Noam Chomsky: Language, Cognition, and Deep Learning | Artificial Intelligence (AI) Podcast


– The following is a
conversation with Noam Chomsky. He’s truly one of the
great minds of our time and is one of the most cited scholars in the history of our civilization. He has spent over 60 years at MIT and recently also joined
the University of Arizona where we met for this conversation, but it was at MIT about
four and 1/2 years ago when I first met Noam. My first few days there I remember getting into an elevator at Stata Center, pressing the button for
whatever floor, looking up and realizing it was
just me and Noam Chomsky riding the elevator, just me
and one of the seminal figures of linguistics, cognitive
science, philosophy, and political thought in the
past century if not ever. I tell that silly story
because I think life is made up of funny
little defining moments that you never forget for
reasons that may be too poetic to try and explain, that was one of mine. Noam has been an inspiration
to me and millions of others. It was truly an honor for me to sit down with him in Arizona. I traveled there just
for this conversation, and in a rare, heartbreaking moment after everything was set up and tested the camera was moved and accidentally the recording button was
pressed stopping the recording. So I have good audio of both
of us but no video of Noam, just a video of me and my
sleep deprived but excited face that I get to keep as a
reminder of my failures. Most people just listen
to this audio version for the podcast as opposed
to watching it on YouTube, but still it’s heartbreaking for me. I hope you understand and still enjoy this
conversation as much as I did. The depth of intellect that Noam showed and his willingness to truly listen to me, a silly looking Russian
in a suit was humbling and something I’m deeply grateful for. As some of you know, this
podcast is a side project for me where my main journey and dream is to build AI systems that
do some good for the world. This latter effort
takes up most of my time but for the moment has
been mostly private, but the former, the podcast
is something I put my heart and soul into and I hope you feel that even when I screw things up. I recently started doing ads at the end of the introduction. I’ll do one or two minutes
after introducing the episode and never any ads in the middle that break the flow of the conversation. I hope that works for you and doesn’t hurt the listening experience. This is the Artificial
Intelligence podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support it on Patreon, or simply
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inspire girls and boys to dream of engineering a better world. And now here’s my conversation
with Noam Chomsky. I apologize for the absurd
philosophical question, but if an alien species
were to visit Earth, do you think we would be able
to find a common language or protocol of communication with them? – [Noam] There are arguments
to the effect that we could. In fact, one of them was Marv Minsky’s. Back about 20 or 30 years ago he performed a brief experiment with a
student of his, Daniel Bobrow they essentially ran the
simplest possible Turing machines just free to see what would happen. And most of them crashed,
either got into an infinite loop or were stopped, the few that persisted essentially gave
something like arithmetic. And his conclusion from that was that if some alien species
developed higher intelligence they would at least have arithmetic. They would at least have what
the simplest computer would do and in fact he didn’t
know that at the time, but the core principles
of natural language are based on operations
which yield something like arithmetic in the limiting
case, in the minimal case. So it’s conceivable that
a mode of communication could be established based
on the core properties of human language and the
core properties of arithmetic which maybe are universally
shared so it’s conceivable. – [Lex] What is the
structure of that language, of language as an internal
system inside our mind versus an external
system as it’s expressed? – [Noam] It’s not an alternative. It’s two different concepts of language. – [Lex] Different. – [Noam] It’s a simple fact that there’s something
about you, a trait of yours, part of the organism you that determines that you’re talking English
and not Tagalog, let’s say. So there is an inner system. It determines the sound and meaning of the infinite number of
expressions of your language. It’s localized, it’s not in your foot obviously it’s in your brain. If you look more closely it’s
in specific configurations of your brain and that’s essentially like the internal
structure of your laptop. Whatever programs it has are in there. Now, one of the things
you can do with language, it’s a marginal thing in
fact is use it to externalize what’s in your head. I think most of your use
of language is thought, internal thought, but can do
what you and I are now doing. We can externalize it. Well, the set of things
that we’re externalizing are an external system, they’re
noises in the atmosphere, and you can call that language in some other sense of the word, but it’s not a set of alternatives. These are just different concepts. – [Lex] So how deep do the roots of language go in our brain? – Well–
– Our mind, is it yet another feature like vision? Or is it something more fundamental from which everything else
