Kind: captions
Language: en
so big dog became LS3 which is the big
load carrying one just just a quick
pause it can carry 400
lb it was designed to carry 400 but we
had it carrying about 1,000 pounds one
of course you did just to sure we had
one carrying the other one we had two of
them so we had one carrying the other
one so one of the things that stands out
about the robots Boston Dynamics have
created is how beautiful the movement is
how natural the walking is and running
is even flipping with throwing is so
maybe you can talk about what what's
involved in making it look natural well
I think having good Hardware is part of
the story and people who think you don't
need to innovate Hardware anymore are
wrong the following is a conversation
with Mark ryber a legendary roboticist
founder and longtime CEO of Boston
Dynamics and recently the executive
director of the newly created Boston
Dynamics AI Institute that focuses on
research and The Cutting Edge on
creating future generations of robots
that are far better than anything that
exists today he has been leading the
creation of incredible legged robots for
over 40 years at CMU at MIT the
legendary MIT leg lab and then of course
boss and Dynamics with amazing robots
like big dog Atlas spot and handle this
was a big honor and pleasure for me this
is Alex Freedman podcast to support it
please check out our sponsors in the
description and now dear friends here's
Mark
rbert when did you first fall in love
with robotics well I was always a
builder from a from a young age I was I
was lucky my father was a
frustrated uh engineer and by that I
mean uh he wanted to be an aerospace
engineer but his mom from the old
country thought that that would be like
a grease monkey and so she said no so he
became an accountant but the but the
result of that was our basement was
always full of uh tools and equipment
and electronics and you know from a
young age I would watch him uh
assembling a kit an IO kit or something
like that I still have a couple of his
old IO kids and uh but it was really uh
during graduate school when
uh uh I followed a professor back uh
from class it was ber told horn at MIT
and I was taking a uh an interim class
it's IAP independent activities period
And I followed him back to his lab and
on the table was a a vik arm robot arm
taken apart in probably a thousand
pieces and uh when I saw that you know
from that day on uh I was a roboticist
do you remember the year 1974 1974 so
there's just this arm in pieces yeah and
you you saw the pieces and you saw in
your in Your Vision the the the arm when
it's back put back together and the
possibilities that holds somehow it uh
it spurred my imagination I I was in the
uh brain and cognitive Sciences
Department as a graduate student doing
neurophysiology I'd been a electrical
engineer as an undergrad at North
Eastern and uh the neurophysiology
wasn't really working for me you know I
it wasn't conceptu enough I couldn't see
really how by looking at single neurons
you were going to get to a place where
you could understand you know control
systems or thought or anything like that
and uh you know the AI lab was always an
appealing this was before seale right
this was in the 70s so the AI lab was
always an appealing idea and so when I
went back to the AI lab with uh you know
following him uh and I saw the arm I
just thought you know this is it that's
so interesting interesting the tension
between the the the BCS brain and
cognitive science approach to
understanding
intelligence and the robotics approach
to understanding intelligence well BCS
is now morphed a bit right they they
have the center for brains minds and
machines which is uh trying to bridge
that Gap and even when I was there you
know David Maher was in the AI lab David
Maher had models of the brain that were
appealing both to biologists but also to
uh computer people so he was a visitor
in the AI Lab at the time and I guess he
became full-time there so that was the
first time a bridge was made between
those two groups then the bridge kind of
went away and then there was another
time in the 80s and then recently uh you
know the last five or so years there's
been a stronger connection you said you
were always kind of a builder what
stands out to you in memory of a thing
you've built maybe a trivial thing that
just kind of like inspired um inspired
you and the possibilities that this
direction of work might hold I mean we
were just doing gadgets when we were
kids you know I have a friend we were
taking you know the I don't know if
everybody remembers but fluorescent
lights had this uh
little aluminum cylinder uh I can't even
remember what it's called now that you
needed a starter I think it was uh and
we would take those apart fill them with
match heads put a tail on it and make it
into little Rockets so it wasn't always
about function it was well well rocket
was pretty pretty much I guess that is
pretty functional but I guess that is a
question how much was it about function
versus just creating something cool I
think it's it's still a balance between
those two there was a time though when I
was a I guess I was probably already a
professor or maybe late in graduate
school when I thought that function was
everything and that uh you know Mobility
dexterity perception and intelligence
those are sort of the function the key
functionalities for robotics that um
that's What mattered and nothing else
mattered and I even had the kind of this
platonic
ideal uh that a robot if you just looked
at a robot and it wasn't doing anything
it would look like a pile of junk which
a lot of my robots looked like in those
in those days but then when it started
moving you'd get the idea that it you
know it had some kind of life or some
kind of interest in its movement and I
think we purposely even designed the
machines not not worrying about the
Aesthetics of the of the structure
itself uh but then uh but then you know
it turns out that the Aesthetics of the
thing itself add and combine with uh the
lifelike things that the robots can do
but the heart of it is you know making
them do things that are that are
interesting so one of the things that
underlies a lot of your work is that the
robots who create the systems you have
created for for over 40 years now have a
kind of they're not cauti I so a lot of
robots that people know about move about
this world very cautiously carefully
very afraid of the world uh a lot of the
robots you built especially in the early
days were very aggressive uh undere exu
they're hopping they're they're wild
moving quickly so what is there a
philosophy underlying that well let me
tell you about how I got started on legs
at all I when I was still a graduate
student I went to a conference and was a
biological legged Locomotion conference
and I think it was in Philadelphia so it
was all biomechanics people you know
researchers who would look at muscle and
maybe neurons and things like that they
weren't so much computational people but
they were more biomechanics and maybe
there were a thousand people there and I
went to a talk uh one of the talks all
the talks were about the body of either
animals or people and respiration things
like that but one talk was by a robotics
guy and he showed a six-legged uh robot
that walked very
slowly um it always had at least three
feet on the ground so it worked like a
table or a chair with tripod stability
and it moved really slowly and I just
looked at that and said wow that's wrong
you know that's not that's not anything
like how people and animals work because
we bounce and fly you know we have to
predict what's going to happen in order
to keep our balance when we're taking a
running step or something like that we
use springiness in our in our legs you
know our muscles and our tendons and
things like that as part of the story
you know the energy circulates we don't
just throw it away every time so and I'm
not sure I understood all that when I
first thought but I I definitely got
inspired to say you know let's try the
opposite and I didn't have a clue as to
how to make a Hopping robot work not
really you know not balance in 3D uh in
fact when I started it was all just
about the energy of bouncing and I was
going to have a springy thing in the leg
and some actuator so that you could get
an energy uh regime going of bouncing
and the idea that balance was an
important part of it didn't come until a
little later uh and then you know might
made the the one-legged the pogo stick
robots now I think that we need to do
that in manipulation if you look at
robot manipulation we've been working we
a community has been working on it for
50 years we're nowhere near human levels
of manipulation I mean we can you know
it's come along but I think it's all too
safe and I think trying to break out of
that safety thing of static grasping you
know if you look at the a lot of work
that goes on it's about the geometry of
the part and then and then you figure
out how to move your hand so that you
can position it with respect to that and
then you grasp it carefully and then you
move it well that's not anything like
how people and animals work you know we
juggle in our hands we had multiple
object objects and can sort them um so
now to be
fair uh being more aggressive is going
to mean things aren't going to work very
well for a while so it's a long it's a
longer term approach to the problem um
but that and that's just Theory now you
know maybe that won't pay off but that's
sort of how I'm trying to think about it
trying to uh encourage our group to to
go at it well yeah I mean we'll talk
about what it means to what is the
actual thing we're trying to optimize
and uh for a robot you know sometimes
especially with human robot interaction
maybe flaws is a good thing Perfection
is not necessarily the right thing to be
chasing just like you said maybe maybe
being good at fumbling an object uh
being good at fumbling might be the
right thing to optimize versus per
perfect modeling of the object and
perfect movement of the arm to gr grasp
that object cuz uh maybe Perfection is
not supposed to exist in the real world
I don't know if you know my friend Matt
Mason who's uh who was the director of
the robotics Institute at Carnegie melon
and we go back to graduate school
together but he analyzed um a movie of
Julia Child's doing a cooking thing and
she did I think he said something like
there were 40 different ways that she
handled a thing and none of them was
grasping he would she would nudge roll
flatten with her you know knife things
like that and none of them was grasping
so okay let's go back to the early days
first of all you've uh created and led
the the leg lab the legendary leg Lab at
MIT so what what was that first hopping
robot can you but first of all the leg
lab actually started at Carnegie melon
Carnegie melon so I was a professor
there starting uh in 1980 uh in to about
1986 and uh so that's where the first
topping machines were built uh starting
I guess we got the first one working in
about
1982 something like that that was a
simplified SP one then we got a
three-dimensional one in
1983 the quadruped that uh we built at
the leg lab the first version was built
in about
19845 and really only got going about 86
or so and took years of development to
get it to let's just pause here for
people who don't know I'm talking to
Mark rabert founder Boston Dynamics but
before that you were a professor
developing some of the most incredible
robots for 15 years and before that of
course a grud and all that so you've
been doing this for a really long time
so you like skipped over this but like
go go to the first hopping robot there's
videos of some of this I mean these are
incredible robots you talked about the F
the very first step was to get a thing
hopping up and down right and then you
realized well balancing is the thing you
should care about and it's actually a
solvable problem so can you just go
through how to create that robot what
was what sure what was involved in
creating that robot well I'm going to
