I konw such cases Chomsky talks about. Richard Feynman told this story once about quantum physics, it goes somehow like: The mayan scientist priests observe the sky. They observe it year by year, and after many years they come up with a prediction for the king: Put 365 beans in a bowl and take one out every day. When the bowl is empty, the stars will be at the exact same spot they are now. The king says. Ok. but what do beans have to do with stars? Feynman said, we are in the same stage with quantum physics. We can make good predictions, but have no idea at all how it works.
Perhaps then humans are not statistical learners. Or to put it more bluntly, correlation is not a designated pattern in discovery but a consequence of static perspective for concepts in rapid motion. "Just as the Sun sends us information to 'continue life' without cessation, the stars and other celestial objects send us visible and non-visible consistency. So these beans (days) are nothing more than localized definitions or integer quantizations of 'time', as this is a lattice with no formal region or boundary." -Mayan Priest _Tulux Spug Dala: On Chaos_
+Omar Omokhodion I had the sme thoughts lately. I have read about google's deep learning algorithm, and its success in recognizing patterns. Basically it checks millions of images clearly associated with objects (image of a cat with a caption "cat"), and slowly getting better at recognizing objects on new images. So after lots and lots of images it can possibly recognize a similar pattern. On the other hand I have a 2 yr old daughter and I show her new things all the time. I have shown her an image of a crocodile, she recognizes practically all the crocodiles afterwards. ONE image. Once. It doesnt seem to be a statistical pattern comparison, but getting the "essence" of the crocodile and recognizing that in every following crocodile.
In this respect, Deep Dream could almost never tell us what is happening in the occipital lobe just as Google Translate could very likely never tell us what is happening in the internal parser. By stating 'what is happening' I mean reflect on the coordinational logic of variability in definitive objects like 'crocodile'. Although I do have to mention one area of interest. It's not as easy to distinguish the difference between a crocodile and alligator or perhaps if you were a 2 year old other large land lizards such as the komodo dragon. In this account Deep Dream might have the upper hand as it utilizes strict cluster boundary controls and contextual clues.
The link between math and reality is the only relevant notion. A substructure's degrees of freedom such as how consistent the night sky appears to the eye will inform you of a correlation.
"I don't do the wiggle-dance, because I'm not a bee." No, Noam, you don't do the wiggle-dance because you are not talking to a bee. You talk to someone/thing in a manner they can understand. Otherwise it's not "talking". Idiotic comments like this are one of the things Chomsky's acolytes are impressed by because they misunderstand his statement in the same way he misstates his point. Which, I suppose, makes it effective communication. But when you actually stop to think about what he says, it's just dumb. P.S. I assume he's not here referring to The Wiggles, because that would just be bizarre.
@@flatebo1 That is precisely his point. Stating that he cannot do it because he is not “talking” to a bee is the same as saying he is not able to do it because he is not a bee. Bee communication is completely different to human communication given that they operate on different innate structures. This is true because of Chomsky’s assumption of innate language capacity, surely for someone willing to offer a criticism you should know this.
People who call those that like Chomsky 'fan boys' because they respect his intellectual integrity compared to weird pop-science writers like Pinker are annoying. Chomsky is mediocre in many aspects, but Pinker isn't even close.
I think he feels very intimidated by Chomsky and therefore nervous. He tried very hard not to sound amateurish or dumb and it backfired. Sadly, he could have used a classic style of communication as he preaches and things would have been better.
LOL wasnt even a question. Think the idiot forgot his phrasing because he ended up just saying" dahhh um finish the sentence... yer um dah yer can you finish the sentence"
I take Noam's comments here to be the distinction we now make between prediction and inference. A lot of the machine learning techniques we use today use models that become so complicated that they cannot be interpreted. The goal of these models, however, is prediction; these models are successful because they can predict things very well. Classically, science has been a field of inference, where we try to infer how systems of nature function. In this way, some scientific disciplines are becoming less interested in problems of inference and more interested in problems of prediction.
Yeah, that's why models like neural networks are called black box solutions. They are not models built up from first principles or assumptions. These techniques are more useful for specific applications, less useful for basic research or theory.
I think you are misconstrued the point that Chomsky is making and creating confusion about the scientific method, which hasn't changed, along with inference and prediction. Are you suggesting that you cannot use classical mechanics to make predictions? such as Kepler's or Newton's laws or Maxwell's equations to state just a few examples? Chomsky makes a powerful point very simply so that even i can understand it. Where statistical analysis is applied to specific and well understood properties of language then significant insights can be usefully drawn and he gave the examples of specific properties of word boundaries. Where analysis is applied more generally to look for "general" properties of language in the hope we can find a more general theory of not just language but deeper insight to our own minds and natures, then this has largely been a failure. And he cited an example and an analogy to show why these mistakes are being made.
Chomsky basically summarized the state of machine learning perfectly. We are getting these statistical models that are becoming more and more accurate in prediction/classifying previously unseen examples. However, what we are getting are approximate models to human counterparts. It's more of an engineering solution where we can use these machines/models to build useful applications. However, we are no closer to understanding how human brain works.
Persons whom, mock Noam Chomsky, for speaking on topics that he is not a scholar in simply fail to see how much time and real effort he puts in each day to understand and explain them. I have not known a more hard working scholar and activist. Disagree with him that is fine. But, do not belittle his efforts that is simply being utterly dishonest.
+ElusiaBoomkin Shush, what he said didn't need interpretation, it was clear enough.... It certainly didn't need a completely derailed interpretation like the one you made of it... But saying "lol u wut m8" at the end belittled any value a reader might've given to your comment.
+Jeremy Reagan Yes but it is an equal fallacy to assume that because he has authority in one sphere that of linguistics then he has authority in other spheres . He has no more than you or I. He has no particular qualifications to speak on matters outside linguistics Amazingly over 21000 people have listened to this video . I doubt that any more than a handful have any idea what he is talking about .
For those wondering what the hell Chomsky is talking about with respect to the measure of success, it may be helpful to see the video below. This shows a neural network (one of the machine learning techniques Pinker mentioned) learning to make speech-like sounds. This sort of thing could be useful in lots of ways. It's clear that with a bit more work, you could have several tracks of this overlaid to sound almost indistinguishable from an actual crowd of people in conversations. Could be useful for making movies, for example. It's also clear, though, that there is no semantic content in the speech. It doesn't mean anything, even if it sounds great. In particular, even if it generates sentences, or hour-long lectures on particle physics, there's no meaning in them because they were drawn at random, in a sense, out of a clever neural network hat. This is Chomsky's point. You can call a neural network successful when it generates speech-like sounds, but that doesn't get you any closer to teaching a machine to produce _meaningful_ speech. In much broader terms: Pinker asked Chomsky to what extent machine learning has been successful in processing natural language. Chomsky said that the only successes he was aware of involved machine learning that started with a substantial injection of human knowledge, where machine learning from scratch has produced nothing interesting (in language). ruclips.net/video/NG-LATBZNBs/видео.html
My point basically still stands, @@basscataz, as "AI" is quite famous for producing eloquent gibberish in several different forms. I can link an example or two if you aren't aware of them already. That said, I'm very impressed with the progress of machine learning. Within limited contexts, AI is already competitive with humans, and those contexts will only be growing.
This is why I dropped out of English language studies and got an English lit degree instead. I really don't understand what these two are talking about, but I know they are both geniuses in the field of linguistics.
Just because you don't know what the fuck it means, as you so eloquently put it, does not mean that it does not exist. It was an option where I went to college. The classes included history of the English language, which forced you to learn to conjigate verbs in old English, and Transformational grammar, which is they type of grammar created by Non Chompsky. I dropped out of it and got my degree in English lit. instead. Tip for life: just because you have never heard of something does not mean it does not exist. If you keep this in mind, you will be able to do something called "learning." (And yes, I also took a class in linguistics, so I know what that is too.)
