4 ms·

Speaking of non-political side of him: was not he wrong about "innate grammar" necessary to understand langage? LLM do not have such circuitry, yet they somehow

Speaking of non-political side of him: was not he wrong about "innate grammar" necessary to understand langage? LLM do not have such circuitry, yet they somehow work well...

yareal 2y ago
LLMs are an approximation of all the human media they consume. An LLM cannot exist with out human circuitry. It's at best an ersatz language user.
- SomeoneFromCA 2y ago
  Unrelated to what I said, with all due respect.
  - sitkack 2y ago
    It isn't tho, if you look at the bulk of tokens needed to train gen1 over LLMs and what is possible with better data and smaller models. The fact that LLMs trained on dumptrucks full of data cannot achieve what a middle schooler begrudgingly achieves using existence and snide remarks.
  - flaminHotSpeedo 2y ago
    I'd consider it related, for two reasons: First and foremost (and what I think the parent comment is getting at) whether you could truly say an LLM "understands" language As a secondary quibble in the context of the parent post, though big overall, I would argue that the whole argument is moot since a human couldn't possibly learn the way an LLM does in a single lifetime
gizmo686 2y ago
No. Innate grammar has always been about how humans aquire language, not how any possible system which understands human language must posses that innate grammar.
- SomeoneFromCA 2y ago
  But that has never been proven that this is how indeed human acquire language; it is essentially a hypothesis. We may as well do it the way LLMs do - some undifferentiated networks acquires the grammar by unknown means.
  - nsingh2 2y ago
    LLMs are universal approximators and can pick up patterns in sequences that are very different from Human languages. Sure, they don't have many inductive biases and can understand language, but as a consequence require a tremendous amount of data to work. Humans don't, which implies a certain bias towards Human language built into our heads. A bias is also implied by the similarities across Human languages, though what structure(s) in the brain are responsible is not exactly clear.
    - SomeoneFromCA 2y ago
      It still does not proof anything, as claiming that "there is certain bias for Human Language built into our heads" is quite different thing that saying there is some universal grammar in the brain structures, as much we do not have innate abilities to comprehend calculus or play chess, yet we still able to learn it, with a lot less training information than LLMs. In fact 2 books will suffice for the both.
      - codeflo 2y ago
        We don’t learn language from textbooks though.
      - nsingh2 2y ago
        My comment was more of a response to > We may as well do it the way LLMs do We almost certainly don't learn the way LLMs do, it's just too data inefficient. And I don't see what current LLMs can say about a universal grammar in the Human brain, unless there is proof that a LLM-style attention mechanism exists in the brain, and that it is somehow related to language understanding.
materielle 2y ago
I don't think LLMs have all that much to do with "innate grammar". "Innate grammar" are essentially the meta-rules that govern why the rules are what they are. For instance, an English phrase can be recognized as valid or invalid by other native speakers according to the rules of the language. But why are the rules what they are? This is especially puzzling due to the dazzling variety of human languages. And the fact that, after a period of immersion, humans seem to have the natural capacity to learn all of them. How do LLMs fit into this? Well, I think it would be interesting if we left a group of LLM to talk to each other for 1000 years. Then see if 1) they developed a new language branch 2) that could be relearned by humans through immersion alone. It's true that LLMs have learned (have they? I suppose that's a loaded word) human languages like English. But it's unclear if they are governed by the same meta-rules that both constrains and drives the evolution of humanities thousands of distinct languages.
codeflo 2y ago
Compared to an LLM, how many hundreds of gigabytes of text do humans need to acquire a language? And isn’t that disparity already proof that some sort of innate structure must be going on?
- EVa5I7bHFq9mnYK 2y ago
  Or that llm learning algos should be further improved, which will happen at some point. I remember Kasparov's tirades to the tune of I have an eternal soul therefore computers can never beat me in chess.
tgv 2y ago
There have been many attempts to model and emulate human syntactic acquisition and processing, but the general consensus is that it cannot be done without presupposing some mechanism that enables hierarchical structure. The number of tokens a child needs to learn syntax is the tiniest fraction of the amount of tokens an LLM is trained on. Humans can also lose parts of their language processing capabilities, without losing others (start at e.g. https://en.wikipedia.org/wiki/Language_disorder https://en.wikipedia.org/wiki/Language_disorder), which is highly suggestive of modular language development. The only question on which there isn't much consensus concerns the origin of that modularity. And humans can lose knowledge while still being able to speak and understand, or lose language while retaining knowledge. LLMs don't have that at all: they predict the next token.
- renonce 2y ago
  LLMs does have that, or at least it’s very likely that we will eventually be able to manipulate LLMs in a modular way (see https://news.ycombinator.com/item?id=40429540 https://news.ycombinator.com/item?id=40429540). One point remains: humans learn language with much fewer tokens than LLMs need, which suggests presence of a priori knowledge about the world. The LLM metaphor is finetuning, so babies are born with a base model and then finetuned with environment data, but it’s still within LLM scope.
  - tgv 2y ago
    > presence of a priori knowledge about the world 1. A certain architecture (e.g. a module that enables syntactic processing) is not knowledge about the world. 2. We model the world according to our capabilities. 3. Modular language models have been tried, but did not meet with success. 4. The link you include is about the conceptual space, which is not (directly) related to human syntactic processing. 5. The question is not about metaphors, but about reality. 6. Babies aren't born with a base model and fine-tuned. They learn. This is the metaphor NNs are actually based on.
graphe 2y ago
https://www.discovermagazine.com/the-sciences/fruit-fly-brain-network-hacked-for-language-processing https://www.discovermagazine.com/the-sciences/fruit-fly-brai... He mentioned a structure and scientists hacked a fruit fly Kenyon organ to process language which it does pretty well, also at MIT. The approach is relatively straightforward. The team began by using a computer program to recreate the network that mushroom bodies rely on — a number of projection neurons feeding data to about 2,000 Kenyon cells. The team then trained the network to recognize the correlations between words in the text. The task is based on the idea that a word can be characterized by it its context, or the other words that usually appear near it. The idea is to start with a corpus of text and then, for each word, to analyze those words that appear before and after it.
randomcarbloke 2y ago
I think the popular perception is that his theory is extremely important, as far as I know the academic consensus is that while hugely influential it is long obsolete.
bux93 2y ago
Somehow the transformer architecture does pretty well at this task, and other architectures do not. You could say a transformer has "innate grammar", while other architectures do not. That an LLM does well at grammar doesn't prove or disprove this possibility. A more poignant criticism of "innate grammar" would be that it's not a hypothesis that can be disproven, and as such not really a scientific statement.

