Dr. Lex Fridman PhD, is a scientist at MIT (Massachusetts Institute of
Technology), working on robotics, artificial intelligence, autonomous
vehicles and human-robot interactions. He is also the host of the Lex
Fridman Podcast where he holds conversations with academics,
entrepreneurs, athletes and creatives. Here we discuss humans, robots,
and the capacity they hold for friendship and love. Dr. Fridman also
shares with us his unique dream for a world where robots guide humans
to be the best versions of themselves, and his efforts to make that
dream a reality.
[bright music] -- Welcome to the "Huberman Lab Podcast," where we
discuss science and science-based tools for everyday life. I'm Andrew
Huberman, and I'm a Professor of Neurobiology and Ophthalmology at
Stanford School of Medicine. Today I have the pleasure of introducing
Dr. Lex Fridman as our guest on the "Huberman Lab Podcast." Dr.
Fridman is a researcher at MIT specializing in machine learning,
artificial intelligence and human robot interactions. I must say that
the conversation with Lex was without question, one of the most
fascinating conversations that I've ever had, not just in my career,
but in my lifetime. I knew that Lex worked on these topics. And I
think many of you are probably familiar with Lex and his interest in
these topics from his incredible podcast, the "Lex Fridman Podcast."
If you're not already watching that podcast, please subscribe to it.
It is absolutely fantastic. But in holding this conversation with Lex,
I realized something far more important. He revealed to us a bit of
his dream. His dream about humans and robots, about humans and
machines, and about how those interactions can change the way that we
perceive ourselves and that we interact with the world. We discuss
relationships of all kinds, relationships with animals, relationships
with friends, relationships with family and romantic relationships.
And we discuss relationships with the machines. Machines that move and
machines that don't move, and machines that come to understand us in
ways that we could never understand for ourselves, and how those
machines can educate us about ourselves. Before this conversation, I
had no concept of the ways in which machines could inform me or anyone
about themselves. By the end, I was absolutely taken with the idea,
and I'm still taken with the idea that interactions with machines have
a very particular kind, a kind that Lex understands and wants to bring
to the world, can not only transform the self, but may very well
transform humanity. So whether or not you're familiar with Dr. Lex
Fridman or not, I'm certain you're going to learn a tremendous amount
from him during the course of our discussion, and that it will
transform the way that you think about yourself and about the world.
Before we begin, I want to mention that this podcast is separate from
my teaching and research roles at Stanford. It is however part of my
desire and effort to bring zero cost to consumer information about
science and science-related tools to the general public. In keeping
with that theme, I'd like to thank the sponsors of today's podcast.
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now, my conversation with Dr. Lex Fridman. -- We meet again.
-- We meet again. Thanks so much for sitting down with me. I have a
question that I think is on a lot of people's minds or ought to be on
a lot of people's minds, because we hear these terms a lot these days,
but I think most people, including most scientists and including me
don't know really what is artificial intelligence, and how is it
different from things like machine learning and robotics? So, if you
would be so kind as to explain to us, what is artificial intelligence,
and what is machine learning? -- Well, I think that question is as
complicated and as fascinating as the question of, what is
intelligence? So, I think of artificial intelligence, first, as a big
philosophical thing. Pamela McCormick said AI was the ancient wish to
forge the gods, or was born as an ancient wish to forge the gods. So I
think at the big philosophical level, it's our longing to create other
intelligence systems. Perhaps systems more powerful than us. At the
more narrow level, I think it's also set of tools that are
computational mathematical tools to automate different tasks. And then
also it's our attempt to understand our own mind. So, build systems
that exhibit some intelligent behavior in order to understand what is
intelligence in our own selves. So all of those things are true. Of
course, what AI really means as a community, as a set of researchers
and engineers, it's a set of tools, a set of computational techniques
that allow you to solve various problems. There's a long history that
approaches the problem from different perspectives. What's always been
throughout one of the threads, one of the communities goes under the
flag of machine learning, which is emphasizing in the AI space, the
task of learning. How do you make a machine that knows very little in
the beginning, follow some kind of process and learns to become better
and better at a particular task? What's been most very effective in
the recent about 15 years is a set of techniques that fall under the
flag of deep learning that utilize neural networks. When your networks
are these fascinating things inspired by the structure of the human
brain, very loosely, but they have a, it's a network of these little
basic computational units called neurons, artificial neurons. And they
have, these architectures have an input and output. They know nothing
in the beginning, and their task with learning something interesting.
What that's something interesting is, usually involves a particular
task. There's a lot of ways to talk about this and break this down.
Like one of them is how much human supervision is required to teach
this thing. So supervised learning is broad category, is the neural
network knows nothing in the beginning and then it's given a bunch of
examples in computer vision that will be examples of cats, dogs, cars,
traffic signs, and then you're given the image and you're given the
ground truth of what's in that image. And when you get a large
database of such image examples where you know the truth, the neural
network is able to learn by example, that's called supervised
learning. There's a lot of fascinating questions within that, which
is, how do you provide the truth? When you given an image of a cat,
how do you provide to the computer that this image contains a cat? Do
you just say the entire image is a picture of a cat? Do you do what's
very commonly been done, which is a bounding box, you have a very
crude box around the cat's face saying, this is a cat? Do you do
semantic segmentation? Mind you, this is a 2D image of a cat. So it's
not, the computer knows nothing about our three-dimensional world, is
just looking at a set of pixels. So, semantic segmentation is drawing
a nice, very crisp outline around the cat and saying, that's a cat.
That's really difficult to provide that truth. And one of the
fundamental open questions in computer vision is, is that even a good
representation of the truth? Now, there's another contrasting set of
ideas that our attention they're overlapping is, well, it's used to be
called unsupervised learning. What's commonly now called self-
supervised learning. Which is trying to get less and less and less
human supervision into the task. So self-supervised learning is more,
it's been very successful in the domain of language model, natural
English processing, and now more and more as being successful in
computer vision task. And the idea there is, let the machine without
any ground-truth annotation just look at pictures on the internet, or
look at texts on the internet and try to learn something generalizable
about the ideas that are at the core of language or at the core of
vision. And based on that, we humans at its best like to call that
common sense. So with this, we have this giant base of knowledge on
top of which we build more sophisticated knowledge. We have this kind
of commonsense knowledge. And so the idea with self-supervised
learning is to build this commonsense knowledge about, what are the
fundamental visual ideas that make up a cat and a dog and all those
kinds of things without ever having human supervision? The dream there
is the, you just let an AI system that's self supervised run around
the internet for awhile, watch YouTube videos for millions and
millions of hours, and without any supervision be primed and ready to
actually learn with very few examples once the human is able to show
up. We think of children in this way, human children, is your parents
only give one or two examples to teach a concept. The dream with self-
supervised learning is that will be the same with machines. That they
would watch millions of hours of YouTube videos, and then come to a
human and be able to understand when the human shows them, this is a
cat. Like, remember this' a cat. They will understand that a cat is
not just the thing with pointy ears, or a cat is a thing that's
orange, or is furry, they'll see something more fundamental that we
humans might not actually be able to introspect and understand. Like,
if I asked you, what makes a cat versus a dog, you wouldn't probably
not be able to answer that, but if I showed you, brought to you a cat
and a dog, you'll be able to tell the difference. What are the ideas
that your brain uses to make that difference? That's the whole dream
with self-supervised learning, is it would be able to learn that on
its own. That set of commonsense knowledge, that's able to tell the
difference. And then there's like a lot of incredible uses of self-
supervised learning, very weirdly called self-play mechanism. That's
the mechanism behind the reinforcement learning successes of the
systems that won at Go, at, AlphaZero that won a chess. -- Oh, I
see. That play games? - [Lex] That play games. -- Got it. -- So
the idea of self-play is probably, applies to other domains than just
games. Is a system that just plays against itself. And this is
fascinating in all kinds of domains, but it knows nothing in the
beginning. And the whole idea is it creates a bunch of mutations of
itself and plays against those versions of itself. And the fascinating
thing is when you play against systems that are a little bit better
than you, you start to get better yourself. Like learning, that's how
learning happens. That's true for martial arts. It's true in a lot of
cases. Where you want to be interacting with systems that are just a
little better than you. And then through this process of interacting
with systems just a little better than you, you start following this
process where everybody starts getting better and better and better
and better until you are several orders of magnitude better than the
world champion in chess, for example. And it's fascinating because
it's like a runaway system. One of the most terrifying and exciting
things that David Silver, the creator of AlphaGo and AlphaZero, one of
the leaders of the team said, to me is a, they haven't found the
ceiling for AlphaZero. Meaning it could just arbitrarily keep
improving. Now, in the realm of chess, that doesn't matter to us. That
it's like, it just ran away with the game of chess. Like it's like
just so much better than humans. But the question is what, if you can
create that in the realm that does have a bigger, deeper effect on
human beings and societies, that can be a terrifying process. To me,
it's an exciting process if you supervise it correctly, if you inject,
if what's called value alignment, you make sure that the goals that
the AI is optimizing is aligned with human beings and human societies.
There's a lot of fascinating things to talk about within the specifics
of neural networks and all the problems that people are working on.
But I would say the really big, exciting one is self-supervised
learning. We're trying to get less and less human supervision, less
and less human supervision of neural networks. And also just a comment
and I'll shut up. -- No, please keep going. I'm learning. I have
questions, but I'm learning. So please keep going. -- So, to me
what's exciting is not the theory, it's always the application. One of
the most exciting applications of artificial intelligence,
specifically neural networks and machine learning is Tesla Autopilot.
So these are systems that are working in the real world. This isn't an
academic exercise. This is human lives at stake. This is safety-
critical. -- These are automated vehicles. Autonomous vehicles. -
Semi-autonomous. We want to be. -- Okay. -- We've gone through
wars on these topics, -- Semi-autonomous vehicles. -- Semi-
autonomous. So, even though it's called a FSD, Full Self-Driving, it
is currently not fully autonomous, meaning human supervision is
required. So, human is tasked with overseeing the systems. In fact,
liability-wise, the human is always responsible. This is a human
factor psychology question, which is fascinating. I'm fascinated by
the whole space, which is a whole 'nother space of human robot
interaction when AI systems and humans work together to accomplish
tasks. That dance to me is one of the smaller communities, but I think
it will be one of the most important open problems once they're
solved, is how the humans and robots dance together. To me, semi-
autonomous driving is one of those spaces. So for Elon, for example,
he doesn't see it that way, he sees semi-autonomous driving as a
stepping stone towards fully autonomous driving. Like, humans and
robots can't dance well together. Like, humans and humans dance and
robots and robots dance. Like, we need to, this is an engineering
problem, we need to design a perfect robot that solves this problem.
To me forever, maybe this is not the case with driving, but the world
is going to be full of problems with always humans and robots have to
interact, because I think robots will always be flawed, just like
humans are going to be flawed, are flawed. And that's what makes life
beautiful, that they're flawed. That's where learning happens at the
edge of your capabilities. So you always have to figure out, how can
flawed robots and flawed humans interact together such that they, like
the sum is bigger than the whole, as opposed to focusing on just
building the perfect robot? -- Mm-hmm. -- So that's one of the
most exciting applications I would say of artificial intelligence to
me is autonomous driving, the semi-autonomous driving. And that's a
really good example of machine learning because those systems are
constantly learning. And there's a process there that maybe I can
comment on, the, Andrej Karpathy who's the head of autopilot calls it
the data engine. And this process applies for a lot of machine
learning, which is you build a system that's pretty good at doing
stuff, you send it out into the real world, it starts doing the stuff
and then it runs into what are called edge cases, like failure cases,
where it screws up. We do this as kids. That you have- -- You do
this as adults. -- We do this as adults. Exactly. But we learn
really quickly. But the whole point, and this is the fascinating thing
about driving, is you realize there's millions of edge cases. There's
just like weird situations that you did not expect. And so the data
engine process is you collect those edge cases, and then you go back
to the drawing board and learn from them. And so you have to create
this data pipeline where all these cars, hundreds of thousands of cars
are driving around and something weird happens. And so whenever this
weird detector fires, it's another important concept, that piece of
data goes back to the mothership for the training, for the retraining
of the system. And through this data engine process, it keeps
improving and getting better and better and better and better. So
basically you send out a pretty clever AI systems out into the world
and let it find the edge cases, let it screw up just enough to figure
out where the edge cases are, and then go back and learn from them,
and then send out that new version and keep updating that version.
-- Is the updating done by humans? -- The annotation is done by
humans. The, so you have to, the weird examples come back, the edge
cases, and you have to label what actually happened in there. There's
also some mechanisms for automatically labeling, but mostly, I think
you always have to rely on humans to improve, to understand what's
happening in the weird cases. And then there's a lot of debate. And
this, the other thing, what is artificial intelligence? Which is a
bunch of smart people having very different opinions about what is
intelligence. So AI is basically a community of people who don't agree
on anything. -- And it seems to be the case. First of all, this is a
beautiful description of terms that I've heard many times among my
colleagues at Stanford, at meetings in the outside world. And there
are so many fascinating things. I have so many questions, but I do
want to ask one question about the culture of AI, because it does seem
to be a community where at least as an outsider, where it seems like
there's very little consensus about what the terms and the operational
definitions even mean. And there seems to be a lot of splitting
happening now of not just supervised and unsupervised learning, but
these sort of intermediate conditions where machines are autonomous,
but then go back for more instruction like kids go home from college
during the summer and get a little, moms still feeds them then
eventually they leave the nest kind of thing. Is there something in
particular about engineers, or about people in this realm of
engineering that you think lends itself to disagreement? -- Yeah, I
think, so, first of all, the more specific you get, the less
disagreement there is. So there's lot of disagreement about what is
artificial intelligence, but there's less disagreement about what is
machine learning and even less when you talk about active learning or
machine teaching or self-supervised learning. And then when you get
into like NLP language models or transformers, when you get into
specific neural network architectures, there's less and less and less
disagreement about those terms. So you might be hearing the
disagreement from the high-level terms, and that has to do with the
fact that engineering, especially when you're talking about
intelligence systems is a little bit of an art and a science. So the
art part is the thing that creates disagreements, because then you
start having disagreements about how easy or difficult the particular
problem is. For example, a lot of people disagree with Elon how
difficult the problem of autonomous driving is. And so, but nobody
knows. So there's a lot of disagreement about, what are the limits of
these techniques? And through that, the terminology also contains
within it the disagreements. But overall, I think it's also a young
science that also has to do with that. So like it's not just
engineering, it's that artificial intelligence truly is a large-scale
discipline, where it's thousands, tens of thousands, hundreds of
thousands of people working on it, huge amounts of money being made as
a very recent thing. So we're trying to figure out those terms. And,
of course, there's egos and personalities and a lot of fame to be
made. Like the term deep learning, for example, neural networks have
been around for many, many decades since the '60s, you can argue since
the '40s. So there was a rebranding of neural networks into the word,
deep learning, term, deep learning, that was part of the re-
invigoration of the field, but it's really the same exact thing. --
I didn't know that. I mean, I grew up in the age of neuroscience when
neural networks were discussed, computational neuroscience and
theoretical neuroscience, they had their own journals. It wasn't
actually taken terribly seriously by experimentalists until a few
years ago. I would say about five to seven years ago. Excellent
theoretical neuroscientist like Larry Abbott and other colleagues,
certainly at Stanford as well that people started paying attention to
computational methods. But these terms, neural networks, computational
methods, I actually didn't know that neural network works in deep
learning where those have now become kind of synonymous. -- No,
they're always the same thing. -- Interesting. It was, so. -- I'm
a neuroscientist and I didn't know that. -- So, well, because neural
networks probably means something else and neural science not
something else, but a little different flavor depending on the field.