Well, why cuss at me? If you don't like it, write to the head of the English department at San Francisco State University. But I got that degree a long time ago, so it may be gone by now.. I would assume that linguistics would have it's own department, if SFSU had one, which I'm not sure it did. This was taught by the ENGLISH departement, and thus the focus on the ENGLISh language.
It's always a pleasure to listen to Professor Chomsky discuss linguistics. The field has widened greatly since the 50's into computational parcels where brute force methods can be applied. The Professor maintains the layer of abstraction necessary to provide an overview of the nature of the problems being tackled.
That was actually a great point. Since there were never supercomputers and myriads of data in the past, scientists were limited to creating their own theories that had a good predicting value. However, the role of science seems greater then that. It's getting the truth about the world with any means possible. If that means running statistics on large amounts of data then so be it. Predicting value without any underling theories (though machine learning can often point you in the direction of generalizable patterns or theories) is still a value.
Yeah. Chomsky is a master at intellectual humiliations. Only someone with a serious reputation can pull it off without getting backhanded too. Some grad student with nothing under his or her belt wouldn't be able to get away with it.
Chomsky humour & amusement is always subtle I have noticed. Did you see his debate with Foucault? The first question asked to Foucault by the public is so good. Look at Chomsky face, it’s hilarious. He’s very much amused & Foucault refused to answer the question because if he did, he would have had to contradict himself. Which Chomsky, right at the moment, realised and smiled from ear to ear, realising the fact.
As an engineer I can see that this is an engineering approach to making a device that works. And I guess that AI is still in that phase. There isn't a complete scientific model for AI or the physical process of parsing speech, so these guys are doing what engineers have always done, they fiddle around until it works and let someone else develop the theory latter.
depends on the branch of AI, neural networks are engineering tools as you describe them, but SVMs are convex and therefore have theoretically strong boundaries to their empirical losses. Some day, this theoretical strength might push SVMs ahead of NN.
As an engineer you guess AI is still in that phase? There isn’t a scientific model, not even an incomplete ‘model’, because such a conception is to meaningless to deserve discussion (according to Alan Turing).
Strangely enough, most people in this comment section simply don't get it that Chomsy and Pinker are in full agreement here regarding the necessity of building in biases for upping the efficiency of pattern-extracting algorithms. Responses can be roughly divided into 3 categories; 1) ain't got the slightest clue what what these guys are talking about because either too convolutedly and/or boringly stated 2) Chomky's a politically biased intellectual who can't just accept his GU wasn't of any use for language processing devices 3) Pinker was all strung up for being face-to-face with the man himself
Once you reach a certain level of intellectual sophistication, once you've known you field so well that you see its connections to philosophy, neuroscience... and once you developed great work ethics of reading enormously, of retaining information like him (encyclopedic memory) and you know the means by which to research, to connect and extract conclusions, you can be a humanist, a person whose interests and depth of knowledge covers many fields of interest... Chomsky is extremely efficient in reading, memorizing and writing.... He wrote many many books! He is one of the top humanistic minds of our era!
Translation: Pinker: 'Many of the recent advances in AI programming and cognitive sciences are down to the use of probability and statistics based on learning but your fields - generative grammar and semantic memory - do not use these techniques at the moment. Since AI and the cognitive sciences are analogous to your work, do you think they might in the future also employ statistical and probabilistic methods?' Chomsky: 'We've used statistics before with more failures than successes. For example, work was done on statistical analysis (of the sound of speech) to identify boundaries between words which failed. If you combine this with existing audible features that we know of (unsure about these) then identifying word boundaries statistically becomes more successful [this is not really addressing Pinker's question]. There is work being done using the sorts of techniques that AI and cognitive science uses (Bayes Theorum etc.) without actually looking at the structure of the language. They have an odd definition of success.' Chomsky then digresses to making an analogy of the use of these techniques in modelling bee behaviour. He describes the difference between a bee scientist looking at individual behaviour versus taking video of many bees and modelling the aggregated behaviour. What you get are approximations of bee behaviour that are better than what the bee scientist gets. He then suggests that it is strange that when people write papers about this modelling they claim 'success' in their modelling and Chomsky knows of no other science where approximations are deemed as success. I am unclear how this relates to the work being done using statistical analysis and probability in linguistics which he referred earlier. I would like to note that statistical analysis, Bayes Theorum etc. are very useful in a host of modelled systems and that there are many, many branches of science which rely on approximation of behaviour and complex systems.
Well, to be fair, as long as you don't fully comprehend and cannot describe a given phenomenon in depth (like bee behavior), statistical analysis is the only tool at your disposal. If, on the other hand, a phenomenon is understood in depth (like an apple falling from a tree), you can make accurate predictions on the outcome based on a theory. Which is, ultimately, also the fruit of observation and statistical analysis but considered as fully understood. So based on this premise I don't understand Chomsky's criticism and dismissal of today's progress and methods employed.
Thankyou, one of the jobs of a scientist is to communicate science, and I feel that sometimes they forget this and unnecessarily intellectually grandstand.
His point is that predictive power alone doesn't make a theory. You can have perfect predictive power for a subset of possible events, yet no understanding of how and why things work the way they do.
I believe his problem is with the investigation of "what" and dismissal of the "why". Predicting bee behaviour using AI modelling can predict the what, but the deeper investigation of an individual bee in the group can give you the "why". I think it goes right down to Richard Feynman's famous division between knowledge and understanding; he believed that understanding was much more important than knowing. You can know what the swarm of bees are going to do but you have no understanding of why they behave that way.
He's a good lad Chomsky, isn't he - I like him too. I can imagine sitting round the fireside with him, talking all kinds of weird shit, and putting the world to rights lol :)
+Jack Stratif I work in machine learning. Chomsky theories were fun, but they were wrong and delayed advanced in natural language processing. He is showing his ignorance in this video. As wikipedia puts it, "This was due both to the steady increase in computational power resulting from Moore's Law and the gradual lessening of the dominance of Chomskyan theories of linguistics (e.g. transformational grammar), whose theoretical underpinnings discouraged the sort of corpus linguistics that underlies the machine-learning approach to language processing."
+Ricardo Cruz much agreed, chomsky has been stifling linquistics for decades; not by his ideas, but by his adamancy; his political values suffer the same.
+Ricardo Cruz Wikipedia's editorial process is very limited in it's scope, and often reflects the thinking of two or three people within a certain field, all of whom have the same bias regarding that field. It should never be quoted as if it's a neutral source.
Working in the field of machine learning is not really all too relevant. Algorithms only go so far as the ability to map Euclidean distance and create predictive co-variance models in the form of cluster boundaries all in the span of the workload in silicone processors the dominant means to compute in modern technology. Presuppose that lingual coherence functioned outside the bounds of means (frequency) acquisition?
Wow. Yannis Varoufakis said roughly the same thing about the pure economics models with their lack of relation to real world economics, in a later discussion with Noam Chomsky on the state and mechanics of the European Union. Another eye opener.
+santos D Because Chomsky is a force of nature, and Pinker has expressed slight disagreements with him. Also, in academia it's generally very competitive, which doesn't mean C or P are jerks, but still, that sort of spirit that pervades academia will create this sort of feeling in someone "lower down the hierarchy." This is all obviously my very subjective opinion.
Kierkegaard I've heard Pinker mention he has slight disagreements with Chomsky regarding linguistics, but whenever he explains what those disagreements are he just seems to be paraphrasing Chomsky. Not really sure what he objects to, but linguistic can get extremely technical sometimes. (not heard him talk about political disagreements, though I can see they exist)
Emotionally, Chomsky's attitude feels right. Its hard to see brute-force computing approaches as being an appropriate measure for science, where theory and carefully designed experiment 'ought' to be the way advancement is made. However on the longer view, I don't think enough credence is given to the influence of technology itself. Chomsky formulated generative grammar when the mathematical tools were available from computer science. Today, raw computing power give rise to big data approaches. Obviously their work strives to be an incredibly nuanced synthesis of linguistic evidence, brain studies, evolution etc. But there is also the sense that when a new technical approach arises, there is a tendency to push it to its limits, to harvest any low-hanging fruit, and see how things look from a new vantage point. And its my belief that in the end, its the new technique that advances things, more than the intellectual grand synthesis.