springs in the human mind? – [Noam] Well in a way it’s like vision. There’s something about
our genetic endowment that determines that we have a mammalian rather than an insect visual system. And there’s something
in our genetic endowment that determines that we have
a human language faculty. No other organism has
anything remotely similar. So in that sense it’s internal. Now, there is a long tradition
which I think is valid going back centuries to the
early scientific revolution at least that holds that language is the sort of the core of
human cognitive nature. It’s the source, it’s the
mode for constructing thoughts and expressing them and
that is what forms thought and it’s got fundamental
creative capacities. It’s free, independent,
unbounded and so on. And undoubtedly I think the basis for our creative capacities
and the other remarkable human capacities that lead
to the unique achievements and not so great
achievements of the species. – [Lex] The capacity to think and reason. Do you think that’s deeply
linked with language? Do you think the internal
language system is essentially the mechanism by which we
also reason internally? – [Noam] It is undoubtedly the
mechanism by which we reason. There may also be other,
there are undoubtedly other faculties involved in reasoning. We have a kind of scientific faculty. Nobody knows what it
is, but whatever it is that enables us to pursue
certain lines of endeavor and inquiry and to decide what makes sense and doesn’t make sense and
to achieve a certain degree of understanding in the
world that uses language but goes beyond it just as using
our capacity for arithmetic is not the same as having the capacity. – [Lex] The idea of capacity,
our biology, evolution, you’ve talked about it defining
essentially our capacity, our limit and our scope. Can you try to define
what limit and scope are, and the bigger question,
do you think it’s possible to find the limit of human cognition? – [Noam] Well that’s an
interesting question. It’s commonly believed,
most scientists believe that human intelligence can answer any question in principle. I think that’s a very strange belief. If we’re biological organisms
which are not angels then our capacities ought
to have scope and limits which are interrelated. – [Lex] Can you define those two terms? – [Noam] Well, let’s
take a concrete example. Your genetic endowment, it determines that you can have a
mammalian visual system and arms and legs and so on and therefore become a
rich, complex organism, but if you look at that
same genetic endowment it prevents you from
developing in other directions. There’s no kind of experience
which would yield the embryo to develop an insect visual system or to develop wings instead of arms. So the very endowment that
confers richness and complexity also sets bounds on what can be attained. Now I assume that our cognitive capacities are part of the organic world therefore they should
have the same properties. If they had no built-in
capacity to develop a rich and complex structure we
would understand nothing just as if your genetic endowment did not compel you to
develop arms and legs you would just be some kind
of a random ameboid creature with no structure at all
so I think it’s plausible to assume that there are limits, and I think we even have some
evidence as to what they are. So for example there’s a classic moment in the history of science
at the time of Newton. There was from Galileo to
Newton modern science developed on a fundamental assumption
which Newton also accepted, namely that the world, the entire universe is a mechanical object and
by mechanical they meant something like the kinds of artifacts that were being developed
by skilled artisans all over Europe, the
gears, levers, and so on. And their belief was, well the world is just a more complex variant of this. Newton to his astonishment
and distress proved that there are no machines, that there’s
interaction without contact. His contemporaries like
Leibniz and Huygens just dismissed this as
returning to the mysticism of the Neo-Scholastics and Newton agreed. He said, “It is totally absurd. “No person of any scientific intelligence “could ever accept this for a moment.” In fact, he spent the rest of his life trying to get around it somehow as did many other scientists. That was the very criterion
of intelligibility for say Galileo or Newton. Theory did not produce
an intelligible world unless you could duplicate it in a machine and he showed you can’t,
there are no machines, any. Finally after a long
struggle, took a long time scientists just accepted
this as common sense, but that’s a significant moment. That means they abandoned the search for an intelligible world
and the great philosophers of the time understood that very well. So for example, David Hume
in his encomium to Newton wrote that, who was the
greatest thinker ever and so on. He said that he unveiled
many of the secrets of nature but by showing the imperfections of the mechanical philosophy,
mechanical science he left us with, he showed
that there are mysteries which ever will remain, and
science just changed its goals. It abandoned the mysteries. It can’t solve it, they’ll put it aside. We only look for intelligible theories. Newton’s theories were intelligible it’s just what they described wasn’t. Well, Locke said the same thing. I think they’re basically right and if so that showed something about
the limits of human cognition. We cannot attain the goal
