> Chomsky has focused on the generative side of language
The answers to "why" that Chomsky pushes so hard for are very valuable to adult language learners. There are basic syntactic rules to generating broadly correct language. Having these rules discovered and explained in the simplest possible form is irreplaceable by statistical models. Neural networks, much like native speakers can say "well this just sounds right," but adult learners need a mathematical theory of how and why they can generate sentences. Yes, this changes with time and circumstances, but the simple rules and theories are there if we put the effort in to look for them.
There are many languages with a very small corpus of training data. The LLMs fail miserably at communicating with them or explaining things about their grammar, but if we look hard for the underlying theories Chomsky was looking for, we can make huge leaps and bounds in understanding how to use them.
This essay is missing the words “cause” and “causal”. There is a difference between discovering causes and fitting curves. The search for causes guides the design of experiments, and with luck, the derivation of formulae that describe the causes.
Norvig seems to be confusing the map (data, models) for the territory (causal reality).
We note that the practice in
applied research of concluding that a model with a
higher predictive validity is “truer,” is not a valid inference. This paper shows that a parsimonious but less
true model can have a higher predictive validity than a
truer but less parsimonious model.
This essay frequently uses the word "insight", and its primary topic is whether an empirically fitted statistical model can provide that (with Norvig arguing for yes, in my opinion convincingly). How does that differ from your concept of a "cause"?
> I agree that it can be difficult to make sense of a model containing billions of parameters. Certainly a human can't understand such a model by inspecting the values of each parameter individually. But one can gain insight by examing (sic) the properties of the model—where it succeeds and fails, how well it learns as a function of data, etc.
Unfortunately, studying the behavior of a system doesn't necessarily provide insight into why it behaves that way; it may not even provide a good predictive model.
Norvig's textbook surely appears on the bookshelf of researchers including those building current top LLMs. So it's odd to say that such an approach "may not even provide a good predictive model". As of today, it is unquestionably the best known predictive model for natural language, by huge margin. I don't think that's for lack of trying, with billions of dollars or more at stake.
Whether that model provides "insight" (or a "cause"; I still don't know if that's supposed to mean something different) is a deeper question, and e.g. the topic of countless papers trying to make sense of LLM activations. I don't think the answer is obvious, but I found Norvig's discussion to be thoughtful. I'm surprised to see it viewed so negatively here, dismissed with no engagement with his specific arguments and examples.
In his view - most ML algos are at level 1 - they look at data and draw associations, and "agents" have started some steps in level 2 - doing.
The smartest of humans operate mostly in level (3) of abstractions - where they see things, gain experience, and later build up a "strong causal model" of the world and become capable of answering "what if" questions.
Thanks for the response, but (per the omitted portion of my sentence before the semicolon) I was not talking about the M in LLM. I was talking about a conceptual or analytic model that a human might develop to try to predict the behavior of an LLM, per Norvig's claim of insight derived from behavioral observation.
But now that I think a bit about it, the observation that an LLM seems to frequently produce obviously and/or subtly incorrect output, is not robust to prompt rewording, etc. is perhaps a useful Norvig-style insight.
Chomsky's talking about predictive models in the context of cognitive science. LLMs aren't really a predictive model of any aspect of human cognitive function.
The generation of natural language is an aspect of human cognition, and I'm not aware of any better model for that than current statistical LLMs. The papers mapping between EEG/fMRI/etc. and LLM activations have been generally oversold so far, but it's active area of research for good reason.
I'm not saying LLMs are a particularly good model, just that everything else is currently worse. This includes Chomsky's formal grammars, which fail to capture the ways humans actually use language per Norvig's many examples. Do you disagree? If so, what model is better and why?
> I'm surprised to see it viewed so negatively here, dismissed with no engagement with his specific arguments and examples.
I struggle to motivate engaging with it because it is unfortunately quite out of touch with (or just ignores) some core issues and the major advances in causal modeling and causal modeling theory, i.e. Judea Pearl and do-calculus, structural equation modeling, counterfactuals, etc [1].
It also, IMO, makes a (highly idiosyncratic) distinction between "statistical" (meaning, trained / fitted to data) and "probabilistic" models, that doesn't really hold up too well.
I.e. probabilistic models in quantum physics are "fit" too, in that the values of fundamental constants are determined by experimental data, but these "statistical" models are clearly causal models regardless. Even most quantum physical models can be argued to be causal, just the causality is probabilistic rather than absolute (i.e. A ==> B is fuzzy implication rather than absolute implication). It's only if you ask deliberately broad ontological questions (e.g. "Does the wave function cause X") that you actually run into the problem of quantum models being causal or not, but for most quantum physical experiments and phenomena generally, the models are still definitely causal at the level of the particles / waves / fields involved.
IMO I don't want to engage much with the arguments because it starts on the wrong foot and begins by making, in my opinion, an incoherent / unsound distinction, while also ignoring or just being out of date with the actual scientific and philosophical progress and issues already made here.