And that's fascinating too, because neuroscience and AI people have
started working together and dancing a lot more in the recent, I would
say probably decade. -- Oh, machines are going into the brain. I
have a couple of questions, but one thing that I'm sort of fixated on
that I find incredibly interesting is this example you gave of playing
a game with a mutated version of yourself as a competitor.
-- Yeah. -- I find that incredibly interesting as a kind of a
parallel or a mirror for what happens when we try and learn as humans,
which is we generate repetitions of whatever it is we're trying to
learn, and we make errors. Occasionally we succeed. In a simple
example, for instance, of trying to throw bulls eyes on a dartboard.
-- Yeah. -- I'm going to have errors, errors, errors. I'll probably
miss the dartboard. And maybe occasionally, hit a bullseye. And I
don't know exactly what I just did, right? But then let's say I was
playing darts against a version of myself where I was wearing a visual
prism, like my visual, I had a visual defect, you learn certain things
in that mode as well. You're saying that a machine can sort of mutate
itself, does the mutation always cause a deficiency that it needs to
overcome? Because of mutations in biology sometimes give us super
powers, right? Occasionally, you'll get somebody who has better than
2020 vision, and they can see better than 99.9% of people out there.
So, when you talk about a machine playing a game against a mutated
version of itself, is the mutation always say what we call a negative
mutation, or an adaptive or a maladaptive mutation? -- No, you don't
know until you get, so, you mutate first and then figure out and they
compete against each other. -- So, you're evolving, the machine gets
to evolve itself in real time. -- Yeah. And I think of it, which
would be exciting if you could actually do with humans. It's not just.
So, usually you freeze a version of the system. So, really you take on
Andrew of yesterday and you make 10 clones of them. And then maybe you
mutate, maybe not. And then you do a bunch of competitions of the
Andrew of today, like you fight to the death, and who wins last. So, I
love that idea of like creating a bunch of clones of myself from like
from each of the day for the past year, and just seeing who's going to
be better at like podcasting or science, or picking up chicks at a bar
or I don't know, or competing in Jujitsu. That's the one way to do it,
I mean, a lot of Lexes would have to die for that process, but that's
essentially what happens, is in reinforcement learning through the
self-play mechanisms, it's a graveyard of systems that didn't do that
well. And the surviving, the good ones survive. -- Do you think
that, I mean, Darwin's Theory of Evolution might have worked in some
sense in this way, but at the population level. I mean, you get a
bunch of birds with different shaped beaks and some birds have the
shaped beak that allows them to get the seeds. I mean, is a trivially
simple example of Darwinian in evolution, but I think it's correct
even though it's not exhaustive. Is what you're referring to? You
essentially that normally this is done between members of a different
species, lots of different members of species have different traits
and some get selected for, but you could actually create multiple
versions of yourself with different traits. -- So, with, I should
probably have said this, but perhaps it's implied with machine
learning, with reinforcement learning through these processes. One of
the big requirements, is to have an objective function, a loss
function, a utility function, those are all different terms for the
same thing, is there's a like any equation that says what's good, and
then you're trying to optimize that equation. So, there's a clear goal
for these systems. -- Because it's a game, like with chess, there's
a goal. -- But for anything. Anything you want machine learning to
solve, there needs to be an objective function. In machine learning,
it's usually called Loss Function, that you're optimizing. The
interesting thing about evolution, it's complicated of course, but the
goal also seems to be evolving. Like it's a, I guess, adaptation to
the environment, is the goal, but it's unclear that you can convert
that always. It's like survival of the fittest. It's unclear what the
fittest is. In machine learning, the starting point, and this is like
what human ingenuity provides, is that fitness function of what's good
and what's bad, which it lets you know which of the systems is going
to win. So, you need to have a equation like that. One of the
fascinating things about humans, is we figure out objective functions
for ourselves. Like it's the meaning of life, like why the hell are we
here? And a machine currently has to have a hard-coded statement about
why. -- It has to have a meaning of- -- Yeah. -- Artificial
intelligence-based life. -- Right. It can't. So, like there's a lot
of interesting explorations about that function being more about
curiosity, about learning new things and all that kind of stuff, but
it's still hard coded. If you want a machine to be able to be good at
stuff, it has to be given very clear statements of what good at stuff
means. That's one of the challenges of artificial intelligence, is you
have to formalize the, in order to solve a problem, you have to
formalize it and you have to provide both like the full sensory
information, you have to be very clear about what is the data that's
being collected, and you have to also be clear about the objective
function. What is the goal that you're trying to reach? And that's a
very difficult thing for artificial intelligence.
-- I love that you mentioned curiosity, I am sure this definition
falls short in many ways, but I define curiosity as a strong interest
in knowing something, but without an attachment to the outcome. It's
sort of a, it could be a random search, but there's not really an
emotional attachment, it's really just a desire to discover and unveil
what's there without hoping it's a gold coin under a rock, you're just
looking under rocks. Is that more or less how the, within machine
learning, it sounds like there are elements of reward prediction and
rewards. The machine has to know when it's done the right thing. So,
can you make machines that are curious, or are the sorts of machines
that you are describing, curious by design? -- Yeah, curiosity is a
kind of a symptom, not the goal. So, what happens, is one of the big
trade-offs in reinforcement learning, is this exploration versus
exploitation. So, when you know very little, it pays off to explore a
lot, even suboptimal, like even trajectories that seem like they're
not going to lead anywhere, that's called exploration. The smarter and
smarter and smarter you get, the more emphasis you put on
exploitation, meaning you take the best solution, you take the best
path. Now, through that process, the exploration can look like
curiosity by us humans, but it's really just trying to get out of the
local optimal, the thing it's already discovered. From an AI
perspective, it's always looking to optimize the objective function,
it derives, and we can talk about the slot more, but in terms of the
tools of machine learning today, it derives no pleasure from just the
curiosity of like, I don't know, discovery. -- So, there's no
dopamine for machine learning. - There's no dopamine. -- There's no
reward, system chemical, or I guess electronic-reward system. --
That said, if you look at machine learning literature and
reinforcement learning literature, that will use, like deep mind, we
use terms like dopamine, we're constantly trying to use the human
brain to inspire totally new solutions to these problems. So, they'll
think like, how does dopamine function in the human brain, and how can
it lead to more interesting ways to discover optimal solutions? But
ultimately currently, there has to be a formal objective function.
Now, you could argue the humans also has a set of objective functions
we try and optimize, we're just not able to introspect them. --
Yeah, we don't actually know what we're looking for and seeking and
doing. -- Well, like Lisa Feldman Barrett who we spoken with at
least on Instagram, I hope you- -- I met her through you, yeah. --
Yeah, I hope you actually have are on this podcast. -- Yes, she's
terrific. -- So, she has a very, it has to do with homeostasis like
that. Basically, there's a very dumb objective function that the brain
is trying to optimize, like to keep like body temperature the same.
Like there's a very dom kind of optimization function happening. And
then what we humans do with our fancy consciousness and cognitive
abilities, is we tell stories to ourselves so we can have nice
podcasts, but really it's the brain trying to maintain a, just like
healthy state, I guess. That's fascinating. I also see the human
brain, and I hope artificial intelligence systems, as not just systems
that solve problems, or optimize a goal, but are also storytellers. I
think there's a power to telling stories. We tell stories to each
other, that's what communication is. Like when you're alone, that's
when you solve problems, that's when it makes sense to talk about
solving problems. But when you're a community, the capability to
communicate, tell stories, share ideas in such a way that those ideas
are stable over a long period of time, that's like, that's being a
charismatic storyteller. And I think both humans are very good at
this. Arguably, I would argue that's why we are who we are, is we're
great storytellers. And then AI I hope will also become that. So, it's
not just about being able to solve problems with a clear objective
function, it's afterwards, be able to tell like a way better, like
make up a way better story about why you did something, or why you
failed.
-- So, you think that robots or, and/or machines of some sort are
going to start telling human stories? -- Well, definitely. So, the
technical field for that is called Explainable AI, Explainable
Artificial Intelligence, is trying to figure out how you get the AI
system to explain to us humans why the hell it failed, or why it
succeeded, or there's a lot of different sort of versions of this, or
to visualize how it understands the world. That's a really difficult
problem, especially with neural networks that are famously opaque,
that we don't understand in many cases, why a particular neural
network does what it does so well, and to try to figure out where it's
going to fail, that requires the AI to explain itself. There's a huge
amount of money, like there's a huge amount of money in this,
especially from government funding and so on. Because if you want to
deploy AI systems in the real world, we humans at least, want to ask
it a question like, why the hell did you do that? Like in a dark way,
why did you just kill that person, right? Like if a car ran over a
person, we want to understand why that happened. And now again, we're
sometimes very unfair to AI systems because we humans can often not
explain why very well. But that's the field of Explainable AI that
people are very interested in because the more and more we rely on AI
systems, like the Twitter recommender system, that AI algorithm
that's, I would say impacting elections, perhaps starting wars, or at
least military conflict, that algorithm, we want to ask that
algorithm, first of all, do you know what the hell you're doing? Do
you understand the society-level effects you're having? And can you
explain the possible other trajectories? Like we would have that kind
of conversation with a human, we want to be able to do that with an
AI. And in my own personal level, I think it would be nice to talk to
AI systems for stupid stuff, like robots when they fail to- -- Why'd
you fall down the stairs? -- Yeah. But not an engineering question,
but almost like an endearing question, like I'm looking for, if I fell
and you and I were hanging out, I don't think you need an explanation
exactly what were the dynamics, like what was the under actuated
system problem here? Like what was the texture of the floor? Or so on.
Or like, what was the- -- No, I want to know what you're thinking.
-- That, or you might joke about like, you're drunk again, go home, or
something, like there could be humor in it, that's an opportunity.
Like storytelling, isn't just explanation of what happened, it's
something that makes people laugh, it makes people fall in love, it
makes people dream, and understand things in a way that poetry makes
people understand things as opposed to a rigorous log of where every
sensor was, where every actuator was. -- I mean, I find this
incredible because one of the hallmarks of severe autism spectrum
disorders is, a report of experience from the autistic person that is
very much a catalog of action steps. It's like, how do you feel today?
And they'll say, well, I got up and I did this, and then I did this,
and I did this. And it's not at all the way that a person who doesn't
have autism spectrum disorder would respond. And the way you describe
these machines has so much humanism, or so much of a human and
biological element, but I realized that we were talking about
machines.
I want to make sure that I understand if there's a distinction between
a machine that learns, a machine with artificial intelligence and a
robot. Like at what point does a machine become a robot? So, if I have
a ballpoint pen, I'm assuming I wouldn't call that a robot, but if my
ballpoint pen can come to me when I moved to the opposite side of the
table, if it moves by whatever mechanism, at that point, does it
become a robot? -- Okay, there's 1 million ways to explore this
question. It's a fascinating one. So, first of all, there's a question
of what is life? Like how do you know something as a living form and
not? And it's to the question of when does sort of a, maybe a cold
computational system becomes a, or already loading these words with a
lot of meaning, robot and machine, So, one, I think movement is
important, but that's a kind of a boring idea that a robot is just a
machine that's able to act in the world. So, one artificial
intelligence could be both just the thinking thing, which I think is
what machine learning is, and also the acting thing, which is what we
usually think about robots. So, robots are the things that have a
perception system that's able to take in the world however you define
the world, is able to think and learn and do whatever the hell it does
inside, and then act on the world. So, that's the difference between
maybe an AI system learning machine and a robot, it's something that's
able, a robot is something that's able to perceive the world and act
in the world. -- So, it could be through language or sound, or it
could be through movement or both. -- Yeah. And I think it could
also be in the digital space as long as there's a aspect of entity
that's inside the machine and a world that's outside the machine. And
there's a sense in which the machine is sensing that world and acting
in it. -- So, we could, for instance, there could be a version of a
robot, according to the definition that I think you're providing,
where the robot, where I go to sleep at night and this robot goes and
forges for information that it thinks I want to see loaded onto my
desktop in the morning. There was no movement of that machine, there
was no language, but it essentially, has movement in cyberspace. --
Yeah, there's a distinction that I think is important in that there's
an element of it being an entity, whether it's in the digital or the
physical space. So, when you have something like Alexa in your home,
most of the speech recognition, most of what Alexa is doing, is
constantly being sent back to the mothership. When Alexa is there on
its own, that's to me, a robot, when it's there interacting with the
world. When it's simply a finger of the main mothership, then the
Alexa is not a robot, then it's just an interaction device, then may
be the main Amazon Alexa AI, big, big system is the robot. So, that's
important because there's some element, to us humans, I think, where
we want there to be an entity, whether in the digital or the physical
space, that's where ideas of consciousness come in and all those kinds
of things that we project our understanding of what it means to be a
being. And so, to take that further, when does a machine become a
robot, I think there's a special moment.
There's a special moment in a person's life and in a robot's life
where it surprises you. I think surprise is a really powerful thing,
where you know how the thing works and yet it surprises you, that's a
magical moment for us humans. So, whether it's a chess-playing program
that does something that you haven't seen before, that makes people
smile like, huh, those moments happen with AlphaZero for the first
time in chess playing, where grand masters were really surprised by a
move. They didn't understand the move and then they studied and
studied and then they understood it. But that moment of surprise,
that's for grandmasters in chess. I find that moment of surprise
really powerful, really magical in just everyday life. -- Because it
supersedes the human brain in that moment? -- So, it's not
supersedes, like outperforms, but surprises you in a positive sense.
Like I didn't think he could do that, I didn't think that you had that
in you. And I think that moment is a big transition for a robot from a
moment of being a servant that accomplishes a particular task with
some level of accuracy, with some rate of failure, to an entity, a
being that's struggling just like you are in this world. And that's a
really important moment that I think you're not going to find many
people in the AI community that talk like I just did. I'm not speaking
like some philosopher or some hippie, I'm speaking from purely
engineering perspective. I think it's really important for robots to
become entities and explore that as a real engineering problem, as
opposed to everybody treats robots in the robotics community, they
don't even call them or he or she, they don't give them, try to avoid
giving them names, they've really want to see like a system, like a
servant. They see it as a servant that's trying to accomplish a task.
To me, and don't think I'm just romanticizing the notion, I think it's
a being, it's a currently perhaps a dumb being, but in the long arc of
history, humans are pretty dumb beings too, so- -- I would agree
with that statement. [Andrew laughing] -- So, I tend to really want
to explore this treating robots really as entities, yeah. So, like
anthropomorphization, which is the sort of the act of looking at a
inanimate object and projecting onto it life-like features, I think
robotics generally sees that as a negative, I see it as a superpower.
Like that, we need to use that. -- Well, I'm struck by how that
really grabs onto the relationship between human and machine, or human
and robot. So, I guess the simple question is, and I think you've
already told us the answer, but does interacting with a robot change
you?
In other words, do we develop relationships to robots? -- Yeah, I
definitely think so. I think the moment you see a robot or AI systems
as more than just servants but entities, they begin to change you, in
just like good friends do, just like relationships just to other
humans. I think for that, you have to have certain aspects of that
interaction. Like the robot's ability to say no, to have its own sense
of identity, to have its own set of goals, that's not constantly
serving you, but instead, trying to understand the world and do that
dance of understanding through communication with you. So, I
definitely think there's a, I mean, I have a lot of thoughts about
this as you may know, and that's at the core of my life-long dream
actually of what I want to do, which is I believe that most people
have a notion of loneliness in them that we haven't discovered, that
we haven't explored, I should say. And I see AI systems as helping us
explore that so that we can become better humans, better people
towards each other. So, I think that connection between human and AI,
human and robot, is not only possible, but will help us understand
ourselves in ways that are like several orders of magnitude deeper
than we ever could have imagined. I tend to believe that [sighing]
well, I have very wild levels of belief in terms of how impactful that
will be, right?
