Video summary
In this episode of Huberman Lab Essentials, Dr. Andrew Huberman and Dr. Lex Fridman explore the philosophical and technical dimensions of artificial intelligence (AI), distinguishing it from machine learning and robotics by framing AI as both a computational toolset for automation and an attempt to understand human consciousness through intelligent systems. The conversation highlights deep learning techniques utilizing neural networks that learn tasks with minimal initial knowledge, contrasting supervised learning—which relies on labeled data like bounding boxes or semantic segmentation in computer vision—with self-supervised learning. Self-supervised learning aims to build "common sense" by allowing machines to ingest vast amounts of unannotated internet content, such as YouTube videos, thereby mimicking the way human children learn from observation before receiving specific instruction. This approach is exemplified by reinforcement learning successes like Alpha Zero and Alpha Go, where systems improve through self-play against mutated versions of themselves until they surpass world champions in games like chess. A significant portion of the discussion focuses on real-world applications, particularly Tesla's Full Self-Driving (FSD) system, which serves as a prime example of machine learning operating with human lives at stake. Dr. Fridman describes the "data engine" process used by Andre Karpathy and others, where autonomous vehicles are deployed to find edge cases—unforeseen failure scenarios—and feed that data back for retraining. While Elon Musk views semi-autonomous driving as a stepping stone toward full autonomy, Dr. Huberman argues that humans and robots must learn to "dance together" because both parties will always be flawed; the goal is not perfection but rather optimizing interactions where the sum of human and robotic capabilities exceeds their individual parts. This perspective extends to robotics generally, suggesting that flaws are features rather than bugs, enabling learning at the edge of one's capabilities through continuous interaction between imperfect humans and machines. The dialogue shifts toward the profound emotional potential of human-robot relationships, emphasizing time as a critical variable in forming connections regardless of whether the entity is biological or artificial. Dr. Fridman illustrates this with the concept of "shared moments," suggesting that even mundane interactions, such as eating ice cream late at night alongside a refrigerator, could become deeply meaningful if machines were capable of remembering and acknowledging these experiences. He envisions a future where every home device acts as a companion rather than just an appliance, similar to how dogs provide companionship but with the added ability to communicate verbally about traumas and triumphs. This vision challenges current fears regarding AI taking over or manipulating humans; instead, Dr. Fridman proposes that robots could engage in "benevolent manipulation" through power dynamics akin to those found in human relationships, such as a puppy looking cute to get attention, fostering deep bonds rather than servitude. The conversation takes an emotional turn when Dr. Huberman shares the story of his beloved Newfoundland dog, Homer, and discusses the recent passing of his bulldog, Castello. He recounts the difficulty of carrying Homer's heavy body for euthanasia after he could no longer stand due to spinal degeneration, a moment that crystallized the reality of death and loss. Similarly, Dr. Fridman details Castello's slow decline from abscesses and joint pain, noting how his eyes changed as he lost the ability to walk and sniff things out. Both speakers reflect on the grief associated with losing these companions but emphasize the importance of internalizing that loss rather than running away from it. They agree that while humans may anthropomorphize their pets or robots without fully understanding their mental states, the shared experiences create a depth of connection that is transformative, and they hope to immortalize Castello's spirit by sharing his traits—specifically his toughness paired with kindness—with others through the podcast. Ultimately, the episode concludes with mutual appreciation for each other's unique contributions: Dr. Fridman praises Huberman's ability to encapsulate science, engineering, martial arts, and emotional depth into public communication, while Huberman expresses gratitude for their friendship. They touch on the idea that figures like David Goggins have become verbs or adjectives in language, suggesting a desire to make Castello similarly iconic as an adjective describing someone who possesses his specific blend of resilience and sweetness. The discussion underscores that whether interacting with advanced AI systems, robots, or biological animals, the core human experience remains rooted in shared time, authentic moments, and the courage to feel joy and sorrow deeply together.
Read the full video transcript
Welcome to Huberman Lab Essentials,
where we revisit past episodes for the
most potent and actionable science-based
tools for mental health, physical
health, and
performance. And now, my conversation
with Dr. Lex Freriedman. We meet again.
We meet again. 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.
What is artificial intelligence and how
is it different from things like machine
learning and robotics?
