Can The Brain Merge With Artificial Intelligence? — With Max Hodak

Channel: Alex Kantrowitz

Published at: 2025-12-12

YouTube video id: -1i4J0eubEk

Source: https://www.youtube.com/watch?v=-1i4J0eubEk

Hey everyone, we have a great crowd with
us here today and we're live streaming
it. So let's hear you make some noise.
Come on.
My name is Alex Kantrowitz. I'm the host
of Big Technology Podcast and I'm
thrilled to be here with Max Hodak, the
CEO and founder of Science for a
conversation about hacking the brain and
the brain computer interface revolution.
Max, great to see you. Thanks for having
me.
Today we have seen that there is
research that the brain computer
interface or the brain itself and the
way that artificial intelligence works
are actually a little bit more similar
than we initially believed. Can you tell
us a little bit about that?
Yeah, so there's this there's this been
this really interesting unification
that's happening between
uh what's happening in the artificial
intelligence community and what's
happening in neuroscience. I think when
you look inside these AI models, there's
like if you think about what people are
talking about a year or two ago when
they were they were much less
sophisticated, they're thinking, "Oh,
these things are glorified auto
completes or they're kind of they call
them stochastic parrots." But that that
really does not seem to be the case.
When you look inside these AI models,
you see these mathematical objects that
look a lot like what you see in what you
see in the brain in neuroscience. Like
the representations are converging.
And this is an empirical finding. Like
there's this uh
there's an area of research uh there's a
paper called the Platonic representation
hypothesis where it there's this
empirical finding where different models
train different architectures on
different data sets converge to the same
underlying representations. And so this
gives you this sense that these models
are are learning something kind of deep
about the universe. That there's this
underlying thing that's like a physical
fact that if you you train these big
computational models, you get you get
these representations that produce
intelligence and they're the same things
that the brain has figured out. And so
there's this really interesting
unification um
that
I don't know. I I mean I think it gives
us a lot of reason to believe that the
work in AI is on the right track.
So it's important to digest what you
just said, which is that there are
similarities between the human brain and
artificial intelligence, the way the
models work today.
Do you think one day we'll be able to
merge with AI?
I I think you have to kind of be
specific about what that means. But
yeah, I mean one of the things that I'm
preoccupied with is is um
the the binding problem with the So all
of your experience, I mean it's
important to realize that kind of all of
this, like everything you see and hear
and feel and think, like all of this is
brain activity. Like that's at the end
of the day that's all it really is. Like
the brain is the thing that is you. It's
the source of of
uh your entire experience of the
universe. But within that, it's composed
of billions of neurons that are
distributed over a large area and spread
out in time. But you don't experience
the activity of these neurons
independently. You experience a unified
moment.
And even with within your brain, you've
got two hemispheres, each of which is
processing one half of your experience.
So the left hemisphere is processing the
right hemi field and vice versa.
But you don't experience two hemi
fields. You experience a a single visual
field. And so how does that happen?
There's some physics that we don't
understand yet. And if you could
understand that, then you could imagine
adding you could imagine building say
conscious machine. You could add a third
hemisphere. You could connect this over
the network. This would in some very
fundamental sense allow you to redraw
the border around a brain and change the
like where your brain ends and begins
and in that sense where where you begin
and you end. Wait, how how far are we
from being able to do that?
I mean I think
>> I probably not next year, but I think
within the next decade. Wow.
>> It's very possible that this stuff is
going to get figured out in a meaningful
way. Um I think like 2035 will be a very
very different world than 2025. Um I
think that the progress that's happening
in AI is is much better known than any
of this, but it's still not priced in.
And yeah, I mean I think that there's a
big change that's coming towards us over
the next decade. So what happens when
we're able to either connect with AI or
even manipulate the brain using
computing?
Well, when I think about
the trajectory of BCIs, so there's on
the one hand there's there's very
pragmatic near-term medical innovations
that are coming to market now. So our
our lead program at Science is a retinal
prosthesis. It's a chip that's implanted
in the back of the eye. Um we just we
finished a major clinical trial last
summer in age-related macular
degeneration where patients
that are unable to recognize faces have
been able to read again. Uh there was a
major publication in the New England
Journal of Medicine about a month ago.
This was actually on the cover of Time
last week.
And that is happening That that work is
happening now.
But then when you look at the trajectory
of the next decade, I think it takes you
to places that are kind of tough to talk
about without kind of sounding like a
lunatic. But let's do that. And
yeah, I mean the Look, the the only
organ that I really care about is the
brain.
The Like you can get a heart transplant
or a liver transplant, but you can't in
concept discuss talk about getting a
brain transplant.