-- So, when I think about human relationships, I don't always break
them down into variables, but we could explore a few of those
variables and see how they map to human-robot relationships. One is
just time, right? If you spend zero time with another person at all in
cyberspace or on the phone or in person, you essentially have no
relationship to them. If you spend a lot of time, you have a
relationship, this is obvious. But I guess one variable would be time,
how much time you spend with the other entity, robot or human. The
other would be wins and successes. You enjoy successes together. I'll
give a absolutely trivial example this in a moment, but the other
would be failures. When you struggle with somebody, whether or not you
struggle between one another, you disagree, like I was really struck
by the fact that you said that robot saying no, I've never thought
about a robot saying no to me, but there it is. -- I look forward to
you being one of the first people I send this robots to. -- So do I.
So, there's struggle. When you struggle with somebody, you grow
closer. Sometimes the struggles are imposed between those two people,
so called trauma bonding, they call it in the whole psychology
literature and pop psychology literature. But in any case, I can
imagine. So, time successes together, struggle together, and then just
peaceful time, hanging out at home, watching movies, waking up near
one another, here, we're breaking down the elements of relationships
of any kind. So, do you think that these elements apply to robot-human
relationships? And if so, then I could see how, if the robot has its
own entity and has some autonomy in terms of how it reacts you, it's
not just there just to serve you, it's not just a servant, it actually
has opinions, and can tell you when maybe your thinking is flawed, or
your actions are flawed. -- It can also leave. -- It could also
leave. So, I've never conceptualized robot-human interactions this
way. So, tell me more about how this might look. Are we thinking about
a human-appearing robot? I know you and I have both had intense
relationships to our, we have separate dogs obviously, but to animals,
it sounds a lot like human-animal interaction. So, what is the ideal
human-robot relationship? -- So, there's a lot to be said here, but
you actually pinpointed one of the big, big first steps, which is this
idea of time. And it's a huge limitation in machine-learning community
currently. Now we're back to like the actual details. Life-long
learning is a problem space that focuses on how AI systems can learn
over a long period of time. What's currently most machine learning
systems are not able to do, is to all of the things you've listed
under time, the successes, the failures, or just chilling together
watching movies, AI systems are not able to do that, which is all the
beautiful, magical moments that I believe are the days filled with,
they're not able to keep track of those together with you. - 'Cause
they can't move with you and be with you. -- No, no, like literally
we don't have the techniques to do the learning, the actual learning
of containing those moments. Current machine-learning systems are
really focused on understanding the world in the following way, it's
more like the perception system, like looking around, understand like
what's in the scene. That there's a bunch of people sitting down, that
there is cameras and microphones, that there's a table, understand
that. But the fact that we shared this moment of talking today, and
still remember that for like next time you're doing something,
remember that this moment happened. We don't know how to do that
technique-wise. This is what I'm hoping to innovate on as I think it's
a very, very important component of what it means to create a deeper
relationship, that sharing of moments together. -- Could you post a
photo of you in the robot, like selfie with robot and the robot sees
that image and recognizes that was time spent, there were smiles, or
there were tears- -- Yeah. -- And create some sort of metric of
emotional depth in the relationship and update its behavior? -- So.
-- Could it... It texts you in the middle of the night and say, why
haven't you texted me back? -- Well, yes, all of those things, but
we can dig into that. But I think that time element, forget everything
else, just sharing moments together, that changes everything. I
believe that changes everything. Now, there's specific things that are
more in terms of systems that I can explain you. It's more technical
and probably a little bit offline, 'cause I have kind of wild ideas
how that can revolutionize social networks and operating systems. But
the point is that element alone, forget all the other things we're
talking about like emotions, saying no, all that, just remembering
sharing moments together would change everything. We don't currently
have systems that share moments together. Like even just you and your
fridge, just all those times, you went late at night and ate thing you
shouldn't have eaten, that was a secret moment you have with your
refrigerator. You shared that moment, that darkness or that beautiful
moment where you were just like heartbroken for some reason, you're
eating that ice cream or whatever, that's a special moment. And that
refrigerator was there for you, and the fact that it missed the
opportunity to remember that is tragic. And once it does remember
that, I think you're going to be very attached to the refrigerator.
You're going to go through some hell with that refrigerator. Most of
us have, like in the developed world, have weird relationships with
food, right? So, you can go through some deep moments of trauma and
triumph with food, and at the core of that, is the refrigerator. So, a
smart refrigerator, I believe would change society. Not just the
refrigerator, but these ideas in the systems all around us. So, I just
want to comment on how powerful that idea of time is. And then there's
a bunch of elements of actual interaction of allowing you as a human
to feel like you're being heard. Truly heard, truly understood, that
we human, like deep friendship is like that, I think, but there's
still an element of selfishness, there's still an element of not
really being able to understand another human. And a lot of the times
when you're going through trauma together, through difficult times and
through successes, you actually starting to get that inkling of
understanding of each other, but I think that could be done more
aggressively, more efficiently. Like if you think of a great
therapist, I think I've never actually been to a therapist, but I'm a
believer I used to want to be a psychiatrist. -- Do Russians go to
therapists? -- No, they don't. They don't. And if they do, the
therapist don't live to tell the story. I do believe in talk therapy,
which friendship is to me, is it's talk therapy, or like you don't
even necessarily need to talk [laughing] it's like just connecting
through in the space of ideas and the space of experiences. And I
think there's a lot of ideas of how to make AI systems to be able to
ask the right questions and truly hear another human. This is what we
try to do with podcasting, right? I think there's ways to do that with
AI. But above all else, just remembering the collection of moments
that make up the day, the week, the months, I think you maybe have
some of this as well. Some of my closest friends still are the friends
from high school. That's time, we've been through a bunch of together,
and that like we're very different people. But just the fact that
we've been through that, and we remember those moments, and those
moments somehow create a depth of connection like nothing else, like
you and your refrigerator. -- I love that because my graduate
advisor, she unfortunately, she passed away, but when she passed away,
somebody said at her at her memorial all these amazing things she had
done, et cetera. And then her kids got up there, and she had young
children and that I knew as when she was pregnant with them. And so,
it was really, you're even now I can feel like your heart gets heavy,
thinking about this, they're going to grow up without their mother.
And it was really amazing, very strong young girls, and now the young
women. And what they said was incredible, they said what they really
appreciated most about their mother, who was an amazing person, is all
the unstructured time they spent together. -- Mm-hmm. -- So, it
wasn't the trips to the zoo, it wasn't she woke up at five in the
morning and drove us to school. She did all those things too. She had
two hour commute in each direction, it was incredible, ran a lab, et
cetera, but it was the unstructured time. So, on the passing of their
mother, that's what they remembered was that the biggest give and what
bonded them to her, was all the time where they just kind of hung out.
And the way you describe the relationship to a refrigerator is so, I
want to say human-like, but I'm almost reluctant to say that. Because
what I'm realizing as we're talking, is that what we think of as
human-like might actually be the lower form of relationship. There may
be relationships that are far better than the sorts of relationships
that we can conceive in our minds right now based on what these
machine relationship interactions could teach us. Do I have that
right? -- Yeah, I think so. I think there's no reason to see
machines as somehow incapable of teaching us something that's deeply
human. I don't think humans have a monopoly on that. I think we
understand ourselves very poorly and we need to have the kind of
prompting from a machine. And definitely part of that, is just
remembering the moments. I think the unstructured time together, I
wonder if it's quite so unstructured. That's like calling this podcast
on structured time. -- Maybe what they meant, was it wasn't a big
outing, there was no specific goal, but a goal was created through the
lack of a goal. Like we would just hang out and then you start
playing, thumb war, and you end up playing thumb war for an hour. So,
it's the structure emerges from lack of structure. -- No, but the
thing is the moments, there's something about those times that creates
special moments, and I think those could be optimized for. I think we
think of like a big outing as, I don't know, going to Six Flags or
something, or some big, the Grand Canyon, or go into some, I don't
know, I think we would need to, we don't quite yet understand, as
humans, what creates magical moments. I think it's possible to
optimize a lot of those things. And perhaps like podcasting is helping
people discover that, like maybe the thing we want to optimize for
isn't necessarily like some sexy, like quick clips, maybe what we
want, is long-form authenticity. -- Depth. -- Depth. So, we were
trying to figure that out, certainly from a deep connection between
humans and humans and NAS systems, I think long conversations, or long
periods of communication over a series of moments like my new,
perhaps, seemingly insignificant to the big ones, the big successes,
the big failures, those are all just stitching those together and
talking throughout. I think that's the formula for a really, really
deep connection. That from like a very specific engineering
perspective, is I think a fascinating open problem that has been
really worked on very much. And for me, from a, if I have the guts
and, I mean there's a lot of things to say, but one of it is guts, is
I'll build a startup around it.
-- So, let's talk about this startup and let's talk about the dream.
You mentioned this dream before in our previous conversations, always
as little hints dropped here and there. Just for anyone listening,
there's never been an offline conversation about this dream, I'm not
privy to anything, except what Lex says now. And I realized that
there's no way to capture the full essence of a dream in any kind of
verbal statement in a way that captures all of it. But what is this
dream that you've referred to now several times when we've sat down
together and talked on the phone? Maybe it's this company, maybe it's
something distinct. If you feel comfortable, it'd be great if you
could share a little bit about what that is. - Sure. So, the way
people express long-term vision, I've noticed is quite different. Like
Elon is an example of somebody who can very crisply say exactly what
the goal is. Also has to do with the fact that problems he's solving
have nothing to do with humans. So, my long-term vision is a little
bit more difficult to express in words, I've noticed, as I've tried,
it could be my brain's failure, but there's a way to sneak up to it.
So, let me just say a few things. Early on in life and also in the
recent years, I've interacted with a few robots where I understood
there's magic there. And that magic could be shared by millions if
it's brought to light. When I first met Spot from Boston Dynamics, I
realized there's magic there that nobody else is seeing. -- Is the
dog. -- The dog, sorry. The Spot is the four-legged robot from
Boston Dynamics. Some people might have seen it, it's this yellow dog.
And sometimes in life, you just notice something that just grabs you.
And I believe that this is something that this magic is something that
could be in every single device in the world. The way that I think
maybe Steve Jobs thought about the personal computer, laws didn't
think about the personal computer this way, but Steve did. Which is
like, he thought that the personal computer should be as thin as a
sheet of paper and everybody should have one, and this idea, I think
it is heartbreaking that we're getting, the world is being filled up
with machines that are soulless. And I think every one of them can
have that same magic. One of the things that also inspired me in terms
of a startup, is that magic can engineered much easier than I thought.
That's my intuition with everything I've ever built and worked on. So,
the dream is to add a bit of that magic in every single computing
system in the world. So, the way that Windows Operating System for a
long time was the primary operating system everybody interacted with,
they built apps on top of it. I think this is something that should be
as a layer, it's almost as an operating system in every device that
humans interacted with in the world. Now, what that actually looks
like, the actual dream when I was officially a kid, it didn't have
this concrete form of a business, it had more of a dream of exploring
your own loneliness by interacting with machines, robots. This deep
connection between humans and robots was always a dream. And so, for
me, I'd love to see a world where there's every home as a robot, and
not a robot that washes the dishes, or a sex robot, or I don't know,
think of any kind of activity the robot can do, but more like a
companion. -- A family member. -- A family member, the way a dog
is. -- Mm-hmm. -- But a dog that's able to speak your language
too. So, not just connect the way a dog does by looking at you and
looking away and almost like smiling with its soul in that kind of
way, but also to actually understand what the hell, like, why are you
so excited about the successes? Like understand the details,
understand the traumas. And that, I just think [sighing] that has
always filled me with excitement that I could, with artificial
intelligence, bring joy to a lot of people. More recently, I've been
more and more heartbroken to see the kind of division, derision, even
hate that's boiling up on the internet through social networks. And I
thought this kind of mechanism is exactly applicable in the context of
social networks as well. So, it's an operating system that serves as
your guide on the internet. One of the biggest problems with YouTube
and social networks currently, is they're optimizing for engagement. I
think if you create AI systems that know each individual person,
you're able to optimize for long-term growth for a long-term
happiness. -- Of the individual, or- -- Of the individual, of the
individual. And there's a lot of other things to say, which is in
order for AI systems to learn everything about you, they need to
collect, they need to just like you and I when we talk offline, we're
collecting data about each others secrets about each other, the same
way AI has to do that. And that allows you to, and that requires you
to rethink ideas of ownership of data. I think each individual should
own all of their data and very easily be able to leave just like AI
systems can leave, humans can disappear and delete all of their data
in a moment's notice. Which is actually better than we humans can do,
is once we load the data into each other, it's there. I think it's
very important to be both, give people complete control over their
data in order to establish trust that they can trust you. And the
second part of trust is transparency. Whenever the data is used to
make it very clear what is being used for. And not clear in a lawyerly
legal sense, but clear in a way that people really understand what
it's used for. I believe when people have the ability to delete all
their data and walk away and know how the data is being used, I think
they'll stay. -- The possibility of a clean breakup, is actually
what will keep people together. -- Yeah, I think so. I think,
exactly. I think a happy marriage acquires the ability to divorce
easily without the divorce industrial complex or whatever. Things
currently going on and then there's so much money to be made from
lawyers and divorce. But yeah, the ability to leave is what enables
love, I think. -- It's interesting. I've heard the phrase from a
semi-cynical friend, that marriage is the leading cause of divorce,
but now we've heard that divorce, or the possibility of divorce could
be the leading cause of marriage. -- Of a happy marriage. -- Good
point. -- Of a happy marriage. So, yeah. So, there's a lot of
details there, but the big dream is that connection between AI system
and a human. And I haven't. There's so much fear about artificial
intelligence systems and about robots that I haven't quite found the
right words to express that vision because the vision I have, it's not
like some naive, delusional vision of like technology is going to save
everybody, it's I really do just have a positive view of ways AI
systems can help humans explore themselves. -- I love that
positivity and I agree that the stance everything is doomed is equally
bad to say that everything's going to turn out all right, there has to
be a dedicated effort. And clearly, you're thinking about what that
dedicated effort would look like. You mentioned two aspects to this
dream [clears throat] and I want to make sure that I understand where
they connect if they do, or if they are independent streams. One was
this hypothetical robot family member, or some other form of robot
that would allow people to experience the kind of delight that you
experienced many times, and that you would like the world to be able
to have, and it's such a beautiful idea of this give.