Chomsky is the master of takedowns. I think he's basically saying, at the end, the "approximation of unanalyzed data" is novel when conceived as a sort of system without parameter or purpose. You can collect lots of randomized data that seemingly has no meaning, and from the perspective in which it is captured, after breaking it down into arbitrary units connected to nothing in particular, get some idea of what 'generally' will or is likely to happen in the future. But its purpose as collected data is simply to be analyzed. It has no bearing on anything meaningful to human beings.
So basically, is he just saying you can either observe a lot and make fairly accurate predictions without understanding the concepts (probabilistic method), or alternatively you can build a simplified model and improve understanding of underlying concept slowly, but get crappy results in the meantime(his method)?
Noam's "novel notion of success" at 5:00 seems to be an argument in favor of science as _statistical inference about a physical model with many training examples_ as opposed to _controlled experiments on approximations of reality inside a laboratory_. For example, you can predict the location of the moon relative to the Earth at a given date and time by 1) applying the laws of motion under ideal circumstances, e.g. the moon occupies a plane with a constant z-coordinate that bisects the Earth; or, 2) record video of the night sky for several months, convert the video into quantitative data, then feed the data into a statistical data structure and let it learn.
+vau0807 "argument in favor of science as statistical inference about a physical model with many training examples" I understand how this is manifest in your moon example. However, I don't understand why laboratory experiments work. Simply because you can't fit the moon in a lab? Or something else?
the whole thing science aims now is to create a "artificial intelligence", a construct capable of "conceiving" reality like we humans do it, a construct capable of taking a massive ammount of info, store it and analyze it by its own. And because it would be made in line with the laws of the physics and science, this construct would be able to do the science by itself. This construct would then be able to tell us the truths we claim beyond our reach. You already know what it sounds like.
I think it's because a lot of the commenters sense, on an unconscious level, that Pinker and Chomsky are vastly more intelligent than they are...even as they claim that these men are spouting nonsense. That's the general feeling I get here.
+jojomojojones to quote chomsky from elsewhere, "you need to be able to hold more than one thought in mind at once" ... which probably requires a fair bit of rigorous academic learning ... do you hold any graduate degrees jojo?
+jojomojojones There was a time I wondered how such a brilliant humanitarian came to present such a monotonous tone....Now I realize how completely he strips the faces of power of all their appealing veneers with his facts and his tone is merciful in its acceptance of the frailty of human amorality.
jojomojojones Yes, one would likely believe such a thing prior to being exposed to the study of linguistics. Similarly, it seems obvious that we understand what leads people to make everyday decisions. Until you hear Daniel Kahnemann show you how obvious it isn't.
There may be things beyond our understanding, that must be taken into account. Better question would be - would making good predictive models cause some harm? I don't understand why have those people spent so much time criticizing probabilistic models? I mean, Pinker some decades, Chomsky whole centuries. :D :D lol ... but why?
I think that's exactly the point Noam is trying to make. Those novel experiments sometimes has extremly specific hypothesis. The problem that arise is that the use of the "sucessful" studies are to rare or complex to teach us anything of value. To my own limited kowledge (correct me if I'm wrong) neural networks might be an example of novel studies turned into very valuable theories over time. When it was presented, I think in the 80's/90's, we didn't have the computers to use it. But as time went by and computers today have became far more faster, neural netwroks has become a very interesting and more usefull tool. But then againg this video was hard to follow and I'm not sure, soooo what ever (:
When people are outraged by what you say - but they can't explain why - there's a good chance you're right. See angry sputtering comments below for examples.
Translation: While solely using statistical analysis in machine learning has been shown to work, within a limited scope, it appears to be much more successful when integrated with other techniques.
Flash! Chompsky (I know, I know) says a ball rolling down an inclined plane is a thing that never happens in nature. Huh? I better go tell my granddaughter whose favorite thing at the moment is rolling a ball down the inclined plane in the front of my daughter's house, ie., the driveway, that she is doing the impossible. I doubt she will believe me.
Language: The most recent and most important language is the language of "Texting". Textos is truly a language and must be considered as important, even More important than most of the tribal languages in Africa and the dialects spoken in many sub cultures on earth.
The math is already there, The brain uses statistics in form of stress. You can avoid math in your models only if you use premolded blocks. How enginners do a basic lowpass filter to alter a reproduced sound? They add a capacitor in the wire to the speakers. The math is there, but you don't need it to make the filter work. How do programmers the same filter: The sound records are not sulpted in solids, the sound waves are encoded. You need strong math (Fourier, I suppose) to transform the data before convert it to waves.
If bee scientists, through laborious experimentation and analysis are able to predict swarm behavior with 95% accuracy, and a machine-learning model has been built that can predict swarm behavior equally or better, what's a key difference? The former results in _knowledge_ and _understanding_ (i.e., true science), the latter, simply information transmission. Taking a look around at our current culture, one can see how important the distinction is.
Chomsky criticized America for not getting involved earlier you liar. If Chomsky was president millions of peoples lives would be saved and the unnecessary nukes and bombing of civilian cities across europe wouldnt have happened
I'm really disappointed in Pinker here. That was incredibly convoluted and abstruse, and didn't need to be. Who's he trying to impress? Normally I'm impressed by how easily and clearly he presents material.
?? he means real success is creating models and theory that has not only predicting power but also are descriptive abstract tools, not only the first in a case by case manner, based on statistical analysis.
+claschxtreme isn't that affirming the consequent? If theory A is true, then B prediction will be true. B prediction is true. Therefore, A. Shouldn't theories first be developed with empirical data and then checked for productive power?
The approach to crunching enormous amounts of data using statistical methods and supercomputers to get deeper insights into the language faculty of humans, or any animal including Bees, has mostly been a failure and he explains why. And it is worth listening to his response again. He also used an analogy as to why this approach in computational science if used in Physics would be like trying to understand and make predictions about the world by looking outside the window to make accurate predictions and provide insight into fundamental properties about the world. If your data set is large enough you might be able to make some predictions but that won't provide understanding of the forces like, gravity and electromagnetism which are at work. This is the point that Chomsky is making. Where analysis is used to provide insight into specific properties of language such as on word boundaries then some progress has been made. What do we know, what can we show? As Chomsky points out on many questions about human nature and behaviour we know very little. As he points out these questions are very difficult.
Noam was 100% incorrect. He was so sure of his opinions. I know he is old now so reflecting upon that may not be possible, but maybe it can be used as a cautionary tale for others.
He still very much believes these views, even after the success of ChatGPT and many linguists would likewise argue he does so for good reason. Predictive text output does not in itself imply any undersatanding. Here is his recent discussion on the subject: ruclips.net/video/axuGfh4UR9Q/видео.html
Ha ha. I guess also clap when my tone suggests particular sincerity or urgency. If he explained in simple English, (I assume it's possible), would he lose popularity?
Ok, how is anything Chomsky said that complex? Bottom line, you can use statistics to predict what sound come next with a big sample, but it's better if you understood the language? Like duh? I think there are some fan boys here giving him more credit than is warranted
I put this German sentence in Google Translate: "Der Frau gibt der Mann das Auto". This English sentence came out: "The Lord gives the man the car." I don't know what methods Google Translate uses, but that's a bogus translation.
+impCaesarAvg I would argue that your sentence is not "German as a language used by people" but "German grammar fantasy by a Besserwisser". If you put the Dativ in its proper place, google translates perfectly. "Der Herr" is wrong, but google "knows" and offers an alternative translation: The woman gives the man the car. Which is still wrong, but not "bogus". Anyway: You do not like g-translate? Wel, go find or do a better one. You will neither find a better one (for general purposes, as google is the best, proven time after time) nor be able to do a better one (for obvious reasons). Same with democracy: Worst form of gov., except all others that have been tried.