of understanding the world, of finding an intelligible world. This mechanical philosophy,
Galileo to Newton, there’s a good case that can be made that that’s our instinctive
conception of how things work. So if say infants are tested with things that if this moves and then this moves they kind of invent something
that must be invisible that’s in between them that’s
making them move and so on. – [Lex] Yeah, we like physical contact. Something about our brain seeks– – [Noam] Makes us want a world like then just like it wants a world that has regular geometric figures
so for example Descartes pointed this out that
if you have an infant who’s never seen a triangle
before and you draw a triangle the infant will see a distorted triangle not whatever crazy figure
it actually is, you know, three lines not coming quite together or one of them a little
bit curved and so on. We just impose a conception of the world in terms of perfect geometric objects. It’s now been shown that
it goes way beyond that, that if you show on a
tachistoscope, let’s say, a couple of lights
shining, you do it three or four times in a row
what people actually see is a rigid object in motion
not whatever’s there. We all know that from a
television set basically. – [Lex] So that gives us
hints of potential limits to our cognition?
– I think it does, but it’s a very contested view. If you do a poll among scientists
they’ll say impossible. We can understand anything. – [Lex] Let me ask and
give me a chance with this. So I just spent a day at a
company called Neuralink, and what they do is try
to design what’s called a brain machine, a brain
computer interface. So they try to just do thousands
of readings in the brain, be able to read what
the neurons are firing and then stimulate back, so two-way. Do you think their dream
is to expand the capacity of the brain to attain information, sort of increase the bandwidth at which we can search
Google kind of thing? Do you think our cognitive
capacity might be expanded, our linguistic capacity,
our ability to reason might be expanded by adding
a machine into the picture? – [Noam] It can be expanded
in a certain sense, but a sense that was known
thousands of years ago. A book expands your
cognitive capacity, okay, so this could expand it, too. – [Lex] But it’s not a
fundamental expansion. It’s not totally new
things could be understood. – [Noam] Well, nothing that goes beyond our native cognitive capacities just like you can’t turn the visual system into an insect system. – [Lex] Well, I mean
the thought is perhaps you can’t directly but you can map. – [Noam] You could be we know
that without this experiment you could map what a
bee sees and present it in a form so that we could follow it. In fact every bee scientist does that. – [Lex] Uh-huh, but you
don’t think there’s something greater than bees that we can map and then all of a sudden
discover something, be able to understand a quantum
world, quantum mechanics, be able to start to be able to make sense. – [Noam] You can, students at MIT study and understand quantum mechanics. – [Lex] (laughs) But they
always reduce it to the infant, the physical, I mean they
don’t really understand– – [Noam] Not physical,
that may be another area where there’s just a
limit to understanding. We understand the theories, but the world that it describes
doesn’t make any sense. So you know the experiment,
the Schrodinger’s cat for example, can understand the theory but as Schrodinger pointed out it’s not an intelligible world. One of the reasons why Einstein
was always very skeptical about quantum theory, he described himself as a classical realist
and wants intelligibility. – [Lex] He has something in
common with infants in that way. So back to linguistics,
if you could humor me, what are the most beautiful
or fascinating aspects of language or ideas in linguistics or cognitive science that you’ve seen in a lifetime of studying language and studying the human mind? – [Noam] Well, I think the
deepest property of language and puzzling property
that’s been discovered is what is sometimes called
structure dependence. We now understand it pretty well, but it was puzzling for a long time. I’ll give you a concrete example. So suppose you say, the
guy who fixed the car carefully packed his tools. That’s ambiguous, he could
fix the car carefully or carefully pack his tools. Now suppose you put carefully in front. Carefully the guy who fixed
the car packed his tools. Then it’s carefully packed,
not carefully fixed. And in fact you do that
even if it makes no sense. So suppose you say, carefully the guy who fixed the car is tall. You have to interpret it
as carefully he’s tall even though that doesn’t make any sense. And notice that that’s
a very puzzling fact because you’re relating carefully not to the linearly closest verb but to the linearly more remote verb. Linear closeness is a easy computation, but here you’re doing a much more, what looks like a more
complex computation. You’re doing something that’s taking you essentially to the more remote thing, it’s now if you look at the
actual structure of the sentence where the phrases are and so on turns out you’re picking out the
structurally closest thing, but the linearly more remote thing. But notice that what’s linear
is 100% of what you hear. You never hear of structure. So what you’re doing is and
instantly this is universal. All constructions, all languages and what we’re compelled
to do is carry out what looks like the
more complex computation on material that we never