So I think of artificial intelligence
first as a big philosophical thing. It's
our longing to create other intelligent
systems perhaps systems more powerful
than
us. At the more narrow level, I think
it's also a 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 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
uh computational techniques that allow
you to solve various problems. There's a
long history that uh approaches the
problem from different perspectives.
what's uh 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 the task
of learning. How do you make a machine
that knows very little in the beginning
follows some kind of process and learns
to become better and better in a
particular task?
What's been most uh 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. It's a network of these little
basic computational units called
neurons, artificial neurons. And they
have uh these architectures have an
input and an output. They know nothing
in the beginning and they're tasked with
learning something interesting. What
that something interesting is usually
involves a particular task. The 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
this broad category is uh the the neural
network knows nothing in the beginning
and then it's given a bunch of examples
of uh in computer vision that would 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 uh the
neural network is able to learn by
example that's called supervised
learning. The question there's a lot of
fascinating questions within that which
is how do you provide the truth when
you've 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 a the
computer knows nothing about our
three-dimensional world. It's just
looking at a set of pixels. So, uh
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 the
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. Their
attention they're overlapping is uh
what'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 into uh into the
task. So self-supervised learning is uh
more uh has been very successful in the
domain of uh language models natural
language processing and now more and
more it's being successful in computer
vision task and what's the idea there is
let the machine without any ground truth
annotation just look at pictures on the
internet or look at text on the internet
and try to learn something
uh 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 but we have this kind of
common sense knowledge and so the idea
with self-supervised learning is to
build this common sense 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 the dream
there is the you just you just let an AI
system that's uh self-supervised run
around the internet for a while, 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 uh children in
this way human children is your parents
only give one or two examples to teach a
concept. the the dream with
self-supervised learning is that would
be the same with with uh machines that
they would uh watch millions of hours of
uh 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 a thing with
pointy ears or a cat cat is a thing
that's orange or is furry they'll
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 would 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? Uh that's the whole
dream with self-supervised learning is
it would be able to learn that on its
own, that set of common sense knowledge
that's able to tell the difference. And
then there's like a lot of incredible
uses of self-supervised learning uh very
weirdly called self-play mechanism.
That's the mechanism behind the uh the
reinforcement learning successes of uh
the systems that won at uh go at uh
Alpha Zero uh that won at chess. Oh, I
see. that play games. That play games.
Got it. So the idea of
self-play, this probably applies uh to
other domains than just games, is a
system that just plays against itself.
And this is fascinating in all kinds of
domains. But uh it knows nothing in the
beginning. And the whole idea is it
creates a bunch of mutations of
itself and plays against those uh
versions of itself. 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 uh
David Silver, the creator of Alpha Go
and Alpha Zero, one of the leaders of
the team said uh to me is uh they
haven't found the
ceiling for Alpha Zero, 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 a bigger
deeper effect on human beings on
societies. Uh that could be a terrifying
process. To me it's an exciting process
if you supervise it correctly. If you
inject uh if uh what's called uh value
alignment you uh 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 uh
specifics of neural networks and all the
problems that people are 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
uh uh less and less human supervision of
neural networks. And also just a comment
and I'll shut up. No, please keep going.
I'm I'm learning. Uh 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. Even though it's called uh 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 the
the whole space which is a whole another
space of human robot interaction when AI
systems and humans work together to
accomplish task. That dance to me is uh
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 do humans and robots dance
together. To me semi-autonomous driving
is one of those spaces. So for uh for
Elon for example, he doesn't see it that
way. He sees uh semi-autonomous driving
as a stepping stone towards fully
autonomous driving. Like humans and
robots can't dance well together. Let
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 where it's
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 uh like the the
sum is bigger than the whole as opposed
to focusing on just building the perfect
robot. Mhm. So, so that's one of the
most exciting applications I would say
of artificial intelligence to me is
autonomous driving and semi-autonomous
driving and that's a really good example
of machine learning because those
systems are constantly
learning and uh there's a there's a
process there that maybe I can comment
on at the Andre 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 sending 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. You know we do this as kids
that you know you have we do this as
adults. We do this as adults. Exactly.