I would also say there is a whole literature on tradeoffs between explanation (descriptive models in the worst case, causal models in the best case) and prediction (models that accurately reproduce some phenomenon, regardless of if they are based on and true description or causal model). There are also loads of examples of things that are perfectly deterministic and modeled by perfect "causal" models but which are of course still defy human comprehension / intuition, in that the equations need to be run on computers for us to make sense of them (differential equation models, chaotic systems, etc). Or just more practically, we can learn to do all sorts of physical and mental skills, but of course we understand barely anything about the brain and how it works and co-ordinates with the body. But obviously such an understanding is mostly irrelevant for learning how to operate effectively in the world.
I.e. in practice, if the phenomenon is sufficiently complex, an accurate causal model that also accurately models the system is likely to be too complex for us to "understand" anyway (or you just have identifiability issues so you can't decide between multiple different models; or you don't have the time / resources / measurement capacity to do all the experiments needed to solve the identifiability problem anyway), so there is almost always a tradeoff between accuracy/understanding. Understanding is a nice luxury, but in many cases not important, and in complex cases, probably not achievable at all. If you are coming from this perspective, the whole "quandary" of the essay seems just odd.
Unless and until neurologists find evidence of a universal grammar unit (or a biological Transformer, or whatever else) in the human connectome, I don't see how any of these models can be argued to be "causal" in the sense that they map closely to what's physically happening in the brain. That question seems so far beyond current human knowledge that any attempt at it now has about as much value as the ancient Greek philosophers' ideas on the subatomic structure of matter.
So in the meantime, Norvig et al. have built statistical models that can do stuff like predicting whether a given sequence of words is a valid English sentence. I can invent hundreds of novel sentences and run their model, checking each time whether their prediction agrees with my human judgement. If it doesn't, then their prediction has been falsified; but these models turned out to be quite accurate. That seems to me like clear evidence of some kind of progress.
You seem unimpressed with that work. So what do you think is better, and what falsifiable predictions has it made? If it doesn't make falsifiable predictions, then what makes you think it has value?
I feel like there's a significant contingent of quasi-scientists that have somehow managed to excuse their work from any objective metric by which to evaluate it. I believe that both Chomsky and Judea Pearl are among them. I don't think every human endeavor needs to make falsifiable predictions; but without that feedback, it's much easier to become untethered from any useful concept of reality.
I had this exact reaction, no discussion of "causal modeling" makes the whole thing seem horribly out of touch with the real issues here. You can have explanatory and predictive models that are causal models, or explanatory and predictive models that are non-causal, and that this the actual issue, not "explanation" vs. "prediction", which is not a tight enough distinction.
> derided researchers in machine learning who use purely statistical methods to produce behavior that mimics something in the world, but who don't try to understand the meaning of that behavior.
It's crazy how wrong Chomsky was about machine learning. Maybe the real truth is that humans are stochastic parrots who have an underlying probability distribution - and because gradient descent is so good at reproducing probability distributions - LLMs are incredibly good at reproducing language.
In more detail: Chomsky is/was not concerned with the models themselves, but rather with the distinction between statistical modelling in general, and "clean slate" models in particular on the one hand, and structural models discovered through human insight on the other.
With "clean slate" I mean models that start with as little linguistically informed structure as possible. E.g., Norvig mentions hybrid models: these can start out as classical rule based models, whose probabilities are then learnt. A random neural network would be as clean as possible.
No it is from 2011. The text mentions an event in 2011, so it couldn't have been written earlier, and the first HN submission [1] was in 2011, so it also wasn't written later.
The title should say (2011), otherwise the whole piece is confusing.
I have many books from Chomsky, and I want to throw them away because it disgusts me to have them. Then I think, why should I throw away things I spent so much on? It makes me more angry. So I have pilled them up somewhere to figure out what ti do with them and each time I walk past it I feel sad to ever passed by his work.
There's an interview with Dan schmachtenberger where he talks about the worst book ever written (his opinion is that it's 'the 48 laws of power'). He made the point that being consistently wrong is actually pretty impressive, and there are worthwhile lessons from watching someone getting taken seriously despite being wrong. Maybe you could revisit them with that approach.
Make sure to vet your entire circle - friends, relatives, books, movies, everything... it's going to take a while. In the meantime you'll stop learning/growing too.
Mine is as ludicrous a suggestion as it is to damn by association.
I assume this comes from his views in politics and/or association with things like Epstein. I would say, independent of that, some works of him can be very valuable. Private life of persons and their work, are better put in totally different context, and not mixed.
The thing is, nothing that usually changes things applies to Chomsky. What he did was most certainly not a normal thing to do in his time. Like one might say about George Washington or even further back, like Clovis. By today's standards they were morally wrong, but not by the standards of their time and they advanced morals. They made things better.
Chomsky is wrong by the standards of his time and is making things worse rather than better.