hear and we ignore 100% of what we hear on the
simplest computation. And by now there’s even
a neural basis for this that’s somewhat understood,
and there’s good theories but none that explain why it’s true. That’s a deep insight
into the surprising nature of language with many consequences. – [Lex] Let me ask you about
a field of machine learning and deep learning, there’s
been a lot of progress in neural network-based machine learning in the recent decade. Of course, neural network
research goes back many decades. – [Noam] Yeah. – [Lex] What do you think are
the limits of deep learning, of neural network-based machine learning? – [Noam] Well, to give
a real answer to that you’d have to understand
the exact processes that are taking place, and
those are pretty opaque so it’s pretty hard to prove a theorem about what can be done
and what can’t be done. But I think it’s reasonably clear, I mean, putting technicalities aside what deep learning is doing
is taking huge numbers of examples and finding some patterns. Okay, that could be interesting
and in some areas it is but we have to ask here
a certain question. Is it engineering or is it science? Engineering in the sense of
just trying to build something that’s useful or science in the sense that it’s trying to understand
something about elements of the world so it takes a Google parser. We can ask that question, is it useful? Yeah, it’s pretty useful. I use Google Translator
so on engineering grounds it’s kinda worth having like a bulldozer. Does it tell you anything
about human language? Zero, nothing, and in
fact it’s very striking. From the very beginning it’s just totally remote from science so what is a Google parser doing? It’s taking an enormous text, let’s say The Wall Street
Journal corpus and asking, how close can we come to
getting the right description of every sentence in the corpus? Well, ever sentence in the corpus is essentially an experiment. Each sentence that you produce
is an experiment which is, am I a grammatical sentence? Now the answer is usually
yes so most of the stuff in the corpus is grammatical sentences, but now ask yourself, is there any science which takes random experiments
which are carried out for no reason whatsoever and tries to find out something from them? Like if you’re, say, a
chemistry PhD student you want to get a thesis can you say, well I’m just gonna do a
lot of, mix a lot of things together, no purpose, and
maybe I’ll find something. You’d be laughed out of the department. Science tries to find
critical experiments, ones that answer some
theoretical question. Doesn’t care about coverage
of millions of experiments. So it just begins by being
very remote from science and it continues like
that so the usual question that’s asked about, say, a Google parser is how well does it do, or some parser, how well does it do on a corpus? But there’s another
question that’s never asked. How well does it do on something that violates all the rules of language? So for example, take the
structure dependence case that I mentioned, suppose
there was a language in which you used linear
proximity as the mode of interpretation, these deep learning would work very easily on that. In fact, much more easily
than on an actual language. Is that a success? No, that’s a failure. From a scientific point
of view that’s a failure. It shows that we’re not discovering the nature of the system at all ’cause it does just as well or even better on things that violate the
structure of the system, and it goes on from there. It’s not an argument against doing it. It is useful to have devices like this. – [Lex] So yes, neural networks
are kind of approximators that look, there’s echoes of
the behavioral debates right, behavioralism.
– More than echoes. Many of the people in deep learning say they vindicated.
– (laughs) Yeah. – [Noam] Terry Sejnowski for
example in his recent book says this vindicates Skinnerian behaviors and it doesn’t have
anything to do with it. – [Lex] Yes, but I think there’s something actually fundamentally different
when the data set is huge, but your point is extremely well taken. But do you think we can learn, approximate that interesting, complex
structure of language with neural networks that will somehow help us understand the science? – [Noam] It’s possible,
I mean, you find patterns that you hadn’t noticed, let’s say. Could be, in fact it’s very
much like a kind of linguistics that’s done, what’s called
corpus linguistics when you, suppose you have some language
where all the speakers have died out but you have records. So you just look at the records and see what you can figure out from that. It’s much better to have actual speakers where you can do critical experiments, but if they’re all dead you can’t do them so you have to try to
see what you can find out from just looking at
the data that’s around. You can learn things. Anthropology is very much like that. You can’t do a critical experiment on what happened two million years ago so you’re kinda forced to
take what data’s around and see what you can figure out from it. Okay, it’s a serious study. – [Lex] So let me venture into
another whole body of work and philosophical question. You’ve said that evil in society
arises from institutions, not inherently from our nature. Do you think most human beings are good, they have good intent or
do most have the capacity for intentional evil that
