YouTube Transcript:
Elon Musk New BRUTALLY Honest Interview LEAVES Audience Speechless (2025)
Skip watching entire videos - get the full transcript, search for keywords, and copy with one click.
Share:
Video Transcript
View:
You got really two choices. You can
either be a spectator or a participant.
We're talking about an economy that is
thousands of times, maybe millions of
times bigger than the economy today. I
went to Russia in like 2001 and 2002 to
buy ICBMs. This was to get to space.
Yeah. As a rocket, not to not to nuke
anyone, but like I think I think we're
quite close to digital super
intelligence. It may happen this year.
digital super intelligence defined as
smarter than any human at anything. And
I'm somewhat troubled by the foamy
paradox. Like why have we not seen any
we bring you Elon Musk's latest
unfiltered interview where he shares
exclusive predictions about artificial
intelligence, the race to Mars, and
building companies that could save
humanity from extinction. In this
supercut, we work on reducing pauses and
filler words while preserving every
crucial insight, saving you over 15
minutes of your valuable time. After
months focused on politics, this
conversation returns to what Elon does
best, engineering the future. We've
structured this into three focused
chapters. First, the foundations that
shaped his thinking. Second, building
the companies to make life multilanetary.
multilanetary.
And third, his predictions for AI and
what comes next? Chapter one, first
principles. How Elon got started. Was
there ever a moment in your life before
all this where you felt I have to build
something great? And what flipped that
switch for you? Well, I didn't
originally think I would build something
great. I wanted to try to build
something useful, but I didn't think I
would build anything particularly great.
You said probabilistically seemed
unlikely, but I wanted to at least try.
So you're talking to a room full of
people who are all technical engineers
uh often you know some of the most
eminent AI researchers coming up in the
game. Okay. I think we should I think I
I like the term engineer better than
researcher. I mean I suppose if there's
some fundamental algorithmic
breakthrough it's it's a research but
otherwise it's engineering. Maybe let's
start way back. I mean when you were
this is a room full of 18 to 25 year
olds. It skews younger because the
founder set is younger and younger. Can
you put yourself back into their shoes
when you know you were 18, 19, you know,
learning to code, even coming up with a
first idea for Zip 2. What was that like
for you? Yeah. Back in '95, I I was
faced with a choice of either do, you
know, grad studies, PhD at Stanford in
in material science, actually working on
ultra capacitors for potential use in
electric vehicles, essentially trying to
solve the range problem for electric
vehicles or try to do something in this
thing that most people have never heard
of called the internet. And uh I talked
to my professor who was Bill Nyx in the
material science department and uh said
like can I like defer for a quarter
because this will probably fail and then
I'll need to come back to college and
and then he said this is probably the
last conversation we'll have and he was
right but I I thought things would most
likely fail not that they would most
likely succeed. And then in 95 I wrote I
think the first or close to the first
maps directions white pages and yellow
pages on the internet. I just wrote I
just wrote that personally and I didn't
even use a web server. I just read the
port directly because I couldn't afford
and I couldn't couldn't afford a T1.
Original office was on Sherman Avenue in
Palo Alto. There was like an ISP on the
floor below. So I drilled I drilled a
hole through the floor and just ran a
land cable directly to the ISP and you
know my brother joined me and another
co-founder Greg Curry who passed away
and we at the time we couldn't even
afford a place to stay so we just the
office was 500 bucks a month so we just
slept in the office and and then
showered at the YMCA on page Milan El
Camino and yeah and we I guess we ended
up doing a little bit of a useful
company as of two in the beginning and
we did build a lot of really good
software technology, but we were
somewhat captured by the legacy media
companies in that nighter, New York
Times, no host, whatnot were investors
and customers and and also on the board.
So they kept they kept wanting to use
our software in ways that made no sense.
So I I wanted to go direct to consumers.
Anyway, it's a long story dwelling too
much on Z2, but the I really just wanted
to do something useful on the internet
because I like two choices like do a do
a PhD and watch people build the
internet or help build the internet in
some small way. And I was like, well, I
guess I can always try and fail and then
go back to grad studies. Anyway, that
ended up being like reasonably
successful. Sold for like $300 million,
which was a lot at the time. These days,
that's like I think minimum impulse bud
for an AI startup is like a billion
dollars. It's like there's so many
freaking unicorns. just like a herd of
unicorns at this point. You know, if
unicorn is a billion dollar situation.