It was very much the opposite of Chomsky's ideology as well. So it additionally means he's fake. BOTH on his morals and politics/activism, from both sides (ie. both helping a paedophile, and helping/entertaining a billionnaire).
So it's (yet another) case of an important figure that supposedly stands for something, not just demonstrating he stands for nothing at all, but being a disgusting human being as well.
> It was very much the opposite of Chomsky's ideology as well.
On the contrary. Chomsky was open about his civil-libertarian principles: If you are convicted, and you complete your court-ordered obligations, you have a clean slate.
Tell me, did that attitude extend to helping billionnaires who are having sex with minors? Because that's what he did. Is that what this ideology stands for?
Read the article above. There is a link at the top of this submission to an essay by Peter Norvig, arguing (correctly, in retrospect) that Chomsky's approach to language modelling is mistaken.
Obviously I did read the article. And I know how the hn site works.
I have a passing familiarity with the debate over Chomsky's theories of universal grammar etc. I didn't notice anything in the article that would cause disgust, and so I wondered what I was failing to understand.
If you have read many books by Chomsky, it might make you angry that you have wasted so much time on what turned out to be a fundamentally mistaken theory.
His russian imperialism support and his broad rejection of the eastern european civilian uprising against the communist project. Like many idealists he took a utopian, idealizing view and ran with it reality and real suffering caused be damned. Like many idealists he offered basically a API for sociopaths to be hijacked and used as a useful idiot against humanity. This way predictable leads to ruin and ashes as legacy and it did so for him. The epstein connection is just the cherry on top.
Sounds like bit of an over-reaction if I am being honest.
Some of his books are deeply insightful even if you decide to draw the opposite conclusion. I wouldn’t say anything would create disgust unless you had a conclusion you wanted supported before reading the book.
Regarding the Epstein thing, bizarre to bring that up when discussing his works, seems like you hate him on a personal level.
Pretty massive stretch making that inference based on the data don’t you think? Or is this an underhand way to get back at someone you disagree with politically?
Dude would talk about manufacturing consent, elitist circles, and what Israel is doing with poor Palestinians and then go aboard Israeli-spy, super elitist, consent manufacturing, sex trafficker, rapist, Epstein's private jet. What a total insult to everyone who ever read his things
Chomsky had a stroke a couple of years ago and isn't capable of speaking; the family is trying to maintain their privacy and so there isn't much public information about it but it came out that he can raise his arm when he sees something he dislikes and it doesn't look like much beyond that.
He already said he had nomoral objections to deal with Epstein knowing about his first conviction for sex trafficking, because in Chomsky's view the man served his time and justice had been served. Yes, to Chomsky Epstein was an innocent man after serving a few months for sex trafficking and having sex with a dozen of minors. The socialist anarchist Chomsky had no ethical objections when he asked a convicted billionaire sex trafficker how to invest a few millions.
But there is no indication or even accusation that he was involved in any sexual activity, let alone anything inappropriate.
It's innuendo and guilt by association, mainly by his political opponents, both on the left and right, that are taking advantage of his inability to defend himself due to his stroke. I think many people are being _justly maligned_ by their association with Epstein, but in a way that distracts from the wider issue of what exactly does it mean when so many powerful and prominent people are found in compromising or potentially compromising situations and to what ends it served. It's US kompromat and the discussion is largely restricted to maligning people without discussing the significance of it.
In terms of Chomsky himself, given his career spanned both linguistics and politics, an honest critique would either deal with their disagreements with Chomsky like how Norvig did in this essay, or how Hitchens did over the Afghan and Iraq wars rather than saying "he had dinner with Epstein" or "he had dinner with Bannon".
In terms of the Epstein issue, the best criticism I can see is that his association with Epstein, Bannon etc. makes him a hypocrite although I don't find this personally convincing. Part of the problem for me here is that his present infirmities make it difficult for him to defend or explain himself and I find it poor form to kick the man when he's down, mainly by people who just didn't like that Chomsky didn't agree with them personally. Especially when he largely made a contribution to the debates even if one doesn't agree with him.
I won't try to defend Chomsky. (Not really a big fan even before this.) But if the mere mention of him is sus to you then I advise you to not study either linguistics or computer science because it's Chomsky normal forms and Chomsky hierarchies all the way down. There's even still people clinging to some iteration of the universal grammar despite the beating it has taken lately.
He's also one of the most prominent political thinkers on the American hard left for the last half century.
There's a joke going around for a while now that you either know Chomsky for his politics, or for his work in linguistics and discrete mathematics, and you are shocked to discover his other work. I guess we can extend that to a third category of fame, or infamy.
The merge operation in the later Chomsky modern linguistics program is similar in a lot of ways to transformer's softmax merging of representations to the next layer.
There's also still a lot to his arguments that we are much more sample efficient. And it isn't like monkies only learn language at a gpt-2 level, bigger brains take us to gpt-8 or whatever. There's a step change where they don't really pick things up linguistically at all and we do. But with a lot more data than we ever get, LLMs seem to distill some of the broad mechanisms what may be our innate ability, though still seems to have a large learned component in us.