depends on their upbringing, depends on their environment, on context? – [Noam] I wouldn’t say that they don’t arise from our nature. Anything we do arises from our nature. And the fact that we
have certain institutions and not others is one mode in which human nature
has expressed itself. But as far as we know, human nature could yield many different
kinds of institutions. The particular ones that have developed have to do with historical contingency, who conquered whom and that sort of thing, then they’re not rooted in our nature in the sense that they’re
essential to our nature so it’s commonly argued that
these days that something like market systems is
just part of our nature, but we know from a huge amount of evidence that that’s not true, there’s
all kinds of other structures. That’s a particular fact of
a moment of modern history. Others have argued that the
roots of classical liberalism actually argue that
what’s called sometimes an instinct for freedom, an instinct to be free of domination
by illegitimate authority is the core of our nature. That would be the opposite of this. And we don’t know, we just
know that human nature can accommodate both kinds. – [Lex] If you look back at your life, is there a moment in
your intellectual life or life in general that jumps from memory that brought you happiness that you would love to relive again? – [Noam] Sure, falling
in love, having children. – [Lex] What about, so
you have put forward into the world a lot of
incredible ideas in linguistics, in cognitive science, in terms of ideas that just excites you
when it first came to you that you love to relive those moments. – [Noam] Well, I mean,
when you make a discovery about something it’s exciting like say even the observation
of structure dependence and on from that the explanation for it, but the major things just
seem like common sense. So if you go back to, take your question about external and internal language. You go back to, say, the 1950s almost entirely language is
regarded as an external object, something outside the mind. It just seemed obvious
that that can’t be true. Like I said, there’s something
about you that determines you’re talking English
not Swahili or something. But that’s not really a discovery. That’s just an observation
of what’s transparent. You might say it’s kind of like the 17th century, the
beginnings of modern science 17th century, they came from being willing to be puzzled about things
that seemed obvious. So it seems obvious that a heavy
ball of lead’ll fall faster than a light ball of lead,
but Galileo was not impressed by the fact that it seemed obvious. so he wanted to know if it’s true He carried out experiments,
actually thought experiments never actually carried
them out which showed that it can’t be true, you know. And out of things like that,
observations of that kind, you know, why does a
ball fall to the ground instead of rising, let’s say? It seems obvious till you
start thinking about it ’cause why does steam rise, let’s say. And I think the beginnings
of modern linguistics roughly in the 50s are kind of like that, just being willing to be
puzzled about phenomena that looked from some
point of view obvious. And for example a kind of doctrine, almost official doctrine
of structural linguistics in the 50s was that languages
can differ from one another in arbitrary ways and
each one has to be studied on its own without any presuppositions and in fact there were
similar views among biologists about the nature of
organisms that each one’s, they’re so different when you look at them that you could be almost anything. Well in both domains it’s been learned that it’s very far from true. There are very narrow constraints on what could be an organism
or what could be a language. But these are, you know, that’s
just the nature of inquiry. – [Lex] Science in general, yeah, inquiry. So one of the peculiar things about us human beings is our mortality. Ernest Becker explored it. In general do you ponder
the value of mortality? Do you think about your own mortality? – [Noam] I used to when
I was about 12 years old. I wondered, I didn’t care
much about my own mortality, but I was worried about the
fact that if my consciousness disappeared would the
entire universe disappear. That was frightening. – [Lex] Did you ever find
an answer to that question? – [Noam] No, nobody’s
ever found an answer, but I stopped being bothered by it. It’s kind of like Woody
Allen in one of his films. You may recall he goes to
a shrink when he’s a child and the shrink asks him,
“What’s your problem?” He says, “I just learned that
the universe is expanding. “I can’t handle that.” – [Lex] (laughs) And
another absurd question is, what do you think is the
meaning of our existence here, our life on Earth, our
brief little moment in time? – [Noam] That’s something we
answer by our own activities. There’s no general answer. We determine what the meaning of it is. – [Lex] The action determine the meaning. – [Noam] Meaning in the
sense of significance not meaning in the sense that
chair means this, you know, but the significance of your
life is something you create. – Noam, thank you so
much for talking today. It was a huge honor, thank you so much. Thanks for listening to this
conversation with Noam Chomsky, and thank you to our
presenting sponsor Cash App. Download it, use code LexPodcast. You’ll get $10 and $10 will go to FIRST, a STEM education nonprofit
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hope to see you next time.