And so I think that the way that like
medicine might go
is like if we're used to on on the one
hand we have this this toolbox of drug
discovery in conventional medicine. And
on the other hand you've got this
toolbox of neural engineering, which I
think is just empirically much more
powerful. If you look at the work I work
in the retina, for example, people have
been trying to restore vision to the
blind for a long time, arguably for
thousands of years. And there's a bunch
of drugs that have been developed.
There's a gene therapy that's on market
that costs almost a million dollars a
patient. And it doesn't First of all,
it's only applicable for like 3% of of
patients that have the type of
blindness.
And it also just doesn't really work.
Like it very marginally slows the rate
of descent for a small number of
patients.
And
the because like dealing with the the
dealing with biology in in terms of this
these molecular details is very
challenging. Humans just aren't good at
this.
But the brain is an information
processing organ. And if you can think
of it from the information perspective,
like the power of of our retinal
prosthesis is we don't really care why
the rods and cones have died. We just
care that we can get the visual
information back into the brain and then
that can be reflected in the mind's eye
as a thing that you see. And so this
this is just an I mean you you put this
in and then these patients can read an
entire eye chart going from not being
able to read any of it. And so one of
the reasons that I like the neural
engineering approach is it produces
these very large effect sizes. Like
cochlear implants really if you are if
you are deaf due to sensorineural
hearing loss, they really work. Or if
you've ever seen a a video of a a
Parkinson's patient getting a deep a
deep brain stimulator being turned on,
they go from like unable to hold a
pencil to like being very still. Um or
like what Neuralink has developed where
you're able to put a like put electrodes
in motor cortex. I mean in an hour or so
after that patient starts to use that,
they can play video games. This just
this produces effect sizes that you
don't see in medicine.
And
um
the uh
Yeah, so I think
there's a direction that this can go
where you kind of you've got the brain
and if you can interface with the brain
and keep that healthy, then you can get
like kind of everything else you can do
and the rest become swappable parts.
Like I'm going to be pretty disappointed
if I'm murdered by my heart or my
pancreas, which as far as I'm concerned
is basically a support function to keep
keep the brain going. Right. So if I'm
hearing you correctly, what you're
saying is
this could be brain computer interfaces
could be a science that develops in
parallel with medicine or maybe even
exceeds medicine and ends up playing
into longevity because once you can
manipulate, control, enhance the brain,
then we can maybe live longer lives.
>> Yeah, I mean like if So the number one
killer is cardiovascular disease. Number
two is cancer. We've made [snorts] great
progress on each of these and there's
you can find graphs online of like the
mortality rate per 100,000 people falls
over time, but still the the
the loss rate here is remains 100%. And
the
curing cardiovascular disease, curing
cancer, we don't know how to do this.
But it is possible that um
by connecting to the brain directly, you
can just avoid the need to solve these
problems in the first place. You don't
need to solve these hard problems if you
can avoid them.
And so you talked about this a couple
times and I'm going to give you a a
moment here to expand upon it. Um
because it's actually remarkable what
you just spoke about uh a couple minutes
ago, that you've built a device called
Prima that enables people who have had
loss of sight to regain that sight. By
what happens? Do you stimulate the
visual cortex?
>> the first thing I'll say is we uh
we're excited to bring this to market
and we've been developing it, but it was
originally invented at at Stanford and
then we licensed it from um an inventor
at a professor at Stanford who I think
really deserves a lot of the credit for
the central idea.
And
but I mean we're I mean it the results
are amazing and we're really excited to
bring this to market to patients. So it
doesn't stimulate cortex directly. So if
you want to restore vision to the brain,
there's So first of all, there's many
reasons that people go blind. You can
there's cataracts, which are easy to fix
through surgery. There's retinal
degenerations like macular degeneration
or retinitis pigmentosa or Stargardt's
disease.
Um
where the the light sensitive cells in
the eye, the rods and cones have died,
but the brain knows how to see and the
optic nerve is intact.
And then there's diseases where the
optic nerve has been lost. Um the most
common of these is glaucoma
where high pressure in the eye can cause
the optic nerve to degenerate. Sometimes
this can also happen through traumatic
injuries.
And then there's other kind of more like
rare diseases where the the brain really
never learned to see in the first place.
So Prima is a chip. It's a It's a tiny
little 2 mm by 2 mm chip that is
implanted under the retina in the back
of the eye that if you look at it under
a microscope, it has all these little
hex cells. And each one of these little
pixels is essentially a solar panel. So
it works in conjunction with glasses
that are worn by the patient that have a
camera that looks out of the world and a
laser that projects into the eye to
strike hit the implant in the infrared
which you can't see, so it doesn't So if
you have any These patients sometimes
have residual peripheral vision that
they can use to walk around, but they
can't read or recognize faces.
The the laser hits the implant and
wherever the energy is absorbed, it