A lot of Chomsky’s appeal I believe is due to his politics as his universal grammar theories turned out to be an academic dead end.
But his politics centers around the moral failings of the West so I think yes, if he was involved in the sexual exploitation of trafficked children, then this would devalue his criticism of the morality of the Western political system.
> But his politics centers around the moral failings of the West so I think yes, if he was involved in the sexual exploitation of trafficked children, then this would devalue his criticism of the morality of the Western political system.
Why would it devalue his criticism assuming he was right?
Moral arguments for me don’t stand alone like a mathematical proof or scientific findings which can be examined as some sort of platonic form.
Morality arguments are social and contextual. That 2+2 is 4 won’t change and captures some sort of eternal truth while what is deemed moral is constantly changing over time and differs across different societies and social groupings.
So morality arguments require and appeal to a particular shared sense of right and wrong. If Chomsky was guilty of sexually abusing children, then I do not share his moral foundation and so his appeals to morality arguments do not convince me.
His criticism of the Western political system was always way too simplicist and why it has immense appeal to college students.
Essentially it can be summed as any Western action must be rationalized as evil, and any anti-west action is therefore good. This is also in line with Christian dualism so the cultural building blocks are already in place.
Then you get Khmer Rouge, Putin, Hezbollah, Iran apologetism or downright support
I doubt you can find any essay or such where he said anti-Western action was good on the sole grounds that it was anti-Western.
It's difficult to summarise so many years of writing in a few sentences but from my own reading, he pointed out
a) many things done by the US lead to death or destruction
b) many of these things are justified in the name of good that doesn't stand up to scrutiny
c) the US government is often hypocritical
d) US citizens are heavily propagandized both for foreign policy and domestic policy
e) as a US citizen, it his duty to try and oppose these actions and since he's not a citizen of Iran, he isn't in a position to do anything about Iran
f) a) through d) explain why he is often seen as an apologist, to use your word, for Iran; he tries to explain, from his point of view, why Iran etc. do the things they do
g) a strong support of freedom of speech and opposition to censorship, including what he regards as private censorship as opposed to merely government censorship.
That doesn't explain why he visited Hezbollah and showed overwhelming support, probably aware of the organization roots and past actions such as kidnapping journalists or killing politicians or its self professed goal of creating a theocracy in Lebanon.
He of course has very complex rationalizing but essentially he assumes the opposite of mainstream western opinion and then tries to build ideological structures upon that.
That creates a very simplified version of reality wrapped in a nice intellectual wrapping
I am not a fan of Chomsky - the opposite in fact. I was deliberately avoiding judging his actual arguments - to make the point that his own morality undermines his lecturing others on their moral failings.
> But it must be recognized that the notion of "probability of a sentence" is an entirely useless one, under any known interpretation of this term.
He was impressively early to the concept, but I think even those skeptical of the ultimate value of LLMs must agree that his position has aged terribly. That seems to have been a fundamental theoretical failing rather than the computational limits of the time, if he couldn't imagine any framework in which a novel sentence had probability other than zero.
I guess that position hasn't aged worse than his judgment of the Khmer Rouge (or Hugo Chavez, or Epstein, or ...) though. There's a cult of personality around Chomsky that's in no way justified by any scientific, political, or other achievements that I can see.
If Chomsky were known only as a mathematician and computer scientist, then my view of him would be favorable for the reasons you note. His formal grammars are good models for languages that machines can easily use, and that many humans can use with modest effort (i.e., computer programming languages).
The problem is that they're weak models for the languages that humans prefer to use with each other (i.e., natural languages). He seems to have convinced enough academic linguists otherwise to doom most of that field to uselessness for his entire working life, while the useful approach moved to the CS department as NLP.
As to politics, I don't think it's hard to find critics of the West's atrocities with less history of denying or excusing the West's enemies' atrocities. He's certainly not always wrong, but he's a net unfortunate choice of figurehead.
I have the feeling we're focusing on different time periods.
Chomsky already was very active and well-known by 1960.
He pioneered areas in Computer Science, before Computer Science was a formal field, that we still use today.
His political views haven't changed much, but they were beneficial back when America was more naive. They are harmful now only because we suffer from an absurd excess of cynicism.*
How would you feel about Chomsky and his influence if we ignored everything past 1990 (two years after Manufacturing Consent)?
---
* Just imagine if Nixon had been president in today's environment... the public would say "the tapes are a forgery!" or "why would I believe establishment shills like Woodward and Bernstein?" Too much skepticism is as bad as too little.
I wrote "when America was more naive" but that isn't entirely correct. Americans are more naive today in certain areas. If my comment weren't locked, I would change that sentence to something like "when Americans believed most of what they read in the newspaper"
I agree that his contributions to proto-computer-science were real and significant, though I think they're also overstated. Note the link to the Wikipedia page for BNF elsewhere in these comments. There's no evidence that Backus or Naur were aware of Chomsky's ideas vs. simply reinventing them, and Knuth argues that an ancient Indian Sanskrit grammarian deserves priority anyways.