100 Replies to “Noam Chomsky: Language, Cognition, and Deep Learning | Artificial Intelligence (AI) Podcast”

  1. I really enjoyed this conversation with Noam. Here's the outline:
    0:00 – Introduction
    3:59 – Common language with an alien species
    5:46 – Structure of language
    7:18 – Roots of language in our brain
    8:51 – Language and thought
    9:44 – The limit of human cognition
    16:48 – Neuralink
    19:32 – Deepest property of language
    22:13 – Limits of deep learning
    28:01 – Good and evil
    29:52 – Memorable experiences
    33:29 – Mortality
    34:23 – Meaning of life

  2. Absolutely great interview! The meaning of life is to maximize the significance of your life within and without limitations you encounter. It is a challenge to express yourself creatively. There was a song in the late 1960s or early 1970s called "Express yourself", one line in that song was silly but yet meaningful: "It's not what you look like when you're doin what you're doin; It's what your doin when your doin what you look like you're doin!" So, therefor your failure to capture the video is meaningless because the verbal weight of the interview was where the gravity of the exercise existed.

  3. The best argument to read a book came out of arguing against the possibility that machines can fundamentally expand consciousness. I can't ignore how intuitive Chomsky's point is; I know without books my capacity for knowledge would be diminished to a fault. His reasoning has left me both validated and shocked. Logically, along with his knowledge of linguists, he described a limit to what A.I. can achieve. Though, the impact will be profound, A.I cannot compete with a book on some fronts. How strange that such a simple technology can be so good at doing that. I perceived Lex struggle with this, and maybe he will spend some years considering Chomsky's view and its implications if true.