+impCaesarAvg Denn dein ist das Reich und die Kraft und die Herrlichkeit. -- For thine is the kingdom and the power and the glory. Not so bad. Because: Google uses an SBMT approach. Wikipedia. As the German who did the algorithms admits: results for German and English leave much to be desired. If one does not like it: Improve it, find a better one or - as both is out of our reach: I am glad that the best MT on earth is FREE. Frohe Weihnachten. It is a wonderful world. And pray that there´s intelligent life somewhere up in space.
+mark rode I guess MT is machine translation, but what is SB? I think, if there ever is decent machine translation, it will be based on chomskyan linguistics. Merry Christmas!
+impCaesarAvg SB Statistics based MT. The linguistic approach in MT: "Tranfer" / "Interlanguage" had its time decades ago ... - I do agree that the future must bring a revival, as SBMT alone may not get much better than now. "gefallen" is usu. translated in a "to like"-construction. / "to appeal to" is MUCH rarer -so SBMT chooses "to like". Which leads to syntactical chaos, obviously. One should know ones limits and others´.
For all you idiots calling Noam an idiot for not understanding him, he's talking about different methods of linguistic optimization for AI/algorithms like that little CC button you see in the video so you can read what he articulates. It's quite comically meta in a way. I just refuted some idiots on this "refuting idiots" channel.
The issue is that statistics yields prediction without explanation. While Chomsky used computer detection of word boundaries in speech as his example, Google Translate is another application. Nothing surprising here: If you know something about the laws governing the behavior of language, you can get better predictions, and with fewer data points, then if you use only raw brute force. I think Chomsky gets thrashed because of his nutty Marxist politics more often than on the merits of what he says about language, his own field, by people who aren't linguists. That reduction hasn't proceeded as far in language as it has in physics doesn't alter his basic point, however.
Pinker is asking if chomsky's theory will be of use in the future, because unlike the new theories (big data), it has no statistiks and propability in it. Chomsky answers that statistics and propabilities are too superficial and that you can't get understanding out of it (only statistically data), and that it is therefore not very usefull. Pinker framed his question in a weird way, but he wanted to kind of embarras Chomsky, because he thinks his theory is a failure. But Pinker embarrast himself.
The character and integrity of Chonsky is well displayed here. Pinker basically says "chomskys wrong because of all the fancy advances the charlatan scholarly class - would be media celebrities like ME PINKER have made." Listen to Chonsky ignore the insult of having to answer questions fro.the likes of Pinker in Chonskys field and notice his integrity in putting that nonsense aside and educating the viewer so superbly on the topic. I could not have had the self restraint or dignity myself. Heres the deal Pinkee attacks and makes a career of misrepresenting Chomky's political and scientific work. Pinker hitches his careerist ambitions of being a "linguistics or cognative scientist" having refuted Chomsky's work. This is hopeless nonsense. If you want a taste of the real Pinker - the pathology of his ambitions and narcissism - view his disgust using attack on Chomsky and his constant lying about Mr Chomsky and his work (chomsky is not "a Marxist?" Could have fooled me since Chomsky uses Marx"s work extensively in his public comments and obviously they are much o the the same page descriptively. Pinker the quaffed but quite unattractive media persona also says that Chomskys scientific contributions are revered because people are su h fans of his political work. Pinker is not a a scientist. He is a vicious charletan To see the real Pinker in action view his comments when cho.sky isnt in the room at ruclips.net/video/wxZ-NrCohGk/видео.html
I konw such cases Chomsky talks about. Richard Feynman told this story once about quantum physics, it goes somehow like:
The mayan scientist priests observe the sky. They observe it year by year, and after many years they come up with a prediction for the king: Put 365 beans in a bowl and take one out every day. When the bowl is empty, the stars will be at the exact same spot they are now.
The king says. Ok. but what do beans have to do with stars?
Feynman said, we are in the same stage with quantum physics. We can make good predictions, but have no idea at all how it works.
Perhaps then humans are not statistical learners.
Or to put it more bluntly, correlation is not a designated pattern in discovery but a consequence of static perspective for concepts in rapid motion.
"Just as the Sun sends us information to 'continue life' without cessation, the stars and other celestial objects send us visible and non-visible consistency. So these beans (days) are nothing more than localized definitions or integer quantizations of 'time', as this is a lattice with no formal region or boundary."
-Mayan Priest
_Tulux Spug Dala: On Chaos_
+Omar Omokhodion I had the sme thoughts lately. I have read about google's deep learning algorithm, and its success in recognizing patterns. Basically it checks millions of images clearly associated with objects (image of a cat with a caption "cat"), and slowly getting better at recognizing objects on new images. So after lots and lots of images it can possibly recognize a similar pattern. On the other hand I have a 2 yr old daughter and I show her new things all the time. I have shown her an image of a crocodile, she recognizes practically all the crocodiles afterwards. ONE image. Once. It doesnt seem to be a statistical pattern comparison, but getting the "essence" of the crocodile and recognizing that in every following crocodile.
In this respect, Deep Dream could almost never tell us what is happening in the occipital lobe just as Google Translate could very likely never tell us what is happening in the internal parser. By stating 'what is happening' I mean reflect on the coordinational logic of variability in definitive objects like 'crocodile'.
Although I do have to mention one area of interest. It's not as easy to distinguish the difference between a crocodile and alligator or perhaps if you were a 2 year old other large land lizards such as the komodo dragon. In this account Deep Dream might have the upper hand as it utilizes strict cluster boundary controls and contextual clues.
The link between math and reality is the only relevant notion. A substructure's degrees of freedom such as how consistent the night sky appears to the eye will inform you of a correlation.
Fair enough, I overstepped boundaries.
Emotional context is relevant.
yes, that was precisely the question that was on my mind.
lol
This goes in the "don't watch while stoned" pile.
Too late
too late indeed
y'all just made me laugh so hard.
Too late. 1 year later...
Haha
"I don't do the wiggle-dance, because I'm not a bee."
-Noam Chomsky, at a talk I saw him give about the evolution of language
That A's do B does not imply that non-A's do not do B. Except in a Bayesian statistical sense. Hoist by his own petard!
Likely he was talking about bee communication. They engage in little dances to communicate things like the location of flowering plants to each other.
"I don't do the wiggle-dance, because I'm not a bee."
No, Noam, you don't do the wiggle-dance because you are not talking to a bee. You talk to someone/thing in a manner they can understand. Otherwise it's not "talking".
Idiotic comments like this are one of the things Chomsky's acolytes are impressed by because they misunderstand his statement in the same way he misstates his point. Which, I suppose, makes it effective communication. But when you actually stop to think about what he says, it's just dumb.
P.S. I assume he's not here referring to The Wiggles, because that would just be bizarre.
and it's WAGGLE dance, not wiggle...so everything noam chomsky ever did is discredited.
@@flatebo1 That is precisely his point. Stating that he cannot do it because he is not “talking” to a bee is the same as saying he is not able to do it because he is not a bee. Bee communication is completely different to human communication given that they operate on different innate structures. This is true because of Chomsky’s assumption of innate language capacity, surely for someone willing to offer a criticism you should know this.
GET READY FOR A COMMENT SECTION FULL OF AGGRESSIVE PEOPLE INSECURE ABOUR THEIR INTELLIGENCE.
OK, I'M READY!
And get ready for some blind fan boy worship as well
Kjobbit amen
Do you even understand rick and morty??
People who call those that like Chomsky 'fan boys' because they respect his intellectual integrity compared to weird pop-science writers like Pinker are annoying. Chomsky is mediocre in many aspects, but Pinker isn't even close.
That was the longest question I've ever heard in my life.
+Mamamonkey What was the question again?......
That was the longest question I've ever heard in my life.
I think he feels very intimidated by Chomsky and therefore nervous. He tried very hard not to sound amateurish or dumb and it backfired. Sadly, he could have used a classic style of communication as he preaches and things would have been better.