And the other is social media or social network platforms that really
serve individuals and their best selves and their happiness and their
growth. Is there crossover between those, or are these two parallel
dreams? -- It's 100% of the same thing. It's difficult to kind of
explain without going through details, but maybe one easy way to
explain the way I think about social networks, is to create an AI
system that's yours. It's not like Amazon Alexa that's centralized,
you own the data, it's like your little friend that becomes your
representative on Twitter that helps you find things that will make
you feel good, that will also challenge your thinking to make you
grow, but not get to that, not let you get lost in the negative spiral
of dopamine, that gets you to be angry, or most just get you to be not
open to learning. And so, that little representative is optimizing
your long-term health. And I believe that that is not only good for
human beings, it's also good for business. I think longterm, you can
make a lot of money by challenging this idea that the only way to make
money, is maximizing engagement. And one of the things that people
disagree with me on, is they think Twitter's always going to win. Like
maximizing engagement is always going to win, I don't think so. I
think people have woken up now to understanding that, like they don't
always feel good, the ones who are on Twitter a lot, that they don't
always feel good at the end of the week. -- I would love feedback
from whatever this creature, whatever, I don't know what to call it,
as to maybe at the end of the week, it would automatically unfollow
some of the people that I follow because it realized through some
really smart data about how I was feeling inside, or how I was
sleeping, or something that, I don't know, that just wasn't good for
me. But it might also put things and people in front of me that I
ought to see, is that kind of a sliver of what this look like? --
The whole point, because of the interaction, because of sharing the
moments and learning a lot about you, you're now able to understand
what interactions led you to become a better version of yourself. Like
the person you yourself are happy with. This isn't, if you're into
flat earth and you feel very good about it, that you believe that
earth is flat, like the idea that you should sensor that is
ridiculous. If it makes you feel good and you becoming the best
version of yourself, I think you should be getting as much flat earth
as possible. Now, it's also good to challenge your ideas, but not
because the centralized committee decided, but because you tell to the
system that you like challenging your ideas, I think all of us do. And
then, which actually YouTube doesn't do that well, once you go down
the flat-earth rabbit hole, that's all you're going to see. It's nice
to get some really powerful communicators to argue against flat earth.
And it's nice to see that for you, and potentially, at least long-term
to expand your horizons, maybe the earth is not flat. But if you
continue to live your whole life thinking the earth is flat, I think,
and you're being a good father or son or daughter, and like you're
being the best version of yourself and you're happy with yourself, I
think the earth is flat. So, like I think this kind of idea, and I'm
just using that kind of silly, ridiculous example because I don't like
the idea of centralized forces controlling what you can and can't see,
but I also don't like this idea of like not censoring anything.
Because that's always the biggest problem with that, is this there's a
central decider, I think you yourself can decide what you want to see
and not, and it's good to have a companion that reminds you that you
felt last time you did this, or you felt good last time you did this.
-- Man, I feel like in every good story, there's a guide or a
companion that flies out, or forges a little bit further, a little bit
differently and brings back information that helps us, or at least
tries to steer us in the right direction. -- So, yeah, that's
exactly what I'm thinking and what I've been working on. I should
mention as a bunch of difficulties here, you see me up and down a
little bit recently. So, there's technically a lot of challenges here.
Just like with a lot of technologies, and the reason I'm talking about
it on a podcast comfortably as opposed to working in secret, is it's
really hard and maybe it's time has not come. And that's something you
have to constantly struggle with in terms of like entrepreneurially as
a startup, like I've also mentioned to you, maybe offline, I really
don't care about money, I don't care about business success, all those
kinds of things.
So, it's a difficult decision to make, how much of your time do you
want to go all in here and give everything to this? It's a big roll
the dice. Because I've also realized that's working on some of these
problems, both with the robotics and the technical side in terms of
the machine-learning system that I'm describing, it's lonely, it's
really lonely. Because both on a personal level and a technical level.
So, on the technical level, I'm surrounded by people that kind of
doubt me, which I think all entrepreneurs go through. And they doubt
you in the following sense, they know how difficult it is. Like the
people that the colleagues of mine, they know how difficult life-long
learning is, they also know how difficult it is to build a system like
this, to build the competitive social network. And in general, there's
a kind of a loneliness to just working on something on your own for
long periods of time. And you start to doubt whether, given that you
don't have a track record of success, like that's a big one. But when
you look in the mirror, especially when you're young, but I still have
that, I'm most things, you look in the mirror, it's like, and you have
these big dreams, how do you know you're actually as smart as you
think you are? Like how do you know you're going to be able to
accomplish this dream? You have this ambition. -- You sort of don't,
but you're kind of pulling on a string hoping that there's a bigger
ball of yarn. -- Yeah. [Andrew laughing] But you have this kind of
intuition. I think I pride myself in knowing what I'm good at, because
the reason I have that intuition, is 'cause I think I'm very good at
knowing all the things I suck at, which is basically everything. So,
like whenever I notice like, wait a minute, I'm kind of good at this,
which is very rare for me. I think like that, that might be a ball of
yarn worth pulling at. And the thing with in terms of engineering
systems that are able to interact with humans, I think I'm very good
at that. And because we talk about podcasting and so on, I don't know
if I'm very good at podcasts. -- You're very good at podcasting,
right? -- But I certainly don't, I think maybe it is compelling for
people to watch a kindhearted idiot struggle with this form, maybe
that's what's compelling. But in terms of like actual being a good
engineer of human-robot interaction systems, I think I'm good. But
it's hard to know until you do it, and then the world keeps telling
you you're not, and it's full of doll, it's really hard. And I've been
struggling with that recently, it's kind of a fascinating struggle.
But then that's where the Goggins thing comes in, is like, aside from
the state-hard motherfucker, is the, like whenever you're struggling,
that's a good sign that if you keep going, that you're going to be
alone in the success, right? -- Well, in your case, however, I
agree. And actually David had a post recently that I thought was among
his many brilliant posts, was one of the more brilliant about how he
talked about this myth of the light at the end of the tunnel. And
instead, what he replaced that myth with, was a concept that
eventually, your eyes adapt to the dark. That the tunnel, it's not
about a light at the end, that it's really about adapting to the dark
of the tunnel. It's very Goggins- -- I love him so much. -- Yeah.
You got share a lot in common knowing you both a bit, share a lot in
common. But in this loneliness and the pursuit of this dream, it seems
to me, it has a certain component to it that is extremely valuable,
which is that the loneliness itself could serve as a driver to build
the companion for the journey. -- Well, I'm very deeply aware of
that. So, like some people can make, 'cause I talk about love a lot, I
really love everything in this world, but I also love humans,
friendship and romantic, like even the cheesy stuff, just- -- You
like romantic movies? -- Yeah, not those, not necessarily. So, well,
I got so much from Rogan about like, was it the Tango scene from
"Scent of a Woman," but I find like there's nothing better than a
woman in a red dress, just like the classy- -- You should move to
Argentina my friend.
My father's Argentine, and you know what he said when I went on your
podcast for the first time? He said, he dresses well. Because in
Argentina, the men go to a wedding or a party or something, in the
U.S., by halfway through the night, 10 minutes in the night, all the
jackets are off. -- Yeah. -- It looks like everyone's undressing
for the party they just got dressed up for. And he said, you know, I
liked the way he dresses. And then when I started, he was talking
about you. And then when I started my podcast, he said, why don't you
wear a real suit like your friend Lex? [laughing] -- I remember
that. -- No, you can't.
But let's talk about this pursuit just a bit more, because I think
what you're talking about, is building a, not just a solution for
loneliness, but you've alluded to the loneliness as itself, an
important thing. And I think you're right. I think within people,
there is like caverns of faults and shame, but also just the desire to
have resonance, to be seen and heard. And I don't even know that it's
seen and heard through language. But these reservoirs of loneliness, I
think, well, they're interesting, maybe you could comment a little bit
about it. Because just as often as you talk about love, I haven't
quantified it, but it seems that you talk about this loneliness, and
maybe you just if you're willing, you'll share a little bit more about
that, and what that feels like now in the pursuit of building this
robot-human relationship. And you've been, let me be direct, you've
been spending a lot of time on building a robot-human relationship,
where's that at? -- Oh, in terms of business, in terms of systems?
-- No, I'm talking about a specific robot. -- Oh [laughing] so,
okay, I should mention a few things. So, one, is there's a startup
with an idea where I hope millions of people can use. And then there's
my own personal like almost like Frankenstein explorations with
particular robots. So, I'm very fascinated with the legged robots in
my own, private sounds like dark, but like in of one experiments to
see if I can recreate the magic. And that's been, I have a lot of
really good already perception systems and control systems that are
able to communicate affection in a dog-like fashion. So, I'm in a
really good place there. The stumbling blocks, which also have been
part of my sadness recently, is that I also have to work with robotics
companies that I gave so much of my heart, soul and love and
appreciation towards Boston Dynamics, but Boston Dynamics has also, as
a company, it has to make a lot of money and they have marketing
teams. And they're like looking at this silly Russian kid in a suit
and tie, it's like, what's he trying to do with all this love and
robot interaction and dancing and so on? So, there was a, I think
let's say for now, it's like, when you break up with a girlfriend or
something, right now, we decided to part ways on this particular
thing. They're huge supporters of mine, they're huge fans, but on this
particular thing, Boston Dynamics is not focusing on, or interested in
human-robot interaction. In fact, their whole business currently, is
keep the robot as far away from humans as possible because it's an in
the industrial setting where it's doing monitoring in dangerous
environments. It's almost like a remote security camera, essentially
is its application. To me, I thought it's still, even in those
applications, exceptionally useful for the robot to be able to
perceive humans, like see humans and to be able to, in a big map,
localize where those humans are and have human intention. For example,
like this, I did this a lot of work with pedestrians, for a robot to
be able to anticipate what the how the human is doing, like where it's
walking. The humans are not ballistics object, just because you're
walking this way one moment, it doesn't mean you'll keep walking that
direction, you have to infer a lot of signals, especially with the
head movement and the eye movement. And so, I thought that's super
interesting to explore, but they didn't feel that. So, I'll be working
with a few other robotics companies that are much more open to that
kind of stuff, and they're super excited and fans of mine. And
hopefully, Boston Dynamics, my first love, like getting back with an
ex-girlfriend, will come around. But so, the algorithmically, it's
basically a done there. The rest, is actually getting some of these
companies to work with. And then there's, for people who'd worked with
robots know that one thing is to write software that works, and the
other is to have a real machine that actually works. And it breaks
down all kinds of different ways that are fascinating. And so, there's
a big challenge there. But that's almost, it may sound a little bit
confusing in the context of our previous discussion because the
previous discussion was more about the big dream, how I hoped to have
millions of people enjoy this moment of magic. This current discussion
about a robot, is something I personally really enjoy, just brings me
happiness, I really try to do now everything that just brings me joy,
I maximize that 'cause robots are awesome. But two, given my like
little bit growing platform, I want to use the opportunity to educate
people. Like robots are cool. And if I think they're cool, I hope be
able to communicate why they're cool to others. So, this little robot
experiment is a little bit of research project too, there's a couple
of publications with MIT folks around that. But the other is just to
make some cool videos and explain to people how they actually work.
And as opposed to people being scared of robots, they could still be
scared, but also excited, like see the dark side, the beautiful side,
the magic of what it means to bring, for a machine to become a robot.
I want to inspire people with that. But that's less, it's interesting
because I think the big impact in terms of the dream does not have to
do with embodied AI. So, it does not need to have a body. I think the
refrigerator's enough, that for an AI system just to have a voice and
to hear you, that's enough for loneliness. The embodiment is just-
-- By embodiment, you mean the physical structure. -- Physical
instantiation of intelligence. So, it's a legged robot, or even just a
thing. I have a few other of humanoid robot, a little humanoid robot
maybe I'll keep them on the table, is like walks around, or even just
like a mobile platform they can just like, turn around and look at
you, it's like we mentioned with the pen. Something that moves and can
look at you, it's like that Butter Robot that asks, what is my
purpose? That is really, it's almost like art. There's something about
a physical entity that moves around, that's able to look at you and
interact with you, that makes you wonder what it means to be human. It
like challenges you to think, if that thing looks like he has
consciousness, what the hell am I? And I like that feeling, I think
that's really useful for us, it's humbling for us humans. But that's
less about research, it certainly less about business and more about
exploring our own selves, and challenging others to think like, to
think about what makes them human. -- I love this desire to share
the delight of an interaction with a robot. And as you describe it, I
actually find myself starting to crave that because we all have those
elements from childhood where, or from adulthood, where we experience
something, we want other people to feel that.
And I think that you're right, I think a lot of people are scared of
AI, I think a lot of people are scared of robots. My only experience,
and of a robotic-like thing is my Roomba Vacuum, where it goes about,
actually, it was pretty good at picking up Costello's hair when he was
shed and I was grateful for it. But then when I was on a call or
something, and it would get caught on a wire or something, I would
find myself getting upset with the Roomba in that moment, I'm like,
what are you doing? And obviously it's just doing what it does. But
that's a kind of mostly positive, but slightly negative interaction.
But what you're describing, it has so much more richness and layers of
detail that I can only imagine what those relationships are like. --
Well, there's a few, just a quick comment. So, I've had, they're
currently in Boston and I have a bunch of Roombas from iRobot. And I
did this experiment- -- Wait, how many Roombas? [Lex laughing] It
sounds like a fleet of Roombas. -- Yeah. So, it's probably seven or
eight, yeah. -- Well, it's a lot of Roombas. This place is very
clean. -- Well, so, this, I'm kind of waiting, this is the place
we're currently in Austin, is way larger than I need. But I basically
got it to make sure I have room for robots. -- So, you have these
seven or so Roombas, you deploy all seven at once? -- Oh, no, I do
different experience with them, different experiments with them. So,
one of the things I want to mention, is this is a, I think there was a
YouTube video that inspired me to try this, is I got them to scream in
pain and moan in pain whenever they were kicked or contacted. And I
did that experiment to see how I would feel. I meant to do like a
YouTube video on it, but then it just seemed very cruel. -- Did any
Roomba rights activists come at you? -- Like I think if I released
that video, I think it's going to make me look insane, which I know
people know I'm already insane- -- Now, you have to release the
video. [Lex laughing] -- Sure. Well, I think maybe if I
contextualize it by showing other robots like to show why this is
fascinating, because ultimately, I felt like there were human almost
immediately. And that display of pain was what did that. -- Giving
them a voice. -- Giving them a voice, especially a voice of dislike,
of pain. -- I have to connect you to my friend Eddie Chang, he
studied speech and language, he's a neurosurgeon, and we're life-long
friends. He studied speech and language, but he describes some of
these more primitive, visceral vocalizations, cries, groans, moans of
delight, other sounds as well, use your imagination, as such powerful
rudders for the other, for the emotions of other people. And so, I
find it fascinating, I can't wait to see this video. So, is the video
available online? -- No, I haven't recorded it, I just hit a bunch
of Roombas that are able to scream in pain in my Boston place. [Andrew
laughing] So, like people already- -- Next podcast episode with Lex,
maybe we'll have that one, who knows? -- So, the thing is like
people, I've noticed because I talk so much about love and it's really
who I am, I think they want to, to a lot of people, seems like there's
there got to be a dark person in there somewhere. And I thought if I
release videos of Roombas screaming and they're like, yep, yep, that
guy's definitely insane. -- What about like shouts of glee and
delight, you could do that too, right? -- Well, I don't know how to,
to me, delight is quiet, right? -- You're a Russian. Americans are
much louder than Russians. -- Yeah. - Yeah. -- Yeah. But like I
don't, unless you're talking about like, I don't know how you would
have sexual relationships with the Roomba. -- Well, I wasn't
necessarily saying a sexual delight, but- -- Trust me, I tried. I'm
just kidding, that's a joke, internet. Okay [giggles] but I was
fascinated in the psychology of how little it took. 'Cause you
mentioned you had a negative relationship with a Roomba. -- Well,
I'd find that mostly, I took it for granted. -- Yeah. -- It just
served me, it collected Costello's hair. And then when it would do
something I didn't like, I would get upset with it. So, that's not a
good relationship, it was taken for granted and I would get upset and
then I'd park it again, and I just like you're in the corner. --
Yeah. -- But there's a way to frame it being quite dumb as almost
cute. You're almost connecting with it for its dumbness. And I think
that's artificial intelligence problem. - [Andrew] It's interesting.
-- I think flaws should be feature, not a bug. -- So, along the
lines of this, the different sorts of relationships that one could
have with robots, and the fear, but also some of the positive
relationships that one could have, there's so much dimensionality,
there's so much to explore.
