I think it is very possible that the

first people to live to a thousand are

alive right now. It still takes some

suspension of disbelief because I think

biotech has just been so incremental.

One of the things that's so exciting

about what's happening now is that no

longer really feels so incremental to

me. I think that BCI we're going to come

to see is not is not a specific product.

I think there going to be a bunch of BCI

companies going after different

applications where different types of

probes will make sense. To me, it feels

like we're firmly in like the takeoff

era now. Like something new has happened

on Earth.

Welcome back to another episode of How

to Build the Future. Today we've got a

real treat, Max Hodak, the co-founder of

Neurolink and also founder of science,

one of the most exciting BCI brain

computer interface companies that we've

ever seen. Max, welcome to How to Build

the Future.

>> Thanks for having me. So science

recently announced more than 40 people

have received one of your first BCI

treatments which gives people their

sight back. What is that? You what h

what's happening?

>> So we finished a big clinical trial last

year which was published in the New

England Journal of Medicine in the fall.

So it's a it's a little chip a tiny

little 2mm x 2mm silicon chip that's

implanted in the back of the eye under

the retina that it's it's this tiny

little array of essentially solar

panels. So the patients wear glasses

that have a camera that looks out at the

world and then a laser projector that

projects an image into the eye. And

wherever the laser hits the implant, it

like the solar panel absorbs the light

and that excites the cells directly

above it. It's a retinal stimulator and

this allows us to bypass the dead rods

and cones like the the cells that

normally make the eye light sensitive to

get a visual signal back into the retina

if they've gone blind because they've

lost the rods and cones. And so yeah, I

mean there there's a big clinical trial

in Europe across 17 sites and it was a

huge effect. And so we are submitting

for approval now. It's not it's not

approved on on the market yet. Hope to

have that later this year.

>> For those watching who have never heard

of a brain computer interface. What is

it? And what have people been able to

do? What are they able to do now?

>> So the brain

is this powerful computer, but it's

encased in the skull. Like it is not

magically connected to things. And so um

it has these these handful of

connections to the world. And these give

you the senses that you know and in and

the motor control that you know but you

can kind of ask like is that so either

do we want to replace these with

something else. So for example like the

simulated reality or the matrix use

case. The other is restoring lost

functionality. So this is I mean this is

how they're deployed today. So if

someone has gone blind you can restore

the ability to see. If they've gone deaf

you can restore the ability to hear. If

they're paralyzed you can restore the

ability to move. And then you can think

about structural neural engineering. And

this is the this is the thing that

people haven't really we haven't gotten

to as a field as much. But looking at

how how does the brain process

information? Can you add new brain

areas? Are there ways to understand how

the brain is like what what is going on

either to use this to build smarter

machines or to think about how to treat

things like depression or addiction? I'm

taken by uh to what degree right now

it's about sort of um taking someone who

has a condition or a disease and then

bringing them like sort of restoring

them to like sort of capability, right?

I think that's playing out in AI right

now as well, right? like you had

computers that had no ability to do like

any sort of pure cognition or like you

know and uh you know no neurons and then

suddenly a bunch of neurons and then AGI

is sort of like what a human can do.

sort of like a restoration of capability

and then of course there's like this

other thing after that which is you know

uh ASI super intelligence do you ever

think about what that might be down the

road you know what is that for BCI there

are many types of BCIs so it's there it

really is going to be a category like

pharma it's not it's not one product I

don't think there's going to be like the

VCI that people get and there are

different modalities that will work for

different things so for example Um I

don't work on ultrasound but one of the

things I think will be possible with

ultrasound is like a digital ambient or

like a digital aderall. So can you like

stimulate part of the brain to cause

focus or sleep and things like that

would not surprise me if that was

possible and that could I could see as

being more of a consumer application

almost and that won't require brain

surgery hopefully right now that the

high quality ultrasound stuff does

require drilling through the skull but I

think that that will be overcome for the

implantable BCIs. I mean this is a very

serious brain surgery. Um I think that's

important to appreciate. So when you

think about how do you actually get this

into humans and who's going to use it. I

mean these are going to be very disabled

patient populations. You always look at

riskreward you start at the most

disabled patients. You get the most

benefit for even relatively basic

functionality. Like I don't think that

you or I would want to get one of the

cortical motor decoders that you might

have seen out there today. Um because

the reality is that like a keyboard and

mouse is like great. It is a much higher

performance. Like it you can get like

spoken word is like 40 bits per second.

