How the brain works is very limited. You know, we've got fMRI,
which is that that's kind of like putting us, you know, a stethoscope
on the outside of a factory wall and been putting it like all over the
factory wall, and you can sort of hear the sounds, but you don't
know what the machines are doing. Really it's hot. You can infer a
few things, but it's very broad breaststroke. In order to really know what's
going on in the brain, you really need you have to have high precision
sensors, and then you want to have stimulus and response, Like if you
trigger a neuron, what, how do you feel? What do you see?
How does the change of perception of the world you're speaking to physically?
Just getting close to the brain, being able to measure signals from the brain
will give us sort of open the door inside the factory. Yes, exactly.
Being able to have high precision sensors that tell you what individual neurons are
doing, and then being able to trigger the neuron and see what the response
is in the brain, so you can see the consequences of of of a
if you fire this neuron, what happens? How do you feel? What
has changed. It's it'll be really profound to have this in people, because
people can articulate their change, like if there's a change in mood or if
they you know, if they can tell you if they can see better or
hear better, or be able to form sentences better or worse, or you
know, their memories are jogged or that kind of thing. So on the
on the human side, there's this incredible general malleability plasticity of the human brain.
The human brain adapts, adjusts, and so on. So that's not
that plastic you're totally frank, so there's a firm structure, but there nevertheless
there's some plasticity. And the open question is, so if I could ask
a broad question, is how much that plasticity can be utilized? Sort of
on the human side, there's some plasticity in human brain, and on the
machine side, we have networks machine learning are ficial intelligence. It's able to
adjust and figure out signals. So there's a mysterious language that we don't perfectly
understand that's within the human brain, and then we're trying to understand that language
to communicate both directions. So the brain is adjusting a little bit. We
don't know how much, and the machine is adjusting. Where do you see
as they try to sort of reach together, almost like with an alien species,
try to find a protocol, communication protocol that works. Where do you
see the biggest the biggest benefit arriving from on the machine side or the human
side? Do you see both of them working together? I should think the
machine side is far more malleable than the biological side by huge amount. So
it'll be the machine that adapts to the brain. That's the only thing that's
possible to brain can't adapt that well to the machine. You can't have neurons
start to regard an electrode as another neuron, not just that this like the
pulse and so something else is pulsing. So there is that, there is
that that elsticity in the interface, which we believe is something that can happen.
But the vast majority of the malleability will have to be on the machine
side. But it's interesting when you look at that synaptic plasticity at the interface
side, there might be like an emergent plasticity because it's a whole nother It's
not like in the brain. It's a whole nother extension of the brain.
You know, we might have to redefine what it means to be malleable for
the brain, so maybe the brain is able to adjust to external interfaces.
There will be some adjustments to the brain because there's gonna be something reading and
simulating the brain, and so it will adjust to that thing. But most
the vast majority of the adjustment will be on the machine side. This is
just, this is just. It has to be that otherwise it will not
work. Ultimately, like we currently operate on two layers. We have sort
of lumbaco like prime primative brain layer, which is where all of our kind
of impulses are coming from. It's sort of like we've got we've got like
a monkey brain where a computer stuck on it. That's that's the human brain,
and a lot of our impulses and everything are driven by the monkey brain
and the computer. The cortex is constantly trying to make the monkey monkey brain
happy. It's not the cortex that's steering the monkey brains. The monkey brain
is steering the cortex, you know. But the cortex is the part that
tells the story of the whole thing. So we convince ourselves it's more interesting
than just the monkey brain. The cortex is like what we call like human
intelligence, you know. So it's like the that's like the advanced computer relative
to other creatures. Other creatures do not have either really they don't have the
computer, or they have a very weak computer relative to humans. But it's
it's like it sort of seems like, surely the really smart thing should can
the dumb thing, but actually, don't think controls a small thing. So
do you think some of the same kind of machine learning methods or whether that's
natural language processing applications are going to be applied for the communication between the machine
and the brain to learn how to do certain things like movement of the body,
how to process visual stimuli and so on. Do you see the value
of using machine learning to understand the language of the two way communication with the
brain? Sure? Yeah, absolutely. I mean we're neural net and that
you know, AI is basically neural net. So it's like digital neural net
will interface with biological neural net and hopefully bring us along for the ride.
But the vast majority of our of our intelligence will be digital. There's like
like like think of like the difference in intelligence between the cortex in your olympics
system is gigantic. Your olympic system really has no comprehension of what the hell
the cortex is doing. You know, it's just literally hungry, you know,
or tired or angry or taxi or something. You know, it's just
and then that in case, that's that impulse to the cortex and tales the
cortex to go satisfy that. So then a lot of a great deal of
like a massive amount of thinking, like truly stupendous amount of thinking has gone
into sex without purpose, without procation, without procreation, which which which is
actually quite a silly action in the absence of procreation. It's it's a bit
silly. Why are you doing it? Because it makes the limbic system happy,
that's why. That's why. But it's pretty absurd, really, well,
the whole of existence, that's pretty absurd in some kind of sense.
Yeah, But I mean, this is a lot of computation has gone into
how can I do more of that with approcreation not even being a factor?