start on the not the technical side but
the uh I guess we could call it the
motivational side or the funding side so
before Carnegie melon I was actually at
JPL at the jet propulsion lab for three
years and while I was there I connected
up with Ivan southernland who is
sometimes regarded as the father of
computer Graphics because of work he did
both at MIT and then University of Utah
and Evans and Southerland anyway
um I got to know him and at one point he
said uh he encouraged me to uh do some
kind of project uh at Caltech even
though I was at JPL you know those are
kind of related
institutions and uh so I I thought about
it uh and I made up a list of three
possible projects and I purposely made
the top one and the bottom one really
boring sounding and in the middle I put
uh pogo stick robot and when he looked
at it you know Ivan is a a brilliant uh
you know brilliant guy brilliant
engineer and uh real cultivator of
people he looked at it and knew right
away what the thing that was worth doing
and so he you know he had an endowed
shair so he had about $3,000 that he
gave me to build the first model which I
went you know I went to the shop and
with my own hands kind of made a first
model which which didn't work uh and was
just you know a beginning
uh shot at it and uh Ivan and I took
that to Washington and in those days you
could just walk into DARPA and walk down
the hallway and see who's there and Ivan
who had been there in his previous life
and so we walked around and uh we looked
in offices of course I didn't know
anything you know I was basically a kid
but Ivan knew his way around and we
found Craig Fields uh in his office
Craig later became the director of DARPA
but in those days he was a program
manager and so we went in I had a little
Samsonite suitcase we opened and it had
just the skeleton of this uh on lugged
hopping robot and we showed it to him
and uh you could almost see the drool
going down his chin ex excitement and he
sent me $250,000 he said okay uh I'll uh
I want to fund this uh and I was between
institutions I was just about to leave
JPL and I hadn't decided yet where I was
going next and then when I landed at CMU
he sent $250,000 which in 1980 was a lot
of a lot of research money did you see
the possibility of where this is going
why this is an important problem no the
balancing I mean it's legged it it has
to do with legged Locomotion I mean it
has to do with all these problems that
that that are the human body solves them
when we're walking for example like all
the fundamentals are there yeah I mean I
think that was the motivation to try and
get more at the fundamentals of how
animals work but the idea that it would
result in you know machines that were
anything like practical uh like we're
making now that that wasn't anywhere in
my head no you know as an academic I was
mostly just trying to do the next thing
you know make some progress impress my
colleagues if I could and have fun and
have fun pogo stick robot pogo stick
robot so what was on the technical side
what are the some of the challenges of
getting a getting to the point where we
saw like in the video the the pogo stick
robot that's actually successfully
hopping and then eventually doing flips
and all this kind of stuff well in the
very early days I needed some better
engineering than I had than I could do
myself and I hired uh Ben Brown we we
each had our way of contributing to the
design and we came up with a thing that
could could start to work I had some
stupid ideas about how the actuation
system should work and uh we you know we
sorted that out it wasn't that hard to
make it Balan once you get the the
physical machine to be working well
enough uh and have enough control over
the degrees of freedom uh and then we
very quickly you know we started out by
having it floating on an inclined air
table and then uh that only gave us like
six foot of travel so once it started
working we switched to a thing that
could run around the room on a another
device it's hard to explain these
without you seeing them but you probably
know what I'm talking about a plan
ariser and uh and then the next big step
was to make it work in 3D which that was
really the scary part would the simple
things you know people had inverted
pendulums at the time for for years and
they could control them by driving a
cart back and forth but could you make
it work in three dimensions while it's
bouncing and all that and uh but it
turned out you know not to be that hard
to do uh at least at the level of
performance we achieved at the time so
okay you mentioned inverted pendulum but
like uh can you explain how a Hopping
stick in 3D can
control can balance itself yeah what
what does the actuation look like uh you
know the simple story is that there's
three things going on there's something
making it bounce and you know we we had
a system that was uh estimating how high
the robot was off the ground and using
that you know uh there's energy that can
be in three places in a in a pogo stick
one is in the spring one is in the
altitude and the other is in the
velocity and so when at the top of the
Hop it's all in the the a height and so
you could just measure how high you're
going and thereby thereby have an idea
of a lot about the cycle and you could
decide whether to put more energy in or
less so that was one element then
there's a part that you decide where to
put the foot and if you think when
you're landing on the ground with
respect to the center Mass so if you
think of a pole vter the key thing the
pole vter has to do is get its body to
the right place when the pole gets stuck
if they're too far forward uh they kind
of get thrown backwards if they're too
far back they go you know over and what
they need to do is get it so that they
go mostly up to get over the thing and
you know High jumpers is the same kind
of thing so there's a calculation about
where to put the foot and we did
something you know relatively simple and
then there's a third part to keep the
body at an attitude that's upright
because if it gets too far you know you
could hopen just keep rotating around
but if it gets too far then you run out
of Mo of the joints at the hips so you
have to do that and we did that by
applying a torque between the legs and
the body every time the foot's on the
ground you only can do it while the
foot's on the ground in the air you know
it it it the physics don't work out how
far does it have to tilt before it's too
late to be able to balance itself or
it's impossible to balance itself
correct itself well you're you're asking
interesting question because
um in those days we didn't actually
optimize things and they probably could
have gone much further than we did and
then had higher performance and we just
kind of got you know a sketch of a
solution and worked on that and then in
years since some people working for us
some people working for others people
came up with all kinds of uh equations
for or you know algorithms for how to do
a better job be able to go faster one of
my students worked on getting things to
go faster another one worked on uh
climbing over obstacles cuz when you're
running it's on the open ground it's one
thing if you're running like up a stair
uh you have to adjust where you are
otherwise things don't work out right
you land your foot on the edge of the
steps so there's other degrees of
freedom to control if you're getting to
you know more realistic practical
situations I think it's really
interesting to ask about the early days
cuz you know believing in yourself
believing that there's something
interesting here and then you mentioned
find finding somebody else Ben Brown
what's that like finding other people
with whom you can build this crazy idea
and actually make it work probably the
smartest thing I ever did is to find the
other people I mean when I look at it
now you know I look at Boston Dynamics
and all the really excellent engineering
there you know people who really make
stuff work you know I'm I'm only the the
dreamer so when you talk about pogo
stick robot or legged robots whether
it's quadrupeds or humanoid robots did
people doubt that this is possible did
you experience a lot of people around
you kind of I don't I don't know if they
doubted whether it was possible but I
think they thought it was a waste of
time oh it's not even an interesting
problem I think for a lot of people you
know people who were I think it's been
it's been both though some people I
think I felt like they were saying oh
you know why you wasting your time on
this stupid problem and then but then
I've been at many things where uh people
have told me it's been an inspiration to
uh to go out and uh you know attack
these uh
these harder things and and I think it
has turned out I think legged Locomotion
has turned out to be a useful thing did
you ever have like doubt about bringing
Atlas to life for example or or or with
big dog just every step of the way did
you have doubt like what this is this is
too hard of a problem I mean at first I
wasn't an Enthusiast for the humanoids
because again it goes back to saying
what's the functionality and the form
wasn't as important as the
functionality uh and I and also you know
there's a an aspect to humanoid robots
that's about uh all about the Cosmetics
where there isn't really other
functionality and that kind of is
offputting for me uh as a roboticist I
think the functionality really matters
so probably that's why I avoided uh
human robots humanoid robots to start
with but I'll tell you um now you know
after we started working on them you
could see that the the connection and
the impact with with other people
whether they're lay people or even other
technical people uh there's a there's a
a special thing that goes on uh even
though most of the humanoid robots
aren't that much like a person but we
anthropomorphize and we see the humanity
U but also like with with spot you can
see not the humanity but the what
whatever we find compelling about social
interactions there in spot as well I'll
tell you you know I go around giving
talks and take spot to to a lot of them
and it's amazing the media likes to say
that they're terrifying and and that
people are afraid and and YouTube
commenters like to say that it's
frightening but when you take a spot out
there now maybe it's self- selecting but
you get a crowd of people who want to
take pictures want to pose for selfies
want to operate the robot want to pet it
want to put clothes on it uh it's
amazing yeah love spot so if we uh move
around history a little bit so you said
I think in the early days of Boston
Dynamics that you quietly worked on
making a running version of IBO yeah
yeah son's robot dog yeah this just an
interesting uh little tidbit of history
for me um what what what like what
stands out to your memory from that task
for people don't know that little dog
robot moves slowly how did that become
big dog what was involved there what was
the dance between how do we make this
cute little dog versus a thing that can
actually carry a lot of payload to move
fast and stuff like that what the
connection was is that at that point
Boston Dynamics was mostly a
physics-based simulation company so when
I left MIT to start Boston Dynamics you
know there was a few years of overlap
but the concept wasn't to start a robot
company the concept was to use this uh
Dynamic simulation tool that we
developed to do robotics to for other
things uh but working with Sony we got
back into robotics uh by doing the IBO
Runner by we programmed we made made
some tools for programming curio uh
which was a small a humanoid this big uh
that could do some dancing and and other
kinds of fun stuff and I don't think it
ever reached the market even though they
they did show it um you know when I look
back I say that we got us back where we
belonged yeah you rediscovered the soul
of the company that's right and so from
there it was always about robots
yeah uh so you started Boston Dynamics
in
1992 right uh what are some fond
memories from the early