you can many people can type in the like

20 20-ish bits um and so the 10 bit per

second cortical motor decode is like not

going to make your life better. I

wouldn't get serious brain surgery for

that. Now as it gets more powerful and

as we are able to produce kind of access

richer representations from more of the

brain especially birectionally

um then you'll start to see like the

risk benefit change where like my my

view on this is not that I think healthy

30-year-olds are going to be getting

these soon but eventually many people

become patients aging is like the

coralate of kind of everything getting

worse and so there's some critical age

where it kind of crosses over where it

makes sense to have something that will

restore some functionality that you had

and then eventually that will kind of c

like cross the origin and then you'll

see people that had something terrible

happen to them who now have a capability

that you're jealous of and that will be

kind of when you start to see it

changing. Talk to me about how uh people

who maybe never had sight, you know, why

is was the optic nerve not you not

actually set up? Like is that not

something that you can do later? How

does plasticity fit in? You know, do you

have to get BCIs when you're incredibly

young while the brain is still plastic?

like how does all this come together?

>> Neuroplasticity is really interesting

and really misunderstood. Um there are

genuine critical periods in early

development that if you miss them, there

are some things that will be very hard

to wire up later. Um there actually are

some cases of patients that were born

blind who um but it wasn't a it wasn't a

loss of the optic nerve. It wasn't

something in the brain, but they had

congenital cataracts. So their vision

was blurry from birth and they were

never able to really form images who

then had this fixed as adults and that

did not work. This was um they didn't

their brain could not make sense of the

information. It was totally

overwhelming. They would wear eye

patches. Several of them committed

suicide. And so there is there are clear

critical periods in early development

where if you miss that, some things are

not going to work. With that said, the

brain stays way more plastic throughout

life and adulthood than I think is is

widely appreciated.

>> That's a relief. Um yeah, if I put an

electrode almost anywhere in your brain

and then wake you up in during surgery

and I show you a flashing light that is

that flashes proportionally to how much

that neuron is firing at least almost

anywhere in cortex within a couple

minutes you can learn to control uh like

that neuron and so the brain is very

plastic under feedback and this is

partly how the the cortical motor

decoders work. Some of it is you're

decoding what the brain was originally

representing um in terms of like a hand

or an arm representation, but also just

if you're getting these signals out of

the brain and you're giving the patient

feedback for like what those signals are

doing, then the brain also adapts to

you. And so in the first experiments for

this, they actually didn't fit anything

at all. They just took a couple they

took two neurons or a handful of neurons

and fixed the weights. So it said when

this neuron fires more, we're going to

go up the screen. When this neuron fires

more, we're going to go down the screen

and sideways. They fix the weights and

let the brain figure it out. Let the

brain learn. And again, the brain is

very plastic under feedback and can do

this.

>> A powerful moment. You have a learn, you

know, we have uh two learning systems

that can learn off of one another

instead of sort of a fixed one with if

statements on this side.

>> Totally. Yeah. And the brain really like

if you give the cortex information, it

is really good at extracting the

meaning. Now, in adulthood, I think one

of the reasons that you don't see it as

being so plastic is because it has

already fit well to reality. And so

there's like if you think of it as this

like energy surface and like the state

of brain states is this like you've got

these hills and valleys. So during

normal development typically for most

people there's this like enormous basin

in this energy surface. And so for most

people like you like during development

you descend into this basin and then

you're down there and it's stable

because you've like fit to reality and

if I show you like weird movies it's not

going to really push you out of that.

You can I think like one of the theories

of what psychedelics do is they kind of

add kind of anneal it so it kind of

shrinks the surface a little bit so you

kind of access these other states but

then when it wears off you just

immediately descend back down into the

energy well that the brain had fit to

and so even though the brain is still

plastic it is in this stable like part

of the attractor system so that it

doesn't you don't see the plasticity as

much but

>> this was selected for

>> um and this was absolutely selected for

yeah and so there's There's this tension

between there absolutely is ongoing

plasticity. If there wasn't plasticity,

you couldn't learn things. And so like

your ability to learn new stuff is like

and have memory like all memory is brain

plasticity in many ways. And so we are

constantly experiencing very dramatic

plasticity. But there are also clear

limits to it especially in how like the

modules of the different brain areas end

up interconnected past these critical

periods.