This is I think a very important era of research, finds FW an agency
that should receive a lot of funding, especially after this conversation. If I
propose the formation of a new agency, Oh boy, what is the most
exciting or some of the most exciting things that you see in the future impact
of neuralink both on the science and engineering and societal broad impact. So neuralink,
I think at first we'll solve a lot of brain related diseases. So
it could be anything from like autism, schizophrenia, memory loss, like everyone
experiences memory loss at certain points in an age. Parents can't remember their kids'
names and that kind of thing. So there's a tremense amount of good that
neuralink can do in solving critical critical damage to the brain or the spinal cord.
There's a lot that can be done to improve quality of life of individuals,
and that will be those will be steps along the way, and then
ultimately it's intended to address the risk existential risk associated with a digital superintelligence,
like we will not be able to be smarter than a digital supercomputer. So
therefore, if you cannot beat them, join them and release, we won't
have that option. So you have hope that your link will be able to
be a kind of connection to allow us to merge to ride the wave of
the improving AI systems. I think the chance is above zero percent, so
it's non zero. There's a chance, and that's what have you seen,
Doumin Dummer? Yes, yes, so I'm saying there's a chance. He's
saying one in a billion or one in a million whatever. It was a
dumb and dumber you know. It went from maybe one in a million to
improving. Maybe it'll be one in a thousand, and then one one hundred,
then one in ten. Depends on the rate of improvement of neuralink and
how fast we're able to do make progress. You know. Well, I've
talked to a few folks here that quite brilliant engineers, so I'm excited.
Yeah, I think it's like fundamentally good, you know, you know,
giving somebody back full motor control after they've had a spinal cord injury, you
know, restoring brain functionality after a stroke, solving debilitating genetically orange brain diseases.
These are all incredibly great, I think. And in order to do
these, you have to be able to interface with neurons at detailed level and
need to be build fire the right neurons, read the right neurons, and
and then effectively you can create a circuit, replace what's broken with with silicon
and such a fill in the the missing functionality, and then over time we
can have we develop a tertiary layer. So if like Olympic system is a
primary layer, then the cortex is like the second layer. And I said
that, you know, obviously the cortex is vastly more intelligent than the Olympic
System. But people generally like the fact that they have Olympic System and cortex.
I haven't met anyone who wants to lead either one of them. They're
like, okay, I'll keep them both. That's cool. The Olympic System
is kind of fun. That's what the fun is. Absolutely, And then
people generally don't lose the cortex either, right, so they're like having the
cortex and the Olympic System. Yeah, and then there's a tertiary layer,
which will be digital superintelligence. And I think there's room for optimism given that
the cortex, the cortex is very intelligent and the Olympic System is not.
Yet they work together. Well, perhaps they can be a tertiary layer where
digital superintelligence lies, and that will be vastly more intelligent than the cortex,
but still coexist peacefully and in of a nine manner with the cortex Olympic System.
That's a super exciting future, both in low level engineering that I saw
as being done here and actual possibility in the next few decades. It's important
that neuralinks solved this problem sooner rather than later, because the point at which
we have digital superintelligence, that's when we pass the singularity and things become just
very uncertain. It doesn't mean that they're necessarily bad or good. For the
point of which we passed singularity, things become extremely unstable. So we want
to have a human brain interface before the singularity, or at least not long
after it, to minimize existential risk for humanity and consciousness as we know it.
But there's a lot of fascinating actual engineering and low level problems here in
your link that yeah, quite exciting. The problems that we face neuralink are
material science, electrical engineering, software, mechanical engineering, micro vocation. It's
a bunch of engineering disciplines essentially. That's what it comes down to is you
have to have a tiny electrode, so it's so small it doesn't hurt neurons,
but it's got to last for as long as a person, so it's
gonna last for decades. Uh. And then you've got to take that signal
you've got to process that single signal locally at low power. So we need
a lot of chip design engineers that, you know, because we've got to
uh signal processing and do so in a very power efficient way so that we
don't heat your brain of because the brain is very heat sensitive. And then
and then we've got to take those signals, we're going to do something with
them. And then we've got to stimulate and stimulate the back to to you
know, so you could bi directional communication. So if somebody's good at material
science, software, mechanical engineering, electrical engineering, trip design, microfabrication,
that's what those are the things we need to work on. We need to
your good at material science so that the we can have tiny electrodes that last
long time. And it's a tough thing with the science problems is a tough
one because you're trying to read and simulate electrically in an electric an electrically active
area. Your brain is very electrically active, electrochemically active. So how do
you have say, a coding on the electrode that doesn't dissolve over time and
uh and is safe in the brain. This is a very hard problem.
And then and then how do you collect those signals in a way that is
the most efficient because you really just have very tiny amounts of power to process
those signals, you know, and then we need to automate the whole thing.
So it's like laser, you know. So it's it's it's not if
this is done by neurosurgeons. There's no way it can scale to a large
numbers of people, and it needs to scales large numbers of people because I
think ultimately we want the future repeated to be determined by a large number of
humans. Do you think that's this has a chance to revolutionize surgery period,
So neurosurgery, and yeah, for sure, it's gotta be like laser.
Like if laser had to be hand done done by hand by a person,
that wouldn't be great. You know, it's done by a robot and then
arphomologist kind of just needs to make sure your your heads in the right position
and then they just press the button and go