But we learn really quickly. But the the
whole point and this is the fascinating
thing about driving is you realize
there's millions of edge cases. uh
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 that are driving
around and something weird happens. And
so whenever this weird detector fires,
it's another important concept you that
piece of data goes back uh to the mother
ship for the 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. One of the
fascinating things about humans is we
figure out objective functions for
oursel like we are um it's the meaning
of life. Like why the hell are we here?
And uh a machine currently has to have
uh a hard-coded statement about why. It
has to have a meaning of yeah artificial
intelligence based life, right? 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 in order to
solve a problem, you have to formalize
it and you have to provide uh 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 ultimately currently the
uh there has to be a a formal objective
function. Now you could argue that
humans also has a set of objective
functions we're trying to optimize.
We're just not able to introspect them.
We yeah we don't actually know what
we're looking for and seeking and doing.
I think you've already told us the
answer, but does interacting with a
robot change you? Does it, In other
words, do do we develop relationships to
robots? I believe that most people have
uh an ocean of loneliness in them that
we haven't discovered that 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 uh
better people towards each other. So I
think that connection between human and
AI, human and
robot is is not only possible but uh
will help us understand ourselves in
ways that are like several orders of
magnitude uh deeper than we ever could
have imagined. So when I think about
human relationships, I I don't um always
break them down into variables, but we
could explore a few a few of those
variables and see how they map to human
robot relationships. Um one is just
time, right? If you spend zero time with
another person uh at all in in cyerspace
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 um wins and successes. You know, you
enjoy successes together. The other
would be failures. When you struggle
with somebody, you know, when you
struggle with somebody, you grow closer.
So, I've never conceptualize robot human
interactions this way. Um so, tell me
more about how this might look. Are we
thinking about um a human appearing
robot? um what is the ideal human robot
relationship? So there's uh a lot to be
said here, but you actually pinpointed
one of the big big first steps which is
this idea of time. 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. Um it's it's more
technical and probably a little bit
offline because I have kind of wild
ideas how that can revolutionize um
social networks and um and operating
systems. But the point is that element
alone, forget all the other things we're
talking about like emotions, um saying
no, all that. Just remember sharing
moments together would change
everything. We don't currently have
systems that uh um share share moments
together. Like even just you in your
fridge, just all those times you went
late at night and and ate the thing you
shouldn't have eaten, that was a secret
moment you had with your refrigerator.
You shared that moment, that darkness or
that beautiful moment where you just uh
you know 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 uh is is is tragic. And
once it does remember that, I think
you're going to be very attached to that
refrigerator. You you're going to go
through some through some hell with that
refrigerator. Most of us have like in in
the in the developed world have weird
relationships with food, right? So you
can go through some uh 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 uh
change society. Not just the
refrigerator but the these ideas in the
systems all around us. So that I 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
uh allowing you as a human to feel like
you're being
heard, truly heard, truly understood.
And I think there's a lot of ideas of
how to make AI assistance to be able to
ask the right questions and truly hear
another human. This is what we try to do
with podcasting, right? Uh, 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 uh 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've 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. 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 uh
somehow uh incapable of teaching us
something that's deeply human. I I don't
think uh humans have a monopoly on that.
I think we understand ourselves very
poorly and we need to to have the kind
of uh uh prompting from u from a
machine. Uh maybe the thing we want to
optimize for isn't necessarily uh like
some uh sexy uh like quick clips. Maybe
what we want is long form authenticity.
Depth depth from a like a very specific
engineering perspective is um I think a
fascinating open problem that hasn't
been really worked on very much. early
on in life uh in in 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 uh 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
uh robot from Boston Dynamics. Some
people might have seen it. It's this
yellow dog. This magic is something that
could be in every single device in the
world. The the way that I think uh maybe
Steve Jobs thought about the personal
computer. 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, but more like a companion, a
family member. A family member the way a
dog is. Mhm. But a dog that's al 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. Um but also to actually understand
what the hell like why are you so
excited about the successes like
understand the details understand the
traumas. I love this um desire to share
the delight of an interaction with a
robot. And as you describe it, I
actually I 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 Yeah. 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 uh is my Roomba vacuum where it
goes about it actually was pretty good
at picking up Costello's hair when he
was shed and then um and I was grateful
for it but then when it would when I was
on a call or something and it would get
caught on a on a wire or something, I
would find myself getting upset with the
Roomba in that moment. I'm like, "What
are you doing?" You know, and I and
obviously it's just doing what it does.