>> I have like a million questions

honestly. I mean one of the things that

I'm super curious about is like well

what is the qualia of the person who has

prima and what is you know I'd be

curious like with the biohybrid approach

like what does it feel like and you know

is it like having a second screen like

you know is there an input or output I'm

very curious yeah so for prima actually

on the topic of plasticity in the time

that the patients are blind the brain

the brain wants to see like again you

the thing you experience is this world

model constructed by the brain and that

is this is this generative model that is

conjuring your reality. And so when it's

not getting input from the from the

optic nerve, it is still trying to see

things. So it kind of turns up the

noise. And so um blind patients often

report like hallucinations and these

like internally generated percepts. When

you first turn on the implant in these

patients, like you hit it with the

laser, um they'll they'll say, "Oh, I

see a flash." But then you can do a

thing where you'll you'll turn on the

laser, they'll see a flash, and you'll

play a tone. And you do this a couple

times and then you like don't turn on

the laser but you play the tone and

they're like I see the flash.

>> And so for the first couple hours of

rehab they kind of just have to like

learn to like dissociate the real

percepts from the phantom percepts

because the brain is like so it is like

so turned up the gain like turned up

turn down the noise floor that um just

like getting learning how to

discriminate real information coming in

from the optic nerve takes a little bit

of rehab. The quailia of prima is is

normal sight. um it's black and white.

It's only a it's a small field of view,

but it's it's vision. The deeper

question is like what is the quality of

like a brainto brain of like an ultra

high bandwidth like a bio-hybrid neural

interface and that is just like I don't

like impossible to imagine. I those

devices will get built and we're going

to find out but um there are some

natural case studies. So there's a pair

of conjoined twins in Canada that it's

really like one head with four

hemispheres. And what's really

interesting is that the two hemispheres

of each of the twins's brains are

connected normally, but they're not

connected with each other except for

this one cable connecting the the the

phalami like from the phalamus to

phalamus. There's this big biological

cable that you can see on an MRI. And

over this they can share meaningful

elements of their conscious experience.

And one of the open questions that

hasn't really been studied in in the

depth that I would like love to see it

um is when they they can see to some

degree through each other's eyes, but

does this show up as new visual field?

Like how is this how do those get

experienced directly? Like we already

most people have two image modes like

you've got your eye open vision but you

also have imagination. Some people are

aphantasic and they don't have internal

imagery. Most people have kind of two

image modes. Do they have three image

modes or four image modes? Or if they um

have internal monologue, they can they

seem to each individually have internal

monologue, but they also can clearly

communicate over this channel because

they've done they've done tasks where

like they can coordinate without saying

anything to to do stuff

>> and they're conscious of it.

>> And they're conscious of it and it also

they don't confuse it for each other.

It's not like like with a schizophrenic

where it's like, oh, I'm hearing voices

and that they're coming from internally

generated me. It's misattributed

monologue. That doesn't happen to them.

they can tell it apart. Um, but they're

experiencing it directly in some way.

And so there's a question of is this

like when you look at that cable, are

they sending the like information in the

classical way or is this is there like

an effect of like phenomenal binding

happening over this cable where it's

more like the two hemispheres of your

brain that are bound together into one

moment. And so there's these natural

case studies that tell us that some

really interesting things might be

possible here, but it's kind of tough to

imagine what it would feel like. paint

the picture for us. You know, you're

here, everything goes really, really

well. Where are we in 5 to 10 years with

this technology?