There's been inflation since. So quite a
bit more money. Yeah. I mean like 90
1995 you could probably buy a burger for
a nickel. Well, not quite, but I mean
yeah, there has been a lot of inflation,
but I mean the hype level in AI is is is
pretty intense as you've seen. you know,
you see companies that are, I don't
know, less than a year old getting
sometimes billion dollar or
multi-billion dollar valuations, which I
guess could could pan out and probably
will pan out in some cases, but it is
eyewatering to see some of these
valuations. Um, yeah. What do you think?
I mean, we I'm pretty bullish
personally. I'm pretty bullish,
honestly. So I I think the people in
this room are going to create a lot of
the value that you know a billion people
in the world should be using this stuff
and that we're not even worried
scratching the surface of it. I love the
internet story in that even back then
you know you are a lot like the people
in this room back then and that you know
this the heads of all the the CEOs of
all the legacy media companies look to
you as the person who understood the
internet and a lot of the world the you
know the corporate world like the world
at large that does not understand what's
happening with AI they're going to look
to the people in this room for exactly
that it sounds like you know what are
some of the tangible lessons it sounds
like one of them is don't give up board
control or be careful about have a
really good lawyer. Uh I guess for the
first my first startup the the big the
really the mistake was having too much
shareholder and board control from
legacy media companies who then
necessarily see things through the lens
of legacy media and that they'll kind of
make you do things that seem sensible to
them but but aren't really don't make
sense with the new technology. I you
know I should point out that I that I I
didn't actually at first intend to start
a company. I like I tried to get a job
at Netscape and I sent my resume into
Netscape but I don't think he ever saw
my resume and then nobody responded. So
and then I tried hanging out in the
lobby of Netscape to see if I could like
bump into someone but I was like too shy
to talk to anyone. So I'm like man this
is ridiculous. So I'll just write
software myself and see how it goes. So
it wasn't actually from the standpoint
of like I want to start a company. I
just wanted to be part of building you
know the internet in some way. and and
since I couldn't get a job at an
internet company, I had to start a
internet company. AI will so profoundly
change the future, it's difficult to
fathom how much. But assuming we don't
things don't go ary and and like AI
doesn't kill us all and itself then you
you'll see ultimately an economy that is
not not 10 times more than the current
economy ultimately like if we become say
or whatever our future machine
descendants or but mostly machine
descend descendants become like a a caut
scale 2 civilization or beyond. We're
talking about an economy that is
thousands of times maybe millions of
times bigger than the economy today. I I
I did sort of feel a bit like, you know,
when I was in DC taking a lot of flack
for like getting rid of waste and fraud,
which was an interesting side quest as
side quests go. fixing the government is
kind of like there's like say the beach
is dirty and there's like some needles
and feces and like trash and you want to
clean up the beach but then there's also
this like thousand ft wall of water
which is a tsunami of AI like and how
much does cleaning the beach really
matter if you got a thousand foot
tsunami about to hit not that much if
you're trying to build a rocket or cars
or you're trying to have software that
compiles and runs reliably then you have
to be maximally truth seeking or your
software or your hardware won't work. Um
like there's not you can't fool like
math and physics are rigorous judges. So
I'm used to being in like a maximally
truth seeeking environment and and
that's definitely not politics. So
anyway, I'm I'm good glad to be back in
you know technology. I guess I'm kind of
curious going back to the Zip 2 moment.
You had hundreds of millions of dollars
or you had an exit of worth of millions
of dollars. I mean I I got $20 million,
right? And you basically took it and you
rolled you kept rolling with X.com which
became PayPal and Conffinity. Yes. I
kept the chips on the table. What drove
you to jump back into the ring? Well, I
I think I I felt for with with Zip 2, we
built like incredible technology, but it
never really got used. You know, I think
at least from my perspective, we had
better technology than say Yahoo or
anyone else, but it was constrained by
our customers. And so I wanted to do
something that where okay, we wouldn't
be constrained by our customers. Go
direct to consumer. And that's what
ended up being like X.com, PayPal.