LOL wasnt even a question. Think the idiot forgot his phrasing because he ended up just saying" dahhh um finish the sentence... yer um dah yer can you finish the sentence"
so Steven Pinker is an idiot who is intimidated by Noam Chomsky? that certainly is news to me!!!
Chomsky always tries his best to explain clearly things as he has come to understand them.
AND he never states the obvious
I take Noam's comments here to be the distinction we now make between prediction and inference. A lot of the machine learning techniques we use today use models that become so complicated that they cannot be interpreted. The goal of these models, however, is prediction; these models are successful because they can predict things very well. Classically, science has been a field of inference, where we try to infer how systems of nature function. In this way, some scientific disciplines are becoming less interested in problems of inference and more interested in problems of prediction.
Wow. An informed, intelligent comment. I didn't think it could happen on RUclips. :)
Haha thank you :)
Yeah, that's why models like neural networks are called black box solutions. They are not models built up from first principles or assumptions. These techniques are more useful for specific applications, less useful for basic research or theory.
I think you are misconstrued the point that Chomsky is making and creating confusion about the scientific method, which hasn't changed, along with inference and prediction.
Are you suggesting that you cannot use classical mechanics to make predictions? such as Kepler's or Newton's laws or Maxwell's equations to state just a few examples?
Chomsky makes a powerful point very simply so that even i can understand it. Where statistical analysis is applied to specific and well understood properties of language then significant insights can be usefully drawn and he gave the examples of specific properties of word boundaries. Where analysis is applied more generally to look for "general" properties of language in the hope we can find a more general theory of not just language but deeper insight to our own minds and natures, then this has largely been a failure. And he cited an example and an analogy to show why these mistakes are being made.
Chomsky basically summarized the state of machine learning perfectly. We are getting these statistical models that are becoming more and more accurate in prediction/classifying previously unseen examples. However, what we are getting are approximate models to human counterparts. It's more of an engineering solution where we can use these machines/models to build useful applications.
However, we are no closer to understanding how human brain works.
michael tomasello begs to differ.
Your comment is biased. Scientists know how the human neurocognitive system works, but you don't.
@@sachacoronel3828 Where are you getting that from. From what i've seen there really isn't much explanation out there for how these things work
Persons whom, mock Noam Chomsky, for speaking on topics that he is not a scholar in simply fail to see how much time and real effort he puts in each day to understand and explain them. I have not known a more hard working scholar and activist. Disagree with him that is fine. But, do not belittle his efforts that is simply being utterly dishonest.
+ElusiaBoomkin Shush, what he said didn't need interpretation, it was clear enough.... It certainly didn't need a completely derailed interpretation like the one you made of it...
But saying "lol u wut m8" at the end belittled any value a reader might've given to your comment.
+ElusiaBoomkin
Your commnent is irrelevant. I was very clear at least as clear as language can be your free to opinion as am I.
+Ayman B.
Thank you for your kindness towards me.
+ElusiaBoomkin This is obnoxious and totally unnecessary.
+Jeremy Reagan Yes but it is an equal fallacy to assume that because he has authority in one sphere that of linguistics then he has authority in other spheres .
He has no more than you or I. He has no particular qualifications to speak on matters outside linguistics
Amazingly over 21000 people have listened to this video . I doubt that any more than a handful have any idea what he is talking about .
This would be a good video to use to analyze Noam's hand gestures and non-verbal communication.
Callme Ishmael haha pure insults to pinker
If you want to see more hand gesture and non verbel communication, watch Jordan Patterson !!
For those wondering what the hell Chomsky is talking about with respect to the measure of success, it may be helpful to see the video below. This shows a neural network (one of the machine learning techniques Pinker mentioned) learning to make speech-like sounds. This sort of thing could be useful in lots of ways. It's clear that with a bit more work, you could have several tracks of this overlaid to sound almost indistinguishable from an actual crowd of people in conversations. Could be useful for making movies, for example. It's also clear, though, that there is no semantic content in the speech. It doesn't mean anything, even if it sounds great. In particular, even if it generates sentences, or hour-long lectures on particle physics, there's no meaning in them because they were drawn at random, in a sense, out of a clever neural network hat. This is Chomsky's point. You can call a neural network successful when it generates speech-like sounds, but that doesn't get you any closer to teaching a machine to produce _meaningful_ speech.
In much broader terms: Pinker asked Chomsky to what extent machine learning has been successful in processing natural language. Chomsky said that the only successes he was aware of involved machine learning that started with a substantial injection of human knowledge, where machine learning from scratch has produced nothing interesting (in language).
ruclips.net/video/NG-LATBZNBs/видео.html
might be worth elaborating on what "meaning" itself... ummm... means. I presume it refers to structure of relations between different things
Who is laughing now
My point basically still stands, @@basscataz, as "AI" is quite famous for producing eloquent gibberish in several different forms. I can link an example or two if you aren't aware of them already.
That said, I'm very impressed with the progress of machine learning. Within limited contexts, AI is already competitive with humans, and those contexts will only be growing.
@@bumpty9830 Cope.
I just decomposed listening to this question
John Cooper - Social Heartist The question or the answer? Lol
You need to strengthen your gut if you want to survive RUclips.
This is why I dropped out of English language studies and got an English lit degree instead. I really don't understand what these two are talking about, but I know they are both geniuses in the field of linguistics.
Just because you don't know what the fuck it means, as you so eloquently put it, does not mean that it does not exist. It was an option where I went to college. The classes included history of the English language, which forced you to learn to conjigate verbs in old English, and Transformational grammar, which is they type of grammar created by Non Chompsky. I dropped out of it and got my degree in English lit. instead.
Tip for life: just because you have never heard of something does not mean it does not exist. If you keep this in mind, you will be able to do something called "learning." (And yes, I also took a class in linguistics, so I know what that is too.)
Well, why cuss at me? If you don't like it, write to the head of the English department at San Francisco State University. But I got that degree a long time ago, so it may be gone by now..
I would assume that linguistics would have it's own department, if SFSU had one, which I'm not sure it did. This was taught by the ENGLISH departement, and thus the focus on the ENGLISh language.
No they aren't. They are profound idiots advocating a metaphysical materialism that would believe electrons can make value judgments.
@AndroidPolitician exactly. a measure of skepticism needs to be applied consistently and universally
My interest is vice versa. I cannot understand literature but I can understand linguistics.
Chomsky is such a boss. A.I. "scientists" exposed as unscientific dreamers.
It's always a pleasure to listen to Professor Chomsky discuss linguistics. The field has widened greatly since the 50's into computational parcels where brute force methods can be applied. The Professor maintains the layer of abstraction necessary to provide an overview of the nature of the problems being tackled.
What did he say?
that is the most long-winded question i've ever heard in my life
Or, your attention span has been destroyed by your own actions.
@@CAKESLAPPAor, he said a lot of nothing 🤷♂️
That was actually a great point. Since there were never supercomputers and myriads of data in the past, scientists were limited to creating their own theories that had a good predicting value. However, the role of science seems greater then that. It's getting the truth about the world with any means possible. If that means running statistics on large amounts of data then so be it. Predicting value without any underling theories (though machine learning can often point you in the direction of generalizable patterns or theories) is still a value.
It's valuable as an engineering task, not as a scientific explanation.
I watched it without sound. Thought I was watching Godfather
Noam's dry irony was hilarious. The people around him didn't seem to get it. Or maybe they did....
Yeah. Chomsky is a master at intellectual humiliations. Only someone with a serious reputation can pull it off without getting backhanded too. Some grad student with nothing under his or her belt wouldn't be able to get away with it.
Chomsky humour & amusement is always subtle I have noticed. Did you see his debate with Foucault? The first question asked to Foucault by the public is so good. Look at Chomsky face, it’s hilarious. He’s very much amused & Foucault refused to answer the question because if he did, he would have had to contradict himself. Which Chomsky, right at the moment, realised and smiled from ear to ear, realising the fact.