>> I mean, I do think that that you can get

to close to native acuity, so kind of

like your normal 2020 vision. We're

definitely not there yet, but I see a

path to get there and be able to get

color and fill in a lot of the field of

view. To be be clear, that is not where

we are right now, but in the next 10

years, I think that that's possible. But

beyond that, I'd say that our worldview

or my worldview kind of the motivating

idea behind the company is you can

contrast this this like there's like a

drug discovery approach to medicine

versus a neural engineering approach to

medicine. I this is much broader than

the retinal prosthesis. We started with

that because it's a huge unmet need and

I think it's the most valuable BCI like

product on the like on the horizon that

I thought was doable now. Humanity just

isn't very good at drug discovery. every

now and then you kind of find a thing

it's amazing like you find a GLP-1 or

you find um like there's every like

there's a handful of drugs that are we

were lucky to find but it's much more

common that you spend a decade going

down this this path and then at the end

you run a study and the answer is no and

then it's like where do you go from

there? There's been a huge amount of

work that's gone into finding drugs to

to like stop um blindness getting worse

or to or to reverse and restore vision

to to basically no effect. there's a

million dollar per patient gene therapy

that has a really very marginal like if

any benefit to a very small small

percentage of patients in the first

place and with our retinal prostthesis

that what we saw in the trial was we can

take a patient who's been unable to see

faces for a decade and allow them to

read every letter on an eye chart and so

not only is the brain the only organ

that really in some deep sense matters

we are also just empirically much better

at engineering it and so I think this

like allows like a really fundamental

reframing of medicine and over the next

decade I think like beyond people need

people see hear have balance have a

kilobit per second of motor control that

is like you and I think like we have

coar implants we have we know how to do

motor decoding the thing we didn't know

how to do is restore vision we're

working we are making real progress on

that I think all of this adds up to

something that speaks I think to the

really foundations like this paradigm

shift in what's possible in healthcare

>> something like this uh I remember

reading about maybe like 10 maybe even

20 years ago they were able to stimulate

the optic nerve ve with electricity

directly, but it was very very low

resolution and it was so invasive that

it could probably only be done in a

clinical setting or in a surgical

setting.

>> It's relatively easy to get flashes of

light um to cause a patient to kind of

see these these flashes. We call these

phosphines. There was a company a decade

ago called Second Sight that had an

electrical stimulator that was implanted

in the eye. It was a 4 and 1 half hour

surgery with a titanium box on the side

of the eye. um it stimulated a different

layer of cells than we do and they were

able to get these flashes where like if

a patient looked at it they could say

like oh there's some flashes here

there's some flashes here it's connected

that's an A and like the next letter and

it's like there's some here there's some

here it's an H but it doesn't the brain

doesn't assemble together these flashes

of light into like a gestalt hole that

is an image in the mind's eye um

similarly when you stimulate cortex um

like the back of the head where the

visual cortical areas are you can get

these flashes of light and you can even

in some cases He's got a lot of them,

but again, the brain doesn't like you.

It's kind of this more psychedelic

effect like this doesn't get assembled

together into form vision. And as far as

I know, our clinical trial was the first

time ever that form vision had been like

had created like a coherent image in the

mind's eye of a of a person.

>> Is there something uh specific about

macular degeneration that causes you

know this to be possible for this set of

patients?

>> So there's a bunch of reasons why people

lose rods and cones. Um there's macular

degeneration, there's retitis

pigmentotosa, there's some rare like

inherited diseases like stararts

disease, diabetic retinopathy can do it,

age- related macular degeneration. It's

the most common. Um so this globally

affects 200 million people. The severe

form geographic atrophy is is a million

to a couple million. In that sense, it's

a big need. One of the nice things about

our device is that it doesn't we're

somewhat agnostic to the reason that you

lost the photo receptors. And so we we

think it'll also work. um for retinized

pigmentotosa, for stararts, for these

other indications. We're actually just

about to start a new clinical trial on

on inherited retinal disease um which

affects much younger people. And this

again this goes back to like the drug

discovery versus neural engineering view

of the world. Like if you want to make a

if you want to make a drug then you care

a lot about exactly like what

molecularly went wrong in the rot

and that is different by disease then

even if you figure this out it's really

hard to like understand what to do about

it. here. We don't really care why the

rods are coincided. We just care that we

can get the the visual signal back into

the computer.

>> I guess I'm just very fascinated by you

obviously uh as a computer scientist

spend a lot of time thinking about

inputs and signals and then what I'm

hearing is that like some of that

thinking does actually translate into uh

from software into wetwware.

>> Well, I mean the brain is a computer and

it's going to saying that is going to

get me yelled at by some corner of of

the field, but I think like I think that

you can take that like almost literally.

It's a it's a very different

architecture than like a like a

vonoyoman architecture electrical

computer, but it processes information.