Essentially X.com merging with
Confinity, which together created PayPal
and and then that that actually the the
sort of PayPal diaspora has it might
have created more companies than so more
companies than probably any anything in
the 21st century. You know, so so many
talented people were at the combination
of of Confinity and and X.com. So, I I
just wanted to like I felt like we we
kind of got our wings clipped somewhat
with Zip 2 and it's like, okay, what if
our wings aren't clipped and we go
direct to consumer and that's that's
what PayPal ended up being. Um, but
yeah, with I got that like $20 million
check for for my share of Zip 2. At the
time, I was living with in a house with
four housemates and had like 10 grand in
the bank. And then the this check
arrives in the mail of all places and
it's in the mail. Um and then and then
my bank balance went from 10,000 to 20
million and 10,000. You're like, well,
okay. Still have to pay taxes on that
and all, but then I ended up putting
almost all of that into X.com and as you
said, like just kind of keeping almost
all the chips on the table. From coding
his first software to nearly losing
everything on Tesla and SpaceX, Elon's
early struggles reveal the cost of
betting on breakthrough technologies.
Now, he explains how these companies
aren't separate ventures. They're
interconnected pieces of a larger
mission to preserve human consciousness
across multiple worlds.
Chapter 2, Engineering a Multilanet
Civilization. Then after PayPal, I was
like I was kind of curious as to why we
had not sent anyone to Mars. And I went
on the went on the NASA website to find
out when we're sending people to Mars.
And there was no date. I thought maybe
it was just hard to find on the website,
but in fact there there was no real plan
to send people to Mars. And I'm I'm I'm
definitely summarizing a lot here, but I
I I my first idea was to do a
philanthropic mission to Mars called
Life to Mars where we send a a small
greenhouse with seas and dehydrated
nutrient gel, land land that on Mars and
grow, you know, hydrate the gel and then
you'd have this this great sort of money
shot of green plants on a red
background. For the longest time, I by
the way I didn't realize money shot I
think is a porn reference. But but
anyway, the point is that that would be
the great shot of green plants on a red
background and to try to inspire, you
know, NASA and the public to to send
astronauts to to Mars. And along the
way, by the way, I went to Russia in
like 2001 and 2002 to buy ICBMs, which
is like that's an adventure, you know,
you go and meet with Russian high
command and say, I'd like to buy some
ICBMs. This was to get to space. Yeah.
Not to not to nuke anyone, but but they
had they had to as a result of arms
reduction talks, they had to actually
destroy a bunch of their their big
nuclear missiles. So I was like, well,
how about if we take two of those, you
know, minus the nuke, add an additional
upper stage for for Mars. But it was
kind of trippy, you know, being in
Moscow in 2001 negotiating with like the
Russian military to buy ICVMs. Like
that's crazy. I was like, man, these
things are getting really expensive. and
and then I I came to realize that
actually the problem was not that there
was insufficient will to go to Mars but
that there was no way to do so without
breaking the budget you know even
breaking the NASA budget so that's where
I decided to start SpaceX SpaceX to
advance rocket technology to the point
where we could send people to Mars and
that was in 2002. So that wasn't, you
know, you didn't start out wanting to
start a business. You wanted to start
just something that was interesting to
you that you thought humanity needed. It
turns out this is could be a very
profitable business. I mean it it is
now, but it there had been no prior
example of really a rocket startup
succeeding. There have been various
attempts to do commercial rocket
companies and they all all failed. So
again, with with SpaceX, starting SpaceX
was really from the standpoint of like I
I think there's like a less than 10%
chance of being successful. If if a
startup doesn't do something to advance
rocket technology, it's definitely not
coming from from the big defense
contractors because they just impeded
match to the government and the
government just wants to do very
conventional things. So there's it's
either coming from a startup or it's not
happening at all. So So like a small
chance of success is better than no
chance of success. And even like when
recruiting people, I didn't like try to,
you know, make out that I said we're
probably going to die, but small chance
we might not die. And if but this is the
only way to get people to Mars and
advance the state-of-the-art. And then I
ended up being chief engineer of the
rocket. Not because I wanted to, but
because I couldn't hire anyone who was
good. So like none of the good sort of
chief engineers would join because
they're like this is too risky. You were
going to die. And so then I ended up
being chief engineer of the rocket. And
you know, the first three flights did
fail. So, it's a bit of a learning
exercise there. And uh fourth one
fortunately worked. But if the fourth
one hadn't worked, I had no money left
and that would have been it would have
been curtains. So, it was a pretty close
thing. If if the fourth launch of Falcon
not worked, it would have been just
curtains and we would have just been
joined the graveyard of prior rocket
startups. So, it's like like my estimate
of success was not far off. We just we
made it by the skin of our teeth. Tesla
was happening sort of simultaneously.
