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The author (bafflingly) seems to have completely missed the point- since anything they state up to page 15 (at which point I stopped reading) does not refute Ch
by neosat 3y ago
The author (bafflingly) seems to have completely missed the point- since anything they state up to page 15 (at which point I stopped reading) does not refute Chomsky's points at all. The author talks about LLMs and how they generate text and then goes on to talk about how it refutes Chomsky's claim about syntax and semantics. However it does not since Chomsky's primary claim is about how HUMANS acquire language.
The fact that you can replicate coherent text from probabilistic analysis and modeling of a very large corpus does not mean that humans acquire and generate language the same way. [edited page = 15]
- CydeWeys 3y ago> The fact that you can replicate coherent text from probabilistic analysis and modeling of a very large corpus does not mean that humans acquire and generate language the same way. Also, the LLMs are cheating! They learned from us. It's entirely possible that you do need syntax/semantics/sapience to create the original corpus, but not to duplicate it. Let's see an AlphaZero-style version of an LLM, that learns language from scratch and creates a semantically meaningful corpus of work all on its own. It's entirely possible that Chomsky's mechanisms are necessary to do so.
- famouswaffles 3y ago>Also, the LLMs are cheating! No...they aren't. Humans aren't learning from thin air by any stretch of the imagination.
- enord 3y agoWe did, at least once.
- meepmorp 3y agoNo, humans learn their languages through observation and generation - watching older people speak, and then imitating it. They get corrections, too, when they mispronounce or misuse words.
- squeaky-clean 3y agoThey mean at one point there were no older people to listen to in order to learn language because language did not exist yet. We somehow transitioned from grunts to words.
- enord 3y agoI didn’t say everyone learns it from scratch at least one, I said we did.
- meepmorp 3y agoThat's not learning, though, is it? Inventing, maybe, or developing or evolving.
- enord 3y agoWe either have the capacity to make boats and traverse the oceans or we don’t. These days almost nobody makes boats, but we sure used to and still can. What’s your point?
- meepmorp 3y agoI have no idea what you're talking about and it doesn't really matter to me anyway. Enjoy your day.
- 3y ago
- famouswaffles 3y agoThe brain is obviously pre-disposed to language. But evolution fueled learning is by no means from "thin air".
- enord 3y agoThat’s a red herring. Ex post facto the activity of language use as a construction must supersede some enaction by capable actors. This is a complete tautology in terms, and any dispute must therefore be over the ontology in which it is expressed. To elaborate how something came to be is not required to express that something is.
- famouswaffles 3y agoWhat makes capable actors capable in the first place is not derived from thin air. There's a reason a capable actor came to be where there was none generations prior. That reason did not come about without reaction to some outside vector. Evolution optimized for language learning abilities before the full capabilities came. Evolution is not thin air.
- enord 3y agoThe «air» is here an allegory for «large language corpus». It is self-evidently true that as we move backwards through history we eventually pass the first language utterance for any given definition of language or utterance. From here on out, the «air» is indeed «thin». There are still other things, but no «air» (i.e. «language corpora»).
- jvanderbot 3y agoHumans are, in the sense that we're working off the checkpoint passed to us from our parents: the bare minimum language centers our brain is evolved to produce regardless. The sequence of checkpoints evolves effectively from scratch, but individual humans adapt the checkpoint for their environment from birth. I like to think of the brain as the general model we've trained with evolution, and the person's experiences as the specialization.
- mjburgess 3y agoHumans learn from the structure of the world -- not the structure of language. LLMs cheat at generating text because they do so via a model of the statistical structure of text. We're in the world, it is us who stipulate the meaning of words and the structure of text. And we stipulate new meanings to novel parts of the world daily. What else is an 'iPhone' etc. ? There's nothing in `i P h o n e` which is at all like an iphone. We have just stipulated this connection. The machine replays these stipulations to us -- it does not make them, as we do.