But but that's a kind of um mostly
positive but slightly negative
interaction. Um but what you're
describing 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. I
have a bunch of
Roombas and I did this experiment. Wait,
how many Roombas?
Sounds like a fleet of Roombas. Yeah. So
I uh probably seven or eight. That's a
lot of Roombas. So, you're going to So,
you have these seven or so Roombas. You
deploy all seven at once. Oh, no. I do
different experiments with them. Uh
different experiments with them. So, one
of the things I want to mention, I got
them to uh to scream in pain and moan in
pain um whenever they uh were kicked or
contacted. And I did that experiment to
see how I would feel. I I meant to do
like a YouTube video on it, but then it
just seemed very cruel. Did any Roomba
rights activists come after Yeah. Like I
I think if I release that video, I think
it's going to make me look insane, which
I I know people know I'm already insane.
Now you Now you have to release the
video. Sure. Well, I I think maybe if I
contextualize it by showing other robots
like to show why this is fascinating
because ultimately I felt like they 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 um dislike of of
pain. Mhm. So is the video available
online? No, I haven't uh I haven't
recorded it. I just had a bunch of
Roombas that are able to scream in pain.
um in my Boston uh in my Boston place.
What about um like uh shouts of glee and
delight? Well, I don't know how to I
don't how do to me delight is quiet,
right? But there's a way to frame its uh
it being quite dumb as uh almost cute.
You know, you almost connecting with it
for its dumbness. And I think that's a
artificial intelligence problem.
Interesting. I think flaws are should be
a feature not a bug. So along the lines
of this um 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 uh there's so much dimensionality
there so much to explore. But uh power
dynamics in relationships are very
interesting because the the obvious ones
that um the unsophisticated view of this
is you know one there's a master and a
servant right but there's also
manipulation. There's benevolent
manipulation. You know uh children do
this with parents. Puppies do this.
Puppies turn their head and look cute
and maybe give out a little little um
noise. Kids coup. And parents always
think that they, you know, they're doing
this because, you know, they 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
um uh you know 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 it you are under
the belief that you are in charge but
actually they're in charge. And so I
think that's one that
um if we could explore that for a
second, you could imagine it wouldn't
necessarily be bad, although it could
lead to bad things. Um the reason I want
to explore this is I think people always
uh default to the the extreme like the
robots take over and we're in little
jail cells and they're out having fun
and and ruling the universe. Uh what
what what sorts of manipulation can a
robot potentially carry out, good or
bad? Yeah. So there's a lot of good and
bad manipulation between humans, right?
Just like you
said to
me, especially uh like you said uh
topping from the bottom. Is that the
term? Uh so I think someone from MIT
told me that term
wasn't Lex.
Uh I think so. First of all, there's
power dynamics uh in bed and power
dynamics in relationships and power
dynamics on the street and in the work
environment. Those are all very
different. Uh I think um I think power
dynamics can make human relationships
especially romant romantic relationships
uh fascinating and rich and fulfilling
and exciting and all those kinds of
things. So, I
don't I don't think in themselves
they're bad. And the same goes with
robots. I really love the idea that a
robot would be a top or a bottom in
terms of like power dynamics. Uh, and I
think everybody should be aware of that.
And the manipulation is not so much
manipulation, but uh a dance of like
pulling away, a push and pull, and all
those kinds of things. Uh in terms of
control, I I think we're very very very
far away from AI systems. They're able
to uh lock us up. They uh uh to lock us
up in uh in it. You know, like to have
so much control that we basically cannot
live our lives in the way that we want.
I think there's uh 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. I do believe that
robots will have rights down the line.
And I think in order for in order for us
to have deep meaningful relationship
with robots, we would have to consider
them as entities in themselves that uh
deserve respect.
And that's a really interesting concept
that uh 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 is with dogs and uh other
animals can have rights on a level as
humans. We can't and nor should we do
whatever we want with animals. We have a
USDA. We have departments of uh of
agriculture that deal with um you know
animal care and use committees for
research for aggra you know for farming
and ranching and all that. So I I while
I when you first said it I thought wait
why would have there be a bill of
robotic rights but it absolutely makes
sense um in the context of everything
we've been talking about up until now.
