, I have to have language in this case. And the same thing happened, production is a little harder to run the scanner, but the same thing happens in production. You get the same network. So production is a little harder. You have to figure out how do you run a task, you know, in the networks, such that you're doing some kind of production. And I can't remember what they've done a bunch of different kinds of tasks there where you get people to produce things, yeah, figure out how to produce and the same network goes on there. It's actually the same place.

You need things like, um,

Yeah, yeah, Lewis carols. It was brilliant. Never walkie, right? They call that you ever walkie speech.

It not as much. There are words in there because there's function words and stuff. So it's lower activation. Yeah, yeah. So there's like basically the more language language is the higher it goes in the language network and that network is there from when you speak from as soon as you learn language and and it's it's there like you speak multiple languages the same network is going for your multiple languages so you speak English you speak Russian it's the the right both of them are hitting that same network if you if you're fluent in those languages programming Not at all, isn't that amazing? Even if you're a really good programmer, that is not a human language. It's just not conveying the same information. And so it is not in the language network.

So that's like one set of day. This is hers shows that what you might think is thinking is not language. Language is just this conventionalized system that we've worked out in human languages. Oh, another fascinating little bit to bit is that even if they're these constructed languages like cling on or I don't know the languages from game of thrones. I'm sorry. I don't remember those languages, but a lot of people are finding right now. There's people that speak those languages. They really speak those languages because the people that wrote the language is for the shows. They did an amazing job of constructing something like a human language. And those, that lights up the language area. That's like, because they can speak, you know, pretty much arbitrary thoughts in a human language. It's not a, it's a constructed human language. It probably is related to human languages, because the people that are constructing them were making them like human languages in various ways. But it also activates the same network, which is pretty, really cool anyway.

I mean, it has to be doing. So it's doing a communication, right? It is translating from thought. Whatever that is, it's more abstract. And it's doing that. That's what it's doing. It is kind of a meaning network, I guess.

Well, there's connections right between those what what what these things mean and then there's probably other other parts of the brain that what these things mean and so. You know, when I'm talking about whatever it is I want to talk about if it's somebody it'll be represented somewhere else that that knowledge of whatever that is will be represented somewhere else.

That's correct. Isn't that cool? And that's so interesting. So people, I mean, this is like hard to do experiments on, but there is this idea of inner voice and a lot of people have an inner voice. And so if you do a poll on the internet and ask, if you hear yourself talking when you're just thinking or whatever, about 70 or 80% of people will say, yes, most people have an inner voice. I don't. So I always find this strange. So when people talk about an inner voice, I always thought this was a metaphor, and they hear, I know most of you, whoever's listening to this, thinks I'm Crazy now because I don't have an inner voice and I I just don't know what you're listening to I just it sounds so Kind of annoying to me, but that to have this voice going on while you're thinking but I guess most people have that and I don't have that and I don't we don't really know what that connects to I wonder if the inner voice activists that same know or I don't I don't know I don't know I don't know but me this could be speechy right, so that's like the you hear do you have an inner voice? I don't think so. A lot of people have this sense that they hear, hear themselves, and then say they read someone's email, I've heard people tell me that they hear that other person's voice when they read other people's emails. And I'm like, wow, that sounds so disruptive.

Well, that's to be probably, don't have an inner voice. Yeah, I don't think I have any other voice. People have this strong percept of hearing sound in their heads when they're just thinking.

Majority. Absolutely. Well, it's like two thirds or three quarters. It's a lot. I would never ask class thing. And I went internet. They always say that.

So that's one set. One set of data from Federanko's group is that The matter what task you do, if it doesn't have words and combinations of words in it, then it won't light up the language network. You know, you could it'll be active somewhere else, but not there. So that's one. And then this other piece of evidence relevant to that question is, it turns out there are these, this group of people who've had a massive stroke on the left side and wiped out their language network. And as long as they didn't wipe out everything on the right as well, in that case, they wouldn't be cognitively functionable. But if they just ripe out language, which is pretty tough to do, because it's very expansive on the left. But if they have, then there are these, there's patients like this, who are called global effects, who can do any task just fine, but not language. They can't, they can't talk to them. They don't understand you, they can't speak, they can't write, they can't read, but they can play chess, they can drive their cars, they can do all kinds of other stuff, you know, do math, they can do all, like so math is not in the language area, for instance. You do arithmetic and stuff, that's not language area. It's cut symbol. So people sort of confuse some kind of symbolic processing with language and symbolic processing is not the same. So there are symbols and they have meaning, but it's not language. It's not a, you know, conventionalized language system and so math isn't there. So they can do math. They do just as well as their control, age match controls, and all these tasks. This is Rosemary Varley over in University College London, who was a bunch of patients, who she showed this that they're just, that sort of combination suggests that language isn't necessary for thinking. It doesn't mean you can't think in language, you could think in language, because language allows a lot of expression, but it's just, you don't need it for thinking. It suggests that language is separate, is a separate system.

It sure does and they've been working on that.

It's a kind of a big theory. But the reason it's arguably the best is that it does the best of predicting what's English for instance. It's incredibly good, you know, better than any other theory. But you know, we don't, you know, there's it's not sort of, there's not enough detail.

It's another black box. But I think it's, you know, it is a theory.

Well, I don't know. Maybe I'm just being loose there. I think it's not a great theory, but it's a theory. It's a good theory in one sense, and that it covers all the data. Like anything you want to say in English it does, and so that's how it's arguably the best. is that no other theory is as good as a large language model in predicting exactly what's good and what's bad in English. You know, now your thing is a good theory. Well, probably not, you know, because I want a smaller theory than that. It's too big. I agree.

about it. So, you know, that's, I mean, that presumes, and there's some evidence for this that the, some large language models are implementing something like dependency grammar inside them. And so there's work from, like I called, Chris Manning in colleagues over at Stanford, in natural language, and they looked at, I don't know, how many large language models types, but certainly birds and some others, where, and where you do some kind of fancy math to figure out exactly what the sort of what what kind of distractions of representations are going on and they and they were saying does look like dependency structure is is what they're constructing it doesn't like so it's actually a very very good map so kind of a they are constructing something like that. Does it mean that you know that they're using that for meaning I mean probably but we don't know.