- deleted 3y ago[deleted]
- somewhereoutth 3y agoExactly. A very uncomfortable truth for those heavily invested (time/money/credence) in this latest AI wave.
- refulgentis 3y agoIt’s odd to see people doomwaving two general reasoning engines. It’s especially hard to parse a dark sweeping condemnation based on…people are investing in it? It doesn’t have the right to assign names to things? Idk what the argument is. My most charitable interpretation is “it cant reason abour anything unless we already said it” which is obviously false.
- root_axis 3y ago> one of which is an average 14 year old, the other an honors student college freshman The point is that they're not those things. Yes, language models can produce solutions to language tests that a 14 year old could also produce solutions for, but a calculator can do the same thing in the dimension of math - that doesn't make a calculator a 14 year old.
- refulgentis 3y agoYes, the AI isn’t literally a 14 year old, and we should do an anthromorphization acknowledgement. Thank you for pointing it out, it can waste a lot of time when you get sloppy with language in AI discussions. I removed the reference, in retrospect, it’s unnecessary. No need to indicate the strong performance, we’re all aware.
- chubot 3y agoChildren raised in isolation will spontaneously develop language I don’t have a reference handy now (someone can probably do better) but I believe one way to see this is via the hearing impaired or hearing and sight impaired
- justrealist 3y agoThere's really no good data to support this claim.
- romwell 3y ago>There's really no good data to support this claim. Fine. We know that languages did not exist at some point. We made them exist.
- justrealist 3y agoYes, I acknowledge that we have evidence that groups of tribal humans will evolve language constructs over tens of thousands of years. Whether that happens in 1 generation or 10,000 generations is completely unknown.
- sudosysgen 3y agoAs others have mentioned in this thread, the Nicaraguan Sign Language shows it can happen in years, not even generations.
- dr-detroit 3y ago[dead]
- akprasad 3y agoThe best example I'm aware of is Nicaraguan Sign Language [1]. > Steven Pinker, author of The Language Instinct, claims that "The Nicaraguan case is absolutely unique in history ... We've been able to see how it is that children—not adults—generate language, and we have been able to record it happening in great scientific detail. And it's the only time that we've actually seen a language being created out of thin air." [1] https://en.wikipedia.org/wiki/Nicaraguan_Sign_Language https://en.wikipedia.org/wiki/Nicaraguan_Sign_Language
- CydeWeys 3y agoHumans invented English, and every other human language. Not one single human, and not in a single lifetime, but yes, we did it. LLMs are not doing this.
- throwawaymaths 3y agoI mean have you seen the whole "encode a poem in made up emoji" followed by "decode the poem from emoji" stuff? I think it's not unreasonable to think with the right prompts LLMs could do this.
- CydeWeys 3y agoThe LLMs that are doing this are trained on trillions of examples of human language. This is not remotely a counterexample. Now if an LLM can invent a new full language from scratch, without any training data of existing languages (like how AlphaZero learned to play Go), then that will be impressive, and a difference in kind.
- tialaramex 3y agoUm but you have the example of English. Modern English was based on Middle English, which in turn is based on Old English, but greatly influenced by Norman on account of the invasion, as well as by Norse
- CydeWeys 3y agoKeep playing it back through history and you'll find the first language invented by people. There is no equivalent accomplishment for AI.
- throwawaymaths 3y agohttps://bair.berkeley.edu/blog/2019/09/19/bit-swap/ https://bair.berkeley.edu/blog/2019/09/19/bit-swap/
- 3y ago
- QuadmasterXLII 3y agoIndividual humans aren’t, but we’re talking about the emergent properties of a swarm of humans. 6 gigabytes of dna describes an entity that, if copied 60 times and dropped on an island, will produce a viable language in inly a few decades. We haven’t found a NN architecture with this property for language, but we have for , eg, chess, starcraft, and go
- datameta 3y agoThis might be too overarching of a statement but "kind" learning environments like games that have set rules and win conditions are very far from the turing completeness of human language.