days uh one of the robots that we built
wasn't wasn't actually robot it was a
surgical simulator but it had force
feedback so it had all the techniques of
Robotics and you look down into this uh
mirror it actually was and it looked
like you were looking down onto the body
you were working on your hands were
underneath the mirror so there were
where you were looking and you had Tools
in your hands that were connected up to
to these force feedback devices made by
uh another MIT spinout sensible
Technologies so they made the force
feedback device we attached the tools
and we wrote all the software and did
all the graphics so we had 3D computer
Graphics it was in the old days when
this was in the late 90s when you had uh
the Silicon Graphics computer that was
about this big uh you know it was the
heater in the office basically and uh
and we were doing uh surgical operations
Anastos is which was uh stitching tubes
together you know tubes like blood
vessels or other things in their body
and you could feel and you could see the
tissues move and it was really exciting
and the idea was to make a trainer to
teach surgeons how to do stuff we built
a scoring system because we interviewed
uh surgeons that told us you know what
you're supposed to do and what you're
not supposed to do you're not supposed
to tear the tissue you're not supposed
to touch it in any place except for
where you're trying to engage there were
a bunch of rules so we built this thing
and took it to a trade show uh a
surgical trade show and the surgeons
were practically lined up well we we
kept the score and we posted their
scores like on a video game and those
guys are so competitive that they really
uh really love doing it and they would
come around and they see someone's score
was higher there so they would come back
but we figured out shortly after that we
thought surgeons were going to pay us to
get trained on these things and the
surgeons thought we should pay them in
order to uh so they could teach us about
the thing and there was no money from
the surgeons and we looked at it and
thought well maybe we could sell it to
hospitals that would teach train their
surgeons and then we said well we're
this at the time we were probably a 12
person company or maybe 15 people I
don't remember uh you there's no way we
could go after a marketing activity you
know the company was all bootstrapped in
those years we we never had investors
until Google bought us which was after
20 years so we didn't have any resour
sources to uh to go after hospitals so
we at one sort of at one day Rob and I
were looking at that and we said we
built another Simulator for knee
arthoscopy and we said this isn't going
to work and we killed it and we moved on
and that was really a milestone in the
company because we you know we sort of
understood who we were and uh and what
would work and what wouldn't even though
technically it was really a fascinating
thing what was that meeting like were
you just like sit at a table you know
what probably we're going to Pivot
completely we're going to let go of this
thing we put so much hard work into and
then go back to the thing it just always
felt right once we did it you know just
look at each other and said let's let's
build robots yeah what was the first
robot you built under the the flag of
Boston Dynamics big dog well there was
the ibow uh runner but it wasn't even a
whole robot it was just legs that we we
took off the legs on eyeballs and
attached uh legs we'd made and um you
know we got that working and showed it
to the Sony people uh we worked pretty
closely with Sony in those years one of
the interesting things is that uh it was
before the internet and zoom and
anything like that so we had six ISDN
lines installed and we would have a
telecon every week that worked at very
low frame rate something like 10 Hertz
uh you know Engish
across the boundary with uh Japan was a
challenge trying to understand what what
each of us was saying and have meetings
every week uh for for several years uh
doing that and uh it was a pleasure
working with them they were really
supporters they they seemed to like us
and what we were doing that was the real
transition from us being a simulation
company into being a robotics company
again it was a quadruped the the legs
were four legs or two legs four legs
yeah and what did you learn from that
experience of uh building a basically a
fast-moving
quadraped mostly we learn that something
that's
small uh doesn't look very exciting when
it's running it's like it's scampering
and you had to you had to watch a
slow-mo for it to look like it was
interesting if you watch it fast it was
just like a funny one of my things was
to show stuff in video even from the
very early days of the hopping machines
um and so I was always focused on how's
this going to look through the
viewfinder and uh running eyebow didn't
look so cool through the
viewfinder so uh what what came next in
terms of uh what was a big next
milestone in terms of a robot you built
I mean you got to say that big dog was
you know sort of put us on the map and
got our heads really pulled together we
scaled up the company big dog was the
result of uh Allan Rudolph at DARPA uh
starting a biotics program and he put
out a you know a request for proposals
and uh I think there were 42 proposals
written and three got funded one was Big
Dog one was a climbing robot rise and
you know that put things in motion we we
hired uh Martin buer he was a professor
at M in Montreal at McGill he was uh
incredibly important for getting big dog
uh out of the lab and into the mud which
is a you know was a key step to really
be willing to go out there and uh and
build it break it fix it which is sort
of one of our mots at the company so
testing it in the real world for people
for people who don't know Big Dog maybe
you can correct me but it's a it's a big
quadruped four-leg robot that it looks
big could probably carry a lot of weight
not the most weight that Boston dyam
have built but a lot well it's the first
thing that worked so let's see if we go
back to the leg lab we built a quadruped
that could do many of the things that
big dog did but it had uh a hydraulic
pump sitting in the room with hoses
connected to the robot it had a vax
computer in the Next Room it needed its
own room because it was this giant thing
with air conditioning and it had this
very complicated uh bus connected to the
robot and the robot itself just had the
actuators it had gyroscopes for sensing
and other some other sensors uh but all
the power and Computing was offboard big
dog had all that stuff integrated uh on
the platform it had a gas engine for
power which was a very complicated thing
to to undertake it had to convert the
rotation of the engine into hydraulic
power which is how we uh actuated uh it
so there was a lot of learning just on
the uh you know building the physical
robot and and the system integration for
that and then there was the controls uh
of it so for Big Dog you brought it all
together on one platform right and then
so you could you could you could take it
out in the woods yeah and you did we did
we spent a lot of time down at the uh
Marine Corps Base in quano where there
was a trail called The gule Canal Trail
and our uh Milestone that DARPA had
specified was that we could go on this
one particular trail that involved you
know a lot of Challenge and we spent a
lot of time our team spent a lot of time
down there those were fun days hiking
with the robot so what did you learn
about like what it takes to balance a
robot like that on a trail on a hiking
trail in the woods basically forget the
woods just the real world that's the big
leap into testing in the real world yeah
as challenging as the woods were working
inside of a home or in an office is
really
harder yeah because when you're in the
woods you can actually take any path up
the up the hill all you have to do is
avoid the obstacles you there's no such
thing as damaging the woods at least you
know to first order whereas if you're in
a house you can't leave scuff marks you
can't bang into the walls the robots
aren't very comfortable bumping into the
walls especially in the early days so I
think those were actually bigger
challenges once once we fa them uh it
was mostly you know getting the systems
uh to work well enough together the the
hardware systems to work and and the
controls in those days we did have a
human operator who did all the visual
perception uh going up the guad Canal
Trail so you there was an operator who
was right there who was very skilled at
even though the robot was balancing
itself and placing its own feet uh if
the operator didn't do the right thing
it wouldn't go but years later we went
back with one of the electric the pre
precursor to spot and uh we had Advanced
the controls and everything so much that
uh an amateur complete amateur could
operate the robot the first time up and
down and up and down whereas it taken us
years to to get there in the previous
robot so if you fast forward big dog
eventually became spot so big dog became
LS3 which is the big load carrying one
just just a quick pause it can carry 400
lb it was designed to carry 400 but we
had it carrying about a th000 pounds one
of course you did just we had one
carrying the other one we had two of
them so we had one carrying the other
one there's a little clip of that we
should put that out somewhere that's
from like 20 years ago but wow wow and
it it can go for very long distances you
can travel 20 mies yeah uh gasoline
gasoline yeah and that that event just
okay sorry so LS3 then what uh how did
that lead to spot so big dog and LS3 had
uh engine power and hydraulic
actuation then we made uh a robot that
was electric uh Power so there's a
battery driving a motor driving a pump
but still hydraulic actuation yeah Larry
sort of asked us could you make
something that weighed 60 pounds that
would not be so intimidating if you had
it in a house uh where there were people
and that was the inspiration behind uh
the spot pretty much as it exists today
we did a prototype the same size that
was the first all El electric um nonel
non-hydraulic robot what was the
conversation with Larry paage like about
so here's a guy that kind of is very
product focused and can can see a for
like what the future holds that's just
interesting kind of aside what was the
brainstorm about the future robotics
with him like I mean it was almost as
simple as what I just said he you know
we having meeting he said yeah gez you
know do you think you could make a
smaller one that wouldn't be so
intimidating you like a big dog yeah uh
if it was in your house and I said yeah
we could do that and we started and and
did is there a lot of technical
challenges to go from hydraulic to
Electric you know I had been in love
with hydraulics and still uh love
Hydraulics uh you know it's it's a great
technology it's too bad that the somehow
the the world out there looks at it like
it's oldfashioned or that it's um icky
and it's true that you do it is very
hard to keep it from having some amount
of dripping from time to time uh but if
you look at the performance uh you know
how strong you can get in a lightweight
package and of course we did a huge
amount of innovation most of hydraulic
uh control that is the valve that
controls the flow of oil had been
designed in the ' 50s for airplanes it
had been made robust enough safe enough
that you could count on it so that
humans could fly in airplanes and very
little Innovation had happened you know
that might not be fair to the people who
make the valves I'm sure that they did
innovate but the basic design had stayed
the same and there was so much more you
could do and so our Engineers designed
valves uh the ones that are in uh in
Atlas for instance that had new kinds of
circuits they sort of did some of the
Computing that could get you much more
efficient use they were much smaller and
lighter so the whole robot could be
smaller and lighter uh we made a
hydraulic power supply that had a bunch