But power dynamics in relationships are very interesting, because the
obvious ones, the unsophisticated view of this, is one, there's a
master and a servant, right? But there's also manipulation, there's
benevolent manipulation, children do this with parents, puppies do
this. Puppies turn their head and look cute and maybe give out a
little noise, kids coup and parents always think that they're doing
this because they love the parent, but in many ways, studies show that
those coups are ways to extract the sorts of behaviors and expressions
from the parent that they want. The child doesn't know it's doing
this, it's completely subconscious, but it's benevolent manipulation.
So, there's one version of fear of robots that I hear a lot about that
I think most people can relate to where the robots take over and they
become the masters and we become the servants. But there could be
another version that in certain communities that I'm certainly not a
part of, but they call topping from the bottom, where the robot is
actually manipulating you into doing things, but you are under the
belief that you are in charge, but actually they're in charge. And so,
I think that's one that if we could explore that for a second, you
could imagine it wouldn't necessarily be bad, although it could lead
to bad things. The reason I want to explore this, is I think people
always default to the extreme, like the robots take over and we're in
little jail cells and they're out having fun and ruling the universe.
What sorts of manipulation can a robot potentially carry out, good or
bad? -- Yeah. Just so, there's a lot of good and bad manipulation
between humans, right? Just like you said. [Lex sighing] To me
[sighing] especially like you said [giggles] topping from the bottom,
is that the term? -- I think someone from MIT told me that term.
[Lex laughing] It wasn't Lex. -- I think. So, first of all, there's
power dynamics in bed, and power dynamics in relationships, and power
dynamics on the street, and in the work environment, those are all
very different. I think power dynamics can make human relationships,
especially romantic relationships fascinating and rich and fulfilling
and exciting and all those kinds of things. So, I don't think in
themselves they're bad, and the same goes with robots. I really love
the idea that a robot will be at top or a bottom in terms of like
power dynamics. And I think everybody should be aware of that. And the
manipulation is not so much manipulation, but a dance of like pulling
away, a push and pull, and all those kinds of things. In terms of
control, I think we're very, very, very far away from AI systems that
are able to lock us up. To lock us up in, like to have so much control
that we basically cannot live our lives in the way that we want. I
think there's a, in terms of dangers of AI systems, there's much more
dangers that have to do with autonomous weapon systems and all those
kinds of things. So, the power dynamics as exercised in the struggle
between nations and war and all those kinds of things. But in terms of
personal relationships, I think power dynamics are a beautiful thing.
Now, there's of course, going to be all those kinds of discussions
about consent and rights and all those kinds of things. -- Well,
here, we're talking about, I always say in any discussion around this,
if we need to define a really the context, it always should be
consensual, age-appropriate, context-appropriate, species-appropriate,
but now we're talking about human-robot interactions. And so, I guess
that- -- No, I actually was trying to make a different point, which
is I do believe that robots will have rights down the line.
And I think in order for us to have deep, meaningful relationships
with robots, we would have to consider them as entities in themselves
that deserve respect. And that's a really interesting concept that I
think people are starting to talk about a little bit more, but it's
very difficult for us to understand how entities that are other than
human. I mean, the same as with dogs and other animals can have rights
on a level as humans. -- Well, yeah. We can't and nor should we do
whatever we want with animals, we have a USDA, we have Department of
Agriculture that deal with animal care and use committees for
research, for farming and ranching and all that. So, when you first
said it, I thought, wait, why would, there'll be a bill of robotic
rights, but it absolutely makes sense in the context of everything
we've been talking about up until now. If you're willing, I'd love to
talk about dogs, because you've mentioned dogs a couple of times, a
robot dog, you had a biological dog.
Yeah. - Yeah. I had a Newfoundland named Homer for many years growing
up. -- In Russia or in the U.S.? -- In the United States. And he
was about, he's over 200 pounds, that's a big dog. -- That's a big
dog. -- People know Newfoundland. So, he's this black dog that's a
really a long hair and just a kind soul. I think perhaps that's true
for a lot of large, but he thought he was a small dog. So, he moved
like that, and- -- Was he your dog? -- Yeah, yeah. -- So, you
had him since he was fairly young? -- Since the very, very
beginning, till the very, very end. And one of the things, I mean, he
had this kind of a, we mentioned like the Roombas, he had kind-hearted
dumbness about him that was just overwhelming, it's part of the reason
I named him Homer, because it's after Homer Simpson, in case people
are wondering which Homer I'm referring to. [Andrew laughing] And so,
there's a. Yeah, exactly. There's a clumsiness that was just something
that immediately led to a deep love for each other. And one of the, I
mean, he was always, it's the shared moments, he was always there for
so many a nights together, that's a powerful thing about a dog that he
was there through all the loneliness, through all the tough times,
through the successes and all those kinds of things. And I remember, I
mean, that was a really moving moment for me, I still miss him to this
day. -- How long ago did he die? -- Maybe 15 years ago. So, it's
been awhile. But it was the first time I've really experienced like
the feeling of death. So, what happened, is he got a cancer. And so,
he was dying slowly. And then there's a certain point he couldn't get
up anymore. Now, there's a lot of things that could say here that I
struggle with. Maybe he suffered much longer than he needed to, that's
something I really think about a lot. But I remember when I had to
take him to the hospital and the nurses couldn't carry him, right? So,
you're talking about a 200 pound dog and I was really into power
lifting at the time. And I remember they tried to figure out all these
kinds of ways to. So, in order to put them to sleep, they had to take
them into a room. And so, I had to carry him everywhere. And here's
this dying friend of mine that I just had to, first of all, that was
really difficult to carry, somebody that heavy when they're not
helping you out. And, yeah. So, I remember it was the first time
seeing a friend laying there and seeing life drain from his body. And
that realization that we're here for a short time was made so real,
that here is friend that was there for me the week before, the day
before, and now he's gone. And that was, I don't know, that spoke to
the fact that he could be deeply connected with the dog. Also spoke to
the fact that the shared moments together that led to that deep
friendship will make life so amazing, but it also spoke to the fact
that death is a motherfucker. So, I know you've lost Costello
recently. -- Yeah. -- And you can- - And as you're saying this,
I'm definitely fighting back the tears. I thank you for sharing that.
That I guess we're about to both cry over, I don't want to say dogs
[laughing] that it was bound to happen just given when this is
happening. Yeah, it's- -- How long did you know that Costello was
not doing well? -- We'll, let's see, a year ago during the start of,
about six months into the pandemic, he started getting abscesses and
he was not, his behavior change and something really changed. And then
I put him on testosterone which helped a lot of things. It certainly
didn't cure everything, but it helped a lot of things, he was dealing
with joint pain, sleep issues, and then it just became a very slow
decline to the point where two, three weeks ago, he had a closet full
of medication. I mean, this dog was, it was like a pharmacy. It's
amazing to me when I looked at it the other day, I still haven't
cleaned up and removed all those things, 'cause I can't quite bring
myself to do it, but- -- Do you think he was suffering? -- Well,
so, what happened, was about a week ago, it was really just about a
week ago, it's amazing. He was going up the stairs, I saw him slip.
And he was a big guy, he wasn't 200 pounds, but he was about 90
pounds, he's a bulldog, he was pretty big and he was fit. And then I
noticed that he wasn't carrying a foot in the back like it was
injured, it had no feeling at all. He never liked me to touch his hind
paws, and I could do, that thing was just flopping there. And then the
vet found some spinal degeneration and I was told that the next one
would go. Did he suffer? Sure, hope not, but something changed in his
eyes. -- Yeah. - Yeah, it's the eyes again, I know you and I spend
long hours on the phone and tell you about like the eyes and what they
convey and what they mean about internal states and for sake of robots
and biology of other kinds, but- -- You think something about him
was gone in his eyes? -- I think he was real, here, I am
anthropomorphizing, I think he was realizing that one of his great
joys in life, which was to walk and sniff and pee on things. [Lex
laughing] This dog. -- The fundamental. - Loved to pee on things, it
was amazing. I've wondered where he put it, he was like a reservoir of
urine, it was incredible. I think, oh, that's Eddie, he'd put like one
drop on the 50 millionth plant. And then we get to the 50 millionth in
one plant, and he just have, leave a puddle. And here I am talking
about Costello peeing. He was losing that ability to stand up and do
that, he was falling down while he was doing that. And I do think he
started to realize. And the passage was easy and peaceful, but I'll
say this, I'm not ashamed to say it, I mean, I wake up every morning
since then just, I don't even make the conscious decision to allow my
self to cry, I wake up crying. And I'm unfortunately able to make it
through the day, thanks to the great support of my friends and you and
my family, but I miss him, man. -- You miss him? -- Yeah, I miss
him. And I feel like, Homer, Costello, the relationship to one's dog
is so specific part. -- So, that part of you is gone? -- That's
the hard thing. What I think is different, is that I made the mistake,
I think. Moreover, I hope it was a good decision, but sometimes I
think I made the mistake of I brought Costello a little bit to the
world through the podcast or posting about him, I anthropomorphized
about him in public. Let's be honest, I have no idea what his mental
life was, or his relationship to me. And I'm just exploring all this
for the first time 'cause he was my first dog, but I raised him since
he was seven weeks. -- Yeah, you got hold it together, I noticed the
episode you released on Monday, you mentioned Costello. Like you
brought them back to life for me for that brief moment. -- Yeah. But
he's gone. -- That's the, he's going to be gone for a lot of people
too. -- Well, this is what I'm struggling with. I think that maybe
you're pretty good at this. Like, have you done this before? [Andrew
laughing] This is the challenge. Is that actually part of me. I know
how to take care of myself pretty well. -- Yeah. -- Not perfectly,
but pretty well. And I have good support. I do worry a little bit
about how it's going to land and how people will feel. I'm concerned
about their internalization. So that's something I'm still iterating
on. -- And you have to watch you struggle, which is fascinating.
-- Right. And I've mostly been shielding them from this, but what
would make me happiest is if people would internalize some of
Costello's best traits. And his best traits were that he was
incredibly tough. I mean, he was a, 22-inch-neck bulldog, the whole
thing. He was just born that way. What was so beautiful is that his
toughness has never what he rolled forward. It was just how sweet and
kind he was. And so if people can take that, then there's a win in
there someplace, so. -- I think there's some ways in which she
should probably live on in your podcast too. You should, I mean, it's
such a, one of the things I loved about his role in your podcast is
that he brought so much joy to you. We mentioned the robots. -- Mm-
hmm. -- Right? I think that's such a powerful thing to bring that
joy into, like, allowing yourself to experience that joy, to bring
that joy to others, to share it with others. That's really powerful.
And I mean, not to, this is like the Russian thing, is [chuckles] it
touched me when Lucy Kay had that moment that I keep thinking about in
this show "Louie," or like an old man was criticizing Louis for
whining about breaking up with his girlfriend, and he was saying like
the most beautiful thing about love, they made a song that's catchy
now that's now making me feel horrible saying it, but like, is the
loss. The loss really also is making you realize how much that person,
that dog meant to you. And like allowing yourself to feel that loss
and not run away from that loss is really powerful. And in some ways
that's also sweet, just like the love was the loss is also sweet
because you know that you felt a lot for that through your friend. So
I, and like continue to bring that joy. I think it would be amazing to
the podcast. I hope to do the same with [laughing] robots, or whatever
else is the source of joy, right? And maybe, do you think about one
day getting another dog? -- Yeah, in time. You're hitting on all the
key buttons here. I want that to, we're thinking about ways to kind of
immortalize Costello in a way that's real, not just creating some
little logo or something silly. Costello much like David Goggins is a
person, but Goggins also has grown into kind of a verb. You're going
to Goggins this or you're going to, and there's an adjective. Like
that's extreme. Like it, I think that for me, Costello was all those
things. He was a being, he was his own being, he was a noun, a verb
and an adjective. So, and he had this amazing super power that I wish
I could get, which is this ability to get everyone else to do things
for you without doing a thing. [Lex laughing] The Costello effect, as
I call it. -- So is an idea I hope he lives on. -- Yes. Thank you
for that. This actually has been very therapeutic for me, which
actually brings me to a question, we're friends, we're not just co-
scientists, colleagues working on a project together and in the world,
that's somewhat similar. -- Just two dogs. -- Just two dogs
basically. But let's talk about friendship, because I think that I
certainly know as a scientist that there are elements that are very
lonely of the scientific pursuit.
There are elements of many pursuits that are lonely. Music, Math
always seem to me like they're like the loneliest people. Who knows if
that's true or not. Also people work in teams. And sometimes people
are surrounded by people interacting with people and they feel very
lonely. But for me, and I think as well for you, friendship is an
incredibly strong force in making one feel like certain things are
possible or worth reaching for, maybe even making us compulsively
reach for them. So, when you were growing up, you grew up in Russia
until what age? - 13. -- Okay. And then you moved directly to
Philadelphia? -- To Chicago. - [Andrew] Chicago. -- And then
Philadelphia, and San Francisco and Boston and so on. But really to
Chicago, that's where I went to high school. -- Do you have
siblings? -- Older brother. -- But most people don't know that.
[Lex laughing] -- Yeah, he is a very different person. But somebody
I definitely look up to. So he's a wild man. He's extrovert, he was
into, I mean, so he's also scientists, a bio engineer, but he's, when
we were growing up, he was the person who did, drank and did every
drug. And, but also as the life of the party. And I just thought he
was the, when your older brother, five years older, he was the coolest
person that I was wanting to be him. So for that, he definitely had a
big influence. But I think for me in terms of friendship, growing up,
I had one really close friend. And then when I came here I had another
close friend, but I'm very, I believe, I don't know if I believe, but
I draw a lot of strength from deep connections with other people, and
just the small number of people. Just a really small number of people.
That's when I moved to this country, I was really surprised how, like,
there were these large groups of friends, quote, unquote. But the
depth of connection was not there at all from my sort of perspective.
Now, I moved to the suburb of Chicago, was Naperville. It's more like
a middle class, maybe upper middle class. So it's like people that
cared more about material possessions than deep human connection. So
that added to the thing. But I drove more meaning than almost anything
else was from friendship. Early on I had a best friend. His name was,
his name is Yura. I don't know how to say it in English. -- How do
you say in Russian? -- Yura. What's his last name? Do you remember
if was... [Lex chuckles] -- Mikolov. Yura Mikolov. So we just spent
all our time together. There's also a group of friends. Like, I dunno,
it's like eight guys. In Russia growing up, it's like parents didn't
care if you're coming back at certain hour. So we'll spent all day,
all night just playing soccer, usually called football, and just
talking about life and all those kinds of things, even at that young
age. I think people in Russia and Soviet Union grew up much quicker.
[Lex chuckles] I think the education system at the university level is
world-class in the United States in terms of like, really creating
really big, powerful minds. At least they used to be, but I think that
they aspire to that. But the education system for like, for younger
kids in the Soviet Union was incredible. Like they did not treat us as
kids. The level of literature, Tolstoy, Dostoevsky. -- When you were
a small child? -- Yeah. -- Amazing. Amazing. -- And like the
level of mathematics, and you're made to feel like shit if you're not
good at mathematics. Like we, I think in this country, there's more
like, especially young kids 'cause they're so cute. Like they're being
babied. We only start to really push adults later in life. Like, so if
you want to be the best in the world at this, then you get to be
pushed. But we were pushed at a young age. Everybody was pushed. And
that brought out the best in people. I think it really forced people
to discover, like discover themselves in the Goggin style, but also
discover what they're actually passionate about, what they're not.
-- Is this true for boys and girls? Were they pushed equally there?