- deleted 3y ago[deleted]
- neosat 3y agointeresting point!
- spullara 3y agoEvery human alive is cheating, they learned from us!
- CydeWeys 3y agoHumanity invented language though. LLMs did not; they're merely parroting our language back to us.
- jackmott42 3y agoMan I remember when people downplayed AlphaGo because it didn't teach itself unsupervised. "Nothing to see here". Only took them a few months to do AlphaZero.
- CydeWeys 3y agoIt's entirely possible that making AlphaGo teach itself with no training examples is much, much easier than doing so for an LLM. Not all problems in AI have the same hardness!
- nyrikki 3y agoAlphaZero works on chess, shogi and go and other perfect information games with discreet moves and board s. LLMs need pairwise linear input that is composed of independent and identically distributed data. Feed forward neural networks are effectively DAGs thus semi-decidable. LLM require a corpus, that data is generated by humans and isn't a perfect information game. If you dig into how many feedforward neural network can be written as a single pairwise linear function in lower dimensions, you can help build an intuition on how they work in higher dimensions that are beyond our ability to visualize. AlphaZero being able to build a model without access to opening books or endgame tables in perfect information games was an achievement in implementation, it was not a move past existential quantifiers to a universal quantification. LLMs still need human produced corpus because the search space is much larger than a simple perfect information game. The game board rules were the source of compression for AlphaZero, while human produced text is the source for LLMs. Neither have a 'common sense' understanding of the underlying data, their results simply fit a finite subset of the data in the same way that parametric regression does. As there are no accepted definitions for intelligence, mathematics is the only way to understand this. VC dimensionally and set shattering is probably the most accessible to programming backgrounds if you are interested.
- deleted 3y ago[deleted]
- raverbashing 3y ago> Also, the LLMs are cheating! They learned from us. Ding ding ding, right answer! Now I leave you with a thought: given that the AI is learning from us, is it possible to have an AI that's much more intelligent than their "source of truth"?
- pepa65 3y agoWell, that is answered by AlphaZero (but not for LLM machines).
- Joeri 3y agoI just asked an LLM to create a language and provide a demonstration and this is what it said. Call it a stochastic parrot if you want, but I’m pretty sure a linguist can prompt it to properly invent a language. Sure, I can invent a new language for you! Let's call it "Vorin" for the purposes of this demonstration. Vorin is a tonal language with a complex system of noun classes and a relatively simple verb conjugation system. It is spoken by the Vorin people, who live in a mountainous region of an imaginary world. Here is a sample conversation in Vorin: Person 1: Ní lé màrì? Person 2: Lé vàlà, nì síkòní. Person 1: Vàlà síkòní? Person 2: Àmà, síkòní là nì tékàlá. Translation: Person 1: How are you? Person 2: I'm fine, thank you. Person 1: Are you working? Person 2: Yes, I'm working right now. In Vorin, the tone of each word is very important, and can change the meaning of the word entirely. For example, "lé" with a high tone means "you", while "lé" with a low tone means "fine". In addition to tone, Vorin has a system of noun classes, which are indicated by prefixes on the nouns themselves. For example, "màrì" means "you" if it is in the second person singular class, but it can also mean "house" if it is in the third person singular class. Vorin's verb conjugation system is relatively simple, with only a few tenses and moods. Verbs are also marked for subject agreement, which means that the verb ending changes depending on the subject of the sentence. For example, "nì síkòní" means "I'm fine", while "là síkòní" means "he/she/it is fine". Overall, Vorin is a complex and interesting language with a rich grammatical structure and unique tonal system.
- CydeWeys 3y agoYou're missing the point though, which is that that LLM was already trained on trillions of examples of human languages. Once it already knows many languages, inventing one more isn't hard. (Though I don't think it's actually "invented" this language to any great depth.) Let's see it invent language from scratch without being presented any examples of languages to use as training data. That's what humanity did. Can LLMs do it? I doubt it, not yet.