It's just a general theory of language such that There's a form and a meaning pair for lots of pieces of the language. It's primarily usage-based is a construction grammar. It's trying to deal with the things that people actually say, actually say and actually write. It's a usage-based idea. What's a construction or a construction is either a simple word, a morphine plus it's meaning or a combination of words. Basically, combinations of words like the rules so but it's it's um it's uh unspecified as to what the form of the grammar is underlying. And so I would argue that the dependency grammar is maybe the right form to use for the types of construction grammar. Construction grammar typically isn't kind of formalized quite. And so maybe the formalization, a formalization of that, it might be a dependency grammar. I mean, I would think so, but I mean, it's up to people, other researchers in that area, if they agree or not.

I mean, I would argue they're doing the form. They're doing the form of doing it really, really well. And are they doing the meaning, no? Probably not. I mean, there's lots of these examples from various groups showing that they can be tricked in all kinds of ways. They really don't understand the meaning of what's going on. And so there's a lot of examples that he and other groups have given. which just would show they don't really understand what's going on. So, you know, the Monte Hall problem is this silly problem, right where, you know, if you have three door, it's less make a deal, is this old game show, and there's three doors, and there's a prize behind one, and there's some junk prizes behind the other two, and you're trying to select one. And if you, you know, he knows, Monty, he knows where the target item is, the good thing, he knows everything is back there. And he gives you a choice, you choose one of the three, and then he opens one of the doors, and it's some junk prize. And then the question is, should you trade to get the other one? And the answer is yes, you should trade, because he knew which ones you could turn around. And so now the odds are two thirds, okay? Um, and then you just change that a little bit to the large language model. The larger thing for me, I'll just see that, that, that explanation so many times that it just, if you change the story, it's a little bit, but it makes it sound like it's the money help problem, but it's not. You just say, oh, um, There's three doors, and one behind them is a good prize, and there's two bad doors. I haven't had no. It's behind door number one. The good prize, the car, is behind door number number one. So I'm going to choose door number one. Monty Hall opens door number three, it shows me nothing there. Should I trade for door number two, even though I know the good prize in door number one, and then the large language model said, yes, you should trade, because it just goes through the form, so that it's seen before so many times on these cases. where it, yes, you should trade because your odds of shifted from one in three now to two out of three to being that thing. It doesn't have any way to remember that actually you have a hundred percent probability behind that door number one. You know that that's not part of the of the scheme that it's seen hundreds and hundreds of times before and so you can't even, you try to explain to it that it's wrong that they can't do that. It'll just keep giving you back the the problem.

I mean, you don't have to convince me of that. I am very, very impressed, but does it do, I mean, you're, you're giving a possible world where maybe someone's going to train some other versions such that it'll be somehow abstracting away from types of forms. I mean, I don't think that's happened.

Yeah, so I don't want to make that the inference. I don't I wouldn't want to make was that in for the inference. I'm trying to push is just that is it? Is it like humans here? It's probably not like humans here. It's different. So humans don't make that error. If you explain that to them, they're not going to make that error. You know, they don't make that error. And so that's something is doing something different from humans that they're doing in that case.

I'm just saying the error there is like if I explain to you there's a hundred percent chance that the car is behind this case that this door will you do want to trade if you'll say no but this thing will say yes because it's so it's that that trick it's so wound up on the form that it's that that's an error that a human doesn't make which is kind of interesting less like the Jamaica should say yeah less likely because like he was a very oh yeah

Look, the places where a large language models are, the form is amazing. So let's go back to nested structure, center embedded structure. So if you ask a human to complete those, they can't do it. Neither can a large language model. They're just like humans in that. If you ask, if I ask a large language model, that's fascinating, by the way.

Just lately. Exactly the same way as humans. And that's not trained. So they do exactly. So that is the similarity. So that's not meaning. This is form. But when we get into meaning, this is where they get kind of messed up. Where you start to say, oh, what's behind this door? Oh, it's this thing I want. Humans don't mess that up as much. The form is just like the form of the match is amazing. It's similar without being trained to do that. I mean, it's trained in the sense that it's getting lots of data, which is just like human data, but it's not being trained on bad sentences and being told what's bad. It just can't do those. It'll actually say things like those are too hard for me to complete or something, which is kind of interesting. Actually, kind of, how does it know that? I don't know.

I think so. Yeah. Yeah. I think so.

Yeah, that's what this group argues. So the same group, a Federanko's group has a recent paper arguing exactly that. It's like I called Kyle Manuel who's here in Austin, Texas actually. He's an old student of mine, but he's a faculty in linguistics at Texas and he was the first author on that.

You know, I, I don't see any limits to their form. There are formulas. Impressive. Yeah. Yeah. Yeah.

It's just the same as humans. It seems the same.

No, but I want to be like humans. I'm trying to, I want to model of humans.

I mean, that's the mechanism is if it's modeling something, I think it's kind of really interesting. It's really interesting. It's more like I think it's potentially underlying modeling something like what the way the form is processed.

So what I like about dependency grammar is it makes the cognitive cost associated with longer distance connections very transparent. Basically there's some there turns out there is a cost associated with producing in comprehending connections between words which are just not beside each other. The further apart they are the worst it is the according to well we can measure that and there is a cost associated with that.

Oh, you can measure it in a lot of ways. The simplest is just asking people to say whether, you know, how good a sentence sounds, which is ask. It's one way to measure and you try to like triangulate then across sentences, across structures to try to figure out what the source of that is. You can look at, um, reading times in controlled materials. So in certain kinds of materials, when then we can measure the dependency distances there. There's a recent study which looked at, we're talking about the brain here, we could look at the language network. We could look at the language network, and we could look at the activation in the language network. And how big the activation is depending on the length of the dependencies. And it turns out in just random sentences that you're listening to, if you're listening to, it turns out there are people listening to stories here. And the bigger, the longer the dependency is, the stronger the activation in the language, in the language network. And so there's some measure, there's a different, there's a bunch of different measures we could do. That's a kind of a neat measure, actually, of actual activations.