Like 2008 was a rough year because at
mid 2008 the third launch of SpaceX had
failed. A third failure in a row. The
Tesla financing round had failed and so
Tesla was going bankrupt fast. It was
just a a tale of warning an exercise in
hubris. Probably throughout that period
a lot of people were saying you know
Elon is a software guy. Why is he
working on hardware? Yeah 100%. So you
can look at the like the because it's
still the you know the press of that
time is still online. and you could just
search it and and they kept calling me
internet guy. So like internet guy aka
fool is attempting to build a rocket
company and it does sound pretty absurd
like internet guy starts rocket company
doesn't sound like a recipe for success
frankly. So I didn't hold it against
them. I was like yeah you know
admittedly it does sound improbable and
I agree that it's improbable. But
fortunately the fourth launch worked and
and and NASA awarded us contract to
resupply the space station. It was like
right before Christmas because even the
fourth launch working wasn't enough to
succeed. It NASA also needed we also
needed a big contract to keep us alive.
So So I got I got that call from like
the NASA team and I literally they said
we're we're awarding you one of the
contracts to resupply the space station.
I like literally blurted out I love you
guys. Which is not normally you know
what they hear. And then we closed the
the Tesla financing round on the last
hour of the last day that it was
possible, which was 6 p.m. December
24th, 2008. We would have bounced
payroll 2 days after Christmas if that
round hadn't hadn't closed. It feels
like one of the through lines was being
able to find and eventually attract the
smartest possible people in those
particular fields. What would you tell
to, you know, the Elon who's never had
to do that yet? I I generally think to
try to try to be as useful as possible.
It's so hard to be useful, especially to
be useful to a lot of people where say
the area under the curve of total
utility is like how much how useful have
you been to your fellow human beings
times how many people. It's almost like
like the physics definition of true
work. It's incredibly difficult to do
that. And I think if you aspire to do
true work, your your probability of
success is much higher. Like don't
aspire to glory. Aspire to work. How can
you tell that it's true work? Like is it
external? Is it like what happens with
other people or you know what the
product does for people? like what you
know what is that for you? I mean, in
terms of of of your end product, you
just have to say like, well, if this
thing is successful, how useful will it
be to how many people? That that's
that's what I mean. And, you know,
whether you're CEO or or any role in a
startup, you do whatever it takes to
succeed. And just always be smash
smashing your ego. Internalize
responsibility. A major failure mode is
when ego to ability ratio is double
greater than sign one. If your ego to
ability ratio is it gets too high, then
you're you're you're going to basically
break the feedback loop to reality. In
AI terms, you're you'll break your RL
loop. So you you want you don't want to
break your you want to have a strong RL
loop, which means internalizing
responsibility and minimizing ego. And
you do whatever the task is, no matter
whether it's, you know, grand or humble.
I prefer the term engineering as opposed
to research. And and I I don't I
actually don't want it to call XAI a
lab. I just want to be a company. It's
like whatever the whatever the simplest,
most straightforward, ideally lowest ego
terms are th those are generally a good
way to go. You want to just close the
loop on reality hard. That's that's a
that's a super big deal. I think
everyone in this room is really looks up
to everything you've done around being
sort of a paragon of first principles
and you know thinking about the stuff
you've done how do you actually
determine your reality? people who have
never made anything, non-engineers, they
will criticize you. But then clearly you
have another set of people who are
builders who are in your circle like you
know how should people approach that you
need to make your way in this world
here. You know here's how to construct a
reality that is predictive from first
principles. Well, the the tools of
physics are incredibly helpful to
understand and make progress in any
field. The first principles mean just
obviously just means you know break
things down to the fundamental axiomatic
elements that are most likely to be true
and then reason up from there as
cogently as possible as opposed to
reasoning by analysis or metaphor and
then you just simple things like like
thinking in the limit like if you
extrapolate you know minimize this thing
or maximize that thing thinking in the
limit is is very very helpful. I use all
the tools of physics. They apply to any
field. This is like a superpower
actually. So you can take say take take
for example like rockets. You can say
well how how much should a rocket rocket
cost. The typical approach to to that
people would take how much rocket should
cost is they look historically at what
the cost of rockets are and assume that
any new rocket must be somewhat similar
to the prior cost of rockets. A first
principles approach would be you look at
the materials that the rocket is
comprised of. So if that's aluminum,
copper, carbon fiber, steel, whatever
the case may be, and say what how much
does that rocket weigh and and and what
are the constituent elements and how
much do they weigh? What is the material
price per kilogram of those constituent
elements? And that sets the actual floor
on what a rocket can cost. It's it can
asmtoically approach the cost of the raw
materials. And then you realize, oh,
actually a rocket, the raw materials of
a rocket are only maybe one or 2% of the
historical cost of a rocket. So the
manufacturing must necessarily be very
inefficient if the raw material cost is
only 1 or 2%. That would be a first
first principles analysis of the
potential for cost optimization of a
rocket and that's before you get to
reusability. you know to give an AI sort
of AI example. I guess last year where
for XEI when we were trying to build a a
training supercluster we we we went to
the various suppliers to ask that we
needed 100,000 H100s to be able to train
coherently. Their estimates for how long
it would take to complete that were 18
to 24 months. It's like well we need to
get that done in 6 months or we won't be
competitive. So so then if you break
that down what well what are the things
you need? Well you need a building you
need power. you need cooling. We didn't
have enough time to build a building
from scratch. So, we had to find an
existing building. So, we found factory
that was no longer in use in Memphis
that used to build Electrolux products.