As an engineer I can see that this is an engineering approach to making a device that works. And I guess that AI is still in that phase. There isn't a complete scientific model for AI or the physical process of parsing speech, so these guys are doing what engineers have always done, they fiddle around until it works and let someone else develop the theory latter.
dick
depends on the branch of AI, neural networks are engineering tools as you describe them, but SVMs are convex and therefore have theoretically strong boundaries to their empirical losses. Some day, this theoretical strength might push SVMs ahead of NN.
Engineers make for bad theorists.
As an engineer you guess AI is still in that phase? There isn’t a scientific model, not even an incomplete ‘model’, because such a conception is to meaningless to deserve discussion (according to Alan Turing).
Trying to understand Latin would have been easier than following that exchange. I don't even know why I clicked on this video. So much hope.
Chomsky seems to like wearing jeans. I saw him in jeans in so many conferences, whereas other people would dress formally.
People should wear what they like or what they feel comfortable in. Perhaps the idea that we should all be formal at such events is manufactured.
It's because he's sponsored by Wrangler.
That's heavy, man :)
@@boorhaave5880 You made me laugh so hard....
@Fishheadmandible Yes and wearing formal clothes adds nothing to the discussion.
Strangely enough, most people in this comment section simply don't get it that Chomsy and Pinker are in full agreement here regarding the necessity of building in biases for upping the efficiency of pattern-extracting algorithms. Responses can be roughly divided into 3 categories;
1) ain't got the slightest clue what what these guys are talking about because either too convolutedly and/or boringly stated
2) Chomky's a politically biased intellectual who can't just accept his GU wasn't of any use for language processing devices
3) Pinker was all strung up for being face-to-face with the man himself
When was that discussion? (Not the upload.)
Once you reach a certain level of intellectual sophistication, once you've known you field so well that you see its connections to philosophy, neuroscience... and once you developed great work ethics of reading enormously, of retaining information like him (encyclopedic memory) and you know the means by which to research, to connect and extract conclusions, you can be a humanist, a person whose interests and depth of knowledge covers many fields of interest... Chomsky is extremely efficient in reading, memorizing and writing.... He wrote many many books! He is one of the top humanistic minds of our era!
Translation:
Pinker: 'Many of the recent advances in AI programming and cognitive sciences are down to the use of probability and statistics based on learning but your fields - generative grammar and semantic memory - do not use these techniques at the moment. Since AI and the cognitive sciences are analogous to your work, do you think they might in the future also employ statistical and probabilistic methods?'
Chomsky: 'We've used statistics before with more failures than successes. For example, work was done on statistical analysis (of the sound of speech) to identify boundaries between words which failed. If you combine this with existing audible features that we know of (unsure about these) then identifying word boundaries statistically becomes more successful [this is not really addressing Pinker's question]. There is work being done using the sorts of techniques that AI and cognitive science uses (Bayes Theorum etc.) without actually looking at the structure of the language. They have an odd definition of success.'
Chomsky then digresses to making an analogy of the use of these techniques in modelling bee behaviour. He describes the difference between a bee scientist looking at individual behaviour versus taking video of many bees and modelling the aggregated behaviour. What you get are approximations of bee behaviour that are better than what the bee scientist gets. He then suggests that it is strange that when people write papers about this modelling they claim 'success' in their modelling and Chomsky knows of no other science where approximations are deemed as success. I am unclear how this relates to the work being done using statistical analysis and probability in linguistics which he referred earlier.
I would like to note that statistical analysis, Bayes Theorum etc. are very useful in a host of modelled systems and that there are many, many branches of science which rely on approximation of behaviour and complex systems.
Well, to be fair, as long as you don't fully comprehend and cannot describe a given phenomenon in depth (like bee behavior), statistical analysis is the only tool at your disposal. If, on the other hand, a phenomenon is understood in depth (like an apple falling from a tree), you can make accurate predictions on the outcome based on a theory. Which is, ultimately, also the fruit of observation and statistical analysis but considered as fully understood.
So based on this premise I don't understand Chomsky's criticism and dismissal of today's progress and methods employed.
Thankyou, one of the jobs of a scientist is to communicate science, and I feel that sometimes they forget this and unnecessarily intellectually grandstand.
His point is that predictive power alone doesn't make a theory. You can have perfect predictive power for a subset of possible events, yet no understanding of how and why things work the way they do.
I believe his problem is with the investigation of "what" and dismissal of the "why". Predicting bee behaviour using AI modelling can predict the what, but the deeper investigation of an individual bee in the group can give you the "why". I think it goes right down to Richard Feynman's famous division between knowledge and understanding; he believed that understanding was much more important than knowing. You can know what the swarm of bees are going to do but you have no understanding of why they behave that way.
thx, haha he tried to critique chomsky by framing the question so obscure, but failed ;( hahaha
Thanks for posting. Chomsky is such a brilliant man and it's amazing to think of just how long he has been a voice of reason.
He's a good lad Chomsky, isn't he - I like him too. I can imagine sitting round the fireside with him, talking all kinds of weird shit, and putting the world to rights lol :)
+Jack Stratif I work in machine learning. Chomsky theories were fun, but they were wrong and delayed advanced in natural language processing. He is showing his ignorance in this video.
As wikipedia puts it, "This was due both to the steady increase in computational power resulting from Moore's Law and the gradual lessening of the dominance of Chomskyan theories of linguistics (e.g. transformational grammar), whose theoretical underpinnings discouraged the sort of corpus linguistics that underlies the machine-learning approach to language processing."
+Ricardo Cruz
much agreed, chomsky has been stifling linquistics for decades;
not by his ideas, but by his adamancy;
his political values suffer the same.
+Ricardo Cruz Wikipedia's editorial process is very limited in it's scope, and often reflects the thinking of two or three people within a certain field, all of whom have the same bias regarding that field. It should never be quoted as if it's a neutral source.
Working in the field of machine learning is not really all too relevant. Algorithms only go so far as the ability to map Euclidean distance and create predictive co-variance models in the form of cluster boundaries all in the span of the workload in silicone processors the dominant means to compute in modern technology.
Presuppose that lingual coherence functioned outside the bounds of means (frequency) acquisition?
Wow. Yannis Varoufakis said roughly the same thing about the pure economics models with their lack of relation to real world economics, in a later discussion with Noam Chomsky on the state and mechanics of the European Union.
Another eye opener.
6:08 A ball will not roll down a frictionless plane, it will slide down without turning.
Yes, Dr. Chomsky stated that it couldn't happen in nature.
Took the words right out of my mouth, Steve.
Mayor Michael Bloomberg thank you for having me .
Usually Pinker is very articulate, but here he seems to stumble when asking his question. Is he nervous in front of Chomsky?
Eric Garr Yes. Yes, he is.
@@roryjamesclark7340 smarter, perhaps. Definelty more full of bs.
It's a bit similar to the Karate club teacher vs Miyagi relationship in Karate Kid movie (1984).
@@roryjamesclark7340 Maybe, but not in terms of intellectual production. Chomsky is other worldly when it comes to linguistics.
the beta trembles before the alpha.
Does Steven Pinker look nervous to you?
+KhasAdun he's in the presence of a linguistic legend.
+KhasAdun More like intimidated, perhaps, which is an emotion he's probably very used to feeling for good damn reason.
+Kierkegaard
Why do you say that?
Not a fan of Pinker, just curious...
+santos D Because Chomsky is a force of nature, and Pinker has expressed slight disagreements with him. Also, in academia it's generally very competitive, which doesn't mean C or P are jerks, but still, that sort of spirit that pervades academia will create this sort of feeling in someone "lower down the hierarchy." This is all obviously my very subjective opinion.
Kierkegaard
I've heard Pinker mention he has slight disagreements with Chomsky regarding linguistics, but whenever he explains what those disagreements are he just seems to be paraphrasing Chomsky.
Not really sure what he objects to, but linguistic can get extremely technical sometimes.