I think Chomsky's political views were pretty terrible, especially before 1990. He spoke favorably of the Khmer Rouge. He dismissed "Murder of a Gentle Land", one of the first Western reports of their mass killing, as a "third rate propaganda tract". As the killing became impossible to completely deny, he downplayed its scale. Concern for human rights in distant lands tends to be a left-leaning concept in the West, but Chomsky's influence neutralized that here. This contributed significantly to the West's indifference, and the killing continued. (The Vietnamese communists ultimately stopped it.)
Anyone who thinks Chomsky had good political ideas should read the opinions of Westerners in Cambodia during that time. I'm not saying he didn't have other good ideas; but how many good ideas does it take to offset 1.5-2M deaths?
> Just imagine if Nixon had been president in today's environment... the public would say "the tapes are a forgery!" or "why would I believe establishment shills like Woodward and Bernstein?" Too much skepticism is as bad as too little.
Today it would not matter in the least if the president were understood to have covered up a conspiracy to break into the DNC headquarters. Much worse things have been dismissed or excused. Most of his party would approve of it and the rest would support him anyway so as not to damage "their side".
I'm not sure what you mean? As the length of a sequence increases (from word to n-gram to sentence to paragraph to ...), the probability that it actually ever appeared (in any corpus, whether that's a training set on disk, or every word ever spoken by any human even if not recorded, or anything else) quickly goes to exactly zero. That makes it computationally useless.
If we define perplexity in the usual way in NLP, then that probability approaches zero as the length of the sequence increases, but it does so smoothly and never reaches exactly zero. This makes it useful for sequences of arbitrary length. This latter metric seems so obviously better that it seems ridiculous to me to reject all statistical approaches based on the former. That's with the benefit of hindsight for me; but enough of Chomsky's less famous contemporaries did judge correctly that I get that benefit, that LLMs exist, etc.
My point is, that even in the new paradigm where probabilistic sequences do offer a sensible approximation of language, would novelty become an emergent feature of said system, or would such a system remain bound to the learned joint probabilities to generate sequences that appear novel, but are in fact (complex) recombinations of existing system states?
And again the question being, whether there is a difference at all between the two? Novelty in the human sense is also often a process of chaining and combining existing tools and thought.
Shannon first proposed Markov processes to generate natural language in 1948. That's inadequate for the reasons discussed extensively in this essay, but it seems like a pretty significant hint that methods beyond simply counting n-grams in the corpus could output useful probabilities.
In any case, do you see evidence that Chomsky changed his view? The quote from 2011 ("some successes, but a lot of failures") is softer but still quite negative.
"BNF itself emerged when John Backus, a programming language designer at IBM, proposed a metalanguage of metalinguistic formulas ... Whether Backus was directly influenced by Chomsky's work is uncertain."
Oh, lots of stuff gets invented multiple times, when it's "in the air". Nothing special about Chomsky here. And I wouldn't see that distracting from this particular achievement.
I'm a big Chomsky nerd, Chomsky fan, and card-carrying ex Chomskyan linguist. I hate to break it to you, but not even Chomsky thought that the Chomsky hierarchy had any very interesting application to natural languages. Amongst linguists who (unlike Chomsky) are still interested in formal language classes, the general consensus these days is that the relevant class is one of the so-called 'mildly context sensitive' ones (see e.g. https://www.kornai.com/MatLing/mcsfin.pdf for an overview).
(I suppose I have to state for the record that Chomsky's ties to Epstein are indefensible and that I'm not a fan of his on a personal level.)
Don't you think people would have figured it out by themselves the moment programmers started writing parsers? I'm not sure his contribution was particularly needed.
Lots of things get invented / discovered multiple times when it's in the air. But just because Newton (or Leibnitz) existed, doesn't mean Leibnitz (or Newton) were any less visionary.
For your very specific question: have a look at the sorry state of what's called 'regular expressions' many programming languages and libraries to see what programmers left loose can do. (Most of these 'regular expressions' add things like back-references etc that make matching their franken-'xpressions take exponential time in the worst case; but they neglect to put in stuff like intersection or complement of expressions, which are matchable in linear time.
The answers to "why" that Chomsky pushes so hard for are very valuable to adult language learners. There are basic syntactic rules to generating broadly correct language. Having these rules discovered and explained in the simplest possible form is irreplaceable by statistical models. Neural networks, much like native speakers can say "well this just sounds right," but adult learners need a mathematical theory of how and why they can generate sentences. Yes, this changes with time and circumstances, but the simple rules and theories are there if we put the effort in to look for them.
There are many languages with a very small corpus of training data. The LLMs fail miserably at communicating with them or explaining things about their grammar, but if we look hard for the underlying theories Chomsky was looking for, we can make huge leaps and bounds in understanding how to use them.
https://www.stat.berkeley.edu/~aldous/157/Papers/shmueli.pdf
To Explain Or To Predict?