But then the the input power was 15
megawatt and we needed 150 megawatt. So,
we rented generators and had generators
on one side of the building and then we
have to have cooling. So, we rented
about a quarter of the mobile cooling
capacity of the US and put the chillers
on the other side of the building. But
that didn't fully solve the problem
because the voltage v the power
variations during training are are very
big. So you can have power can drop by
50% in 100 milliseconds which the
generators can't keep up with. So then
we combi we added Tesla mega packs and
modified the software in the mega packs
to be able to smooth out the uh the
power variation during the training run.
almost it sounds like almost any of
those things you mentioned I could
imagine someone telling you very
directly no you can't have that you
can't have that power you can't have
this and it sounds like one of the
salient pieces of first principles
thinking is actually let's ask why let's
you know figure that out and actually
let's challenge the person across the
table and if they if I don't get an
answer that I feel good about I'm going
to you know not allow that to be I'm not
going to let that no to stand I think
these general principles
of first principal thinking applied to
software and hardware applied to
anything really. I'm just using kind of
a hardware example of of how we were
told something is impossible, but once
we broke it down into the constituent
elements of we need a building, we need
power, we need cooling, we need we we
need power smoothing and then and then
we could solve those constituent
elements. But it it was and then we and
then we just ran the the networking
operation to to do all the cabling
everything in four shifts 247
and and I was like sleeping in the data
center and also doing cabling myself
with rockets built and electric vehicles
scaling. The final challenge isn't
mechanical, it's intelligence itself.
In this final chapter, Elon shares his
timeline for artificial general
intelligence. Why trueing AI matters and
his predictions for technologies that
could reshape everything we know about
human capability.
Chapter 3, the future of AI, robots and
human evolution. Is it your view that
you know training still working and you
larger the scaling laws still hold and
whoever wins this race will have
basically the biggest smartest possible
model that you could distill. Well,
there's of the various elements that
side competitiveness for for large AI,
there's there's for sure the the talent
of the people, the scale of the hardware
matters and how well you able to bring
that hardware to bear. So, you can't
just order a whole bunch of GPUs and
then you can't just plug them in. So,
you've got to you've got to get a lot of
GPUs and have them train coherently and
stably. Then, it's like what unique
access to data do you have? I guess
distribution matters to some degree as
well. Like how do people get exposed to
your AI? Those those are those are
critical factors for if it's going to be
like a large foundation model that's
competitive and like right now we're
we're training Grock 3.5 which is a
heavy focus on reasoning. What I heard
for reasoning is hard science
particularly physics textbooks are very
useful for reasoning whereas I think
researchers have told me that social
sciences totally useless reasoning. Uh
yes that's probably true. You know,
something that's going to be very
important in the future is combining
Deep AI, the data center or supercluster
with robotics. You know, things like
like the Optimus humanoid robot. Yeah,
Optimus is awesome. There's going to be
so many humanoid robots and and robots
of all robots of all sizes and shapes,
but my prediction is that there will be
more humanoid robots by far than all
other robots combined by maybe an order
of magnitude. Like a a big difference.