(not heard him talk about political disagreements, though I can see they exist)
That was a good fucking answer, and that’s what all this evolution has done for me, writing this on YT to add data to the algorithm
Emotionally, Chomsky's attitude feels right. Its hard to see brute-force computing approaches as being an appropriate measure for science, where theory and carefully designed experiment 'ought' to be the way advancement is made.
However on the longer view, I don't think enough credence is given to the influence of technology itself. Chomsky formulated generative grammar when the mathematical tools were available from computer science. Today, raw computing power give rise to big data approaches. Obviously their work strives to be an incredibly nuanced synthesis of linguistic evidence, brain studies, evolution etc. But there is also the sense that when a new technical approach arises, there is a tendency to push it to its limits, to harvest any low-hanging fruit, and see how things look from a new vantage point. And its my belief that in the end, its the new technique that advances things, more than the intellectual grand synthesis.
0:29 = the typical sideline on a Saturday afternoon at my grandpa's bacci court.
And I thought he was going to ask him what his favourite colour is
Chomsky is so bright it is alarming. How can he remember all this stuff!
I'd like to ask Chomsky what he thinks about vocal fry.
@@ProxyAuthenticationRequired lmao what!
?
Chomsky is the master of takedowns. I think he's basically saying, at the end, the "approximation of unanalyzed data" is novel when conceived as a sort of system without parameter or purpose. You can collect lots of randomized data that seemingly has no meaning, and from the perspective in which it is captured, after breaking it down into arbitrary units connected to nothing in particular, get some idea of what 'generally' will or is likely to happen in the future. But its purpose as collected data is simply to be analyzed. It has no bearing on anything meaningful to human beings.
So basically, is he just saying you can either observe a lot and make fairly accurate predictions without understanding the concepts (probabilistic method), or alternatively you can build a simplified model and improve understanding of underlying concept slowly, but get crappy results in the meantime(his method)?
RIP Marvin :'(
I don't suppose this whole conference is online in full anywhere, is it?
Noam's "novel notion of success" at 5:00 seems to be an argument in favor of science as _statistical inference about a physical model with many training examples_ as opposed to _controlled experiments on approximations of reality inside a laboratory_. For example, you can predict the location of the moon relative to the Earth at a given date and time by 1) applying the laws of motion under ideal circumstances, e.g. the moon occupies a plane with a constant z-coordinate that bisects the Earth; or, 2) record video of the night sky for several months, convert the video into quantitative data, then feed the data into a statistical data structure and let it learn.
+vau0807 "argument in favor of science as statistical inference about a physical model with many training examples"
I understand how this is manifest in your moon example. However, I don't understand why laboratory experiments work. Simply because you can't fit the moon in a lab? Or something else?
the whole thing science aims now is to create a "artificial intelligence", a construct capable of "conceiving" reality like we humans do it, a construct capable of taking a massive ammount of info, store it and analyze it by its own. And because it would be made in line with the laws of the physics and science, this construct would be able to do the science by itself. This construct would then be able to tell us the truths we claim beyond our reach. You already know what it sounds like.
Seeing this comment field, I feel like I've stumbled into a room full of angry people, and yet I cannot see any reason for anger. Why the hate here?
I think it's because a lot of the commenters sense, on an unconscious level, that Pinker and Chomsky are vastly more intelligent than they are...even as they claim that these men are spouting nonsense. That's the general feeling I get here.
People don't like his politics and so feel bound to dismiss the scientific work that gives him, and by extension his politics, credibility
You would think a linguist would be easier to listen to.
+jojomojojones to quote chomsky from elsewhere, "you need to be able to hold more than one thought in mind at once" ... which probably requires a fair bit of rigorous academic learning ... do you hold any graduate degrees jojo?
+Lance Jackson great point about grasping more than one thought at once.
+jojomojojones There was a time I wondered how such a brilliant humanitarian came to present such a monotonous tone....Now I realize how completely he strips the faces of power of all their appealing veneers with his facts and his tone is merciful in its acceptance of the frailty of human amorality.
jojomojojones Yes, one would likely believe such a thing prior to being exposed to the study of linguistics. Similarly, it seems obvious that we understand what leads people to make everyday decisions. Until you hear Daniel Kahnemann show you how obvious it isn't.
@@lancejackson9108 I think he has one in Marine Biology and the study of dolphins
Mr Chomsky, sharp as ever.
Is there anyway to get the entirety of this talk?
What did i just watch?
It's above your level :)
Above mine too
Yes, it could be used to predict but would it produce any understanding?
There may be things beyond our understanding, that must be taken into account. Better question would be - would making good predictive models cause some harm? I don't understand why have those people spent so much time criticizing probabilistic models? I mean, Pinker some decades, Chomsky whole centuries. :D :D lol ... but why?
Hmmm... you might be right...?
I think that's exactly the point Noam is trying to make. Those novel experiments sometimes has extremly specific hypothesis. The problem that arise is that the use of the "sucessful" studies are to rare or complex to teach us anything of value.
To my own limited kowledge (correct me if I'm wrong) neural networks might be an example of novel studies turned into very valuable theories over time. When it was presented, I think in the 80's/90's, we didn't have the computers to use it. But as time went by and computers today have became far more faster, neural netwroks has become a very interesting and more usefull tool.
But then againg this video was hard to follow and I'm not sure, soooo what ever (:
Noam looks like a gangsta here
Odessa
Where’s the link to the full talk?
what an epic fucking answer
Chomsky is in his late 80's in this video!
Reading the comments. the best way to understand something is to read something you don't like. Trite, but true.
When people are outraged by what you say - but they can't explain why - there's a good chance you're right. See angry sputtering comments below for examples.
MArvin Minsky kept quiet. He's on Web of Stories (RUclips) trashing Chomsky's whole project as essentially a waste of time
Translation: While solely using statistical analysis in machine learning has been shown to work, within a limited scope, it appears to be much more successful when integrated with other techniques.
WHY DOES SOUND LIKE HES ABOUT TO FUCKING CRY LMFAOOO
Flash! Chompsky (I know, I know) says a ball rolling down an inclined plane is a thing that never happens in nature. Huh? I better go tell my granddaughter whose favorite thing at the moment is rolling a ball down the inclined plane in the front of my daughter's house, ie., the driveway, that she is doing the impossible. I doubt she will believe me.
frictionless planes
Oh I was just being a snark. Because I revere the man I look for things to cavel about because I despise personality cults.
+Erg Budster even rarer than frictionless planes: someone admitting when they are wrong.
Pinker stumbles a bit because of nausea...he was with Chomsky, and that would make anyone sick.
Language: The most recent and most important language is the language of "Texting".
Textos is truly a language and must be considered as important, even More important than most of the tribal languages in Africa and the dialects spoken in many sub cultures on earth.
I like when he talks about things other than politics
amazing minds right here
In 2024, ai has come a long way
The math is already there, The brain uses statistics in form of stress. You can avoid math in your models only if you use premolded blocks.
How enginners do a basic lowpass filter to alter a reproduced sound? They add a capacitor in the wire to the speakers. The math is there, but you don't need it to make the filter work.
How do programmers the same filter: The sound records are not sulpted in solids, the sound waves are encoded. You need strong math (Fourier, I suppose) to transform the data before convert it to waves.
chatgpt says: this didn’t age well
Bravo Chomsky. He made fantastic efforts no to answer the question, and... he succeeded!!!
That was one of the most poorly worded question I have ever heard. It was basically Pinker trying to sound smart instead of smartly asking a question.
first off, about the question asked....huh?
i feel like Chomsky understood it but....i couldn't tell from his answer.
If bee scientists, through laborious experimentation and analysis are able to predict swarm behavior with 95% accuracy, and a machine-learning model has been built that can predict swarm behavior equally or better, what's a key difference?
The former results in _knowledge_ and _understanding_ (i.e., true science), the latter, simply information transmission. Taking a look around at our current culture, one can see how important the distinction is.
Chomsky , the Prophet of Human future.
Urghhh.........
If chomsky was the president during WW2, you would be speaking german right now
you may consider me an ignorant and explain me why you said that ...