-- Yeah. They were pushed. Yeah, they were pushed equally, I would
say. There was a, obviously there was more, not obviously, but at
least from my memories, more of a, what's the right way to put it? But
there was like gender roles, but not in a negative connotation. It was
the red dress versus the suit and tie kind of connotation, which is
like, there's a, like guys like lifting heavy things and girls like
creating beautiful art, and, like there's- -- A more traditional
view of gender, more 1950, '60s. -- But we didn't think in terms of,
at least at that age, in terms of like roles and then like a homemaker
or something like that or not, it was more about what people care
about. Like girls cared about this set of things, and guys cared about
the set of things. I think mathematics and engineering was something
that guys cared about and sort of, at least my perception of that
time. And then girls cared about beauty. So like guys want to create
machines, girls want to create beautiful stuff. [Lex laughing] And
now, of course, that I don't take that forward in some kind of
philosophy of life, but it's just the way I grew up and the way I
remember it. But all, everyone worked hard. The value of hard work was
instilled in everybody. And through that, I think it's a little bit of
hardship. Of course also economically everybody was poor, especially
with the collapse of the Soviet Union. There's poverty everywhere. You
didn't notice it as much, but there was a, because there's not much
material possessions, there was a huge value placed on human
connection. Just meeting with neighbors, everybody knew each other. We
lived in an apartment building very different than you have in the
United States these days. Everybody knew each other. You would get
together, drink vodka, smoke cigarettes, and play guitar and sing sad
songs about life.
-- What's with the sad songs in the Russian thing? I mean, Russians
do I express joy from time to time. -- Yeah, they do. -- Certainly
you do. But what do you think that's about? Is it 'cause it's cold
there? But it's called other places too, right? -- I think, let's
just, first of all the Soviet Union, the echoes of World War II and
the millions and millions and millions of people that, civilians that
were slaughtered, and also starvation is there, right? So like the
echoes of that, of the ideas, the literature, the art is there. Like
that's a grandparents, that's parents, that's all there. So that
contributes to it, that life can be absurdly unexplainably cruel. At
any moment everything can change. So that's in there. Then I think
there's an empowering aspect to finding beauty in suffering that then
everything else is beautiful too. It's like, if you just linger or
it's like, why you meditate on death? Is like, if you just think about
the worst possible case and find beauty in that, then everything else
is beautiful too. And so you write songs about the dark stuff. And
that's somehow helps you deal with whatever comes. There's a
hopelessness to the Soviet Union that, like, inflation, all those
kinds of things where people were sold dreams and never delivered. And
so like, there's a, if you don't sing songs about sad things, you're
going to become cynical about this world. -- Mm-hmm. Interesting.
-- So they don't want to give in to cynicism. Now, a lot of people
did, one of the, but that is the battle against cynicism. One of the
things that may be common in Russia is a kind of cynicism about, like,
if I told you the thing I said earlier about dreaming about robots,
it's very common for people to dismiss that dream, of saying, no,
that's not, that's too wild. Like, who else do you know that did that?
Or you want to start a podcast? Like who else? Like nobody's making
money on podcasts. Like, why do you want to start a podcast? That kind
of mindset I think is quite common, which is why I would say
entrepreneurship in Russia is still not very good. Which to be a
business, like, to be an entrepreneur you have to dream big, and you
have to have others around you, like friends and support group that
make you dream big. But if you don't give in to cynicism and
appreciate the beauty in the unfairness of life, the absurd unfairness
of life, then I think it just makes you appreciative of everything.
It's like a, it's a prerequisite for gratitude. And so, yeah, I think
that instilled in me ability to appreciate everything, just like
everything. Everything's amazing. And then also there is a culture of
like romanticizing everything. Like, it's almost like romantic
relationships were very like soap opera, like is very like over the
top dramatic. And I think that it was instilled in me too, not only do
I appreciate everything about life, but I get like emotional about it.
In a sense, like, I get like a visceral feeling of joy for everything.
And the same with friends or people of the opposite sex. Like, there's
a deep, like emotional connection there that like [laughing] that's
like way too dramatic too. Like, I guess relative to what the actual
moment is. But I derive so much deep, like dramatic joy from so many
things in life. And I think I would attributed that to the upbringing
in Russia. But the thing that sticks most of all is the friendship.
And have now since then had one other friend like that in the United
States, he lives in Chicago. His name is Matt. And slowly here and
there accumulating really fascinating people, but I'm very selective
with that. Funny enough, the few times, it's not few it's a lot of
times now interacting with Joe Rogan [chuckles] it's sounds surreal to
say, but there was a kindred spirit there. Like I've connected with
him. And there's been people like that also in the grappling sports
that are really connected with. I've actually struggled, which is why
I'm so glad to be your friend, is I've struggled to connect with
scientists. -- They can be a little bit wooden sometimes. - [Lex]
Yeah. -- Even the biologist. I mean, one thing that I, well, I'm so
struck by the fact that you work with robots, you're an engineer, AI,
science technology, and that all sounds like hardware, right? But what
you're describing and I know is true about you is this deep emotional
life and this resonance and it's really wonderful. I actually think
it's one of the reasons why so many people, scientists and otherwise
have gravitated towards you and your podcast is because you hold both
elements. In the Hermann Hesse's book, I don't know if you, "Narcissus
and Goldmund," right? It's about these elements of the logical
rational mind and the emotional mind and how those are woven together.
And if people haven't read it, they should, and you embody the full
picture. And I think that's so much of what draws people to you. --
I've read every Hermann Hesse book by the way. -- As usual
[chuckles] as usual I've done about 9% of what life is. No, it's true.
You mentioned Joe, who is a phenomenal human being, not just for his
amazing accomplishments, but for how he shows up to the world one on
one.
I think I heard him say the other day on an interview, he said, there
is no public or private version of him. And he's like, this is me. He
said that it was beautiful. He said, I'm like the fish that got
through the net. And there is no onstage offstage version. And you're
absolutely right. And I. -- Fish. [Lex laughing] -- So, but, well,
you guys, I have a question actually about- -- But that's a really
good point about public and private life. He was a huge, if I could
just comment real quick. Like that, he was a, I've been a fan of Joe
for a long time, but he's been an inspiration to not have any
difference between public and private life. I actually had a
conversation with Naval about this, and he said that you can't have a
rich life, like exciting life if you're the same person publicly and
privately. And I think I understand that idea, but I don't agree with
it. I think that's really fulfilling and exciting to be the same
person privately and publicly with very few exceptions. Now that said,
I don't have any really strange sex kinks. So like, I feel like it can
be open with basically everything. I don't have anything I'm ashamed
of. There's some things that could be perceived poorly, like the
screaming Roombas, but I'm not ashamed of them. I just have to present
them in the right context. But there's a freedom to being the same
person in private as in public. And that Joe made me realize that you
can be that. And also to be kind to others. It sounds kind of absurd,
but I really always enjoyed like being good to others. Like just being
kind towards others. But I always felt like the world didn't want me
to be. Like, there's so much negativity when I was growing up, like
just around people. If you actually just notice how people talk, they,
from like, complaining about the weather, this could be just like the
big cities that I've visited. But there's a general negativity, and
positivity is kind of suppressed. You're not, one, you're not seen as
very intelligent, and two, there's a kind of, you're seen as like a
little bit of a weirdo. And so I always felt like I had to hide that.
And what Joe made me realize, one, I could be fully just the same
person private and public, and two, I can embrace being kind, in just,
in the way that I like, in the way I know how to do. And sort of for
me on like, on Twitter or like publicly, whenever I say stuff, that
means saying stuff simply almost to the point of cliche. And like, I
have the strength now to say it, even if I'm being mocked. [Lex
laughing] You know what I mean? Like, just it's okay. If everything's
going to be okay. Okay, some people will think you're dumb. They're
probably right. The point is, like, just enjoy being yourself. And
that Joe, more than almost anybody else, because he's so successful at
it, inspired me to do that. Be kind and be the same person, private
and public. -- I love it. And I love the idea that authenticity
doesn't have to be oversharing, right? That it doesn't mean you reveal
every detail of your life. It's a way of being true to an essence of
oneself. -- Right. There's never a feeling when you deeply think and
introspect that you're hiding something from the world or you're being
dishonest in some fundamental way. So, yeah, that's truly liberating.
It allows you to think, it allows you to like think freely, to speak
freely, to just to be freely. That said, it's not like there's not
still a responsibility to be the best version of yourself. So, I'm
very careful with the way I say something. So, the whole point, it's
not so simple to express the spirit that's inside you with words. I
mean, some people are much better than others. I struggle. Like
oftentimes when I say something and I hear myself say it, it sounds
really dumb and not at all what I meant. So that's the responsibility
you have. It's not just like being the same person publicly and
privately means you can just say whatever the hell. It means there's
still responsibility to try to be, to express who you truly are. And
that's hard. [Lex chuckles] -- It hard. And I think that, we have
this pressure, all people, when I say we, I mean all humans, and maybe
robots too, feel this pressure to be able to express ourselves in that
one moment in that one form. And it is beautiful when somebody, for
instance, can capture some essence of love or sadness or anger or
something in a song or in a poem or in a short quote, but perhaps it's
also possible to do it in aggregate, all the things how you show up.
For instance, one of the things that initially drew me to want to get
to know you as a human being and a scientist and eventually we became
friends, was the level of respect that you brought to your podcast
listeners by wearing a suit. -- Yeah. - I'm being serious here. I
was raised thinking that if you overdress a little bit, overdressed by
American, certainly by American standards, you're overdressed for a
podcast, but it's genuine. You're not doing it for any reason, except
I have to assume, and I assumed at the time, that it was because you
have a respect for your audience, you respect them enough to show up a
certain way for them. It's for you also, but it's for them. -- Yeah.
-- And I think between that and your commitment to your friendship,
just the way that you talk about friendships and love and the way you
hold up these higher ideals, I think at least as a consumer of your
content and as your friend, what I find, is that in aggregate, you're
communicating who you are, it doesn't have to be one quote or
something. And I think that we're sort of obsessed by like the one
Einstein quote, or the one line of poetry or something, but I think
you so embody the way that, and Joe as well, it's about how you live
your life and how you show up as a collection of things and said and
done. -- Yeah, that that's, and so, the aggregate is the goal, the
tricky thing, and Jordan Peterson talks about this because he's under
attack way more than you and I will ever be, but- -- Right now? --
For now, right? This is very true for now. That the people who attack
on the internet, this is one of the problems with Twitter, is they
don't consider the aggregate, they take a single statements. And so,
one of the defense mechanisms, like again why Joe has been an
inspiration, is that when you in aggregate, a good person, a lot of
people will know that. And so, that makes you much more immune to the
attacks of people that bring out an individual statement that might be
a misstatement of some kind, or doesn't express who you are. And so,
that, I like that idea is the aggregate. And the power of the podcast,
is you have hundreds of hours out there, and being yourself and people
get to know who you are. And once they do, and you post pictures of
screaming Roombas as you kick them, they will understand that you
don't mean well. By the way, as a side comment, I don't know if I want
to release this because it's not just the Roombas- -- You have a
whole dungeon of robots. -- Okay. So, this is a problem, the Boston
Dynamics came up against this problem. But, let me work this out like
workshop this out with you, and maybe because we'll post this, people
will let me know.
So, there's legged robots, they look like a dog, I'm trying to create
a very real human-robot connection, but like they're also incredible
because you can throw them like off of a building and they'll land
fine. And this beautiful. -- That's amazing. I've seen the Instagram
videos of like cats jumping off of like fifth story buildings and then
walking away. But no one should throw their cat out of a window of a
building. -- Well, this is the problem I'm experiencing, all
certainly kicking the robots, its really fascinating how they recover
from those kicks. But like just seeing myself do it and also seeing
others do it, it just does not look good, and I don't know what to do
with that. 'Cause it's such a- - Ill 'do it. [Lex laughing] -- See.
But you don't, 'cause you are- - A robot, no, I'm kidding. What's
interesting? -- Yeah. -- Before today's conversation, I probably
could do it, and I'm thinking about robots, bills of rights and
things. Not to satisfy you or to satisfy anything, except that if they
have some sentience aspect to their being, then I would load to kick
it. -- I don't think we'd be able to kick it, you might be able to
kick the first time, but not the second, this is the problem of
experience. One of the cool things, is one of the robots I'm working
with, you can pick it up by one leg and is dangling, and you can throw
it in any kind of way and it'll land correctly. So, it's really- --
I had a friend who had a cat like that. [Lex laughing] -- Oh man, we
look forward to the letters on the cat- -- Oh no, I'm not suggesting
anyone did that, but he had this cat, and the cat, he would just throw
it onto the bed from across the room, and then it would run back for
more, or somehow that was the nature of the relationship. I think no
one should do that to an animal, but this cat seemed to return for
whatever reason. -- But a robot is a robot, and it's fascinating to
me how hard it is for me to do that. So, it's unfortunate, but I don't
think I can do that to a robot. Like I struggle with that. So, for me
to be able to do that with a robot, I have to almost get like into the
state that I imagine like doctors get into when they're doing surgery,
like I have to do what robotics colleagues of mine do, which is like
start seeing it as an object. -- Dissociate. -- Like dissociate.
So, it was just fascinating that I have to do that in to do that with
a robot. I just want to take that little bit of a tangent. -- No, I
think it's an important thing. I mean, I'm not shy about the fact that
for many years I've worked on experimental animals, and that's been a
very challenging aspect of being a biologist. Mostly mice, but in the
past no longer, thank goodness 'cause I just don't like doing it,
larger animals as well. And now I work on humans, which I can give
consent, verbal consent. So, I think that it's extremely important to
have an understanding of what the guidelines are and where one's own
boundaries are around this. It's not just an important question, it
might be the most important question before any work can progress.
-- So, you asked me about friendship. I know you have a lot of
thoughts about friendship, what do you think is the value of
friendship in life? -- Well, for me personally, just because of my
life trajectory and arc friendship, and I should say, I do have some
female friends that are just friends, they're completely platonic
relationships, but it's been mostly male friendship to me, has been-
-- It has been all male friendships to me actually, yeah. --
Interesting. - Yeah. -- It's been an absolute lifeline. They are my
family, I have a biological family and I have great respect and love
for them and an appreciation for them, but it's provided me the, I
won't even say confidence because there's always an anxiety in taking
any good risk, or any risk worth taking. It's given me the sense that
I should go for certain things and try certain things to take risk to
weather that anxiety. And I don't consider myself a particularly
competitive person, but I would sooner die than disappoint, or let
down one of my friends. I can think of nothing worse actually, than
disappointing one of my friends, everything else is secondary to me.
-- What disappointment? -- Disappoint, meaning not, I mean,
certainly I strive always to show up as best I can for the friendship,
and that can be in small ways. That can mean making sure the phone is
away, sometimes it's about, I'm terrible with punctuality 'cause I'm
an academic. And so, I just get lost in time and I don't mean
anything, but it's striving to, to listen to, to enjoy good times and
to make time. It kind of goes back to this first variable we talked
about, to make sure that I spend time and to get time in person and
check in. And I think there's so many ways in which friendship is
vital to me, it's it's actually to me, what makes life worth living.
-- Yeah. Well, there's a, I am surprised like with the high school
friends how we don't actually talk that often these days in terms of
time, but every time we see each other, it's immediately right back to
where we started. So, I struggled that how much time you really
allocate, for the friendship to be deeply meaningful because they're
always there with me even if we don't talk often. So, there's a kind
of loyalty. I think maybe it's a different style, but I think to me,
friendship is being there in the hard times, I think. Like I'm much
more reliable when you're going through shit than in like- -- You're
pretty reliable anyway. -- No, but if you're like a wedding or
something like that, or like, I don't know, like you want an award of
some kind, yeah, I'll congratulate the shit out of you, but like
that's not, and I'll be there, but that's not as important to me as
being there when like nobody else is like just being there when shit
hits the fan, or something's tough where the world turns their back on
you, all those kinds of things, that, to me, that's where friendship
is meaningful. -- Well, I know that to be true about you and that's
a felt thing and a real thing with you.