Nice quote
We note that the practice in applied research of concluding that a model with a higher predictive validity is “truer,” is not a valid inference. This paper shows that a parsimonious but less true model can have a higher predictive validity than a truer but less parsimonious model.
Hagerty+Srinivasan (1991)
*like TFA it's a sorta review of Breiman
Unfortunately, studying the behavior of a system doesn't necessarily provide insight into why it behaves that way; it may not even provide a good predictive model.
Whether that model provides "insight" (or a "cause"; I still don't know if that's supposed to mean something different) is a deeper question, and e.g. the topic of countless papers trying to make sense of LLM activations. I don't think the answer is obvious, but I found Norvig's discussion to be thoughtful. I'm surprised to see it viewed so negatively here, dismissed with no engagement with his specific arguments and examples.
Pearl defines a ladder of causation:
1. Seeing (association) 2. Doing (intervention) 3. Imagining (counterfactuals)
In his view - most ML algos are at level 1 - they look at data and draw associations, and "agents" have started some steps in level 2 - doing.
The smartest of humans operate mostly in level (3) of abstractions - where they see things, gain experience, and later build up a "strong causal model" of the world and become capable of answering "what if" questions.
But now that I think a bit about it, the observation that an LLM seems to frequently produce obviously and/or subtly incorrect output, is not robust to prompt rewording, etc. is perhaps a useful Norvig-style insight.
I'm not saying LLMs are a particularly good model, just that everything else is currently worse. This includes Chomsky's formal grammars, which fail to capture the ways humans actually use language per Norvig's many examples. Do you disagree? If so, what model is better and why?
I struggle to motivate engaging with it because it is unfortunately quite out of touch with (or just ignores) some core issues and the major advances in causal modeling and causal modeling theory, i.e. Judea Pearl and do-calculus, structural equation modeling, counterfactuals, etc [1].
It also, IMO, makes a (highly idiosyncratic) distinction between "statistical" (meaning, trained / fitted to data) and "probabilistic" models, that doesn't really hold up too well.
I.e. probabilistic models in quantum physics are "fit" too, in that the values of fundamental constants are determined by experimental data, but these "statistical" models are clearly causal models regardless. Even most quantum physical models can be argued to be causal, just the causality is probabilistic rather than absolute (i.e. A ==> B is fuzzy implication rather than absolute implication). It's only if you ask deliberately broad ontological questions (e.g. "Does the wave function cause X") that you actually run into the problem of quantum models being causal or not, but for most quantum physical experiments and phenomena generally, the models are still definitely causal at the level of the particles / waves / fields involved.
IMO I don't want to engage much with the arguments because it starts on the wrong foot and begins by making, in my opinion, an incoherent / unsound distinction, while also ignoring or just being out of date with the actual scientific and philosophical progress and issues already made here.
I would also say there is a whole literature on tradeoffs between explanation (descriptive models in the worst case, causal models in the best case) and prediction (models that accurately reproduce some phenomenon, regardless of if they are based on and true description or causal model). There are also loads of examples of things that are perfectly deterministic and modeled by perfect "causal" models but which are of course still defy human comprehension / intuition, in that the equations need to be run on computers for us to make sense of them (differential equation models, chaotic systems, etc). Or just more practically, we can learn to do all sorts of physical and mental skills, but of course we understand barely anything about the brain and how it works and co-ordinates with the body. But obviously such an understanding is mostly irrelevant for learning how to operate effectively in the world.
I.e. in practice, if the phenomenon is sufficiently complex, an accurate causal model that also accurately models the system is likely to be too complex for us to "understand" anyway (or you just have identifiability issues so you can't decide between multiple different models; or you don't have the time / resources / measurement capacity to do all the experiments needed to solve the identifiability problem anyway), so there is almost always a tradeoff between accuracy/understanding. Understanding is a nice luxury, but in many cases not important, and in complex cases, probably not achievable at all. If you are coming from this perspective, the whole "quandary" of the essay seems just odd.
[1] https://plato.stanford.edu/entries/causal-models/
So in the meantime, Norvig et al. have built statistical models that can do stuff like predicting whether a given sequence of words is a valid English sentence. I can invent hundreds of novel sentences and run their model, checking each time whether their prediction agrees with my human judgement. If it doesn't, then their prediction has been falsified; but these models turned out to be quite accurate. That seems to me like clear evidence of some kind of progress.
You seem unimpressed with that work. So what do you think is better, and what falsifiable predictions has it made? If it doesn't make falsifiable predictions, then what makes you think it has value?
I feel like there's a significant contingent of quasi-scientists that have somehow managed to excuse their work from any objective metric by which to evaluate it. I believe that both Chomsky and Judea Pearl are among them. I don't think every human endeavor needs to make falsifiable predictions; but without that feedback, it's much easier to become untethered from any useful concept of reality.