Chomsky criticized America for not getting involved earlier you liar. If Chomsky was president millions of peoples lives would be saved and the unnecessary nukes and bombing of civilian cities across europe wouldnt have happened
they are not liars ... just idiots .
I'm really disappointed in Pinker here. That was incredibly convoluted and abstruse, and didn't need to be. Who's he trying to impress? Normally I'm impressed by how easily and clearly he presents material.
Mr Chomsky is too old
wheres the full video
I don't get this but question whether I should. Thanks.
6:35 Statistical analysis, unknown in the history of science? What about thermodynamics?
?? he means real success is creating models and theory that has not only predicting power but also are descriptive abstract tools, not only the first in a case by case manner, based on statistical analysis.
+claschxtreme isn't that affirming the consequent?
If theory A is true, then B prediction will be true.
B prediction is true.
Therefore, A.
Shouldn't theories first be developed with empirical data and then checked for productive power?
...'If theory A is true...' If you are referring to Theories in the Standard Model, _NO_ Theory can be be proved - only _disproved._
The approach to crunching enormous amounts of data using statistical methods and supercomputers to get deeper insights into the language faculty of humans, or any animal including Bees, has mostly been a failure and he explains why. And it is worth listening to his response again.
He also used an analogy as to why this approach in computational science if used in Physics would be like trying to understand and make predictions about the world by looking outside the window to make accurate predictions and provide insight into fundamental properties about the world. If your data set is large enough you might be able to make some predictions but that won't provide understanding of the forces like, gravity and electromagnetism which are at work. This is the point that Chomsky is making. Where analysis is used to provide insight into specific properties of language such as on word boundaries then some progress has been made.
What do we know, what can we show? As Chomsky points out on many questions about human nature and behaviour we know very little. As he points out these questions are very difficult.
Full vid: ruclips.net/video/JtbgghTqVOs/видео.html
Noam was 100% incorrect. He was so sure of his opinions. I know he is old now so reflecting upon that may not be possible, but maybe it can be used as a cautionary tale for others.
He still very much believes these views, even after the success of ChatGPT and many linguists would likewise argue he does so for good reason. Predictive text output does not in itself imply any undersatanding.
Here is his recent discussion on the subject: ruclips.net/video/axuGfh4UR9Q/видео.html
@@Michael-HammerschmidtNor does UG imply any understanding.
Yes, he sees the supposed failings in other methods and ignores the weaknesses in his own.
who asks the question, "ill let you complete the sentence" ? thats not a question
moron
I haven't a clue what they are talking about. which is quite frustrating.
I don't understand why science wouldn't be interested in finding paterns and predicting the world.
all of the smartest men in history were those not afraid to be wrong.
is that DR GOLDSTEINBERG?
Anyone know what he said.
Ha ha. I guess also clap when my tone suggests particular sincerity or urgency. If he explained in simple English, (I assume it's possible), would he lose popularity?
didn't understand the question, but what he said about novelty physics problem solving was embarrassingly wrong.
Fantastic
Ok, how is anything Chomsky said that complex? Bottom line, you can use statistics to predict what sound come next with a big sample, but it's better if you understood the language? Like duh?
I think there are some fan boys here giving him more credit than is warranted
The hair is a bit out of style no?
a wig?
I put this German sentence in Google Translate: "Der Frau gibt der Mann das Auto". This English sentence came out: "The Lord gives the man the car." I don't know what methods Google Translate uses, but that's a bogus translation.
+impCaesarAvg I would argue that your sentence is not "German as a language used by people" but "German grammar fantasy by a Besserwisser". If you put the Dativ in its proper place, google translates perfectly. "Der Herr" is wrong, but google "knows" and offers an alternative translation: The woman gives the man the car. Which is still wrong, but not "bogus". Anyway: You do not like g-translate? Wel, go find or do a better one. You will neither find a better one (for general purposes, as google is the best, proven time after time) nor be able to do a better one (for obvious reasons). Same with democracy: Worst form of gov., except all others that have been tried.
+mark rode Mir gefallen die Wagen nicht. ==> I did not like the car.
+impCaesarAvg Denn dein ist das Reich und die Kraft und die Herrlichkeit. -- For thine is the kingdom and the power and the glory. Not so bad. Because: Google uses an SBMT approach. Wikipedia. As the German who did the algorithms admits: results for German and English leave much to be desired. If one does not like it: Improve it, find a better one or - as both is out of our reach: I am glad that the best MT on earth is FREE. Frohe Weihnachten. It is a wonderful world. And pray that there´s intelligent life somewhere up in space.
+mark rode I guess MT is machine translation, but what is SB? I think, if there ever is decent machine translation, it will be based on chomskyan linguistics.
Merry Christmas!
+impCaesarAvg SB Statistics based MT. The linguistic approach in MT: "Tranfer" / "Interlanguage" had its time decades ago ... - I do agree that the future must bring a revival, as SBMT alone may not get much better than now. "gefallen" is usu. translated in a "to like"-construction. / "to appeal to" is MUCH rarer -so SBMT chooses "to like". Which leads to syntactical chaos, obviously. One should know ones limits and others´.
Why do I think Noam looks like Warren now ?
These guys are woke af
Stop saying woke
They're also officially lit, swole and fleek.
Yahya K Except Pinker. Pinker is poke AF.
Shadow Fox So is Chomsky choke?
Yahya K Yeah... he does :3
For all you idiots calling Noam an idiot for not understanding him, he's talking about different methods of linguistic optimization for AI/algorithms like that little CC button you see in the video so you can read what he articulates. It's quite comically meta in a way.
I just refuted some idiots on this "refuting idiots" channel.
I understand how my brain works, I poses one and have done for the last 68 years, and the 'expert' is me, academia is speculative innocent ignorance.
The issue is that statistics yields prediction without explanation. While Chomsky used computer detection of word boundaries in speech as his example, Google Translate is another application. Nothing surprising here: If you know something about the laws governing the behavior of language, you can get better predictions, and with fewer data points, then if you use only raw brute force. I think Chomsky gets thrashed because of his nutty Marxist politics more often than on the merits of what he says about language, his own field, by people who aren't linguists. That reduction hasn't proceeded as far in language as it has in physics doesn't alter his basic point, however.
Those little bottles of water are just daft. Whats the point?
The difference between me and Chomsky is that any one can understand what I am saying.
Pinker is asking if chomsky's theory will be of use in the future, because unlike the new theories (big data), it has no statistiks and propability in it. Chomsky answers that statistics and propabilities are too superficial and that you can't get understanding out of it (only statistically data), and that it is therefore not very usefull. Pinker framed his question in a weird way, but he wanted to kind of embarras Chomsky, because he thinks his theory is a failure. But Pinker embarrast himself.
The character and integrity of Chonsky is well displayed here. Pinker basically says "chomskys wrong because of all the fancy advances the charlatan scholarly class - would be media celebrities like ME PINKER have made." Listen to Chonsky ignore the insult of having to answer questions fro.the likes of Pinker in Chonskys field and notice his integrity in putting that nonsense aside and educating the viewer so superbly on the topic. I could not have had the self restraint or dignity myself. Heres the deal Pinkee attacks and makes a career of misrepresenting Chomky's political and scientific work. Pinker hitches his careerist ambitions of being a "linguistics or cognative scientist" having refuted Chomsky's work. This is hopeless nonsense. If you want a taste of the real Pinker - the pathology of his ambitions and narcissism - view his disgust using attack on Chomsky and his constant lying about Mr Chomsky and his work (chomsky is not "a Marxist?" Could have fooled me since Chomsky uses Marx"s work extensively in his public comments and obviously they are much o the the same page descriptively. Pinker the quaffed but quite unattractive media persona also says that Chomskys scientific contributions are revered because people are su h fans of his political work. Pinker is not a a scientist. He is a vicious charletan
To see the real Pinker in action view his comments when cho.sky isnt in the room at
ruclips.net/video/wxZ-NrCohGk/видео.html