stimulates. It creates an electric
field. And so in this sense it acts
essentially as an electronic
photoreceptor. Like it it bypasses the
rods and cones to stimulate the next
layer of cells in the retina
um called the bipolar cells. So in the
retina there's really three layers of
cells. There's 150 million rods and
cones. These connect to 100 million
bipolar cells. Bipolar because they have
two ends. And then this compresses down
to 1.5 million optic nerve cells which
is this big cable that goes into the
brain.
And we So if you've lost the rods and
cones, Prima will electrically stimulate
the bipolar cells. And this empirically
as a This was a finding of the clinical
trial that if you do this in humans,
they get an image in the mind's eye.
They can see it.
We We think that this is the right place
to restore vision. Now if you've lost
the optic nerve, then you have a more
challenging problem, but most I mean
these patients haven't.
And
it's
the bipolar cells are easier to work
with because it is before this 100x
compression. So if you stimulate the
optic nerve
at that point, you've already you've
already compressed a lot of the visual
information like edges, color, relative
motion. You'd have You have to figure
out how to encode that for the brain,
and nobody knows how to do that right
now.
But we know that if you stimulate an
image onto the bipolar cells, you get an
image in the mind's eye.
And that that works. Now from the 1.5
million optic nerve cells, that
eventually connects up to
1/4 billion to 1/2 a billion cells in
visual cortex.
And that that in humans is extremely
difficult to stimulate. No one is I mean
you get some flashes of light if you do
that, but you don't get structured form
vision.
So
about a year ago, I got a chance to sit
with Nolan Arbaugh. He's the first
patient of Neuralink uh company that you
co-founded. He's quadriplegic.
And since his accident 8 years ago or 9
years ago now, he hadn't been able to
use a computer.
And he got the implant like you talked
about. And as you suggested, he started
to be able to play video games. In fact,
I played a video game against Nolan, and
he beat me. Yeah, it's pretty cool. It's
amazing.
>> Yeah. And one of the things that he told
me was that
he was able to move faster than a
typical human game player because often
times we have the intent to move and
then we move. We think about moving
somewhere and then maybe we press
something on a joystick, and then it
moves. But all he has to do is think
about moving let's say a cursor
somewhere, and it's there already. And
so he told me that it's given him
superpowers, and he could probably beat
world-class video game players at some
point because
his ability to move is much faster. So
as we continue to plug computing into
the brain,
where do you think that's going to lead
us? Do you think we're going to create a
new class of humans that have
superpowers over the rest of us that
don't have brain computer interfaces? I
mean I think it's important I mean So
first of all, that is extremely cool.
And yes, it cut a couple like tens of
milliseconds off the connection from
motor cortex out to the muscle.
But
I mean it's possible certainly. Um it's
These are very serious brain surgeries.
I think that it's tough to imagine kind
of healthy 30-year-olds getting these
soon, but many many people as you age,
the body fails, and many people
eventually I think will become patients.
And yeah, when I think about the next
generation BCI technologies that are on
the horizon that are getting developed,
I think it's very possible that in the
next four or five years, there'll be
some some patients that maybe had a
stroke, maybe had um
some other some other injury who
you kind of go from like this terrible
thing happened that in retrospect kind
of became like this amazing opportunity.
Um
it's
I mean it's a little tough to imagine,
but yeah, I mean these things are going
to substantially change the world.
We have about a minute left. Uh this is
one of those technologies maybe similar
to AI that has a lot of buzz,
but then you ask, okay, well, where is
the business plan going to be? And
we sort of stop to think for a bit and
say, how's that exactly going to work?
And is it just going to drive insurance
costs higher? So what's your perspective
on how to make this a profitable
business?
>> Oh man, I don't know if we can answer
this in a minute. But I mean yes, in the
near term, the
for all of the BCI labs,
it's these are reim- medical devices
that will be reimbursed by payers. And
these are for serious medical diseases.
But I think that this is I mean there's
a deeper tension here in healthcare.
Like as techno- as time goes on and
there are more technologies that produce
better outcomes for more people and
allow them to have higher qualities of
life for longer, there's just more stuff
to spend money on.
But healthcare is kind of fundamentally
this fixed bucket of money that
increases very slowly. Like 20 years ago
uh phones and computers were like they'd
fallen in price by almost 90% over this
time, but we spend 10 times plus more on
them. And
this This is a great thing, but if we
spend
if we had new technologies that meant
that we could spend 10 times as much on
healthcare, this would be a catastrophe.
And so I think reconciling that like as
these technologies
uh really improve and we are really able
to extend life and improve it um for for
many decades, this is going to be
There's going to be some kind of
reckoning in healthcare.
Well, it's a fascinating new frontier.
I've called 2025 the year of the brain
computer interface. And as I watch the
progress from companies like yours, I'm
feeling really good about that
assessment that came in before the year.
So Max, thank you so much. Thanks. Thank
you everybody.
>> [applause and cheering]