Is it true that you you're planning a
robot army of a sort whether we do it or
or or you know whether Tesla does it you
know Tesla works closely with XAI like
you've seen how many humanoid robot
startups are there like it's like I
think Jensen Bong was on stage with a
massive number of robots from different
companies. I think there was like dozen
different humanoid robots. I mean, I
guess, you know, part of what I've been
fighting and maybe what has slowed me
down somewhat is that I'm a I'm a little
I don't want I don't want to make
Terminator real. I've been sort of, I
guess, at least until recent years,
dragging my feet on on AI and and
humanoid robotics. And then I sort of
come to the realiz realization it's it's
happening whether I do it or not. So,
you got really two choices. Particip you
could either be a spectator or a
participant. And so, like, well, I guess
I'd rather be a participant than a
spectator. And so now it's, you know,
pedal to the metal on humanoid robots
and digital super intelligence. So I
guess, you know, there's a third thing
that everyone has heard you talk a lot
about that I'm really a big fan of, you
know, becoming a multilanetary species.
How do you think about it? There's, you
know, AI obviously there's embodied
robotics and then there's being a multip
multilanetary species. Does everything
sort of feed into that last point or,
you know, what what are you driven by
right now for the next 10, 20, and 100
years? Jeez, 100 years, man. I hope
civilization's around in 100 years. If
it is around, it's going to look very
different from civilization today. I
mean, I'd predict that there's going to
be at least five times as many humanoid
robots as there are humans. Maybe 10
times. One way to look at the progress
of civilization is percentage completion
cautev. So, if you're, you know,
cautious of scale one, you've you've
harnessed all the energy of a planet.
Now in my in in my opinion we've only
harnessed maybe one or two% of Earth's
energy. So we've got a long way to go to
be KV scale one. Then Kv 2 you've
harnessed all the energy of a sun which
would be I don't know a billion times
more energy than Earth maybe closer to a
trillion. And then Khv 3 would be all
the energy of a galaxy. Pretty far from
that. So we're at the very very early
stage of the intelligence big bang. I I
I hope I hope we're in terms of being
multilanetary like I think I think we'll
have enough mass transferred to Mars
within like roughly 30 years to make
Mars self-sustaining such that Mars can
continue to grow and prosper even if the
resupply ships from Earth stop coming.
That greatly increases the probable
lifespan of civilization or or
consciousness or intelligence both
biological and digital. And I'm somewhat
troubled by the foamy paradox like why
have we not seen any aliens? And it
could be because intelligence is
incredibly rare and maybe we're the only
ones in this galaxy. Um, in which case
the intelligence of consciousness is
this like tiny candle in a vast dogmas
and we should do everything possible to
ensure the tiny candle candle does not
go out. And being a multilanet species
or making consciousness multilanetary
greatly improves the probable lifespan
of civilization and it's it's it's the
next step before going to other star
systems. Um once you once you at least
have two planets then you've got a
forcing function for the improvement of
space travel and and that that
ultimately is what will lead to
consciousness expanding to the stars.
The Fermy paradox dictates once you get
to some level of technology you destroy
yourself. What would you prescribe to I
mean a room full of engineers like what
can we do to prevent that from
happening? Yeah. How do we avoid the
great filters? One of the great filters
would obviously be global thermonuclear
war. So we we should try to avoid that.
Building benign AI, robots that AI that
loves humanity and robots that are
helpful. Something that I think is
extremely important in building AI is is
a very rigorous adherence to truth, even
if that truth is politically incorrect.
My intuition for what could make AI very
dangerous, is if if you force AI to
believe things that are not true. How do
you think about you know there's sort of
this argument for open open for safety
versus closed for competitive edge you
know there's fast takeoff and it's only
in one person's hands you know that
might you know sort of collapse a lot of
things whereas now we have choice which
is great how do you think about this
yeah I do think there will be several
deep intelligences may maybe at least
five I'm not sure that there's going to
be hundreds but it's probably close like
maybe there'll be like 10 or something
like that of which maybe four will be in
the US. But but yeah, se several deep
intelligences. What will these deep deep
intelligences actually be doing? Will it
be scientific research or trying to hack
each other? Probably all of the above. I
mean hopefully they will discover new
physics and I think they will definitely
going to invent new technologies like I
think I think we're quite close to
digital super intelligence. It may
happen this year and if it doesn't
happen this year, next year for sure. A
digital super intelligence defined as
smarter than any human at anything.
Well, so how do we direct that to sort
of super abundance? You know, we have we
could have robotic labor, we have cheap
energy, intelligence on demand, you
know, is that sort of the white pill?