It gets information down one of 12

cranial nerves or 31 spinal. So all of

the information that flows in or out of

the brain goes through a small number of

cables. The optic nerve we'd call

cranial nerve 2. Um the vestibular coar

nerve that carries hearing balance,

cranial nerve 8. Um there's 31 spinal

nerves that carry commands out to the

muscles and sensory information into the

brain. And you can think of that as like

the API of the brain. And if you can

like get all the signals going down

those then like that's like the brain is

not magically connected to the

environment. It is reality is whatever

spikes are on the cranial and spinal

nerves. And in that sense you've got

this like well- definfined interface to

it. Then with the processing once it

gets this information is enormously

complicated. It constructs everything we

experience. Like I think it's important

to appreciate you experience yourself

being in the world. You kind of see the

the walls and the room and the lights

and everything. But that of course

you're not experiencing directly. you're

experiencing a world model like

fabricated by your brain. But I I think

one of the interesting things that's

come out of progress in artificial

intelligence is we're seeing this big

unification in neuroscience and and AI.

I think we're actually learning a lot

from AI re more than I think we thought

we would learn from AI research. I mean

I can tell you 10 years ago we thought

it would go the other way and that the

AI people would learn a lot from

neuroscience and it's really been the

other way around.

>> I'm always curious. I mean you were

mentioning second side sort of you know

flashes of light and yet you know here

you know how did you figure out the API

I mean if I was you know trying to

reverse engineer it I guess I would like

try to measure the signals is it similar

with you know biology

>> it's just it's difficult to measure the

signals so brain brain computer

interface research and development is

limited by your ability to record and

stimulate these signals that

neuroscience comparatively is actually

pretty simple as soon as you can record

these signals we've very quickly figured

out what we we talk about neural

representations what they are second

sight's instructive so in the retina

there's three layers of cells that

matter there's 150 million rods and

cones this connects to 100 million

bipolar cells bipolar because they've

got two ends and that connects the rods

and cones to 1.5 million optic nerve

cells call them retinal ganglen cells

gang is like a fancy word for like

reaches a far distance and connects to

somewhere we stimulate the 100 million

bipolar cells second sight stimulated

the 1.5 million ganglen cells and so

they were trying to get the signal into

the brain past that 100x compression and

the retina was doing a lot of

computation there. The eyes of camera

light shines in from the front, it hits

the rods and cones like that. The

representation in the rods and cones is

a bit mapped image. It's just like you

take the image, you tile it across the

rods and cones that that's what it is.

>> Now, in the the 1.5 million optic nerve

cells, it's not like that. Like if you

just project an image onto them, you get

a bunch of trash because at that point

it's already compressed things like

edges, relative motion, a bunch of other

like blobby shapes, color. And so if you

stimulate a cell there, you're not going

to get just like a pixel. You're going

to get like some uh edge mo like

direction gradient thing. And when you

excite that, you you can't do that

selectively because we don't like first

of all, you just can't do it selectively

enough. And we don't know like the

codec. We don't have like the know how

to pattern it appropriately. And so you

end up getting these flashes of light.

It was an empirical discovery of of our

study that if you excite the bipolar

cells with an image, you get an image in

the mind's eye because that is clearly

the critical processing step in the

retina that you wanted to preserve.

>> Did you know that that would happen or

did you have to try different parts?

When we started the company, we I think

we're a little bit different than most

medical device or biotech companies

because they're often founded around

like a specific asset like a a patent or

some specific piece of IP that they're

going to spin out of a university or

maybe something that the founders have

worked on. We weren't like that. We did

we had a couple ideas at the beginning.

Um we had this like neural engineering

centric view of healthcare. We had a

specific um BCI probe idea in biohybrid

and we had a sense that the most

valuable thing that we could build in

the near term was a retinal prostthesis.