  4. Have on Peter Joseph. He has a point of view worth people's time on the subject of A.I.'s capacity to solve economic inefficiencies and perhaps even save us all from ourselves.

  5. Chomsky's voice is expressive to the point that a lack of video in no way diminishes what he says. So, Lex, bitchslap yourself for the screwup, as that's what makes us learn, but rest assured that, with an icon like Noam, nothing was really lost.
    But kneel before the universal gods, and be grateful you had this opportunity.

  6. Lex remember that Jocko Willink would say that it’s ‘GOOD.’ that the video cut out, now Chomsky’s facial expression will only ever exist in one special place: in the memory of a future legend of technology and conversation.

  7. i majored in Linguistics at UC Santa Cruz my Linguistics professors were big on Noam Chomsky’s work in the field of Linguistics.
    A common language between humans and and aliens would be meditative thought. Dr. Steven Greer would be the one to ask about that. Dr. Steven Greer was a Vedic meditation teacher before becoming a traumatologist and later heading the Disclosure Project. his latest documentary is titled Unacknowledged and well worth watching. At the end there a video clip of a with a strange band around his head and seeming lifting a small ball into the air with his mind.
    https://youtu.be/NQKxTklSsPg

  8. Why not get into things that touches upon the political aspects of his life? Ask him to tell you about your wolves and sheep, the pros and cons of collectivism and so on. I feel that you're deliberately tip toeing around the questions that would be of most value to you for the sake of presenting a clean and clever structure.

  9. We want an interview from Constantinos Daskalakis. Also Christos Papadimitriou and Scott Aaronson ! 😀 Keep up the good work !

  10. Wow. I'm blown away you got Chomsky on here. He doesn't seem to wanna do podcasts.

    First a new Grimes release and now this?? This is a good fucking night.

  11. from one former teacher to another teacher, Lex. Always befriend the Alpha male or Alpha female.and the classroom will behave much better. oh, and don't get sick. R-1 probiotic yogurt by Meiji, works to prevent the flu. I've got an impaired immune system and can't get flu shots. in the past 16 years i've caught the flu maybe once. Amazing stuff.

  12. Thank you Lex for all of your time and effort pursuing these excellent conversations. We may never know the influence that you create by connecting us all to these profound thinkers. May all of your efforts be repaid 1000 fold.

  13. I just woke up. I fell asleep listening to this earlier. very relaxing 🎶👂 thank you for sharing. I'll watch again 🖤

  14. Listening to professor Chomsky talk with you is the highlight of my week! Thank you doctor Fridman!
    Defining intelligence as adaptability and exploitation does not limit the ways of thinking to our brain. Machines can think differently, but one of the few tools we have for developing them is to see how well they perform. All we are bound to do for now, is to come up with ideas and playgrounds to compare their performance. The ideas that persist through time, similar to the process of life, will be the alternative ways of thinking. This is part of what professor Chomsky calls Engineering in Deep Learning. A lot of what we know now was considered "Art" at its infancy, "Engineering" when it became transferable and widely-adopted, and then "Science" when it was reverse-engineered, and given philosophical and mathematical basis. Intelligence is by far the hardest thing to engineer, but this is our hope as AI scientists.

  15. My thinking is in words, my internal dialog that I hear and speak in my head. My thoughts originate and are motivated by my emotions and feelings. This part is deeper and doesn't use words. This all evolved from birth till now. I do not believe this can be done with a computer, quantum or not. The closest we can come is a simulation and that requires very strict limitations.

  16. Lmao you can not be serious. A hypothetical conversation about things you have no control/ influence over. Nothing more than over 25 mins of verbal masturbation….utter nonsense.