of components integrated in this tiny
package it's about this big you know the
size of a football weighs five uh
kilograms and it produces 5 kilowatts of
power of course it has to have a battery
operating but it's got a motor a pump
filters heat exchanger to keep it cool
some valves all of all in this tiny
little package so Hydraulics you know
could still have a ways to go one of the
things that stands out about the robots
Boston Dynamics have created is how
beautiful the movement is how natural
the walking is and running is even
flipping with throwing is so maybe you
can talk about what what's involved in
making it look natural well I think
having good Hardware is part of the
story and people who think you don't
need to innovate Hardware anymore are
wrong in my opinion um so I think one of
the things certainly in the early years
for me taking a dynamic approach where
you think about what's the evolution of
the motion of the thing going to be uh
in the future and having a prediction of
that that's used at the time that you're
giving signals to it as opposed to it
all being serving which is servoing is
sort of backward looking it says okay
where am I now I'm gonna I'm G to try
and adjust for that but you really need
to think about what's coming so how far
ahead do you do you have to look in time
uh it's interesting I think that the
number is only a couple of seconds for
spot so there's a limited Horizon uh
type approach where you're recalculating
assuming what's going to happen in the
next a second or second and a half and
then you keep iterating you know at the
next even though a tenth of a second
later you'll say okay let's do that
again and see what's happening and
you're looking at what the obstacles are
where the feet are going to be placed
how to you know you have to coordinate a
lot of things if you have obstacles and
you're balancing at the same time and
it's that uh limited Horizon type
calculation that's doing a lot of that
but if you're doing something like a
somersault you're looking out a lot
further right if you want to stick the
landing you have to get the you you have
to at the time of launch have uh you
know momentum and uh rotation all those
things coordinated so that a landing is
Within Reach how hard is it to stick a
landing I mean it's very much undere
actuated like you once you've in the air
you don't have as much control about
anything so how hard is it to get that
to work you first of all did flips with
a Hopping robot
if you look at the first time we ever
made a robot do a somersault it was in a
planer robot you know it had a boom uh
so it could only it was restricted to
the surface of a sphere we call that
planer so it could move for and a it
could go up and down and it could rotate
and so the calculation of what you need
to do to get a to stick a landing isn't
all that complicated you have to look at
you know you have to get time to make
the rotation so how hard you jump how
high you jump gives you time uh you look
at how quickly you can rotate and so you
know if you get those two right then
when you land you have the feet in the
right place and you have to get rid of
all that rotational and uh linear
momentum but you know that's not too
hard to figure out and we made you know
back in uh about 1985 or six I can't
remember we had a simple robot doing
somersaults to do it in 3D really the
calculation is the same you just have to
be balancing in the other degrees of
freedom if you just doing a somersault
it's just a a planer thing R Rob was my
graduate student and we were at MIT
which is when we made you know a
two-legged robot do a 3D somersault for
the first time um there we in order to
get enough rotation rate you needed to
do tucking also uh you know withdraw the
legs in order to accelerate it and he
did some really fascinating work on on
how you stabilize more complicated
Maneuvers remember he was a gymnast a
champion gymnast before he'd come to me
so he had he had the physical abilities
and he was a you know an engineer so he
could translate some of that into the
math and the algorithms that you need to
to do that he knew how humans do it he
just had to get robots to do the same
unfortunately though when you humans
don't really know how they do it yeah
right we we're coached we we have ways
of learning but do we really understand
in a physical in a physics way uh what
we're doing probably most gymnast and
athletes don't know so in some way by
building robots you are in part
understanding how humans do like walking
most of us walk without considering how
we walk really right and how we make it
so natural and efficient all those kinds
of things at still doesn't walk like a
person and it still doesn't walk quite
as gracefully as a person even though
it's been getting closer and closer the
running might be close to a human but
the Walking is Still a challenge that's
interesting right that running is closer
to a human
it just shows that the more aggressive
and kind of the more you leap into the
unknown the more natural it is I mean
walking is kind of falling always right
and something weird about the knee that
you can kind of do this folding and
unfolding and get it to work out just a
human can get it to work out just right
there's compliances compliance means
springiness in the in the design that
are important to how it all works well
we used to have a motto at the bosson
Dynamics in the early days which was you
have to run before you can
walk uh that's a that's a good motto CU
you also had
Wildcat which was one of the along the
way towards spot which is a quadruped
that went 19 M an hour right on flat
terrain is that the fastest you've ever
built oh yeah might be the fastest
quadruped in the world I don't know for
quadruped probably of course it was
probably the loudest too so we had this
little racing go-kart engine on it and
we would get people from you know three
bill away uh sending us you know
complaining about how loud it was so at
the leg lab I believe most of the robots
didn't have
knees how what's the how do you figure
out what is the right number of
actuators what what are the joints to
have what do you need to have uh you
know we humans have knees and all kinds
of interesting stuff on the feet the toe
is an important part I guess for humans
or maybe it's not I inured my my toe
recently and it made running very
unpleasant so that seems to be kind of
important so how do you figure out for
efficiency for function for Aesthetics
uh how many joints to have how many
actuates to have well it's always a
balance between wanting to get where you
really want to get and what's practical
to do based
on uh your resources or what you know
and all that so I mean the whole idea of
the of the POG stick was to do a simp
ific ation obviously it didn't look like
a human I think a technical scientist
could appreciate that we were capturing
some of the things that are important in
human Locomotion without it looking uh
like it without having a knee an ankle
I'll tell you the first sketch that Ben
Brown made uh when we were talking about
building this thing was a very
complicated thing with zillions of
Springs lots of joints it looked like
much more like a a kangaroo or a or an
ostrich or something like that things we
were paying a lot of attention to at the
time um you know so my job was to uh say
okay well let's do something simpler to
get started and maybe we'll get there at
some point I just love the idea that you
you you two were studying Kangaroos and
ostriches oh yeah we we did uh we filmed
and and digitized uh uh data from horses
I I did a dissection of a ostrich at one
point which has absolutely remarkable
legs dumb question uh do o have like mus
mus a lot of musculature on the legs or
no most of it's up in the feathers but
there's a huge amount going on in the
feathers including a knee joint the knee
joint's way up there the thing that's
halfway down the leg that looks like a
backwards knee is actually the ankle the
thing on the ground which looks like the
foot is actually the toes it's an
extended toe fascinating but you know
the basic morphology is in is the same
in in uh all these animals what do you
think is the the most beautiful movement
of an animal like what animal you think
is the coolest land animal let's gool
cuz fish is pretty cool like the way
fish goes to water but like legged
Locomotion you know the slow MOS of
cheetah's running are are incredible you
know they're they there's so much back
motion and uh you know Grace and they of
course they're moving very fast uh the
animals running away from the cheetah
pretty exciting you know the prong Horn
uh which you know they they do this all
four legs at once jump called the prong
to kind of confuse the especially if
there's a group of them to confuse
whoever's chasing them so they do like a
misdirection type of thing yep they do
MISD Direction thing the Fronton views
of the cheetah is running fast where the
tail is whipping around to help in the
turns to help us stabilize in the turns
so that's pretty exciting cuz they spend
a lot of time in the air I guess as
they're running that fast but they also
turn very fast is that a tail thing or
is that do you have to have contact with
the ground oh everything in the body is
probably helping turn because they're
chasing something that's trying to get
away that's also zigzagging around but I
I I would be remiss if I didn't say you
know humans are are pretty pretty good
too you know you watch gymnast uh
especially these days they're doing just
incredible uh stuff well like especially
like Olympic level gymnast see but there
could be I there could be cheetah their
Olympic level we might be watching the
average cheetah versus like that could
be like a really special cheetah that
can do like you're right when did the
knees first come to play in in you
building legged robots uh in Big Dog big
dog yeah big dog came first and then
little dog was later and you know there
was a there's a big compromise there uh
human knees have multiple muscles and
you could argue that
there's uh I mean it's a technical thing
about negative work uh when you're when
you're Contracting a joint but you're
pushing out that's negative work and if
you don't have a place to store that it
can be very expensive to do negative
work and most of and in Big Dog there
was no place to store negative work uh
in the
knees but big dog also had pogo stick uh
Springs down below so part of the action
was to comply in a bouncing motion you
know later on in spot we we took that
out and as we got further and further
away from the leg lab uh we had more uh
you know energy-driven
controls is there something to be said
about like knees that go uh forward
versus backward sure there's this idea
called the passive Dynamics which says
that although although you can use
computers and actuators to make a motion
a me a mechanical system can make a
motion just by itself if it gets
stimulated the right way uh so uh Tad
mcgear in the uh I think in the mid 80s
uh maybe it was in the late 80s starting
to started to work on that and he made
this uh legged system that could walk
down an inclined plane where the legs
folded and unfolded and swung forward
you know do the whole walk Walking
motion where the only thing there was no
computer there were some adjustments to
the mechanics so that there were dampers
and springs in some places that help the
uh the mechanical action happen it was
essentially a mechanical computer and
the idea the interesting idea there is
that it's not all about the brain uh
telling dictating to the body what the
body should do the body is a participant
in the motion so a a great design for a
robot has a mechanical component where
the movement is efficient even without a
brain yes how do you design that I think
that these days most robots aren't doing
that most robots are are basically using
the computer to to govern the motion now
the the brain though is taking into
account what the mechanical thing can do
uh and how it's going to behave
otherwise it would have to really