Speaking of non-political side of him: was not he wrong about "innate grammar" necessary to understand langage? LLM do not have such circuitry, yet they somehow work well...

yareal 2y ago

LLMs are an approximation of all the human media they consume. An LLM cannot exist with out human circuitry. It's at best an ersatz language user.

SomeoneFromCA 2y ago
Unrelated to what I said, with all due respect.
- sitkack 2y ago
  It isn't tho, if you look at the bulk of tokens needed to train gen1 over LLMs and what is possible with better data and smaller models. The fact that LLMs trained on dumptrucks full of data cannot achieve what a middle schooler begrudgingly achieves using existence and snide remarks.
- flaminHotSpeedo 2y ago
  I'd consider it related, for two reasons: First and foremost (and what I think the parent comment is getting at) whether you could truly say an LLM "understands" language As a secondary quibble in the context of the parent post, though big overall, I would argue that the whole argument is moot since a human couldn't possibly learn the way an LLM does in a single lifetime

gizmo686 2y ago

No. Innate grammar has always been about how humans aquire language, not how any possible system which understands human language must posses that innate grammar.

SomeoneFromCA 2y ago
But that has never been proven that this is how indeed human acquire language; it is essentially a hypothesis. We may as well do it the way LLMs do - some undifferentiated networks acquires the grammar by unknown means.
- nsingh2 2y ago
  LLMs are universal approximators and can pick up patterns in sequences that are very different from Human languages. Sure, they don't have many inductive biases and can understand language, but as a consequence require a tremendous amount of data to work. Humans don't, which implies a certain bias towards Human language built into our heads. A bias is also implied by the similarities across Human languages, though what structure(s) in the brain are responsible is not exactly clear.
  - SomeoneFromCA 2y ago
    It still does not proof anything, as claiming that "there is certain bias for Human Language built into our heads" is quite different thing that saying there is some universal grammar in the brain structures, as much we do not have innate abilities to comprehend calculus or play chess, yet we still able to learn it, with a lot less training information than LLMs. In fact 2 books will suffice for the both.
    - codeflo 2y ago
      We don’t learn language from textbooks though.
    - nsingh2 2y ago
      My comment was more of a response to > We may as well do it the way LLMs do We almost certainly don't learn the way LLMs do, it's just too data inefficient. And I don't see what current LLMs can say about a universal grammar in the Human brain, unless there is proof that a LLM-style attention mechanism exists in the brain, and that it is somehow related to language understanding.