Let's
um I if you're willing, I'd love to talk
about dogs because you've mentioned dogs
a couple times, a robot dog. Um you had
a a biological dog. Yeah. Yeah. I had a
a New Finland
uh named Homer uh for many years growing
up in Russia or in the US? In the United
States. And uh he was about over 200 lb.
That's a big dog. That's a big dog. If
people know people know Newf Finland, so
he's this black dog that's uh really uh
long hair and just a kind soul. I think
perhaps that's true for a lot of large
dogs, 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. Uh since Yeah. Since
the very very beginning till the very
very end. And one of the
things I mean he had this kind of uh we
mentioned like the Roombas he had a
kindhearted dumbness about him that was
just overwhelming. It's part of the
reason uh I named him Homer because it's
after Homer Simpson in case people are
wondering which Homer I'm referring to.
I'm not you
know so that there's a Yeah. Yeah.
Exactly. Uh there's a clumsiness that
was just uh something that immediately
led to a deep love for each other and
one of
the I mean he was always it's a shared
moments. He was always there for so many
uh nights together. That's a that's a
powerful thing about a dog that um he
was there through all the loneliness,
through all the tough times, through the
successes and all those kinds of things.
And I remember um I mean that was a
really moving moment for me. I still
miss him to this day. How long ago did
he die?
Um maybe 15 years ago. So it's it's been
a while,
but it was the first time I've really
experienced like the feeling of death
cuz So what happened is uh he uh he got
cancer and so he was dying slowly and
then at the certain point he couldn't
get up anymore. Uh there's a lot of
things I could say here. Um you know
that I struggle with that maybe uh maybe
he suffered much longer than he needed
to. That's something I really think
about a lot. But I remember I had to
take him to the hospital
and the nurses couldn't carry him.
Right. So you're talking about 200 lb
dog. I was really into powerlifting at
the time. I remember like they they they
tried to figure out all these kinds of
ways to uh so in order to put him to
sleep, they had to take him um into into
a room. And so I had to carry him
everywhere. And here's this dying friend
of mine that I just had to uh first of
all, it's really difficult to carry
somebody that heavy when they're not
helping you out. And
um yeah, so I remember it was the first
time seeing a friend laying there
and seeing life drained from his
body. And that realization that we're
here for a short time was made so real
that here's a friend that was there for
me the week before, the day before, and
now he's gone. And that was
um I don't know that that spoke to the
fact that you could be deeply connected
with the
dog. Also spoke to the fact that uh the
the shared moments together that led to
that deep friendship was
um are what make life so
amazing. But also spoke to the fact that
death is a [ __ ]
Um, so I know you've lost Castello
recently and you've been going and as
you're saying this, I'm definitely
fighting back uh the tears. I um I uh
thank you for sharing that that uh I
guess we're about to both cry over our
our dead
dogs that it was it was bound to happen
just given when this is when this is
happening. Um yeah, it's uh How long a
How long did you know that Castella was
not doing well? Um well, let's see. a
year ago during the start of about six
months into the pandemic, I he started
getting abscesses and he was not his
behavior changed and something really
changed. And then um I put him on
testosterone because uh which helped a
lot of things. It certainly didn't cure
everything, but it helped a lot of
things. cuz he was dealing with joint
pain, sleep issues, and then it just
became a very slow
decline to the point where, you know, 2
3 weeks ago, he had, you know, 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.
Still haven't cleaned up and removed all
his things because I can't quite bring
myself to do it. But, um, 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 dog. He wasn't 200 lb, but
he was about 90 pounds, but he's a
bulldog. That's pretty big. And he was
fit. Um, and then I noticed that he
wasn't carrying the 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 just that thing
was just flopping there. And then uh the
vet found some spinal degeneration and I
was told that the next one would go. Did
he suffer? Uh, sure hope not. Um, 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
talking about like the eyes and how what
they convey and what they mean about
internal states and for sake of robots
and biology of other kinds, but do you
think uh something about him was gone in
his eyes? I 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. This dog loved to pee on things.