  17. Thank you Lex. Your depth of understanding, combined with your evident humility, is refreshing to say the least. 🙄

  18. I think it's clear from various aberrations in development – feral children, sequestered children, autistics, that language is learned, like walking is learned, like everything that makes us human, that separates us from the other mammalian species, is learned. Thought experiment – newborn is raised in a box to say age 6 or 7 with zero input other than the box, a minimal food delivery system and a minimal cleaning system, no human contact. He is let out of the box onto a city street. What will happen?

  19. ambiguity:
    1: ((the guy) who ((fixed the car) carefully) packed (his tools)
    2: ((the guy) who (fixed the car)) carefully (packed (his tools))
    no ambiguity:
    carefully [,] (the guy who fixed the car) packed (his tools)
    nonsense:
    carefully [,] (the guy who fixed the car) is (tall)

    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2205530

  20. 21:01, this grammar flaw is called "misplaced modifiers". I levelled up significantly after learning about those. It makes your writing crystal clear if you make sure it never contains such flaws that make sentences seem ok but are actually very difficult to quickly understand. The most basic example is something like "David smells bad". Does that mean his nose doesn't work good, or that he is emitting a foul odor? Care could be taken to avoid such confusion while reading.

  21. Lex, thank you so much for the thoughtful and incredibly well driven interview. Chomsky is undoubtedly one of the most brilliant minds of our time and has not only radically impacted the world of linguistics and politics but also expanded our understanding of the human experience as a whole.

  22. Noam Chompsky is a complete idiot for the following reason: he does not understand the difference between a poetically ironic point, and being correct by virtue of TESTING a hypothesis and observing a STATISTICALLY VALID set of data points that confirm the idea. He rarely makes any recommendations because HE KNOWS this will expose how vacuous his intellect is.

  23. 23:45. Does anyone have any commentary what Noam says : "Does it tell you anything about human language : Zero…Nothing" ?

    – Embedding spaces tell us something about the similarity of individual words.
    – Attention mechanisms tell us something about the importance of words in a sentence.
    – Ostensibly, a GAN makes judgments about the quality of observations, which is something akin to science.
    – Throw an LSTM at a letter-split corpus in a phonetic language, and you can form a probabilistic model of how many consecutive vowels or consonants might run together before humans get tongue-tied.

    Fair enough : we haven't applied semantic deconstruction, or put together a Chinese room thought experiment. But the words "Zero…Nothing" seem to be misplaced.

  24. (22:00) This is by design.
    And why God constructed the plan of salvation in a chaistic form. "The first shall be last."

  25. Hey Lex, great stuff. Do you think you would have a productive conversation that's relevant to your podcast with Professor Richard Dawkins? Thanks.

  26. Thank you, Lex, for being such a great chap. It's really great to see how you're putting yourself out there, and so fully into something. Thank you, you inspire me.

    Additionally, please have David Deutsch on to talk about The Fabric of Reality, and the Four Strands. He's brilliant, and the theorems he puts forward are brilliant, and I hope with utmost sincerity that you'll manage to make that conversation work. He's like a holistic Eric Weinstein. Truly brilliant. Again, Lex, thank you.

  27. "A silly looking Russian in a suit", LOL. We love you, Lex. Your podcast is such a great inspiration!
    Don't worry about the missing video, like you said, many of us consume it as a podcast (including me, for the most part).

  28. This was too short conversation, but it was very interesting nevertheless. The fact that video was lost did not changed its quality. Enjoyed every minute!

  29. thanks a lot for getting in such a famous linguist, especially one with such a deep knowledge of history / science at the same time! Also really appreciate the commitment to not interrupting the actual interview with ads.

  30. One of the great Gnomes that man. 🙂 If I ever get my set of balding greats, I can may consider myself one, if im lucky.

  31. 18:56 i agree. it doesn't make any sense. but it doesn't mean that the knowledge and capability to make it work is unattainable. it's heartbreaking to hear lex trying to make noam (who he look up to) understand 🙁

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