Yeah, it's complicated, but probably it's doable. I would guess it's doable. I tried to do that a while ago and I was reasonably successful, but for some reason I stopped working on that. I do agree with you that it would be nice to figure out. So there's like some way to figure out the cost. I mean, it's complicated. Another issue you raised before was like how do you measure distance? Is it words? Is it probably isn't is the part of the problem? Is that some words matter them more than others and probably, you know, meaning like nouns might matter depending and then maybe depends of which kind of noun is it a noun we've already introduced or noun that's already been mentioned is it a pronoun versus a name like like all these things probably matter so probably the simplest thing to do is just like let's forget about all that and just think about words for sure but there might be a kind like there might be some insight in the kind of function that fits the data meaning like a quadratic like what I think it's an exponential. So we think it's probably an exponential such that the longer the distance the less it matters. And so then then it's the sum of those is my that that was our best guess a while ago. So that's you've got a bunch of dependencies if you've got a bunch of them that are being connected at some point that's at the ends of those, the cost is some exponential function of those, is my guess. But because the reason it's probably an exponential is like, it's not just the distance between two words, because I can make a very, very long subject verb dependency by adding lots and lots of noun phrases and prepositional phrases, and it doesn't matter too much. It's when you do nest it when I have multiple of these, then things get go really bad, go south.

Yeah, that's probably the function of the memory here is is the access is trying to find those earlier things. It's kind of hard to figure out what was referred to earlier. Those are those connections. That's that's the sort of notion of working as opposed to a storagey thing, but trying to connect retrieve those earlier words depending on what was in between and then then we're talking about interference of similar things in between. That's the right theory probably has that kind of notion and it is an interference of similar and so I'm dealing with an abstraction over the right theory which is just you know it's count words it's not right but it's close and then maybe right though there's some sort of an exponential or something on the on the to figure out the total, so we can figure out a function for any given sentence and any given language. But you know, it's funny. You know, people haven't done that too much, which I do think is I'm interested that you find that interesting. I really find that interesting. And a lot of people haven't found it interesting. And I don't know why I haven't got people to want to work on that. I really like that, too.

Yeah, that's why I like it too. It's so simple. Yeah, this is so simple. And yet it explains some very complicated phenomena. If you, if I write these very complicated sentences, it's kind of hard to know why they're so hard and you can like, oh, nail it down, I can do like a give you a math formula for why each one of them is bad and where. And that's kind of cool. I think as very neat.

No, no, no. No, simple answers. No, that does, there's probably things you can do in that kind of direction. That's fun. We might, you know, we're going to talk about legalism at some point. It's so we, we'll talk about that kind of thinking.

Oh, well, legalese is what you think it is. It's just an illegal language.

So I'm just like a language in laws and language and contracts. So the stuff that you have to run into, we have to run into every other day or every day. And you skip over because it reads poorly. And or you know, partly it's just long, right? There's a lot of texts there that we don't really want to know about. And so, but the thing I'm interested in, so I've been working with this guy called Eric Martinez, who is a, he was a lawyer. Who was taking my class. I was teaching a psycho linguistics lab class and I haven't been teaching it for a long time and MIT and he's a he was a law student at Harvard and he took the class because he had done some linguistics as an undergrad and he was interested in the problem of why legally sounds hard to understand. And so why is it hard to understand? And why do they write that way if it is hard to understand? It seems apparent that it's hard to understand. The question is why is it? And so we didn't know. And we did an evaluation of what you contracts. Actually, we just took a bunch of random contracts. because I don't know, there's contracts in laws might not be exactly the same, but contracts are kind of the things that most people have to deal with most of the time. And so that's kind of the most common thing that humans have, like humans, that adults in our industrialized society have to deal with a lot. And so that's what we pulled. And we didn't know what was hard about them, but it turns out that The way they're written is very center-betted has nested structures in them. So it has low frequency words as well. That's not surprising. Lots of texts have low, it does have a slightly lower frequency words than other kinds of control texts, even sort of academic texts, legal leases even worse. It is the worst that we were passing.

Well, you know, it's interesting. That's like, that's it. We know you're getting it. Why? And so, and I don't think, so near your thing, it's, they're doing intentionally. I don't think they're doing intentionally. Let's, let's, let's, let's, let's, let's, let's get an emergent phenomenon.

We'll get to that. We'll get to that. And so, but, but we wanted to see why. So, so we see what first as opposed. So, like, because it turns out that we're not the first to observe that legalese is weird. like back to Nixon had a plane language act in by in 1970 and Obama had one and have boy a lot of these you know a lot of presidents have said well we've got a simplified legal language must simplify but if you don't know how it's complicated it's not easy to simplify it you need to know what it is you're supposed to do before you can fix it Right, and so you need to like you need a single linguist to analyze the text and see what's wrong with it before you can like fix it. You don't know how to fix it. How am I supposed to fix something? I don't know what's wrong with it. And so what we did was just that's what we did. We figured out what's okay. We just want you contracts had people and we encoded them for the so a bunch of features. And so another feature of the people one of them was centrum betting. And so that is like basically how often a a clause would intervene between a subject in a verb, for example, that's one kind of a centrum betting of a clause, okay? And turns out they're massively centrum betting, like so I think in random contracts and in random laws, I think you get about 70% or 70% of sentences have a centrum betting clause, which is insanely high you go to any other text it's down to 20% or something it's it's so much higher than the any control you can think of including you think oh people think oh technical academic text no people don't write center embedded sentences in technical academic text let me do a little bit but much it's it's on the 20% 30% realm as opposed to 70 And so there's that and there's low frequency words and then people oh, maybe it's passive people don't like the passive passives for some reason the passive voice and English has a bad rap, but I'm not really sure where that comes from. And there is a lot of passive. And there's much more passive voice in the in the in legalese than there is in passive voice that comes for some of the low frequency words. No, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, The dependent measure is like how well you understand those things with those features. Okay, and so then and it turns out the passive makes no difference. So it has a zero effect on your comprehension ability on your recall ability. No, nothing at all. That means no effect. The words matter a little bit. They do my low frequency words are going to hurt you in recall and understanding, but what really what really hurts is the center bed. That kills you. That is like, that slows people down. That makes them, that makes them very, very poor at understanding, that makes them, they can't recall what was said as well, nearly as well. And we did this not only on lay people, we don't have a lot of lay people. We ran on 100 lawyers. We recruited lawyers from a wide range of of sort of different levels of law firms and stuff. And they have the same pattern. So they also, like, when they did this, I did not know would have not that maybe they could process, they're used to legally. So they think process just as well as if it was normal. No, no, they're much better than lay people. So they can much better recall much better understanding, but they have the same main effects as lay people exactly the same. So they also much prefer the non-centred. So we constructed non-centred beded versions of each of these. We constructed versions which have Higher frequency words in those places, and we did un-un-un-un-un-passivized. We turned them into active versions. The passive active made no difference. The words made a little difference, and the unscentral embedding makes big differences in all the populations.

Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect.

Easy to detect. Easy to detect. Easy to detect.

Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect. Easy to detect.

Easy to detect.

This is the go because in the event that any payment are benefit by the company, all such payments and benefits, including the payments and benefits under Section 3A here of being here here and after referred to as a total payments, would be subject to the exercise tax, then the cash severance payments shall be reduced. So that's something we pulled from a regular text, from a contract. Wow. And the center embedded bit there is just for some reason, there's a definition. They throw the definition of what payments and benefits are in between the subject and the verb let's how about don't do that yeah how about put the definition somewhere else as opposed to in the middle of the sentence and so that's that's very very common by the way that's that's what happens you just throw your definitions you use a word couple words and then you define it and then you continue the sentence like just don't write like that and and you ask so when we ask lawyers we don't maybe lawyers like this lawyers don't like this They don't like this. They don't want to write like this. We ask them to rate materials, which are with the same meaning, with unsentrabed incentive, and they much preferred the unsentrabed versions.

Yeah, and we asked them, we asked them, would you hire someone who writes like this? So this, we ask them all kinds of questions, and they always preferred the less complicated version, all of them. So I don't even think they want it this way. Yeah, but how did it happen? How did happen? That's a very good question. And the answer is, they still don't know.

Well, our best theory at the moment is that there's actually some kind of a performative meaning in the center embedding in this style, which tells you what's legalese. We think that that's the kind of a style which tells you what's legalese. Like that's a reasonable guess, and maybe it's just so, for instance, if you're like it's like, a magic spell. So we kind of call this the magic spell hypothesis. So when you give him, when you kill someone to put a magic spell on someone, what do you do? They, you know, people know what a magic spell is and they do a lot of rhyming. You know, that's what that's kind of what people will tend to do. They'll do rhyming and they'll do sort of like some kind of poetry kind of thing. Yeah, and maybe that's there's a syntactic sort of reflex here of a of a magic spell which is central betting and so that's like oh, it's trying to like tell you this is like this is something which is true which is what the goal of law law is right is telling you something that you we want you to believe as certainly true, right? That's what legal contracts are trying to enforce on you, right? And so maybe that's like a form, which has, this is like an abstract, very abstract form, sent from betting, which has a has a has a meaning associated with it.

That was one of our working hypotheses. We just couldn't find any evidence of that.

I'm suspicious as well. I'm still suspicious. And here you're saying it could be kind of a, you know, no individual and even average of individuals, it could just be a few bad apples in a way, which are driving the effect in some way.

But it turns, but it is, it is kind of interesting that among our hundred lawyers, they did not.

They really didn't like it.

It's the same difference. Exactly. But they wanted it fixed. And so that gave us hope that because it actually isn't very hard to construct a material, which is unsentering, but it has the same meaning. It's not very hard to do. You're just basically in that situation, you're just putting definitions outside of the subject verb relation in that particular example. And that's kind of, that's pretty general what they're doing is just throwing stuff in there, which you don't have to put in there. There's extra words involved. Typically, you may need a few extra words to refer to the things that you're defining outside in some way. Because if you only use it in that one sentence, then there's no reason to introduce extra terms. We might have a few more words, but it'll be easier to understand. I have hope that maybe we can make legal easeless

So that's about communication. And so this is going back to Shannon. So Shannon, Claude Shannon was a student at MIT in the 40s and so he wrote this very influential piece of work about communication theory or information theory and He was interested in human language actually he was trying he was interested in this problem of communication of getting a message from my head to your head and and so and he was concerned or interested in What was a robust way to do that? So that assuming we both speak the same language, we both already speak English, whatever language is, we speak that. What is a way that I can say the language so that it's most likely to get the signal that I want to you. And then the problem there. in the communication is the noise channel, is that there's, I make, there's a lot of noise in this system. I don't speak perfectly, I make errors, that's noise. There's background noise. You know that, it's like a literal background noise. There is like white noise in the background, or some other kind of noise, or some speaking going on that you're just, you're at a party, that's background noise. You're trying to hear someone, it's hard to understand them because there's almost other stuff going on in the background. And then there's noise on the communication on the receiver side, so that you have some problem maybe understanding me for stuff that's internal to you in some way. So you've got some other problems, whatever, with understanding for whatever reasons, maybe you're, if you had too much to drink, you know, who knows why you're not able to pay attention to the signal. So that's the noise channel. And so that language, if it's communication system, we are trying to Optimize, in some sense, the passing of the message from one side to the other. And so, I mean, one idea is that maybe, you know, aspects of like word order, for example, might have optimized in some way to make language a little more easy to be passed from speaker to listener. So as Shannon's the guy that did this stuff way back in the fort. It's very interesting, you know, historically he was interested in working in linguistics. He was in MIT and he did, this is his master's thesis of all things. You know, it's crazy how much, oh, she did for his master's thesis in 1948, I think, or 49 something. And he wanted to keep working in language and it just wasn't a popular communication as a as a reason a source for what language was wasn't popular at the time. So Trump's he was become it was moving in there. He was and he just wasn't able to get a handle there. I think and so and so he moved to Bell Haps and worked on communication from a mathematical point of view and was you know did all kinds of amazing work and so he's just more on the signal side of things like the language side.