forcefully move everything around all
the time which probably some solutions
do but I think you end up with a more
efficient and more graceful thing if
you're taking into account what the what
the machine wants to do so this might be
a good place to mention you're
now uh leading up the the Boston
Dynamics AI Institute newly formed which
is focused more on designing the robots
of the
future I think one of the things maybe
you can tell me the big vision for
what's going on but one of the things is
uh this idea that Hardware still matters
with with Organic design and so on maybe
before that can you zoom out and tell me
what the vision is for the AI in
Institute you know I like to talk about
intelligence having two parts an
athletic part and a cognitive part and
uh I think you know Boston Dynamics in
my view has sort of set the standard for
uh what athletic intelligence can be and
you know it has to do with all the
things we've been talking about the the
mechanical design the the real-time
control the energetics and that kind of
stuff but obviously uh people have
another kind of intelligence and and
animals have another kind of
intelligence you know we can make a plan
uh our meeting started at at 9:30 I
looked up on Google Maps how long it
took to walk over here was you know 20
minutes so uh I decided okay I'd leave
my house at 9ine which is what I did um
you know simple intelligence but we use
that kind of stuff all the time it's
sort of what we think of as going on in
our heads um and I think that's in short
supply for robots most robots are pretty
dumb and as a result it takes a lot of
skilled people to program them to do
everything they do and it takes a long
time and if robots are going to you know
satisfy our dreams uh they need to be
smarter uh so the in AI Institute is
designed to combine that physicality of
the athletic side with uh the cognitive
side so for instance we're trying to
make robots that can walk a human do a
task uh understand what it's seeing and
then do the task itself so sort of OJT
for Rob on the job training for robots
uh as a
paradigm uh now you know that's pretty
hard uh and it's it's sort of Science
Fiction but our idea is to work on a
longer time frame and and work on uh
solving those kinds of problems and I
have a whole list of things that are
kind of like in that in that vein maybe
we can just take many of the things you
mention just take it as a tangent okay
first of all athletic intelligence is a
super cool term uh and that's that
really is intelligence we humans kind of
take it for granted that we're so good
at walking and moving about the world
and using our hands you know the
mechanics of interacting with all you
know these parts I'll take these two
things you know you never touched those
before never tou well I've touched ones
like this look at all the things I can
do right I can juggle and I'm rotating
this way I can rotate it without looking
I could fetch these things out of my
pocket and figure out which one was
which and all that kind of stuff and uh
I don't think we have much of a clue how
all that works yet right and that's I
really like putting that under the
banner of athletic uh
intelligence what are the big open
problems in athletic intelligence so
Boston
Dynamics with spot with Atlas just have
shown time and time again like push the
limits of what we think is possible with
robots but Where Do We Stand actually if
we kind of zoom out what are the big
open problems on the athletic
intelligence side I mean one question
you could ask isn't my question but you
know are they commercially uh viable uh
could will they increase productivity
yeah and I think you know we're getting
very close to that uh I don't think
we're quite there still you know most of
the robotics companies it's it's a it's
a struggle you know it's really the lack
of the cognitive side that probably is
the biggest barrier at the moment even
for the physically successful robots but
uh you know your questions good I mean
you can always do a thing that's uh more
efficient lighter more reliable I'd say
reliability you know I know that spot
they've been working very hard uh on
getting the the tail of the reliability
curve up and they've made huge progress
so the robots you know there's a 1500 of
them out there now uh many of them being
used in uh practical applications stay
in in day out uh where you know where
they have to work reliably and uh you
know it's very exciting that they've
done that but it takes a huge effort to
get that kind of reliability uh in the
robot there's cost too you know you'd
like to get the cost down uh spots are
still pretty
expensive uh and I don't think that they
have to be but it takes you know a
different kind of activity to do that
now that uh you know I think you know
that uh Boston Dynamics is owned
primarily by Hyundai now and I think
that the skills of Hyundai in making
cars can be brought to bear in uh uh
making robots that are less expensive
and more reliable and those kinds of
things so on the cognitive side uh for
the I institute what's what's the
tradeoff between moonshot projects for
you and maybe incremental progress
that's a good question I think we're
we're using the Paradigm called Stepping
Stones to to moonshots I don't I don't
believe and that that was in my original
proposal for The Institute Stepping
Stones to moonshots I think if you go
more than a year without seeing a
tangible status report of where you are
which is the stepping ststone uh and it
could be a simplification right you
don't necessarily have to solve all the
problems of your target goal even though
your target goal is going to take
several years uh you know those those
stepping stone results give you feedback
uh give motivation because usually
there's some success in there uh and so
you know that's the Mantra uh we've been
working on and that's pretty much how uh
you know i' I'd say Boston Dynamics has
worked uh you know where you make
progress uh and show it as you go show
it to yourself if not to the world what
does success look like like what what
are some of the Milestones you're uh
you're
chasing well we've we've with watch
understand do the project I mentioned
before you know we've broken that down
into uh getting some progress with what
is meaningfully watching something mean
uh breaking down uh an observation of a
person doing something into the
components you know segment segmenting
you know you watch me do something I'm
gonna pick up this thing and put it down
here and stack this on it well it's not
obvious if you just look at the raw data
uh uh what the sequence of Acts are it's
it's really a creative intelligent act
for you to to break that down into the
pieces and understand them in a way so
you could say okay what skill do I need
to accomplish each of those things uh so
we're working on you know the front end
of of that kind of a problem where we
observe and translate the if it may be
video it may be live into uh a
description of what we think is going on
and then try and map that into skills to
accomplish that and we been developing
skills as well so you know we have kind
of multiple stabs at the pieces of of
doing that and this is usually video of
humans manipulating objects with their
hands kind of thing mhm we're starting
out with bicycle repair some simple
bicycle repair tasks that seems
complicated that seems really
complicated it is but but there's some
parts of it that aren't like uh putting
the seat in you know into the you know
you have a tube that goes inside of
another tube and there's a latch you
know that's that should be within range
is it possible to to observe to watch a
video like this without having explicit
model of what a bicycle looks like I
think it is and I think that's the kind
of thing that people don't recognize let
me translate it to navigation you know
uh I think the basic Paradigm for
navigating a space is to get some kind
of sensor that tells you where an
obstacle is and what's open build a map
and then go through the space but if I
if we were doing on the job training
where I was giving you a task I wouldn't
have to say anything about the room
right we came in here uh all we did is
adjust the chair but we didn't say
anything about the room and you know we
could navigate it so I think there's
opportunities to build that kind of
navigation skill into robots uh and
we're you know we're hoping to be able
to do that so operate successfully under
a lot of uncertainty like yeah and and
lack of specification lack of
specification I mean that's what sort of
intelligence is right kind of dealing
with a Sit understanding a situation
even though it wasn't explained so H how
big of a role does machine learning
uh play in all of this is this more and
more learning
based you know since chat gbt which is a
year ago basically uh there's a huge
interest in that and a and a huge uh
optimism about it and I think that
there's a lot of things that machine
learn that kind of machine learning now
Chris there's lots of different kinds of
machine learning I think there's a you
know a lot of interest and optimism
about it I think the you know the facts
on the ground are that doing physical
things with physical robots is a little
bit different than language and the
tokens you know the tokens sort of don't
exist you know pixel pixel values aren't
like Words um but I think that there's a
lot that can be done there we have
uh uh we have several people working on
machine learning approaches I don't know
if you know but we we opened an office
in Zurich recently and uh Marco hutter
who's one of the real leaders in uh
reinforcement learning for robots uh is
the the director of that office he's
still halftime at uh
eth uh the university there where he has
an unbelievably fantastic lab and then
he's halftime uh leading uh will be
leading off efforts in the Zurich office
so we have a healthy uh learning
component but there's part of me that
still says if you look out in the world
at what the most impressive performances
are are they're still pretty much uh I
hate to use the word traditional but
that's what everybody's calling it
traditional controls like model
predictive
control uh you know the thing the the
atlas performances that you've seen are
mostly model predictive control they've
started to do some learning stuff that's
really incredible I don't know if it's
all been shown yet but you'll see it
over over time um and then Marco's done
some great stuff and and others so
especially for the athletic intelligent
piece uh the traditional approach seems
to be the one that still performs the
best I think we're going to find a a
mating of the two and we'll have the
best of both worlds and we're working on
that at the Institute too if I can talk
to you about teams you've built an
incredible team of Boss Dynamics before
at MIT and CMU at Boston Dynamics and
now at the AI Institute and you said
that there's four components to a great
team uh technical fearlessness diligence
intrepidness and fun technical fun can
you explain each technical fearlessness
what do you mean by that sure uh
technical fearlessness means being
willing to take on a problem that you
don't know how to solve uh and you know
uh study it uh figure out an an entry
point you know maybe a simplified
version or a simplified solution or
something learn from the stepping stone
and uh and go back and uh
eventually make a solution that
meets your goals and I think that's
really important the fearlessness comes
into play because some of it has never
been done before yeah and you don't know
how to do it and you know there's easier
stuff to do in life uh so you know I
mean I don't know watch understand do
it's a it's a mountain of a of a
challenge so that's the really big
challenge you're you're tackling now can
we watch humans at scale and have robots
by watching humans become effective
actors in the world yeah I mean we have
others like that I we have one called
inspect diagnose fix like uh you know
you uh call up the mayag repairment okay