- norgie 3y agoI don't see how this proves anything. This isn't how human languages came about, there's a lot of conlang content online, and this doesn't describe a complete language anyway.
- dllthomas 3y agoIt's been a while since I've engaged with the ideas, but it's my understanding that Chomsky was discussing the ability for children to learn the language of the society they're raised in. LLMs are not cheating at that task in the manner you describe. They do seem to need a significantly larger corpus, though, so it's not clear that it actually refutes Chomsky.
- EGreg 3y agoAnd let’s not forget that they are trained on a giga cluster of machines! I am not sure how brute forcing a chess using Monte Carlo Tree Search, or solving Checkers via exhaustive search, would refute a theory about how people with efficient, low-power-consumption brains that grow organically, are able to master Chess.
- dllthomas 3y agoEh, it's certainly true that we're throwing tremendously more hardware and power at the problem with an LLM than with a toddler; that's only relevant to whether LLMs refute Chomsky to whatever degree his argument relied on hardware or power consumption (explicitly or implicitly) and my impression is that it didn't.
- EGreg 3y agoWait so then what is his argument? Because you can always postulate that a large enough computer can simulate every human and therefore can learn stuff too — thus you don’t need a human to learn language, nyeh! Obviously, all that stuff ChatGPT says about feelings and emotions came from humans writing it!
- dllthomas 3y agoAs I understand it, the question was whether humans learn language starting from a "blank slate" or whether there's some meaningful structure built in (that's therefore common across all human languages). Chomsky's argument was that children are not exposed to enough example sentences to learn all the rules they learn. It's an argument from the information content of the corpus made available to the language learner, irrespective of the capabilities of the learner. Therefore, if we're able to do the same thing by simply applying more resources, that would undermine his argument in a way that doing the same thing with a vastly larger corpus (whatever the resources we throw at it) doesn't. I should note that this is based on recollections from 20+ years ago and no serious engagement with the article at hand, so, uh, appropriate salt.
- version_five 3y agoA kind of corollary that I'm sure others have thought of: if llms are so smart and human thought is nothing more than a big language model, why can't they (llms) make up their own training data. Any discussion about how they are "thinking" the way we do is BS, I don't know how so many people who know better have been conned.
- toyg 3y ago> I don't know how so many people who know better have been conned. The simple reason is: because they don't actually "know better". Maybe they are knowledgeable and skilled in some area, but that doesn't mean they are knowledgeable and skilled in everything.
- famouswaffles 3y agoOr...you know he's just wrong. No idea why he thinks making training data is this unsurmountable task. https://arxiv.org/abs/2305.07759 https://arxiv.org/abs/2305.07759
- famouswaffles 3y agoHaha what ? They can make training data just fine. https://arxiv.org/abs/2305.07759 https://arxiv.org/abs/2305.07759
- pepa65 3y agoOnly after they have been fed human language, which was the point.
- famouswaffles 3y agoThat wasn't the point lol. Read his comment. It wouldn't even make any sense. What do you think you're fed ? alien data ?
- MrBuddyCasino 3y agoWordcels think LLMs imitate the human brain, when a shape rotator knows they really just imitate human language.
- steveBK123 3y agodoesn't this make LLM a dead end towards AGI and mostly just a neat specific trick?
- travisgriggs 3y agoA better and better parrot is still a parrot then? (I’m agreeing with you basically)
- adastra22 3y agoWhy do you think you are anything more?
- littlestymaar 3y agoWhy do you think you're anything more than a pocket calculator?
- adastra22 3y agoI don’t.
- AbrahamParangi 3y agoIn order to believe this, you'd need to be able to imagine a specific test of something that an LLM could not do under any circumstances. Previously, that test could have been something like "compose a novel sonnet on a topic". Today, it is much less clear that such a test (that won't be rapidly beaten) even exists.