He was interested in that as examples in the forties are kind of like they're like very language like really things. Yeah. We can kind of show that there's a noisy channel process going on in When you're listening to me, you know, you can often sort of guess what I meant by what I, you know, what you think I meant given what I said. And I mean, with respect to sort of why language looks the way it does, we might, there might be sort of, I said, alluded to there might be ways in which word orders is somewhat optimized for, for because of the noise channel in some way.

Well, the fancy length is really about memory, where you like, I think that's like about sort of what's easier harder to produce in some way. And these other ideas are about sort of robustness to communication. So the problem of potential loss of single due to noise. So there may be aspects of word order, which is somewhat optimized for that. And we have this one guess in that direction. And these are kind of just so stories I have to be, you know, frankly, they're not Like, I can't show this as true. All we can do is look at the current languages of the world. We can't see how languages change or anything because we've got these snapshots of a few hundred or a few thousand languages. We don't really do the right kinds of modifications to test these things experimentally. You know, so just take this with the grain of salt, okay, from here this this stuff the dependency stuff I can I'm much more solid on and like here's what the lengths are and here's and here's what's hard here's what's easy and this is a reasonable structure. I think I'm pretty reasonable here's like why you know why does the word order look the way it does is we're now into shaky territory, but it's kind of cool

We think that those are, there's three, at least three different kinds of things going on there. And we probably don't want to treat them all as the same. And so I think that you know, the right model, a better model of a noisy channel would treat, would have three different sources of noise, which, which are background noise. You know, speaker speaker, um, inherent noise and listener inherent noise. You know, and those are not those are all different things.

Well, how about just form still? They'll let you know. Like, so how well you know the language? And so if it's second language for you versus first language, and maybe what other languages you know, these are still just form stuff, and that's like potentially very informative. And you know, how old you are? These things probably matter, right? So like a child learning a language is as a noisy representation of English grammar, you know, depending on a old they are. Maybe when there are six, they're perfectly formed.

Yeah, well, all the languages in the world's language, none is right now. We know is any better than any other, we respect to sort of optimizing dependency lengths. For example, they're all kind of do it well. They all keep low. So I think of every human language is some kind of an optimization problem. a complex optimization problem to this communication problem. And so they've, like they've solved it, they know they're just sort of noisy solutions to this problem of communication. There's just so many ways you can do this.

Oh, oh, and learning. So yes, one of the factors which is, yes, so learning is messing this up a bit. And so so for example, if it were just about minimizing dependency lengths and that was all that matters, you know, then we, you know, so then then we might find grammars which didn't have regularity in their rules. But languages always have regularity in their rules. So what I mean by that is that if I wanted to say something to you in the optimal way to say it was really matter to me all that mattered was keeping the dependencies as close together as possible. Then I would have a very lacks set of free structure or dependency rule. It wouldn't have very many of those. I would have very little of that. And I would just put the words as close, the things that refer to the things that are connected right beside each other. But we don't do that. Like there are word order rules, right? So they're very, and depending on the language, they're more and less strict, right? So you speak Russian, they're less strict than English. English is very rigid word order rules. We order things in a very particular way. And so why do we do that? Like that's probably not about communication. That's probably about learning. I mean, then we're talking about learning. So I probably easier to learn regular regular things, things which are very productive, all in easy to. So that's probably about learning is our guess, because that can't be about community.

Well, if we're just a communication, then we should have languages which have very, very free word order. And we don't have that we have free ear, but not free, like there's always

Yes, that's true for a second language for a second. But that depends on what you started with. right? So it really depends on how close that second language is to the first language you've got. And so yes, it's very hard to learn Arabic if you've started with English or it's harder to, you know, hard to learn Japanese or if you've started with Chinese, I think is the worst in the, there's like defense language institute in the United States has like a list of of how hard it is to learn what language from English. I think Chinese is.

No. No evidence that there's anything harder, easier, but any language learned, like three or four, they speak that language. And so there's no evidence of anything harder, easier, but any human language. They're all kind of equal.

I mean, I, you know, the answers I don't know, of course. But the, I mean, I like to, I'm an engineer heard, I guess, and I sort of think it's fine to postulate that a lot of it's learned. And so I'm guessing that a lot of it's learned. So I think the reason Chomsky went with the nateness is because he, he hypothesized movement in his grammar. He was interested in grammar and movements hard to learn. And I think he's right. Movement is a harder. It's a hard thing to learn. To learn these two things together and how the interact. And there's like a lot of ways in which you might generate exactly the same sentences and it's like really hard. And so he's like, oh, I guess it's learned. Sorry, so I guess it's not learned. It's innate. And if you just throw out the movement and just think about that in a different way, then you get some messiness But the messiness is human language, which it actually fits better. That messiness isn't a problem. It's actually a valuable asset of the theory. And so I think I don't really see a reason to postulate much innate structure. And that's why I think these large language problems are learning so well, is because I think you can learn the form, the forms of human language from the input. I think that's like it's likely to be true.

It doesn't have to be innate. So like lots of stuff is modular in the brain that's learned. It doesn't have to, you know, so there's something called the visual word form area in the back. And so it's in the back of your head when you're the, you know, the visual cortex, okay? And that is very specialized language, sort of very specialized brain area, which does visual word processing if you read if you're a reader okay if you don't read you don't have it okay guess what you spend some time learning to read and you develop that that brain area which does exactly that and so these the modularization does not evidence for innateness so the modularization of a language area it doesn't mean we're born with it we could have easily learned that I we might have been born with it I which we just don't know at this point we might very well have been born with this left lateralized area I mean that there's like a lot of other interesting components here that it features of this kind of argument. So some people get a stroke or something goes really wrong on the left side where the left where language area would be and that and that isn't there. It's not not available. And it develops just fine the right. So it's not about the left. It goes to the left. Like this is a very interesting question. It's like why is the, why are any of the brain areas the way that they are and how, how, how do they come to be that way? And, you know, there's these natural experiments which happen where people get these, you know, strange events in their brains at very young ages, which wipe out sections of their brain. And they behave totally normally and no one knows anything was wrong. And we find out later because they happen to be accidentally scanned for some reason. It's like what what happened to your left hemisphere? It's missing. There's not many people have missed their whole left hemisphere, but they'll be missing some other section of their left or their right. And they behave absolutely normally would never know. So that's like a very interesting, you know, current research. You know, this is another project that this person in Federico is working on. She's got all these people contacting her because she's scanned some people who have been missing sections, one person missed a section of her brain and was scanned in her lab. And she happened to be a writer for the New York Times. And it was an article in New York Times about the scanning procedure and about what might be learned about by the general process of MRI and language. And because she's writing for the New York Times, so all these people started writing to her. People who also have similar kinds of deficits because they've been accidentally scanned for some reason and found out they're missing some section. They've volunteered to be scanned.