he's the one who you don't have to call
but you you you know you call up the the
dishwasher repair person and they come
to your house and they look at your
machine it's already been actually
figured out that something doesn't work
but they have to kind of examine it and
figure out what what's wrong and then
fix it m and uh I think robots should be
able to do that uh we already Boston
Dynamics already has spot
robots collecting data on machines
things like thermal data reading the
gauges listening to them getting sounds
and that data are used to determine
whether they're healthy or not but the
interpretation isn't done by the robots
yet and the uh certainly the the fixing
the diagnosing and the fixing isn't done
yet but I think it could be and you know
that's bringing the AI and combining it
with the physical skills to do it yeah
and you're referring to the fixing in
the physical world I can't wait until it
can fix the psychological problems of
humans and show up and talk do therapy
yeah that's a that's a different thing
yeah it's a different well it's all part
of the same thing again
Humanity maybe maybe you mean convincing
you it's okay that the dishwasher is
broken just do
the the marketing approach yeah exactly
it's all yeah don't s don't don't sweat
the small
stuff yeah as opposed to fixing the
dishwasher it'll convince you that it's
okay that the dishwasher is broken it's
a different
approach uh diligence why is diligence
important well if you want a real robot
solution it can't be uh a very narrow
Solution that's going to break at the
first variation in what the robot does
or the environment if it wasn't exactly
as you expected it
so how do you get there I think uh
having an approach that leaves you
unsatisfied until you've embraced the
bigger problem is the is the diligence
I'm talking about and uh again I'll
point at boss Dynamics I think they've
done you know some of the videos that we
had showing the engineer making it hard
for the robot to do its task uh spot
opening a door and then the guy gets
there and pushes on the door so it
doesn't open the way it's supposed to
pulling on the on the Rope that's
attached to the robot so it's navigation
has been screwed up uh we have one where
the robot's climbing stairs and an
engineer is tugging on a rope that's
pulling it back down the stairs you know
that's totally different than just the
robot seeing the stairs making a model
putting its feet carefully on each step
but that's what probably robotics needs
to succeed and having that
broader that broader idea that you want
to come up with a robust solution is
what I meant by diligence
so really testing it in all conditions
perturbing the system in all kinds of
ways right and as a result creating some
epic videos the the legendary the fun
part the hockey stick and then yes
tugging on spot is is trying to open the
door I mean the it's it's great testing
but it's
also I don't know it's just somehow
extremely
compelling demonstration of Robotics in
video form I learned something very
early on with the first three
hopping machine if you just show a video
of it
hopping it's a so what if you show it
falling over a couple of times and you
can see how easily and fast it falls
over then you appreciate what the
robot's doing when it's when it's doing
its thing so I think you know you're the
reaction you just gave to the D the
robot getting kind of interfered with or
tested while it's going through the door
it's showing you the scope of the
solution the the limits of the system
the the challenges involved in Failure
if showing both failure and success
makes you appreciate the the success
yeah and then just the way the videos
are done in Boston dyamics are
incredible because they're not there's
no flash there's no extra like
production is just raw testing of the
robot well you know I was the final edit
for most of the videos up
until uh until about three years ago or
four years ago and uh you know my theory
of the video is no no explanation if
they can't see it then it's not the
right thing and if you do something
Worth showing then let them see it don't
don't interfere with uh you know a bunch
of titles that slow you down or a bunch
of distraction just you know do
something Worth showing and then show it
that's brilliant it's hard it's hard
though for for people to buy into that
yeah I mean people always want to add
more stuff but the Simplicity of just do
something Worth showing and show it
that's brilliant and don't add extra
stuff now people people have
criticized uh especially the the big dog
videos where there's a human uh driving
the robot and and I understand the
criticism now at the time we wanted to
just show look this thing's using its
legs to get up the hill so we focused on
showing that which was we thought the
the story the fact that there was a
human so they were thinking about
autonomy whereas we were thinking about
the the
mobility uh and so you know we've we've
adjusted to a lot of things that we see
that people care about uh trying to be
honest we've always tried to be
honest but also just show cool stuff in
this raw form the limits of the system
to see the system be perturbed and be
robust and resilient and all that kind
of stuff and uh and dancing with some
music uh uh intrepidness and fun so
Intrepid I mean it might be the most
important ingredient and that is you
know robotics is hard it's not going to
work right right away so don't be
discouraged is all it really means so
usually when I talk about these things I
show videos and I show a long string of
outakes you know and you know you have
to have courage to be to be Intrepid
when you know you work so hard you built
your machine you know and then you're
trying and it just doesn't do what you
thought it would do what you want it to
do and uh you know you have to stick to
it and keep trying how long I mean we
don't often see that the story behind
spot and
Atlas how long how many failures was
there along the way to get you know a
working Atlas a working spot in the
early days even working big dog there's
a video of Atlas climbing three big
steps and it's very Dynamic and it's you
know it's really exciting real
accomplishment it took uh 109 tries and
we have video of every one of them you
know we shoot everything again we this
is at Boston Dynamics um uh so it took
109 tries but once it did it it had a
high percentage of success so it's not
like we're cheating by just showing the
best one but we do show the evolved you
know performance not everything along
the way but the everything along the way
is informative and you know it shows
sort of uh there's you know stupid
things that go wrong like like the robot
just when you say go and it collapses
right there on the start that doesn't
have to do with the steps uh or the
perception didn't work right so you miss
the target when you jump or something
breaks and there's oil flying everywhere
uh but that's fun yeah so the hardware
failures and and maybe some software
lots of control of evolution during that
time I think it took six weeks to get
that those uh 109 trials you know
because there was there was uh
programming going on you know it was it
was actually robot learning but there
were human in the loop helping with the
learning so all data driven but uh okay
and so and you always are learning from
that failure so
right and how do you how do you protect
Atlas from not getting damaged from
109 uh
attempts it was re it's remarkable one
of the accomplishments of Atlas is that
the engineers have made a machine that's
robust enough that it can take that kind
of testing where it's falling and stuff
and it doesn't break every time it still
breaks and we had you know part of the
the Paradigm is to have people to repair
stuff you got to figure that in if
you're going to do this kind of work um
you know I sometimes criticize the
people who have their goldplated thing
and they keep it on the shelf and
everybody and they're afraid to kind of
use it I don't think you can make
progress if you're working that way you
you need to be ready to have it break
and and go in there and fix it it's part
of the thing you know plan your budget
so you have spare parts and a crew and
all that stuff yeah if it falls 10 times
it's okay wow um so Intrepid truly and
that applies to spot that applies to all
the other re to everything I think it
applies to everything anybody tries to
do that's worth doing yeah and
especially with system in the real world
right yeah uh and so fun fun technical
fun I usually say have technical fun I
think that the life as an engineer is
really
satisfying I think you get to uh you
know to some degree it can be like
crafts work where you get to do things
with your own hands or your own design
or whatever your you know your media is
and it's very satisfying to be able to
just do the work unlike you know a lot
of people who have to do something that
they don't like doing I think Engineers
typically get to do something that they
that they like and there's a lot of
satisfaction from that then there's um
you know in many cases you can have
impact uh on the world somehow because
you've done something that other people
admire which is different from the own
just the craft fund of of building a
thing uh so that's a second way that uh
that being engineer is good I think the
third thing is that that if you're lucky
to be working in a team where you're uh
getting the benefit of other people's
skills that are helping you do your
thing uh you know none of us has all the
skills needed to do um most of these
projects and uh if you have a team where
you're working well with the others that
can be very satisfying and then if
you're an engineer you also usually get
paid and so you kind of get paid four
times yeah uh in my view of the world
yeah so what could be better than that
get paid to have fun I mean what what do
you love about engineering what when you
say engineering what does that what does
that mean to you exactly what is this
kind
of big thing that we call engineering I
think it's both being a scientist or
getting to use science at the same time
as being kind of an artist or a Creator
because you're making some you know
scientists only get to describe to to
study what's out there and engineers get
get to make stuff that didn't exist
before and so it's really I think a
higher calling even though I think most
you know the public out there thinks
science is top and engineering is
somehow secondary but I think it's the
other way around and at The Cutting Edge
I think when you when you talk about
robotics there is possibility to do art
in that you do like the first of its
kind thing so then there's a ma
production at scale which is its own
beautiful thing but when you do the
first new robot or the First new thing
that's a possibility to create something
totally new that is bringing metal to
life or a machine to life is kind of is
fun and uh
you know it was fun doing the D the
dancing videos where uh got a huge you
know public response and we're going to
do more can do some we're doing some at
The Institute and we'll we'll do more
well that metal to life moment I mean to
me that's still magical like uh when
when uh inanimate object comes to life
that's still like to me to this day is
still an incredible moment the human
intelligence can
create systems that instill life or
whatever that is in into inanimate
objects it's is really it's truly
magical especially when it's at the
scale of that humans can perceive and
appreciate like
directly but I think sort of with it
going going back to the pieces of that
you know you design a linkage that turns
out to be half the weight and just as
strong that's that's very satisfying and
you know there people who do that and
it's it's a creative a creative act uh
what what do you is the most beautiful
about
robotics sorry for the big romantic
question I think having the robots move
in a way that's uh uh evocative of life
is is pretty exciting so the Elegance of
movement yeah or or if it's a high
performance act where it's doing it you