We thought the time was there like the

technology was all there that that would

be possible circuit 2021 and that was

also further from stuff that I had

worked on before and so it felt like a

good thing for us to to kind of go

explore. I think we took this very very

like first principles approach and you

have to be careful with first principles

in biology because first principles are

not enough in biology like they'll get

you very far in many other areas of

engineering but in biology you also have

to understand like what did evolution

actually do and there's a lot of other

nuance there but in this case we we

looked at the retina there were kind of

reasons intuitions to think that past

that would be much harder and so in the

retina you've got this 2x2 matrix you've

got a choice of do if you've lost the

rods and cones do you stimulate the

bipolar cells or the optic nerve cells

And do you do it electrically or with a

technique called optogenetics? And we

just went and explored all four

quadrants of that. We uh very quickly

figured out that stimulating the the

optic nerve cells was very difficult for

these reasons. You end up with this like

1 million degree of freedom calibration

that you have to do per patient that

like can't be done in practice. And so

that led us to the bipolar cells which

was before this compression. And so then

the question was do you want to

stimulate them electrically or using

optogenetics? And we developed both. And

so we have a state-of-the-art

optogenetic gene therapy in house.

Published a paper last fall on on the

world's most sensitive optogenetics

option proteins. These are proteins that

you can express in a neuron to make a

neuron that is not normally light

sensitive responsive to light.

>> Oh wow.

>> But the drawback was that the

conventional optogenetic proteins take

like a bright laser to activate them.

And so what we were able to do were find

optogenetic proteins that are so

sensitive that they're sensitive to like

indoor office lighting. And so this you

could use in very different ways. and

then we could target them to the bipolar

cells, but that still has like 5 to

seven years of clinical translation away

if it ends up working and there's a

bunch of pitfalls it could run into

along the way. And then we also um just

surveyed the world to see what was the

state-of-the-art for the best out there

in um in electrical stimulation and

there was this technology that had been

invented at Stanford about a decade ago

that a small company in Europe had been

uh kind of developing in the meantime

and we got convinced that that was the

right way to go and so we acquired them

a few years ago and this was kind of all

from this like bird's eye view of if you

want to restore vision in the retina

kind of how would you do that what are

the promising approaches narrow that

down and and that brought us to hear.

>> That's insane. That's so cool. I wanted

to jump to your start in tech broadly. I

mean, did you start in bio and software

and engineering? Like, you know, what

was your sort of journey into what

you're doing now, which is I mean,

giving people blindsight is the wildest

thing people watching might be asking

themselves like, well, you know, I hear

a lot about B2B SAS, but you know, how

do I actually become uh something more

like you? I was certainly doing software

and my deepest hard skill is software.

Um my I have a degree in biomedical

engineering but I grew up programming

and so I was doing that well before I

was doing any any biotech stuff. My

parents tell me a story about how I um

sat on the floor of a Barnes & Noble and

cried until they bought me a Learn

Visual Basic book. I was always

interested in the brain. I was

definitely inspired by science fiction.

Um the Matrix had a big impact on me.

Um, both because the idea of this like

world of bits was just so alluring for

for a bunch of like fundamental reasons.

Like when I look around at at the world

like it's hard to build things. Um,

space is constrained. It's like the

earth is small. The resources are

intensely contested. The like space is

large. The speed of light is low. Like

you don't have any of those constraints

in in the machine. And so if you could

simulate a world kind of anything was

possible there. But then also if you

then kind of turned that inside out, if

you realize that you can build this and

that you couldn't tell the difference,

then the coral area of that was must be

like the thing that matters is the brain

and if you can engineer the brain and

support the brain, then kind of all the

rest of it is replaceable. And that just

seemed like a kind of a fairly deep

insight that was not being borne out in

the world in the way that it seemed like

like it should be. Some of it is um if

you can surround that consciousness with

like the correct inputs.

>> Yeah. I mean this also gets into

questions of like what is consciousness

like the how does the brain create our

experience. There's this meme out there

that BCI is an artificial intelligence

adjacent story um and that the goal is

to we have to merge humans and machines.

And I do think that there's something to

that but I think in the more immediate

thing here is that ICBC is really a

longevity like healthcare adjacent

story. If the end of the quest of

artificial intelligence are super

intelligent machines, then I think the

end of the BCI quest are actually

conscious machines, it might turn out

that there's actually no measurement

that we can take that will tell us if

something is conscious or not or what

it's like. And the only thing that you

can actually know on that is your own.

And so if that's the case, then to study

consciousness, we will need to use brain

computer interfaces to like see it for

ourselves. And once you've developed

that, then I think that you kind of can

understand the fundamental physics of

what's happening there, whether that's

new fundamental physics or it's emergent

in some way. But if you can learn how to

build like kind of understand whatever

the brain is taking advantage of that

our universe supports, then eventually

you get super intelligent conscious

machines that we can be part of through

these these ultra high bandwidth

connections. Uh I think that's a very

different narrative than how people

usually think about BCI today.