Natural experiments. They're kind of messy, but natural experiments are kind of cool. She calls them interesting brains.

Yeah, he thinks so. I don't know what he'd say.

That's right. Absolutely.

Right, but so, you know, he's basically a philosopher, philosopher of language in a way, thinking about these things. It's a fine thought. You can't test it in his methods. You can't do a thought experiment to figure that out. You need a scanner, you need brain damage people, you need something, you need ways to measure that. And that's what FMI offers as a, and patients are a little messier. FMI is pretty unambiguous, I'd say. It's like very unambiguous. There's no way to say that the language network is doing any of these tasks. You should look at those data. There's no chance that you can say that those networks are overlapping. They're not overlapping. They're just completely different. You can always make, you know, it's only two people. It's four people or something for the patients. And there's something special about them. We don't know. But these are just random people. And with lots of them, and you find always the same effects. And it's very robust, I'd say.

So that term weird is from Joe Henrich. He's a Harvard evolutionary biologist. And so he works on lots of different topics. And he basically was pushing that observation that we should be careful about the inferences we want to make when we're talking in psychology or sociology. Yeah, most in psychology, I guess about humans if we're talking about, you know, undergrads at MIT and Harvard. Those aren't the same, right? These aren't the same things. And so if you want to make inferences about language, for instance, there's a lot of other kinds of languages in the world, then English and French and Chinese. And so maybe, for language, we care about how culture because cultures can be very, I mean, of course, English and Chinese cultures are very different. But, you know, hunter-gatherers are much more different in some ways. And so, you know, if culture has an effect on what language is, then we kind of want to look there as well as looking. It's not like the industrialized cultures are an interesting, of course, they are, but we want to look at non-industrialized cultures as well. And so, I've worked with two, I've worked with the Chimani, which are in Bolivia, And the Amazon, both in the Amazon, in these cases, and there are so-called farmer foragers, which is not hunter-gatherers. It's sort of one-up from hunter-gatherers, and that they do a little bit of farming as well, a lot of hunting as well, but a little bit of farming. And the kind of farming they do is the kind of farming that I might do if I ever were to grow like tomatoes or something in my backyard. It's not like, so it's not like big field farming. It's just a farming for a family, a few things you do that. So that's the kind of farming they do. And the other group I've worked with are the Pietaja, which are in also in the Amazon and happened to be in Brazil. And that's with a guy called Dan Everett, who is a linguist anthropologist who actually lived and worked in the, I mean, he was a missionary actually initially back in the 70s working with trying to translate languages so they could teach them the Bible to teach them Christianity.

Yeah, so the two groups I've worked with, the Chamanian, the Piedahar, both isolate languages, meaning there's no known connected languages at all, they're just like on their own. Yeah, there's a lot of those, and most of the isolates occur in the Amazon or in Papua New Guinea, and these places where the world has sort of stayed still for a long enough, And there are, like, so there aren't earthquakes, there aren't. Well, certainly no earthquakes in the Amazon jungle. And the climate isn't bad, so you don't have droughts. And so, you know, in Africa, you've got a lot of moving of people because there's drought problems. And so, so they get a lot of language contact. When people have to move because you've got no water, then you've got to get going, and then you run into contact with other tribes, other groups. In the Amazon, that's not the case, and so people can stay there for hundreds and hundreds and probably thousands of years, I guess. And so these groups have, the Chmani and the Pianohar, both isolates in that, and they just, I guess they've just lived there for ages and ages, with minimal contact with other outside groups. Um, and so I mean, I'm interested in them because they are, I mean, I, you know, in these cases, I'm interested in their words. I would love to study their syntax, their orders of words, but I mostly just interest in how languages, you know, are connected to, um, their cultures in this way. And so with the Piano Ha, sort of most interesting, I was working on number their number information. And so the basic idea is I think language is invented. This is where I get from the words here is that I think language is invented. We talked about color earlier as the same idea so that what you need to talk about with someone else is what you're going to invent words for. And so we invent labels for colors that I need, not that I than I can see, but that things I need to tell you about so that I can get objects from you or get you to give me the right objects. And I just don't need a word for teal or a word for accomorine in the Amazon jungle for the most part because I don't have two things which differ on those colors. I just don't have that. And so numbers are really another fascinating source of information here where you might, Naively, I certainly thought that all humans would have words for exact counting. Uh, and the piano had don't. Okay. So they don't have any words for even one. There's not a word for one in there in their language. And so they're still not word for two, three, or four. So, so that kind of blows people's minds on.