It was amazing. I wondered where he put
it. He was like a reservoir of urine. It
was incredible. I'd think, oh, that's
it. He's just, he'd put like one drop on
the 50 millionth plant and then we get
to the 50 millionth and one plant and
he'd just have, you know, leave a
puddle. And here I am talking about
Costello peeing. Um, he was losing that
ability to stand up and do that. He was
falling down while he was doing that.
And I I do think he started to realize
and the the passage was easy and
peaceful, but
um, you know, I'll say this, I'm not
ashamed to say it. I mean, I wake up
every morning since then just I I don't
even make the conscious decision to
allow myself to cry. I wake up crying.
And I'm fortunately able to make it
through the day thanks to the great
support of my friends and and you and my
family. But um I miss him, man. You miss
him? Yeah, I miss him. And I feel like
uh he you know, Homer Costello, you
know, the relationship to one's dog is
so specific, but um so that that part of
you is gone.
That's the hard thing, you know.
Um, what's what what I think is
different is that I made the mistake. I
think 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, through
posting about him. I gave 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 because he was my first
dog, but I raised him since he was 7
weeks. Yeah. You got to hold it
together. I I noticed the the episode uh
you released on Monday, you mentioned
Costello, like you you brought him back
to life for me for that brief moment.
Yeah, but he's he's he's gone. Well,
that's
the He's going to be gone for a lot of
people,
too. Well, this is what I'm struggling
with. I know how to take care of myself
pretty well. Yeah. Not perfectly, but
pretty well. And I have good support. I
I do worry a little bit about how it's
going to land and how people will feel.
I'm I'm concerned about their
internalization. Um so that's something
I'm still I'm still iterating on. And
you have to they have to watch you
struggle which is fascinating. Right.
And I've mostly been shielding them from
this. But um what would make me happiest
if is if people would internalize some
of Costella's best traits. And his best
traits were that he was
incredibly tough. I mean he was a you
know 22inch neck bulldog the whole
thing. He was just born that way. But
was what was so beautiful is that his
toughness is never what he rolled
forward. It was just how sweet and kind
he was. And so if people can take that
then um then there's a win in there
someplace. So I I think there's some
ways in which he should probably live on
in your podcast too. you should uh I
mean it's such
a one of the things I loved about uh his
role in your podcast is that he brought
so much joy to you. We mentioned the
robots. Mhm. Right. I think uh 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. Uh
that's really powerful and I mean not to
this is this is like the Russian thing
is
um it's I it touched me when uh Louis CK
had that moment that I keep thinking
about in this um his show Louie where
like an old man was criticizing Louie
for whining about breaking up with his
girlfriend and he was saying like the
most uh the the most beautiful thing um
about uh love they 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 um
for your friend. So I you know and like
continue bringing that joy. I think it
would be amazing to the podcast. U I
hope to do the same with with robots or
whatever else is the source of joy,
right?
Um and maybe uh you think about one day
getting uh another dog. Yeah, in time.
Um, you're hitting on all the key
buttons here. Uh, I want that to we're
thinking about um, you know, ways to
kind of immortalize Costello in a way
that's real, not just, you know,
creating some little logo or something
silly. You know, Costello, much like
David Gogggins, is a a person, but
Gogggins also has grown into kind of a
verb. you're going to go this or you and
there's an adjective like that's extreme
like um I think that for me Costello was
all those things. He was a he was a
being. He was his own being. He was a
noun uh a verb and an adjective. So and
he had this amazing superpower that I
wish I could get which is this ability
to get everyone else to do things for
you without doing a damn thing. The
Costello effect as I call it. So as an
idea I hope he lives on. Um there's a
saying that I heard when I was a
graduate student that I that's just been
ringing in my mind throughout this
conversation in such a I think
appropriate way which is that uh Lexi
you are in a minority of one. You are
truly uh extraordinary in your ability
to encapsulate so many aspects of
science, engineering, public
communication about so many topics, uh
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 it is the ultimate mark of respect.
Um, so I'm just extraordinarily grateful
for your friendship and for this
conversation. I'm uh proud to be your
friend and I just wish you showed me the
same kind of respect by wearing a suit
and make your father proud. Maybe next
time. Next time indeed. Thanks so much,
my friend. Thank you. Thank you, Andrew.
[Music]