Like where do you sit on the spectrum
and are there tangible things that you
would encourage everyone here to be
working on to make that white pill
actually reality? I think I think it
most likely will be a good outcome. I I
guess I'd sort of agree with Jeff Hinton
that maybe it's a 10 to 20% chance of
annihilation, but look on the bright
side, that's 80 to 90% probability of a
great outcome. Yeah, I can't emphasize
this enough. A rigorous adherence to
truth is is the most important thing for
AI safety and obviously empathy for
humanity and life as we know it. You're
working on closing the input and output
gap between humans and machines. How
critical is that to AGI, ASI? And you
know once that link is made can we not
only read but also write the neural link
is not necessary to solve digital super
intelligence that'll happen before
neural link is at scale but what what
Neurolink can effectively do is solve
the the input output bandwidth
constraints with a with a neural link
interface you can massively increase
your output bandwidth and your input
bandwidth input being right to you you
have to do write operations to the
brain. We have now five humans who have
received the kind of the read input
where it's reading signals and you've
got people with with ALS who really have
they're tetroplegics but they they can
now communicate at similar bandwidth to
a human with a fully functioning body
and control their computer and phone
which is pretty cool. In the next 6 to
12 months, we'll be doing our first
implants for vision where even if
somebody's completely blind. Uh we we
can write directly to the the visual
cortex and and we've had that working in
monkeys. One of our monkeys now has had
the visual implant for 3 years. At first
it'll be relatively fairly low
resolution, but longterm you would have
very high resolution and be able to see multisspectral
multisspectral
wavelengths. So you could see an
infrared ultraviolet radar. It's like a
superpower situation. At some point, the
cybernetic implants would would not
simply be correcting things that went
wrong, but augmenting human capabilities
dramatically. But digital super
intelligence will happen well before
that. I guess one of the limiting
reagents to all of your efforts across
all of these different domains is access
to the smartest possible people. like
what's going to happen in you know five
ten years and what should the people in
this room do to make sure that you know
they're the ones who are creating
instead of maybe below the API line.
Well they call it the singularity for a
reason because we don't know what's
going to happen in in the not that far
future. The percentage of intelligence
that is human will be quite small. At
some point the collective sum of human
intelligence will be less than 1% of all
intelligence. I guess just to end off
where do we go? So, how do we go from
here? I mean, I mean, all of this is
pretty wild sci-fi stuff that also could
be built by the people in this room. Do
you have a closing thought for the
smartest technical people of this
generation right now? If you're doing
something useful, that's great. Just
just try to be as useful as possible to
your fellow human beings and that that
then you're doing something good. I keep
harping on this like focus on super
truthful AI. That's the most important
thing for AI safety. You know, obviously
if anyone's interested in working at
XAI, I mean, please please please let us
know. We're aiming to make Grock the
maximally truth seeeking AI. Hopefully,
we can understand the nature of the
universe. That that's really I guess
what AI can hopefully tell us. Maybe AI
AI can maybe tell us where are the
aliens, you know, how did the universe
really start? How will it end? What are
the questions that we don't know that we
should ask? And are we in a simulation
or what level of simulation are we in?
Well, I think we're going to find out. NPC.
NPC.
From first principles thinking to
multilanetary civilization, this
conversation shows how Elon approaches
humanity's biggest challenges, not as
abstract problems, but as engineering
puzzles to solve. If you enjoyed this,
we've selected two more videos you'll
find fascinating. Check them out on your
screen now, and subscribe for more
content that cuts through the noise to
show you what's really shaping our
future. Elon, thank you so much for
joining us. Everyone, please give it up
Click on any text or timestamp to jump to that moment in the video
Share:
Most transcripts ready in under 5 seconds
One-Click Copy125+ LanguagesSearch ContentJump to Timestamps
Paste YouTube URL
Enter any YouTube video link to get the full transcript
Transcript Extraction Form
Most transcripts ready in under 5 seconds
Get Our Chrome Extension
Get transcripts instantly without leaving YouTube. Install our Chrome extension for one-click access to any video's transcript directly on the watch page.
Works with YouTube, Coursera, Udemy and more educational platforms
Get Instant Transcripts: Just Edit the Domain in Your Address Bar!
YouTube
←
→
↻
https://www.youtube.com/watch?v=UF8uR6Z6KLc
YoutubeToText
←
→
↻
https://youtubetotext.net/watch?v=UF8uR6Z6KLc