Let me ask one more thing about that actually, because I'm not a
practitioner Jujitsu, I know you are, Joe is, but years ago, I read a
book that I really enjoyed, which is Sam Sheridan's book, " A
Fighter's Heart," he talks about all these different forms of martial
arts. And maybe it was in the book, maybe it was in an interview, but
he said that fighting, or being in physical battle with somebody,
Jujitsu boxing or some other form of direct physical contact between
two individuals creates this bond unlike any other. Because he said
it's like a one night stand, you're sharing bodily fluids with
somebody that you barely know. -- Yeah. -- And I chuckled about it
'cause it's kind of funny and it kind of tongue in cheek. But at the
same time, I think this is a fundamental way in which members of a
species bond is through physical contact. And certainly, there are
other forms, there's cuddling, and there's hand holding, and there's
in their sexual intercourse, and there's all sorts of things. --
What's cuddling? I haven't heard of it. -- I heard this recently, I
didn't know this term, but there's a term, they've turned the noun
cupcake into a verb, cupcaking it turns out, I just learned about
this. Cupcaking is when you spend time just cuddling. I didn't know
about this. You heard it here first, although I heard it first just
the other day. Cupcaking is actually a- -- Cuddling is everything,
it's not just like, is it in bed, or is it in the coach? Like what's
cuddling? I do look up what cuddling is- -- We need to look at this
up and we need to define the variables. I think it definitely has to
do with physical contact, I'm told, but in terms of battle, a
competition, and the Sheridan quote, I'm just curious. So, do you get
close, or feel a bond with people that, for instance, you rolled
Jujitsu with, or even though you don't know anything else about them,
was he right about this? -- Yeah, I mean on many levels. He also has
the book, what? "A Fighter's Mind." -- Yeah, that was the third one.
He's actually an excellent writer. What's interesting about him, just
briefly about Sheridan, I don't know him, but I did a little bit of
research, he went to Harvard, he was an art major at Harvard, he
claims all he did was smoke cigarettes and do art. I don't know if his
art was any good. And I think his father was in the SEAL teams. And
then when he got out of Harvard, graduated, he took off around the
world learning all the forms of martial arts, and was early to the
kind of ultimate fighting kind of mixed martial arts and things. Great
book. Yeah, yeah. -- It's amazing. I don't actually remember it, but
I read it, and I remember thinking that was an amazing encapsulation
of what makes fighting like the art, like what makes it compelling. I
would say that there's so many ways that Jujitsu grappling, wrestling,
combat sports in general, is like one of the most intimate things you
could do. I don't know if I would describe in terms of bodily liquids
and all those kinds of things. -- I think he was more or less
joking. -- I think there's a few ways that it does that. So, one,
because you're so vulnerable [sighs] So, the honesty of stepping on
the mat and often all of us have ego thinking we're better than we are
at this particular art. And then the honesty of being submitted, or
being worse than you thought you are and just sitting with that
knowledge, that kind of honesty, we don't get to experience it in most
of daily life. We can continue living somewhat of an illusion of our
conceptions of ourselves 'cause people are not going to hit us with
the reality, the mat speaks only the truth, the reality just hits you.
And that vulnerability is the same as like the loss of a loved one,
though it's the loss of a reality that you knew before, you now have
to deal with this new reality. And when you're sitting there in that
vulnerability, and there's these other people that are also sitting in
that vulnerability, you get to really connect like, fuck, like I'm not
as special as I thought I was, and life is like not, life is harsher
than I thought I was, and we're just sitting there with that reality,
some of us can put words to them, some we can't. So, I think that
definitely, is a thing that at least the intimacy. The other thing is
the human contact. There's something about, I mean, like a big hug,
like during COVID, very few people hugged me and I hugged them, and I
always felt good when they did. Like we were all tested, and
especially now we're vaccinated, but there's still people, this is
true of San Francisco's, it's true in Boston, they want to keep, not
only six feet away, but stay at home and never touch you. That loss of
basic humanity is the opposite of what I feel in Jujitsu, where it was
like that contact where you're like, I don't give a shit about
whatever rules we're supposed to have in society where you have to
keep a distance and all that kind of stuff. Just the hug, like the
intimacy of a hug, that's like a good bear hug, and you're like just
controlling another person, and also there is some kind of love
communicated through just trying to break each other's arms. I don't
exactly understand why violence is the such a close neighbor to love,
but it is. -- Well, in the hypothalamus, the neurons that control
sexual behavior, but also non-sexual contact, are not just nearby the
neurons that control aggression and fighting, they are salt and pepper
with those neurons. It's a very interesting, and it almost sounds kind
of risky and controversial and stuff, I'm not anthropomorphizing about
what this means, but in the brain, those structures are
interdigitated, you can't separate them except at a very fine level.
And here, the way you describe it, is the same as a real thing. -- I
do want to make an interesting comment. Again, these are the things
that could be taken out of context, but one of the amazing things
about Jujitsu, is both guys and girls train it. And I was surprised.
So, like I'm a big fan of yoga pants [giggles] at the gym kind of
thing. It reveals the beauty of the female form. But the thing is,
like girls are dressed in skintight clothes in Jujitsu often. And I
found myself not at all, thinking like that at all when training with
girls. -- Well, the context is very non-sexual. -- But I was
surprised to learn that. When I first started to Jujitsu, I thought,
wouldn't that be kind of weird to train with the opposites that in
something so intimate. -- So, boys and girls, men and women, they
roll Jujitsu together? -- Completely. - Interesting. -- And the
only times girls kind of try to stay away from guys, I mean, there's
two contexts, of course, there's always going to be creeps in this
world. So, everyone knows who kind of stay away from, and the other is
there's a size disparity. So, girls will often try to roll with people
a little bit closer weight-wise, But no, that's one of the things that
are empowering to women, that's what they fall in love with when they
started doing Jujitsu, is first of all, they gain an awareness and a
pride over their body, which is great. And then second, they get to
[chuckles] especially later on, start submitting big dudes like these
bros that come in who are all shredded and like muscular, and they get
to technique to exercise dominance over them, and that's a powerful
feeling. -- You've seen women force a larger guy to tap her, or even
choke them up. -- Well, I was deadlifting like a four, oh boy, I
think it's 495. So, I was really into power-lifting when I started at
Jujitsu, and I remember being submitted by, I thought I walked in
feeling like I'm going to be, if not the greatest fighter ever, at
least top three. And so, as a white belt, you roll in like all happy.
And then you realize that as long as you're not applying too much
force, that you're having, I remember being submitted many times by
like 130, 120-pound girls at our Balance Studios in Philadelphia, that
a lot of incredible female Jujitsu players. And that's really humbling
too that technique can overpower in combat pure strength. And that's
the other thing, there is something about combat that's primal. Like
there, it just feels, it feels like we were born to do this. Like
that- -- We have circuits in our brain that are dedicated to this
kind of interaction. There's no question. -- And that's what it felt
like, it wasn't that I'm learning a new skill. It was like, somehow I
am a remembering echoes of something I've learned in the past. --
Well, it's like hitting puberty. A child before puberty has no concept
of boys and girls having this attraction, regardless of whether or not
they're attracted to boys or girl, doesn't matter. At some point, most
people, not all, but certainly, but most people, when they hit
puberty, suddenly people appear differently, and certain people take
on a romantic or sexual interest for the very first time. -- Yeah.
-- And so it's like, it's revealing a circuitry in the brain. It's not
like they learn that it's innate. And I think it, when I hear the way
you describe Jujitsu and enrolling Jujitsu, it reminds me a little
bit, Joe was telling me recently about the first time he went hunting
and he felt like it revealed a circuit that was in him all along, but
he hadn't experienced before. -- Yeah. That's definitely there. And
of course, there's the physical activity. One of the interesting
things about Jujitsu is it's one of the really strenuous exercises
that you can do late into your adult life, like into your 50, 60, 70s,
80s. When I came up, there's a few people in their 80s that were
training. And as long as you're smart, as long as you practice
techniques and pick your partners correctly, you can do that kind of
art. That's late into life. And so you're getting exercise. There's
not many activities I find that are amenable to that. So, because it's
such a thinking game, the Jujitsu in particular is an art or technique
pays off a lot. So you can still maintain, first of all, remain injury
free if you use good technique, and also through good technique be
able to go, be active with people that are much, much younger. And so
that was, to me, that and running are the two activities you can kind
of do late in life. Because to me a healthy life has exercises as the
piece of the puzzle.
-- No, absolutely. And I'm glad that we're on the physical
component, because I know that there's for you, you've talked before
about the crossover between the physical and the intellectual and the
mental. Are you still running at ridiculous hours of the night for
ridiculously long? -- Yeah, so, definitely. I've been running late
at night here in Austin. People tell, the area we're in now, people
say it's a dangerous area, which I find laughable coming from the
bigger cities. No, I run late at night. There's something. -- If you
see a guy running through Austin at 2:00 a.m. in a suit and tie, it's
probably. [Lex laughing] -- Well, yeah. I mean, I do think about
that 'cause I get recognized more and more in Austin. I worry that,
but not really, that I get recognized late at night. But there is
something about the night that brings out those deep philosophical
thoughts and self-reflection, that really enjoy. But recently I
started getting back to the grind. So I'm going to be competing or
hoping to be compete in September and October. -- In Jujitsu? --
In Jujitsu, yeah. To get back to competition. And so that requires
getting back into a great cardio shape. I've been getting, running as
part of my daily routine. -- Got it. - [Lex] Yeah. -- Well, I
always know I can reach you regardless of time zone in the middle of
the night, wherever that happens. -- Well, part of that has to be
just being single and being a programmer. Those two things just don't
work well in terms of a steady sleep schedule. -- It's not bankers
hours kind of work. Nine to five. I want to, you mentioned single.
I want to ask you a little bit about the other form of relationship,
which is romantic love. So, your parents are still married? -- Still
married, still happily married. -- That's impressive. - [Lex] Yeah.
-- A rare thing nowadays. - [Lex] Yeah. -- So you grew up with that
example? -- Yeah. I guess that's a powerful thing, right? If there's
an example that I think can work. -- Yeah. I didn't have that in my
own family, but when I see it, it's inspiring and it's beautiful. The
fact that they have that, and that was the norm for you, I think is
really wonderful. -- Well, it was a, in the case of my parents it
was interesting to watch 'cause there's obviously tension. Like,
there'll be times where they fought and all those kinds of things.
They obviously get frustrated with each other and they like, but they
find mechanisms how to communicate that to each other, like to make
fun of each other a little bit, like to tease, to get some of that
frustration out, and then ultimately to reunite and find their joyful
moments and be that the energy. I think it's clear 'cause I got
together in there I think early 20s, like very, very young. I think
you grow together as people. -- Yeah. You're still in the critical
period of brain plasticity. [laughing] -- And also, I mean, it's
just like divorce was so frowned upon that you stick it out. And I
think a lot of couples especially from that time, the Soviet Union,
that's probably applies to a lot of cultures. You stick it out and you
put in the work, you learn how to put in the work. And once you do,
you start to get to some of those rewarding aspects of being, like
through time has sharing so many moments together. That's definitely
something that was an inspiration to me, but maybe that's where I
have. So I have a similar kind of longing to have a lifelong partner,
like to have that kind of view, where same with friendship, lifelong
friendship is the most meaningful kind. That there is something with
that time of sharing all that time together. Like till death do us
part is a powerful thing. Not by force, not because of the religion
said it or the government said it or your culture said it, but because
you want to. -- Do you want children? -- Definitely, yeah.
Definitely want children. It's- -- How many Roombas do you have?
-- Oh, I thought- -- You should, no, no- -- Human children? --
No, human to human children. - 'Cause I already have the children.
-- Exactly. What I was saying, you probably need to at least as many
human children as you do Roombas. Big family, small family. -- So.
-- In your mind's eyes, they're a bunch of Fridman's running around.
-- So I'll tell you, like realistically, I can explain exactly my
thinking, and this is similar to the robotics work is, if I'm like
purely logical right now, my answer would be I don't want kids.
Because I just don't have enough time. I have so much going on. But
when I'm using the same kind of vision I use for the robots is I know
my life will be transformed with the first. Like I know I would love
being a father. And so the question of how many, that's on the other
side of that hill. It could be some ridiculous number. So I just know
that- -- I have a feeling and I could be, I don't have a crystal
ball, but I don't know. I see an upwards of, certainly three or more
come comes to mind. -- So much of that has to do with the partner
you're with too. So like that, that's such an open question,
especially in this society of what the right partnership is. 'Cause
I'm deeply empathetic. I want to see, like to me, what I look for in
your relationship is for me to be really excited about the passions of
another person, like whatever they're into, it doesn't have to be a
career success. Any kind of success, just to be excited for them, and
for them to be excited for me. And like share in that excitement and
build, and build and build. But there was also practical aspects of
like, what kind of shit do you enjoy doing together? And I think
family is a real serious undertaking. -- It certainly is. I mean, I
think that I have a friend who said it, I think best, which is that
you first have, he's in a very successful relationship and has a
family. And he said, you first have to define the role and then you
have to cast the right person for the role. [Lex laughing] -- Well,
yeah, there's some deep aspects of that, but there's also an aspect to
which you're not smart enough from this side of it to define the role.
I think there's part of it that has to be a leap that you have to
take. And I see having kids that way. You just have to go with it and
figure it out also. As long as there's love there, like what the hell
is life for even? So I've, there's so many incredibly successful
people that I know that I've gotten to know that all have kids. And
the presence of kids for the most part has only been something that
energizes them, something they gave them meaning, something that made
them the best version of themselves, like made them more productive,
not less, which is fascinating to me. -- It is fascinating. I mean,
you can imagine if the way that you felt about Homer, the way that I
feel and felt about Costello is at all a glimpse of what that must be
like then. -- Exactly. The downside, the thing I worry more about is
the partner side of that. I've seen, the kids are almost universally a
source of increased productivity and joy and happiness. Like, yeah,
they're a pain in the ass. Yeah, is complicated. Yeah, so and so
forth, people like to complain about kids. But then when you actually
look past that little shallow layer of complaint, kids are great. The
source of pain for a lot of people is if when the relationship doesn't
work. And so I'm very kind of concerned about like, dating is very
difficult, and I'm a complicated person. And so it's been very
difficult to find the right kind of person. But that statement doesn't
even make sense because I'm not on dating apps, I don't see people.
You're like the first person I saw in awhile. It's like you and
Michael Malice and like Joe. So, like, I don't think I've seen like a
female. What is it? An element of the female species in quite a while.