- mLuby 3y ago
- shaunxcode 3y agoThank you! It is like arguing that a human engaging in the creation of a landscape portrait using the traditional method of oil painting has been "refuted" by a computer generating vector graphics from statistical descriptions of the same scene. Both yield art but they are clearly different in interesting ways. Neither refutes or outmodes the other. Or maybe I'm wrong and actually trees have refuted mushrooms!
- janalsncm 3y agoSince large fungi came first, maybe trees have refuted the mushrooms? https://en.m.wikipedia.org/wiki/Prototaxites https://en.m.wikipedia.org/wiki/Prototaxites
- shaunxcode 3y agoThat is my point though: the notion of one plant refuting another is absurd if they both still thrive. Likewise the underpinnings of how LLMs work does not refute the conceptual framework of universal grammar. Especially as refutation means to disprove (not improve, increment, evolve or augment). One more analogy: jiu jitsu does not refute aikido even if it is better in an MMA context. When reaching for refutation prefer synthesis.
- adastra22 3y agoIt is far, far more likely that the way humans learn language resembles LLMs than it does Chomsky’s model, however. Biology is intrinsically local. For Chomsky’s model of language instinct to work, it would have to reduce down to some sort of embryonic developmental process consisting of entirely of local gene-activated steps over the years it takes for a human child to begin speaking grammatical sentences. This is in direct contrast to most examples of human instinct, which disappear very quickly as the brain develops. Really the main advantage that Chomsky’s ideas had is that no one could imagine how something simpler could possibly result in linguistic understanding. But large language models demonstrate that no, actually one simple learning algorithm is perfectly sufficient. So why evoke something more complex?
- taeric 3y agoI wouldn't be shocked to find that humans don't learn from syntax and semantics, all told. We certainly aren't doing that with our kids, as they learn. And when they start picking up language, it is rapid and impressive. Note that it comes before they can speak, too. Seeing kids ability to understand some complicated directions when they can only do rudimentary sign language is eye opening.
- asdff 3y agoImagine being told all you need to do to learn Spanish, is to read a 300,000 word Spanish dictionary end to end so that you can probalistically come up with 1000 conversational phrases. Anyone who has learned a language can tell you it just doesn't work like that. You don't work by accumulating a massive dataset and training on it. No one can hold such a massive dataset of anything in their head at once.
- kristopolous 3y agoGoing from zero to one is different than one to two ("second language acquisition") Zero to one is closer to mimicry and immersion. There's a long Wikipedia article on the field of study https://en.m.wikipedia.org/wiki/Language_acquisition https://en.m.wikipedia.org/wiki/Language_acquisition Furthermore, humans probably aren't static learners and likely have more beneficial times of certain study than others. There's a theory in that too https://en.m.wikipedia.org/wiki/Critical_period_hypothesis https://en.m.wikipedia.org/wiki/Critical_period_hypothesis Saying there's a "digital brain" is more of a framework since the term "brain" looks like it's a moving target In another comment I referred to these systems as like comparing hydraulic pumps to human biceps, cars to horses, etc. We can use the same units of measure, give them the same tasks, but saying they're the same thing only works in the world of poetry
- jackmott42 3y agoThe LLM doesn't hold the whole dataset in its head either.
- aezart 3y agoNot for a lack of trying. If you give it a small enough training set or a big enough neural network, it will directly memorize the whole thing. You have to intentionally make its brain too small to do that in order to force it to find patterns in the data instead.
- kristopolous 3y agoIt's kinda of like calling a hydraulic pump "mechanical muscle". These types of "mistakes" are more about the authors letting their intentions and hopes known on how they wish the thing to be used.
- guerrilla 3y ago> I also respond to several critiques of large language models, including [...] skepticism that they are informative about real life acquisition Yeah the whole thing hinges on this... and uh yeah good luck with that one...