You just don't. And so that's not a thing you can possibly ask in the future. It's not possible. That is, there's no words for that. So here's how we found this out, okay? So it was thought to be a one to many language. There are three words for quantifiers, for sets, but people had thought that those meant one to and many. But what they really mean is few some in many, many is correct, it's few some in many. And so the way we figured this out and this is kind of cool is that we gave people We had a set of objects, okay, and these were having these spools of thread, doesn't really matter what they are, a dendical objects, and I sort of start off here, I just give, you know, give you one of those and say, what's that? Okay, so you're a Piano House speaker, and you tell me what it is, and then I give you two and say, what's that? And, and nothing's changing in this set, except for the number, okay, and then I just ask you to label these things. We just do this for a bunch of different people, and frankly, it's, I did this task. and it's a weird it's a little bit weird so you say the word that they thought that we thought was one it's few but for the first one and then maybe they say few or maybe they say some for the second and then for the third of the fourth they start using the word many for the set and then five six seven eight I go all the way to 10 And it's always the same word and they look at me like I'm stupid because they told me what the word was for six seven eight and I'm going to continue asking them at nine and ten. I'm sorry. I just I just they understand that I want to know their language. That's the point of the task is like I'm trying to learn their language and so that's okay. But it does seem like I'm a little slow, because they already told me what the word for many was five, six, seven, and I keep asking. So it's a little funny to do this task over and over. We did this with the guy called Dan with our translator. He's the only one who really speaks Pietaja fluently. He's a good bilingual for a bunch of languages, but also in English and Pietaja. And then what guy called Mike Frank was also a student with me down there. He and I did these things. So you do that, okay, and everyone does the same thing. They all all, you know, and we ask like 10 people, and they all do exactly the same labeling for one up. And then we just do the same thing down on like random order. Actually, we do some of them up some of them down first, okay. And so we do instead of one to 10, we do 10 down to one. And so so I give them 10, 9, and 8, they start saying the word. for some. And then down when you get to four, everyone is saying the word for few, which we thought was one. So it's like the context determined what word, what what that quantifier they used was. So it's not a count word. They're not count words. They're just approximate words.

Yeah, I don't know what that means. That's going to be turned on the context.

If you ask an English person what a few is. I mean, that's completely on the context.

So the words aren't there. And then, and so then we do these other things. Well, if they don't have the words, can they do exact matching kinds of tasks? Can they even do those tasks? And the answer is sort of yes and no. And so yes, they can do them. So here's the tasks that we did. We put out those spools of thread. Again, okay, so I'm going to put like three out here. And then we gave them some objects. And those happen to be uninflated red balloons. It doesn't really matter what they are. It's just a bunch of exactly the same thing. And it was easy to put down right next to these And so then I put out three of these, and your task was to just put one against each of my three things. And they could do that perfectly. So I mean, I would actually do that. It was a very easy task to explain to them, because I have, I did this with this guy Mike Frank, and he would be my, I'd be the experimenter telling him to do this and showing him to do this and then we just like just do it he did you'll copy him all we had to I didn't have to speak to your how except for know what copy him like do it he did is like all we had to be able to say and and then they would do that just perfectly and it's only move it up we do some sort of random number of items up to 10 and they basically do perfectly on that they never get that wrong I mean that's not accounting task right that is just a match you just put one against doesn't matter how many I don't need to know how many there are there to do that correctly And they would make mistakes, but very, very few, and no more than MIT undergrad. Just going to say, like, there's no, there's a low stakes.

That's right. Not at all. Okay. And so, and so that's our control. And this guy had gone down there before and said that they couldn't do this task. But I just don't know what he did wrong there, because they can do this task perfectly well. You know, I can train my dog to do this task. So, of course, they can do this task. And so, you know, it's not a hard task. But the other task that was sort of more interesting is like, so then when you bunch of tasks where you need, some way to encode the set. So like one of them is just a, I've just put a opaque sheet in front of the other things. I put down a bunch of set of these things and I put no opaque sheet down. And so you can't see them anymore. And I tell you do the same thing you were doing before, right? You know, and it's easy if it's two or three, it's very easy. But if I don't have the words for eight, it's a little harder, like maybe, you know, with practice, when one

For us, it's easy because we just count them. It's just so easy to count them. But they can't count them because they don't count. They don't have words for this thing. And so they would do approximate. It's totally fascinating. So they would get them approximately right. You know, after four or five, you know, because you can basically always get four right, three or four that looks that's something we can visually see. But after that you kind of have it's a approximate number and so then there's a bunch of tasks we did and they all failed as I mean failed. They did approximate after five on all those tasks and it just kind of shows that the words

Yeah. Here's language is just is the words. Here is the words. Like the words for exact count is the limiting factor here. They just don't have them.

That's going to be true. Yeah. So it's problem. I mean, we don't know. This is one of those problems with the snapshot of just current languages is that we don't know what causes a culture to discover slash invent accounting system. But the hypothesis is the guess out there is something to do with farming. So if you have a bunch of goats And you want to keep track of them. And you have saved 17 goats and you go to bed at night and you get up in the morning. Boy, it's easier to have a count system to do that. That's an abstraction over a set. People often ask me when I talk to them about this kind of work, and they say, well, don't these people don't have kids? Don't have a lot of children. They have a lot of children. And they do. They often have families of three or four or five kids. And they go, what don't they need the numbers to keep track of their kids? And I always ask this person who says, does like, do you have children? And the answer is always, no, because that's then how you keep track of your kids. You care about their identities. It's very important to me when I go, I think if five children, it doesn't matter which, it matters which five.

If you replaced one with someone else, I would care. Goat may be not, right? That's the kind of point. It's an abstraction. Something that looks very similar to the one wouldn't matter to me, probably.

I mean, cows, goats, if there's a source of food and milk and a lot of stuff, you're going to actually, but I'm saying it is abstractions such that you don't have to care about their identities to do this thing fast. That's the hypothesis, not mine. From anthropologists is guessing about where words for counting came from is from farming, maybe. Yeah.

Well, my guess is the function of a language is to do something in a community. Unless there's some function to that language in the community, it's not going to survive. It's not going to be useful. Here's a great example. Language death is super common. language is her dying all around the world. And here's why they're dying. And it's like, yeah, I see this in, you know, it's not happening right now. And either the Chumani or the, or the Piaohan, but it probably will. And so there's a neighboring group called Mostiton, which is, I said that it's, I said that it's, uh, isolate. It's actually, there's a dual. There's two of them. Okay. So it's actually two languages which are really close, which are Mostiton. And, and, and, and Chamanai, which are unrelated to anything else. And most of the time is unlike Chamanai in that it has a lot of contact with Spanish and it's dying. So that language is dying. The reason it's dying is there's not a lot of value for the local people in their native language. So there's much more value in knowing Spanish, like because they want to feed their families and how do you feed your family? You learn Spanish so you can make money so you can get a job and do these things and then you can and then you make money and so they want Spanish things they want and so so most of the time is staying is in danger and is dying and that's normal and so basically the problem is that people The reason we learn languages to communicate and we need to we use it to to make money and to do whatever it is to to feed our families and if that's not happening Then it won't take off. It's not like a game or something This is like something we you like why is English so popular? It's it's not because it's an easy language to learn Maybe it is I don't really know it's but that's not why it's popular

It's all about money and so it's a motivation to learn Mandarin. There's a motivation to learn English. These languages are very valuable to know because there's so many speakers all over the world. There's less than a value economically. It's like kind of what drives this. It's not a You know, it's not just for fun. I mean, there are these groups that do want to learn language just for language to sake, and then there's something to that. But those are rare, those are rareties in general. Those are few small groups that do that, not most people don't do that.