know faster bigger than uh than other
robots usually we're not doing it bigger
faster than people but you know we're
getting there in a few narrow Dimensions
so fast are bigger
smoother more elegant more graceful I
mean I'd like to do dancing that that
starts you know we're nowhere near the
uh the dancing capabilities of a human
we we've been having a ballerina in
who's uh kind of a well-known ballerina
and she's been programming uh the robot
we've been working on the tools that can
make it so that she can use her way of
talking uh you know way of doing a
choreography or something like that more
accessible uh to uh to get the robot do
things and starting to produce some
interesting stuff well we should mention
that there is a choreography tool there
is I I mean I I guess I saw versions of
it uh which is pretty cool you can kind
of at at slices of time control
different parts at the high level the
movement of the robot spot we hope to
take that forward and make it you know
more tuned to how uh the Dance World
wants to talk wants to communicate and
and get better performances I mean we've
done done a lot but there's still a lot
possible and I'd like to have
performances where the robots are
dancing with people so right now almost
everything that we've done on Dancing uh
is to a fixed time base so once you
press go the robot does its thing and
plays out its thing it's not listening
it's not watching but I think it should
do those things I think I would love to
see a professional ballerina like alone
in a room with a robot slowly teaching
the robot just actually the the process
of a clueless robot trying to figure out
a small little piece of a dance so it's
not like because right now Atlas and
spot have done like perfect dancing
right uh to a beat and so on well so you
know uh to a degree but like the
learning
process of interacting with a human
would be like incredible to watch one of
the cool things going on you know that
there's a class at Brown university
called choreo robotics Sydney Sky better
is a Dancer uh choreographer and he he
teamed up with Stephanie telx who's a
computer science professor and they
taught this class and I think they have
some uh graduate students help him teach
it where they have two spots and people
come in most uh I think it's 5050 of uh
computer science people and dance people
and uh they do they program performances
that are that are very interesting I
show some of them sometimes when I give
a talk and making that process of a
human teaching the robot more efficient
and more intuitive maybe part language
part
movement that'd be fascinating that'd be
really fascinating because I I mean one
of the things I've kind of realized is
um humans communicate with
movement a lot it's not just language
there's a lot there's body language
there's so many intricate little things
and totally and like that you know to to
watch a human and spot communicate get
back and forth with movement is uh I
mean there's so many wonderful
possibilities there but it's also a
challenge you know we we get asked to
have our robots perform with uh with
famous dancers and they can you know
they have 200 degrees of freedom or
something right every little Ripple and
thing and they have all this head and
neck and shoulders and stuff and the
robots mostly don't have all that stuff
and it's it's a it's a daunting
challenge to not look stupid you know
physically stupid next to them so we've
we've pretty much avoided that kind of
performance but we'll we'll get to it I
think even with the limited degrees of
freedom we could still have some SASS
and flavor and so on you can figure out
your own thing even if you can't and we
can reverse things like if you watch a
human do uh robot animation which is a
dance style where you know you jerk
around sort of and you po you pop and
pop and lock and all that stuff I think
the robots could show up the D the
humans by uh you know doing unstable
oscillations and things that are faster
than a person so that's sort of on my
you know my plan but we haven't quite
gotten there yet you you mentioned about
building teams and Robotics teams and so
on how do you how do you find great
Engineers how do you hire gr Engineers I
think you need to have an environment
where interesting engineer well you know
it's a chicken and egg if you have an
environment where interesting
engineering is going on on then
Engineers want to work there and
uh uh you know I think it took a long
time to develop that at Boston Dynamics
in fact when we started uh although you
know I had the experience of building
things in the in the my in the leg lab
both at CMU and at MIT uh we weren't
that sophisticated of uh an engineering
thing compared to what Boston lamics is
now uh but it was our ambition to do
that and you know Saros was another
robot company so I always thought of us
as being uh this much on the Computing
side and this much on the hardware side
and they were like this uh and then over
the years we you know I think we
achieved the same or better uh levels of
engineering meanwhile you know sarov got
Acquired and then they went through all
kinds of changes and uh I don't know
exactly what their current status is but
uh so it took it took many years is is
part of the answer m
uh I think you get you got to find
people who love it in the early days we
would we paid a little less so we only
got people who were doing it because
because they really loved it we also
hired people who might not have
professional degrees you know people who
were building bicycles and uh building
kayaks we have some people who come from
that M kind of the maker world and
that's really important uh uh for the
kind of work we do to have that be part
of the mix whatever that is the whatever
the magic ingredient that makes a great
Builder maker that that that's the big
part of it people who took who repaired
the car the cars or uh built or
motorcycles or whatever in their garages
when they were kids there's a kind of
like the robotics students grass
students and just roboticist that uh I
know and hang out with there's a kind of
endless energy and like there're just
they're just happy like say uh I compare
it another group of people that are like
that are people that Skydive
professionally there's just like a
excitement in general energy that I
think probably has to do with the fact
that they're just
constantly first of all fail a lot and
then the the joy of building a thing
that you eventually works yeah talk
about being happy they used to be a time
when when I was doing the Machine Shop
work myself back in those JPL and
Caltech days when if I came home
smelling like the Machine Shop you know
cuz it's an oily place my wife would say
oh you you had a good day today CU you
could
that that's where i' been you've done
you yeah you've actually built something
you've done something in the physical
world um yeah and probably the videos
help right the videos help show off what
robotics is oh you know at Boston
Dynamics it put us on the map uh we uh I
remember interviewing some sales guy and
he was from a company uh and he said
well no one's ever heard of my company
but we have products uh you know really
good products you guys everybody knows
who you are but you don't have any any
products at all which was true so it was
and you know we thank YouTube for that
YouTube came we caught the YouTube wave
and it had a huge impact on on our
company I mean this that's it's it's a
big impact on not just on your company
but on robotics in general and helping
people understand Inspire what is
possible yeah with robots they Inspire
imagination fear and everything all the
full spectrum of human emotion was was
aroused which is yeah which is great
which is is great for the entirety of
humanity and and also probably inspiring
for young people that want to get into
Ai and Robotics yeah uh let me ask you
about some competitors sure you've been
uh complimentary of Elon and Tesla's
work on Optimus
robot uh with this their humanoid robot
what do you think of uh their efforts
there with the humanoid
robot you know I really admire uh Elon
uh as a techn ologist I think that uh
what he did with Tesla was just totally
mindboggling that he could go from this
totally
Niche area that you know less than 1% of
anybody seemed to be interested to
making it so that essentially every car
company in the world is uh trying to do
what uh what he's done so you got to
give it to him then look at SpaceX you
know he's basically replaced NASA if you
could that might be a little
exaggeration but not by much um so you
know you got to admire the guy and uh
you know I wouldn't count him out for
for anything you know I don't think uh
Optimus today is uh is where Atlas is
for instance I don't know it's a little
hard to compare them to the other uh
companies uh you know I I I visited
figure I think they're doing well and
they have a good team
uh I've visited EP tronic and I think
they're they haven't a good team and
they're doing well uh but Elon has a lot
of
resources he has a lot of
ambition i' like to take some credit for
his ambition I think uh I think if I
read between the lines it's hard not to
think that uh him seeing what Atlas is
doing is a little bit of an inspiration
I I hope so do you think Atlas and
Optimus will will hang out at some point
I would love to host that you know now
that I'm not at Boston Dynamics you know
I'm not officially connected I am on the
board but I'm not officially connected I
would love to host a uh robot meetups a
root Meetup
yeah does the AI Institute work with
spots and atlases is it focus on spots
mostly right now as a platform we have a
bunch of different robots we bought
everything we could buy so we have uh uh
spots uh I think we have a good siiz
Fleet in them I don't know how many it
is but a good size Fleet we have a
couple of animal robots um you know
animal is a company founded by Marco
hutter even though he's not that
involved anymore but we have a couple of
those we have a bunch of arms like uh
you know francas and uh us uh robotics
uh because you know even though we have
Ambitions to build stuff and we are bu
starting to build stuff uh you know day
one getting off the ground we just you
know just bought stuff and uh I love
this like robot playground you've built
yeah you can come over and take a look
if you want that's great so it's like
all these kinds of robots legged arms it
doesn't feel that much like well there's
some areas that feel like a playground
but it's not like they're all Frolic
together hey again maybe you'll arrange
it uh a robot Meetup um but in general
what's your view on competition in the
space for especially like humanoid and
leg of robots are you are you excited by
the competition or the the friendly
competition I think that um it it
doesn't you know I don't think I don't
think about competition that much uh you
know I'm not a commercial guy uh I think
for many years at Boston you know the
many years I was at Boston Dynamics we
we didn't think about competition we
were just kind of doing our thing there
wasn't it wasn't like there were
products out there that we were
competing no you know maybe there was
some competition for DARPA funding which
we got you know got a lot of got very
good at at getting but even there uh in
in a couple of cases where we might have
competed we ended up just being the
robot provider that is for the little
dog program you know we we just made the
robots we didn't participate as
developers except for developing the
robot and in the darer robotics
challenge we didn't compete we uh
provided the robots so uh uh you know in
the AI world now now that we're working
on cognitive stuff it feels much more
like a a competition you know the the
entry uh requirement ments in terms of
computing hardware and uh and the skills
of the team are and and hiring Talent
it's it's a much tougher place so I
think much more about competition now on
the cognitive side on the physical side
it doesn't feel like it's that much
about competition yet obviously with 10