materielle 2y ago

I don't think LLMs have all that much to do with "innate grammar". "Innate grammar" are essentially the meta-rules that govern why the rules are what they are. For instance, an English phrase can be recognized as valid or invalid by other native speakers according to the rules of the language. But why are the rules what they are? This is especially puzzling due to the dazzling variety of human languages. And the fact that, after a period of immersion, humans seem to have the natural capacity to learn all of them. How do LLMs fit into this? Well, I think it would be interesting if we left a group of LLM to talk to each other for 1000 years. Then see if 1) they developed a new language branch 2) that could be relearned by humans through immersion alone. It's true that LLMs have learned (have they? I suppose that's a loaded word) human languages like English. But it's unclear if they are governed by the same meta-rules that both constrains and drives the evolution of humanities thousands of distinct languages.

codeflo 2y ago

Compared to an LLM, how many hundreds of gigabytes of text do humans need to acquire a language? And isn’t that disparity already proof that some sort of innate structure must be going on?

EVa5I7bHFq9mnYK 2y ago
Or that llm learning algos should be further improved, which will happen at some point. I remember Kasparov's tirades to the tune of I have an eternal soul therefore computers can never beat me in chess.

tgv 2y ago

There have been many attempts to model and emulate human syntactic acquisition and processing, but the general consensus is that it cannot be done without presupposing some mechanism that enables hierarchical structure. The number of tokens a child needs to learn syntax is the tiniest fraction of the amount of tokens an LLM is trained on. Humans can also lose parts of their language processing capabilities, without losing others (start at e.g. https://en.wikipedia.org/wiki/Language_disorder https://en.wikipedia.org/wiki/Language_disorder), which is highly suggestive of modular language development. The only question on which there isn't much consensus concerns the origin of that modularity. And humans can lose knowledge while still being able to speak and understand, or lose language while retaining knowledge. LLMs don't have that at all: they predict the next token.

renonce 2y ago
LLMs does have that, or at least it’s very likely that we will eventually be able to manipulate LLMs in a modular way (see https://news.ycombinator.com/item?id=40429540 https://news.ycombinator.com/item?id=40429540). One point remains: humans learn language with much fewer tokens than LLMs need, which suggests presence of a priori knowledge about the world. The LLM metaphor is finetuning, so babies are born with a base model and then finetuned with environment data, but it’s still within LLM scope.
- tgv 2y ago
  > presence of a priori knowledge about the world 1. A certain architecture (e.g. a module that enables syntactic processing) is not knowledge about the world. 2. We model the world according to our capabilities. 3. Modular language models have been tried, but did not meet with success. 4. The link you include is about the conceptual space, which is not (directly) related to human syntactic processing. 5. The question is not about metaphors, but about reality. 6. Babies aren't born with a base model and fine-tuned. They learn. This is the metaphor NNs are actually based on.

graphe 2y ago

https://www.discovermagazine.com/the-sciences/fruit-fly-brain-network-hacked-for-language-processing https://www.discovermagazine.com/the-sciences/fruit-fly-brai... He mentioned a structure and scientists hacked a fruit fly Kenyon organ to process language which it does pretty well, also at MIT. The approach is relatively straightforward. The team began by using a computer program to recreate the network that mushroom bodies rely on — a number of projection neurons feeding data to about 2,000 Kenyon cells. The team then trained the network to recognize the correlations between words in the text. The task is based on the idea that a word can be characterized by it its context, or the other words that usually appear near it. The idea is to start with a corpus of text and then, for each word, to analyze those words that appear before and after it.

randomcarbloke 2y ago

I think the popular perception is that his theory is extremely important, as far as I know the academic consensus is that while hugely influential it is long obsolete.

bux93 2y ago

Somehow the transformer architecture does pretty well at this task, and other architectures do not. You could say a transformer has "innate grammar", while other architectures do not. That an LLM does well at grammar doesn't prove or disprove this possibility. A more poignant criticism of "innate grammar" would be that it's not a hypothesis that can be disproven, and as such not really a scientific statement.