So, I think you have to put yourself out there. What is it? Daniel
Johnston says, true love will find you, but only if you're looking. So
there's some element of really taking the leap and putting yourself
out there in kind of different situations. And I don't know how to do
that when you're behind a computer all the time. -- Well, you're a
builder and you're a problem solver, and you find solutions, and I'm
confident the solution is out there, and. -- I think you're implying
that I'm going to build the girlfriend, which I think. -- Well, and
maybe we shouldn't separate this friendship, the notion of friendship
and community, and if we go back to this concept of the aggregate,
maybe you'll meet this woman through a friend, or maybe you'll or
something of that sort. -- So, one of the things, I dunno if you
feel the same way, I definitely one of those people that just falls in
love and that's it. -- Yeah, I can't say I'm like that. With
Costello it was instantaneous. -- Yeah. -- It really was. I mean,
I know it's not romantic love, but it was instantaneous. No, I, but
that's me. And I think that if you know, you know, because that's a
good thing that you have there. -- It's, I'm very careful with that,
because you don't want to fall in love with the wrong person. So I try
to be very kind of careful with, I've noticed this because I fall in
love with every, like this mug, everything I fall in love with things
in this world. So, like, you have to be really careful because a girl
comes up to you and says she loves DUSTY HUSKY, that doesn't
necessarily mean to marry her tonight. -- Yes. And I like the way
you said that out loud so that you heard it, you doesn't mean you need
to marry her tonight, right? - [Lex] Exactly. - [Andrew] Right. --
But I mean, but people are amazing, and people are beautiful and
that's, so I'm fully embraced that, but also you have to be careful
with relationships. And at the same time, like I mentioned to you
offline, I don't, there's something about me that appreciates swinging
for the fences and not dating, like doing serial dating, or dating
around. -- Like you're a one guy, one girl kind of guy. - [Lex]
Yeah. -- And you said that. -- And it's tricky because you want to
be careful with that kind of stuff. Especially now there's a growing
platform that have a ridiculous amount of female interests of a
certain kind. But I'm looking for deep connection, and I'm looking by
sending home alone, and every once in a while talking to Stanford
professors. -- Perfect solution. - On a podcast. -- Perfect
solution. -- Is going to workout great. -- It's well, it's part
of, that constitutes machine learning of sorts. -- Yeah, of sorts.
-- I do, you mentioned what has now become a quite extensive and
expansive public platform, which is incredible. I mean, the number of
people out, first time I saw your podcast, I noticed the suit, I was
like, he respects his audience, which was great, but I also thought
this is amazing. People are showing up for science and engineering and
technology information and those discussions and other sorts of
discussions. Now, I do want to talk for a moment about the podcast. So
my two questions about the podcast are, when you started it, did you
have a plan? And regardless of what that answer is, do you know where
you're taking it, or would you like to leave us? I do believe in an
element of surprise is always fun. But what about the podcast? Do you
enjoy the podcast? I mean, your audience certainly includes me, really
enjoys the podcast. It's incredible. -- So I love talking to people,
and there's something about microphones that really bring out the best
in people. Like you don't get a chance to talk like this. If you and I
were just hanging out, we would have a very different conversation in
the amount of focus we allocate to each other. We would be having fun
talking about other stuff and doing other things. There'll be a lot of
distraction. There would be some phone use and all that kind of stuff.
But here we're 100% focused on each other and focus on the idea. And
like sometimes playing with ideas that we both don't know the answer
to, like a question we don't know the answer to. We're both like
fumbling with it, trying to figure out, trying to get some insights at
something we haven't really figured out before and together arriving
at that. I think that's magical. I don't know why we need microphones
for that, but we somehow do. -- It feels like doing science. -- It
feels like doing science for me, definitely. That's exactly it. And
I'm really glad you said that because I don't actually often say this,
but that's exactly what I felt like. I wanted to talk to friends and
colleagues at MIT to do real science together. That's how I felt about
it. Like to really talk through problems that are actually
interesting, as opposed to like incremental work that we're currently
working for for a particular conference. So really asking questions
like, what are we doing? Like, where's this headed to? Like, what are
the big, is this really going to help us solve, in the case of AI,
solve intelligence? Like, is this even working on intelligence?
There's a certain sense, which is why I initially called it artificial
intelligence. Is like most of us are not working on artificial
intelligence. You're working on some very specific problem and a set
of techniques, at the time it's machine learning to solve this
particular problem. This is not going to take us to a system that is
anywhere close to the generalizability of the human mind. Like the
kind of stuff the human mind can do in terms of memory, in terms of
cognition, in terms of reasoning, common sense reasoning. This doesn't
seem to take us there. So the initial impulse was, can I talk to these
folks do science together through conversation? And I also thought
that there was not enough, I didn't think there was enough good
conversations with world-class minds that I got to meet. And not the
ones with the book, or like this was just the thing. Oftentimes you go
on this tour when you have a book, but there's a lot of minds that
don't write books. -- And the books constrain the conversation too,
when you're talking about this thing, this book. -- But there's,
I've noticed that, with people that haven't written a book who are
brilliant, we get to talk about ideas in a new way. We both haven't
actually, when we raise a question, we don't know the answer to it
once the question is raised. And we try to arrive there. Like, I
dunno, I remember asking questions of world-class researchers in deep
learning of, why do neural networks work as well as they do? That
question is often loosely asked, but like when you have microphones
and you have to think through it, and you have 30 minutes to an hour
to think through it together, I think that's science. I think that's
really powerful. So that was the one goal. The other one is, again,
don't usually talk about this, but there's some sense in which I
wanted to have dangerous conversations. Part of the reasons I wanted
to wear a suit is like, I want it to be fearless. The reason I don't
usually talk about it is because I feel like I'm not good at
conversation. So it looks like it doesn't match the current skill
level. But I wanted to have really dangerous conversations that I
uniquely would be able to do. Not completely uniquely, but like, I'm a
huge fan of Joe Rogan, and I had to ask myself, what conversations can
I do that Joe Rogan can't? For me, I know I bring this up, but for me
that person I thought about at the time was Putin. Like that's why I
bring him up. He's just like with Costello, he's not just a person.
He's also an idea to me for what I strive for. Just to have those
dangerous conversations. And the reason I'm uniquely qualified as both
the Russian, but also there's the judo and the martial arts, there's a
lot of elements that make me have a conversation he hasn't had before.
And there's a few other people that I kept in mind, like Don Knuth, is
a computer scientist from Stanford that I thought is one of the most
beautiful minds ever. And nobody really talked to him, like really
talked to him. He did a few lectures, which people love, but really
just have a conversation with him. There's a few people like that. One
of them passed away, John Conway, that I never got, we agreed to talk,
but he died before we did. There's a few people like that, that I
thought like it's such a crime to not hear those folks. And I have the
unique ability to know how to purchase a microphone on Amazon and plug
it into a device that records audio and then publish it, which seems
relatively unique. Like that's not easy in the scientific community.
People knowing how to plug in a microphone. -- No. They can build
Faraday cages, and two-photon microscopes and bioengineer, all sorts
of things, but the idea that you could take ideas and export them into
a structure or a pseudo structure that people would benefit from seems
like a cosmic achievement to them. -- I don't know if it's fear or
just a basically they haven't tried it, so they haven't learned the
skill level. -- But I think they're not trained. I mean, we could
riff on this for awhile, but I think that, but it's important. And
maybe we should, which is that it's, they're not trained to do it.
They're trained to think in specific games and specific hypotheses,
and many of them don't care to, right? They became scientists because
that's where they felt safe, and so why would they leave that Haven of
safety? -- Well, they also don't necessarily always see the value in
it. We're all together learning, you and I are learning the value of
this. I think you're probably having an exceptionally successful and
amazing podcast that you started just recently. -- Thanks to your
encouragement. -- Well, but there's a raw skill there that's, you're
definitely an inspiration to me in how you did the podcast in the
level of excellence you reach. But I think you've discovered that
that's also an impactful way to do science. That podcast. And I think
a lot of scientists have not yet discovered that. That this is a, if
they apply same kind of rigor as they do to academic publication or to
even conference presentations, and they do that rigor and effort to
podcast, whatever that is, that could be a five-minute podcast, a two-
hour podcasts, it could be conversational, or it can be more like
lecture like, if they apply that effort, you have the potential to
reach over time, tens of thousands, hundreds of thousands, millions of
people. And that's really, really powerful. But yeah, for me giving a
platform to a few of those folks, especially for me personally, so
maybe you can speak to what fields you're drawn to, but I thought
computer scientists were especially bad at this. So there's brilliant
computer scientists that I thought it would be amazing to explore
their mind, explore their thinking. And so that I took that almost as
an, on as an effort. And at the same time I had other guests in mind,
or people that connect to my own interests. So the wrestling.
Wrestling, music, football, both American football and soccer. I have
a few particular people that I'm really interested in. Buvaisar
Saitiev. The Saitiev brothers, even Khabib for wrestling, just to talk
to them, 'cause. -- Oh, 'cause you can, you guys can communicate-
-- In Russian and in wrestling, right? As wrestlers and as Russians.
And so that little, it's like an opportunity to explore a mind that
I'm able to bring to the world. And also it, I feel like it makes me a
better person, just that being that vulnerable and exploring ideas
together. I don't know, like good conversation. I don't know how often
you have really good conversation with friends, but like podcasts are
like that. And it's deeply moving. -- It's the best. And what you
brought through. I mean, when I saw you sit down with Penrose, Nobel
Prize winning physicist, and these other folks that, it's not just
'cause he has a Nobel, it's what comes out of his mouth is incredible.
And what you were able to hold in that conversation was so much
better, light years beyond what he had any other interviewer, I don't
want to even call you an interviewer 'cause it's really about
conversation. Light years beyond what anyone else had been able to
engage with him was such a beacon of what's possible. And I know that,
I think that's what people are drawn to. And there's a certain
intimacy, that certainly to people, our friends, as we are, and they
know each other, that there's more of that, but there's an intimacy in
those kinds of private conversations that are made public. And. --
Well, that's the, with you, you're probably starting to realize, and
Costello, is like, part of it, because you're authentic and you're
putting yourself out there completely, people are almost not just
consuming the words you're saying, they also enjoy watching you,
Andrew, struggle with these ideas or try to communicate these ideas.
They like the flaws, they like a human being. -- Oh, good, that
flaws. -- Well, that's good 'cause I got plenty of those. -- But
they like the self-critical aspects, like where you're very careful,
where you're very self-critical about your flaws. I mean, in that same
way, it's interesting I think for people to watch me talk to Penrose,
not just because Penrose is communicating ideas, but here's this like
silly kid trying to explore ideas. Like they know this kid. There's a
human connection that is really powerful. Same, I think with Putin,
right? Like it's not just as a good interview with Putin, it's also,
here's this kid struggling to talk with one of the most powerful, some
will argue dangerous people in the world. They love that. The
authenticity that led up to that. And in return, I get to connect,
everybody I run to in the street and all those kinds of things,
there's a depth of connection there, almost within like a minute or
two that's unlike any other. -- Yeah, there's an intimacy that
you've formed with with them. -- Yeah, we've been on this like
journey together. And yeah, I have the same thing with Joe Rogan
before I ever met him, right? Like I was, because I was a fan of Joe
for so many years, there's something, there's a kind of friendship as
absurd as it might be to say in podcasting and listening to podcasts.
-- Yeah. Maybe it fills in a little bit of that or solves a little bit
of that loneliness that you've been talking about earlier. -- Until
the robots are here. [laughing] -- I have just a couple more
questions, but one of them is on behalf of your audience, which is,
I'm not going to ask you the meaning of the hedgehog, but I just want
to know, does it have a name?
And you don't have to tell us the name, but just, does it have a name?
Yes or no? -- Well, there's a name he likes to be referred to as,
and then there's a private name in the privacy of his own company that
we call each other. No. [Lex laughing] I'm not that insane. No, his
name is Hedgy. He's a hedgehog. I don't like stuffed animals. But his
story is one of minimalism. So I gave away everything I own, now three
times in my life. By everything I mean almost everything, kept jeans
and shirt and a laptop. And recently it's also been guitar, things
like that. But he survived because he was always in, at least in the
first two times was in the laptop bag, and he just got lucky. And so I
just liked the perseverance of that. And I first saw him in the, the
reason I got a stuffed animal, I don't have other stuffed animals, is
it was in a thrift store, in this like giant pile of stuffed animals
and he jumped out at me, because unlike all the rest of them, he has
this intense mean look about him. That he's just, he's upset at life,
at the cruelty of life. And it's just, especially in the contrast of
the other stuffed animals, they have this dumb smile on their face. If
you look at most stuffed animals, they have this dumb look on their
face. They're just happy. Is like "Pleasantville." -- It's what we
say in neuroscience, they have a smooth cortex, not many form. --
Exactly. And this, like Hedgy like saw through all of it. He was like
Dustyesky's man from underground. I mean, there's a sense that he saw
the darkness of the world and persevered. So like, and there's also a
famous Russian cartoon, "Hedgehog in the Fog" that I grew up with, I
connected with. [Lex laughing] People who know of that cartoon, you
could see it on YouTube, it's. - "Hedgehog in the Fog." -- Yeah.
[Lex laughing] It's just, as you would expect, especially from like
early Soviet cartoons. It's a hedgehog, like sad, walking through the
fog, exploring like loneliness and sadness. It's like, but it's
beautiful. It's like a piece of art, people should, even if you don't
speak Russian, you'll see, you'll understand. -- Oh, the moment you
said that I was going to ask, so it's in Russian? But of course it's
in- -- It's in Russian, but it's more, it's very little speaking in
it. It's almost a, there's an interesting exploration of how you make
sense of the world when you see it only vaguely through the fog. So
he's trying to understand the world. -- We have Mickey Mouse, we
have Bugs Bunny. We have all these crazy animals, and you have the
"Hedgehog in the Fog." -- So there's a certain period, and this is
again, I don't know what it's attributed to, but it was really
powerful, which there's a period in Soviet history, I think probably
'70s and '80s where like, especially kids were treated very seriously.
Like they were treated like they're able to deal with the weightiness
of life. And that was reflected in the cartoons. And there was, it was
allowed to have like really artistic content, not like dumb cartoons
that are trying to get you to like smile and run around, but like
create art. Like stuff that, you know how like short cartoons or short
films can win Oscars, like that's what they're swinging for. -- So
what strikes me about this is a little bit how we were talking about
the suit earlier, it's almost like they treat kids with respect. --
Yeah. -- Like that they have an intelligence and they honor that
intelligence. -- Yeah, they're really just adult in a small body.
Like you want to protect them from the true cruelty of the world. --
Sure. -- But in terms of their intellectual capacity or like
philosophical capacity, they are right there with you. And so that the
cartoons reflected that, the art that they consumed, education
reflected that. So he represents that. I mean, there's a sense of,
because it's survived so long and because I don't like stuffed
animals, that it's like we've been through all of this together and
it's the same, sharing the moments together as the friendship. And
there's a sense in which, if all the world turns on you and goes to
hell, at least we got each other. And he doesn't die, because he's an
inanimate object, so. -- Until you animate him. -- Until you
animate him. And then I probably would want to know what he was
thinking about this whole time. He's probably really into Taylor Swift
or something like that. And it's like that I wouldn't even want to
know anyway. -- Well, I now feel a connection to Hedgy, the hedgehog
that I certainly didn't have before. And I think that encapsulates the
kind of possibility of connection that is possible between human and
other object and through robotics certainly.
There's a saying that I heard when I was a graduate student that's
just been ringing in my mind throughout this conversation in such a, I
think appropriate way, which is that, Lex, you are in a minority of
one, you are truly extraordinary in your ability to encapsulate so
many aspects of science, engineering, public communication, about so
many topics, martial arts and the emotional depth that you bring to
it. And just the purposefulness, and I think if it's not clear to
people, it absolutely should be stated. But I think it's abundantly
clear that just the amount of time and thinking that you put into
things is, it is the ultimate mark of respect. So, I'm just
extraordinarily grateful for your friendship and for this
conversation. -- I'm proud to be a friend. And I just wished you
showed me the same kind of respect by wearing a suit and make your
father proud maybe next time. [Andrew laughing] -- Next time indeed.
Thanks so much my friend. -- Thank you. Thank you, Andrew. --
Thank you for joining me for my discussion with Dr. Lex Fridman. If
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