It's crazy how wrong Chomsky was about machine learning. Maybe the real truth is that humans are stochastic parrots who have an underlying probability distribution - and because gradient descent is so good at reproducing probability distributions - LLMs are incredibly good at reproducing language.
In more detail: Chomsky is/was not concerned with the models themselves, but rather with the distinction between statistical modelling in general, and "clean slate" models in particular on the one hand, and structural models discovered through human insight on the other.
With "clean slate" I mean models that start with as little linguistically informed structure as possible. E.g., Norvig mentions hybrid models: these can start out as classical rule based models, whose probabilities are then learnt. A random neural network would be as clean as possible.
https://hn.algolia.com/?query=Chomsky%20and%20the%20Two%20Cu...
The oldest submission is from 15 y.o ago - that is 2010.
I resubmitted it - thinking - with the success of LLMs - felt this was worth a revisit from "how real-world scientific progress works" point of view.
The title should say (2011), otherwise the whole piece is confusing.
1: https://news.ycombinator.com/item?id=2591154
Could it be this?
> https://www.youtube.com/watch?v=eIzRV4TxHo8
Not sure the approach holds.
Mine is as ludicrous a suggestion as it is to damn by association.
Chomsky is wrong by the standards of his time and is making things worse rather than better.
It was very much the opposite of Chomsky's ideology as well. So it additionally means he's fake. BOTH on his morals and politics/activism, from both sides (ie. both helping a paedophile, and helping/entertaining a billionnaire).
So it's (yet another) case of an important figure that supposedly stands for something, not just demonstrating he stands for nothing at all, but being a disgusting human being as well.
On the contrary. Chomsky was open about his civil-libertarian principles: If you are convicted, and you complete your court-ordered obligations, you have a clean slate.
I have a passing familiarity with the debate over Chomsky's theories of universal grammar etc. I didn't notice anything in the article that would cause disgust, and so I wondered what I was failing to understand.
Some of his books are deeply insightful even if you decide to draw the opposite conclusion. I wouldn’t say anything would create disgust unless you had a conclusion you wanted supported before reading the book.
Regarding the Epstein thing, bizarre to bring that up when discussing his works, seems like you hate him on a personal level.
It's innuendo and guilt by association, mainly by his political opponents, both on the left and right, that are taking advantage of his inability to defend himself due to his stroke. I think many people are being _justly maligned_ by their association with Epstein, but in a way that distracts from the wider issue of what exactly does it mean when so many powerful and prominent people are found in compromising or potentially compromising situations and to what ends it served. It's US kompromat and the discussion is largely restricted to maligning people without discussing the significance of it.
In terms of Chomsky himself, given his career spanned both linguistics and politics, an honest critique would either deal with their disagreements with Chomsky like how Norvig did in this essay, or how Hitchens did over the Afghan and Iraq wars rather than saying "he had dinner with Epstein" or "he had dinner with Bannon".
In terms of the Epstein issue, the best criticism I can see is that his association with Epstein, Bannon etc. makes him a hypocrite although I don't find this personally convincing. Part of the problem for me here is that his present infirmities make it difficult for him to defend or explain himself and I find it poor form to kick the man when he's down, mainly by people who just didn't like that Chomsky didn't agree with them personally. Especially when he largely made a contribution to the debates even if one doesn't agree with him.
The article by Peter Norvig is still interesting.
He's also one of the most prominent political thinkers on the American hard left for the last half century.
There's a joke going around for a while now that you either know Chomsky for his politics, or for his work in linguistics and discrete mathematics, and you are shocked to discover his other work. I guess we can extend that to a third category of fame, or infamy.
There's also still a lot to his arguments that we are much more sample efficient. And it isn't like monkies only learn language at a gpt-2 level, bigger brains take us to gpt-8 or whatever. There's a step change where they don't really pick things up linguistically at all and we do. But with a lot more data than we ever get, LLMs seem to distill some of the broad mechanisms what may be our innate ability, though still seems to have a large learned component in us.
(I don't like Chomsky for other reasons, but having an obituary ain't no reason to disregard someone's thoughts.)
But his politics centers around the moral failings of the West so I think yes, if he was involved in the sexual exploitation of trafficked children, then this would devalue his criticism of the morality of the Western political system.
Why would it devalue his criticism assuming he was right?
Morality arguments are social and contextual. That 2+2 is 4 won’t change and captures some sort of eternal truth while what is deemed moral is constantly changing over time and differs across different societies and social groupings.
So morality arguments require and appeal to a particular shared sense of right and wrong. If Chomsky was guilty of sexually abusing children, then I do not share his moral foundation and so his appeals to morality arguments do not convince me.
Essentially it can be summed as any Western action must be rationalized as evil, and any anti-west action is therefore good. This is also in line with Christian dualism so the cultural building blocks are already in place.