- williamcotton 3y agoWhat about the fact that trying to use Chomsky's approach to universal grammar does not result in working language models yet a statistical approach does? The Norvig-Chomsky debate is kind of old at this point: https://www.tor.com/2011/06/21/norvig-vs-chomsky-and-the-fight-for-the-future-of-ai/ https://www.tor.com/2011/06/21/norvig-vs-chomsky-and-the-fig...
- mempko 3y agoBecause Chomsky is trying to build a bird, and Norvig is trying to build an airplane. It's much easier to build an airplane to fly than a bird. Chomsky is trying to explain how humans create language. LLM are creating language, but not the way humans do. Nothing about this paper refutes Chomsky's claims.
- williamcotton 3y agoChomsky has been adding parameters to his theory to handle exceptions in a way that mimics the endless series of conditional statements appended to knowledge systems of yore. In neuroscience, predictive processing has gained immense favor and can explain language in ways that have nothing to do with innate grammar. https://en.wikipedia.org/wiki/Predictive_coding https://en.wikipedia.org/wiki/Predictive_coding Exactly how well did "building a bird" work for building flying machines? Birds use the same principle as a fixed wing when it comes to soaring flight. "Building a bird" without the principles of an airfoil and just mimicking the flapping wings does not result in flight.
- bbor 3y ago…he has? Isn’t his modern term “minimalism”, where he tries to simplify things as much as possible? Regardless, continuing to study the field in no way implies that he’s backed down or meaningfully evolved his basic theories of Universal Grammars. He’s very much still confident in them. Re: predictive processing, in what way does that relate to language…? Even if you apply it to language in a way not mentioned in the linked article at all, I don’t see even the rough shape of how it would refute (/be mutually exclusive with) generative grammars. Maybe I’m just missing something because I don’t know much neuro? Re: building a bird… yeah that’s their point, you don't try to build a bird, you try to study birds. Chomsky cares about what we are, not building machines to do our drudgery. I don’t think I agree entirely with that singular focus, but you see the appeal, no?
- lsy 3y agoFor people who don't understand this, the reason humans refer to "Alex" much later in a story is not because they are statistically recalling that they said "Alex" dozens or hundreds of words earlier (as the LLM is described doing in the paper), but because they have a world-model they are actively describing, where "Alex" refers to an entity in that world-model. We know that the LLM is only saying "Alex" because it appeared earlier, but we also know humans don't work like that, so how can the LLM's generation of language say anything about how humans acquire and use it?
- FabHK 3y agoChomsky: Birds fly by flapping their wings in a specific way while changing the angle in order to create lift and propulsion. This paper: Planes fly, but don’t flap their wings, ergo Chomsky is wrong.
- pfdietz 3y agoChomsky was saying specific things had to be in the brain because it was impossible to do things otherwise. LLMs shoot this argument down even if they aren't how the brain does it.
- riku_iki 3y ago> The fact that you can replicate coherent text from probabilistic analysis and modeling of a very large corpus does not mean that humans acquire and generate language the same way. we actually don't know what is inside LM too, so it is possible LM statistically learns syntax and semantics, and it is major part of output quality.
- GuB-42 3y agoWe could use programming languages as a counterpoint. LLMs can code in the same way they can use natural languages. But we know that programming languages have structure, we made them that way, from scratch, using Chomsky's theory no less. Saying that because LLMs can learn programming languages using a different approach and therefore disprove the very theory they are built on is absurd. Anyways, the paper is long and full of references, I didn't analyse it, does it include looks inside the model? For example, for LLMs to write code correctly, the structure of programming languages must be encoded somewhere in the weights of the model. A way to more convincingly disprove Chomsky's ideas would be to find which part of the network encodes structure in programming languages, and show that there is nothing similar for natural languages.
- spookie 3y ago> But we know that programming languages have structure, we made them that way, from scratch, using Chomsky's theory no less. Very much so, it's astounding really. I still remember deriving "words" and using Chomsky's Normal Form when making the CFG to build a compiler.