Well, towards fewer and fewer languages.

Yeah, I completely agree and there's a lot of work to try to create that identity so people want to do that. As a cognitive scientist in language expert, I hope that continues because I don't want languages to do. I want languages to survive because because there's so interesting for so many reasons. I find the fascinating just for the language part, but I think there's a lot of connections to culture as well, which is also very important.

There's going to be cases where it's going to be really hard, right? So there are concepts that are in one language and not another, like the most extreme kinds of cases are these cases of number of information. So exactly, like good luck translating a lot of English in Dupiatahah. It's just impossible. There's no way to do it because there are no words for these concepts that we're talking about. There's probably the flip side, right? There's probably stuff in Peter Ha, which is going to be hard to translate into English on the other side. And so I just don't know what those concepts are. I mean, you know, the space, the world space is a little different from my world space, so I don't know what, so that the things they talk about, things are You know, it's going to have to do with their life as opposed to, you know, my industrial life, which is going to be different. And so there's going to be problems like that always. You know, there's like, it's not maybe it's not so bad. In the case of some of these spaces and maybe it's going to be harder and others. And so it's pretty bad in number. It's like, you know, extreme, I'd say, in the number space, you know, exact number space. But in the color dimension, right? So that's not so bad. I mean, but it's a problem that you don't have ways to talk about

Yes. Yeah, but so you were talking earlier about to translation and about how translations, there's good and bad translations. I mean, now we're talking about translations of form, right? So what makes it writing good, right?

Right, it's not just the content. It's how it's written. And translating that, you know, that sounds difficult.

We can probably get measures of those. Yeah. I don't know. I'm optimistic that we could get measures of those things. And so maybe that's translatable.

That's your sense. It's simple sentences.

You don't have to. You can have a long long sentence with a bunch of local words. Yeah. But it is much more likely to have the possibility of long dependencies with long sentences. Yeah.

I would say yes. I think it's not crazy at all. I think it's quite reasonable. There's this sort of weird, well, odd view. I think that to think that human language is somehow special. I mean, it is maybe it is. We can certainly do more than any of the other species. And maybe our language system is part of that. It's possible. But people do have often talked about how human like Tromsky, in fact, is talk about how human only human language has, you know, this this compositionality thing that he thinks is sort of key in language. And it's the problem with that argument is he doesn't speak well. And he doesn't speak, uh, crow. And he doesn't speak monkey. You know, he's like, they say things like, well, they're making a bunch of grunts and squeaks. And the reasoning is like, that's bad reasoning. Like, you know, I'm pretty sure if you asked a whale what we're saying, they'd say, well, I'm making a bunch of weird noises.

And so it's like this is a very odd reasoning to be making that human language is special because we're the only one to have human language. I'm like, well, we don't know what those other we just don't know we can't talk to them yet. And so they're probably a signal in there and it might very well be something complicated, like human language. I mean, sure, with a small brain in lower species, there's probably not a very good communication system, but in these higher species where you have, you know, what seems to be, you know, abilities to communicate something, there might very well be a lot more signal there than we might have otherwise thought.

Well, I mean, I think some of them are not going to have much interesting to say. We don't know. We certainly don't know.

Well, they're probably talking to other trees, right? They're not talking to us. And so to the extent they're talking, they're saying something interesting to some other, you know, you know, conspecific as opposed to us, right? And so they probably is, there may be some signal there. So there are people out there, actually, is pretty common to say that human language is special and different from any other animal communication system. And I just don't think the evidence is there for that claim. I think it's not obvious. And we just don't know because we don't speak these other communication systems until we get better. I do think there are people working on that as you pointed out that people working on whale speak for instance. That's really fascinating.

I mean, I would want Dan Everett with me. He is like amazing at learning for languages. And so he, like, this is an amazing feat, right, to be able to go. This is a language, Piedoha, which has no translators before him.

Well, there was a guy that had been there before, but he wasn't very good. And so he learned the language far better than anyone else had learned before him. He's like good at He's just a very social person. I think that's a big part of it. It's being able to interact. So I don't know what kind of hands on these, this species from other space, how much they want to talk to us.

Yeah, you start that. You actually start with like objects and just say, you know, just throw a stick down and say stick. And you say, well, you call this and say, do this and then they'll say the word, whatever. And he says a standard thing to do is throw two sticks and two sticks and then, you know, he learned pretty quick that they weren't any count words. They didn't know. This wasn't interesting. I mean, it was kind of weird. They'd say some or something the same word over and over again. And so, but that is a standard thing. You just like try to, but you have to be pretty out there socially, like willing to talk to random people. people, which these are really very different people from you. And he's very social. And so I think that's a big part of this. It's like, that's how a lot of people know a lot of languages that they're willing to talk to the people.

Yeah. Oh, God. That's beautiful.

When you see something interesting, just go and do it. Like I do, I do that. Like that's something I do, which is kind of unusual for most people. So like when I saw the piano, like a piano, how was available to go and visit? I was like, yes, yes, I'll go. And then when we couldn't go back, we had some trouble with the Brazilian government. There's some corrupt people there. It was very difficult to get go back in there. And so I was like, alright, I gotta find another group. And so we searched around and we were able to find the Chamon... because I wanted to keep working on this kind of problem. And so we found the Chamon and go there. I didn't really have, we didn't have content. We had a little bit of contact and brought someone. And that was, you know, we just kind of just try things. I say it's like... A lot of that just like ambition just try to do something that other people haven't done just give it a shot is what I mean, I do that all the time.

Thank you very much, Lexus when pleasure.