Then you get Khmer Rouge, Putin, Hezbollah, Iran apologetism or downright support
It's difficult to summarise so many years of writing in a few sentences but from my own reading, he pointed out
a) many things done by the US lead to death or destruction b) many of these things are justified in the name of good that doesn't stand up to scrutiny c) the US government is often hypocritical d) US citizens are heavily propagandized both for foreign policy and domestic policy e) as a US citizen, it his duty to try and oppose these actions and since he's not a citizen of Iran, he isn't in a position to do anything about Iran f) a) through d) explain why he is often seen as an apologist, to use your word, for Iran; he tries to explain, from his point of view, why Iran etc. do the things they do g) a strong support of freedom of speech and opposition to censorship, including what he regards as private censorship as opposed to merely government censorship.
He of course has very complex rationalizing but essentially he assumes the opposite of mainstream western opinion and then tries to build ideological structures upon that.
That creates a very simplified version of reality wrapped in a nice intellectual wrapping
> But it must be recognized that the notion of "probability of a sentence" is an entirely useless one, under any known interpretation of this term.
He was impressively early to the concept, but I think even those skeptical of the ultimate value of LLMs must agree that his position has aged terribly. That seems to have been a fundamental theoretical failing rather than the computational limits of the time, if he couldn't imagine any framework in which a novel sentence had probability other than zero.
I guess that position hasn't aged worse than his judgment of the Khmer Rouge (or Hugo Chavez, or Epstein, or ...) though. There's a cult of personality around Chomsky that's in no way justified by any scientific, political, or other achievements that I can see.
There's no point minimizing his intelligence and achievements, though.
His linguistics work (eg: grammars) is still relevant in computer science, and his cynical view of the West has merit in moderation.
The problem is that they're weak models for the languages that humans prefer to use with each other (i.e., natural languages). He seems to have convinced enough academic linguists otherwise to doom most of that field to uselessness for his entire working life, while the useful approach moved to the CS department as NLP.
As to politics, I don't think it's hard to find critics of the West's atrocities with less history of denying or excusing the West's enemies' atrocities. He's certainly not always wrong, but he's a net unfortunate choice of figurehead.
Chomsky already was very active and well-known by 1960.
He pioneered areas in Computer Science, before Computer Science was a formal field, that we still use today.
His political views haven't changed much, but they were beneficial back when America was more naive. They are harmful now only because we suffer from an absurd excess of cynicism.*
How would you feel about Chomsky and his influence if we ignored everything past 1990 (two years after Manufacturing Consent)?
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* Just imagine if Nixon had been president in today's environment... the public would say "the tapes are a forgery!" or "why would I believe establishment shills like Woodward and Bernstein?" Too much skepticism is as bad as too little.
I think Chomsky's political views were pretty terrible, especially before 1990. He spoke favorably of the Khmer Rouge. He dismissed "Murder of a Gentle Land", one of the first Western reports of their mass killing, as a "third rate propaganda tract". As the killing became impossible to completely deny, he downplayed its scale. Concern for human rights in distant lands tends to be a left-leaning concept in the West, but Chomsky's influence neutralized that here. This contributed significantly to the West's indifference, and the killing continued. (The Vietnamese communists ultimately stopped it.)
Anyone who thinks Chomsky had good political ideas should read the opinions of Westerners in Cambodia during that time. I'm not saying he didn't have other good ideas; but how many good ideas does it take to offset 1.5-2M deaths?
Today it would not matter in the least if the president were understood to have covered up a conspiracy to break into the DNC headquarters. Much worse things have been dismissed or excused. Most of his party would approve of it and the rest would support him anyway so as not to damage "their side".
The question then becomes on of actual novelty versus the learned joint probabilities of internalised sentences/phrases/etc.
Generation or regurgitation? Is there a difference to begin with..?
If we define perplexity in the usual way in NLP, then that probability approaches zero as the length of the sequence increases, but it does so smoothly and never reaches exactly zero. This makes it useful for sequences of arbitrary length. This latter metric seems so obviously better that it seems ridiculous to me to reject all statistical approaches based on the former. That's with the benefit of hindsight for me; but enough of Chomsky's less famous contemporaries did judge correctly that I get that benefit, that LLMs exist, etc.
And again the question being, whether there is a difference at all between the two? Novelty in the human sense is also often a process of chaining and combining existing tools and thought.
In any case, do you see evidence that Chomsky changed his view? The quote from 2011 ("some successes, but a lot of failures") is softer but still quite negative.
It's of rather limited use for natural languages.
https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form
I'm not sure it required Chomsky's work.
(I suppose I have to state for the record that Chomsky's ties to Epstein are indefensible and that I'm not a fan of his on a personal level.)
For your very specific question: have a look at the sorry state of what's called 'regular expressions' many programming languages and libraries to see what programmers left loose can do. (Most of these 'regular expressions' add things like back-references etc that make matching their franken-'xpressions take exponential time in the worst case; but they neglect to put in stuff like intersection or complement of expressions, which are matchable in linear time.