humanoid companies out there 10 or 12 I
mean there's probably others that I
don't know about um they're definitely
in competition will be in competition
how much room is there
for a quadruped and especially a
humanoid robot to become cheaper so like
cutting cost and like how low can you
go and how much of it is just mass
production so questions of you know
Hyundai like how to produce versus like
engineering Innovation how to simplify
um I think there's a huge way to go I
don't think we've seen the bottom of it
or the bottom inth lower prices uh you
know I think you should be totally
optimistic that at ASM toote things
don't have to be anything like as
expensive as they are now back to
competition I wanted to say one thing I
think in the quadruped space having
other people selling quadrupeds is a
great thing for Boston Dynamics because
the question I believe the question in
the users Minds is which quadruped do I
want it's not oh can a quadri do I want
a quadruped can a quadruped do my job
uh it's much more like that which is a a
great place for it to be yeah then then
you're just you know doing doing the
things you normally do to make your
product better and compete and sell
selling and all that stuff and that'll
be the way it is with humanoids at some
point well there's a lot of humanoids
and you're just not even it's like
uh iPhone versus Android and people just
buying both and it's kind of just yeah
uh you're not really you're creating the
category you or the category is
happening
I mean right now the use cases you know
that that's the the key thing having
realistic use cases that are money
making uh in robotics is is a big
challenge you know there's the warehouse
use case that's probably the only thing
that makes anybody any money in robotics
at this point there's got to be a moment
there's old fashioned robot I mean
there's AR fixed arms doing
manufacturing I don't want to yes say
that they're not making money industrial
robotics yes but I there's got to be a
moment when social robotics starts
making real money meaning like a spot
type robot in the home and there's tens
of millions of them in the home and
they're like you know I don't know how
many dogs there are in the United States
as pets but this feels many it feels
like there's something we love about
having a intelligent companion with us
that remembers us that's excited to see
us all that kind of stuff but it's also
true that the companies making those
things there' have been a lot of
failures in recent times right there's
that one year when I think three of them
went under
um so it's it's not that easy to do that
right getting you know getting uh
performance safety and cost all to be
where they need to be at the same time
is uh that's that's hard but also some
of it is like you said you can have a
product but uh people might not be aware
of it so like also part of it is the
videos or however you connect with the
public the the culture and like create
the category make make people realize
this is the thing you want cuz from a
you know there's a lot of negative
perceptions you can have do you really
want a system with a camera in your home
walking around right um if if it's
presented correctly and if there's like
the right kind of boundaries around it
that you understand how it works and so
on that uh a lot of people would want to
and if they don't they might be
suspicious of it so that that's an
important like we all use smartphones
and that has a camera that's looking at
us yeah it has two or three or four and
it's listening is very few people are
are uh you know suspicious about it they
kind of take it for granted and so on
and I think robots would be the same
kind of way I I
agree so as you work on the cognitive
aspect of uh of these robots do you
think we'll
ever get to human level or superhuman
level
intelligence there's been a lot of
conversations about this recently given
the rapid development in large language
models um I I think that intelligence is
a lot of different things and I think
some things computers are already
smarter than people and some things
they're not even close and you know I
think you need a menu of of detailed
categories to come up with uh with that
but I also think that the you know the
the the conversation that seems to be
happening about agis puzzles me it's
sort of soorry ask you a question do you
think there's anybody smarter than you
in the world AB absolutely yes does do
you find that threatening no so I don't
understand even if computers were
smarter than people why we should assume
that that's a threat uh especially since
they could easily be smarter but still
available to us or under our control
which is basically how computers
generally are I think the the fears that
they would be 10x 100 act smarter and um
operating under different morals and
ethical codes that humans like naturally
do and so almost become
misaligned in uh unintended ways and
therefore harm humans in ways we just
can't predict and uh even if we program
them to do a thing as on the way of
doing that thing they would cause a lot
of harm and when they're 100 times a
thousand times 10,000 times smarter than
us we won't be able to stop it or we
won't be able to even see the harm as
it's happening until it's too late that
kind of stuff so you can construct all
kinds of like possible trajectories of
how the world ends because of super
intelligent
systems it's a little bit like that line
in the Oppenheimer
movie uh where they contemplate whether
the first time they set off a reaction
all matter on Earth is going to uh you
know go go up I don't remember what the
the verb they used was for uh for it uh
the Chain Reaction right um yeah I guess
it's possible but uh I don't I don't
think I personally don't think it's
worth worrying about that I think that
the you know it's an opportunity
balancing opportunities in Risk I think
if you take any
technology uh there's opportunity in
risk and you know it's easy to point
I'll point at the car uh they pollute
and they um about what um 1.25 million
people get killed every year around the
world because of them despite that I
think they're a boon to humankind very
useful we all love many of us love them
uh and those technical problems can be
solved I think they are becoming safer I
think they're becoming less polluting at
least some of them are um and every
technology you can name has a story like
that in my
opinion what's the story we find behind
the Hawaiian shirt is it a fashion
statement philosophical statement is it
just a statement of
rebellion uh engineering statement it
was born of me being a contrarian yes
someone a symbol someone told me once
that uh I was wearing one when I only
had one or two and they said oh those
things are so oldfashioned you can't
wear that Mark and I stopped wearing
them for about a week yeah and then I
said I'm not going to let them tell me
what to do and so every day since pretty
much so it's like a that was years ago
that was 20 years ago 15 years ago
probably ah that says something about
your personality that's great that's
you're not it took me a while to realize
I was a contrarian but you know it can
be a useful
tool have have you had people tell you
about on the robotic side that like I
don't think you could do this the kind
of uh negative
motivation uh I'd rather talk about uh
there's a guy uh when we were doing a
lot of Dara work there was a marine uh
Ed Tovar who's still around who uh his
his what he would always say is when
someone would say oh you can't do that
he'd say why not yeah and it's a great
question I ask all the time when I'm
thinking oh that's gonna We're not gonna
do that and I say why not and uh I give
him credit for opening my eyes to to uh
to resisting that so yeah yeah the
Hawaiian shirt is almost like a symbol
of why not okay um what advice would you
give to young folks that are trying to
figure out what they want to do with
their life how to have a life they can
be proud of how they can have a career
they can be proud of when I was uh
teaching at MIT I for a while I had
undergraduate advises where you know
people would have to meet with me uh
once a semester or something and they
frequently would ask you know uh what
they should do and I think the advice I
used to give was something like uh well
if you had no constraints on you uh no
resource constraints no opportunity
constraints and no still skill
constraints what would you could you
imagine doing and I said well start
there and see how close you can get you
know what's realistic for how close you
can get you know the other version of
that is you know try and figure out what
you want to do and and do that because I
don't I don't think a lot of people
think that they're in a channel right
and there's a limited opportunities but
yeah it's usually wider than they think
yeah the opportunities really are
Limitless but like at the same time you
want
to pick a thing right and it's the the
the
diligence and really really pursue it
right really pursue it yeah um because
sometimes like the really special stuff
happens after years of pursuit yeah oh
absolutely it can take it can take a
while I mean you've been doing this for
40 plus years people some people think
I'm in a rut right why don't I do and in
fact the some of the inspiration for the
uh AI Institute is to say okay I've been
working in Locomotion for however many
years it was uh let's do something else
and uh it's it's a really fascinating
and interesting Challenge and and you uh
you're hoping to show it off also in the
same way as just about to start showing
some stuff off yeah
I hope we have YouTube channel I mean
one of the challenges is it's one thing
to show athletic skills on YouTube
showing cognitive function is a lot
harder and I haven't quite figured out
yet how that's going to work uh they
might be a way there's a way there's a
way why not I also do
think sucking at a task is also
compelling like the uh incremental
Improvement a robot being like really
terrible task and then slowly becoming
better even in athletic intelligence
honestly like learning to walk and
falling and slowly figuring that out I
think there's something extremely
compelling about that we we like flaws
especially with a cognitive task it's
okay to be clumsy it's okay to be
confused and a little silly and all that
kind of
stuff it it feels like in that space is
where we can there's charm there's charm
the charm the CH there's charm and
there's something inspiring about a
robot sucking and then becoming less
terrible slowly at a task no I think
you're right that kind of reveals
something about about
ourselves and ultimately that's what's
one of the coolest things about robots
is it's kind of a mirror about what
makes humans special just by watching
how hard it is to make a robot do the
things that humans do you realize how
special we are
mhm uh what do you think is the meaning
of this whole thing why are we here
Mark you ever ask about the big
questions as you try to create these
humanoid humanlike intelligence systems
I don't know I think you have to have
fun while you're here that's about all I
know uh it would be a waste it would be
a waste not to right the ride is pretty
short so might as well have
fun Mark uh I'm a huge fan of yours it's
a huge honor that you would talk with me
this is really amazing and your work for
many decades has been amazing I can't
wait to see what you do at the AI
Institute I'm going to be uh waiting
impatiently for the videos and the demos
and and the next robot Meetup for maybe
uh Atlas and uh Optimus to hang out I
would love to do that that would be fun
thank you so much for talking today
thank you it was fun talking to you
thanks for listening to this
conversation with Mark rbert to support
this podcast please check out our
sponsors in the description and now
let's let me leave you with some words
from Arthur C
Clark whether we're based on carbon or
on Silicon makes no fundamental
difference we should each be treated
with appropriate
respect thank you for listening and hope
to see you next
time