>> I mean, we're at the beginning of that,

right?

>> Oh yeah, we're at the very beginning of

that. the current trial that you have I

mean it's uh low it's relatively low

bandwidth but it's going to get much

higher bandwidth and then I mean like

anything you sort of bootstrap with the

thing that works which I think you know

what what you have is a clear

breakthrough as it is and then if you

look at like the PC revolution for

instance it's like could you believe

that all of this that we have today

started with like a little blue box like

in Altter it still takes some suspension

of disbelief because I biotech has just

been so incremental. Like it's been so

like there's there's been big advances,

but at the same time, these time

constants historically, I mean, you

could easily spend 10 years on something

that feels very incremental. And I think

that one of the things that's so

exciting about what's happening now is

that no longer really feels so

incremental to me. To me, it feels like

we're firmly in like the takeoff era

now. Like something new has happened on

Earth. But I think it's also important

to remember that this didn't start in

like 2019 or 1999. This started in the

late 1800s with the industrial

revolution. just a few years before the

industrial revolution really kicked off.

I mean, life was more or less unchanged

in a fundamental sense for several

thousand years. And they didn't really

even have like a concept of progress in

many ways. And I don't think there's any

way they could have imagined like the

way that their life would have changed

over the course of the like first 10 15

years of the steam engine. And that is

how I feel like looking at the next 15

years right now.

>> Yeah. I mean, so we have an electrical

stimulation right now. And then at the

same time you also do have a bioupling

like it's not purely just electrical.

Would you call it a V2 or like sort of a

next frontier? So this is a totally

different area. I mean the

>> you might be able to use a provision. So

one of the diseases that prima or

electrical stimulator doesn't treat is

glaucoma which is loss of the optic

nerve itself. And so it's possible that

you could use our biohybrid BCI

technology for that. But that's not what

we're doing right now. There are three

elements to our pipeline at at science.

The first is our work in the retina in

blindness especially with the prima

implant. The second is our work in

neural interfaces and the third is is um

our work in profusion with our vessel

program. The biohybrid neural interfaces

the idea here is like if your brain is a

bunch of neurons like how would how

would nature solve this problem like we

often look to nature for inspiration.

Evolution is a way better engineer than

we are at least when dealing with

biology. I think the intuition here kind

of started from your brain is is

composed of two hemispheres and they

kind of process different halves of the

world separately but you don't

experience two hemispheres or two hemi

fields we would say you experience one

integrated moment and this is there's a

cable that connects the two hemispheres

of the brain called the corpus colosum

it's about 200 million fibers and I was

thinking like if nature wanted to build

a ultra high bandwidth braintobrain

connection Like what would how did or if

you wanted to make a new cranial nerve.

So instead of having an optic nerve or a

vestigular nerve, it wanted to have like

the internet nerve like how would nature

solve this problem is it would grow like

a new nerve. It would have a new fiber

bundle with a USB port at the end. So

the intuition here is like if your brain

is a bunch of neurons, what happens if I

culture some neurons on your neurons? Do

they like when you do that in in a lab

that neurons will typically grow

together and wire up and form new

biological connections? And so we have

an approach to the device where we seed

our the implant with living neurons.

These heavily engineered stem cell

derived neurons that we've created. Are

they related to your own neurons or

>> No. So really interestingly, this is

actually one of the deep areas of

research. So we um there's it's one cell

line and the probably the single deepest

area of of of IP on this is that we've

hidden them from the immune system. So,

we're one of a really small number of

companies that have, I think, like

pretty convincing what we call

hypoimmunogenic stem cells. You don't

need to manufacture it per patient,

which would be really expensive and take

much longer. We've got this hypoamogenic

um stem cell derived engineered neuron

that we load into the device in a dish

and then that kind of gets stuck there

and then you engraft this onto the

brain. So, we don't um we don't place

any wires into the brain. We also don't

need to genetically modify the like your

brain. um some of the other ideas out

there, for example, using optogenetics

or things like ultrasound. This requires

using a gene therapy to genetically

modify the neurons in your brain, which

first of all, that's like a one-way

door. And if it goes wrong, that can go

really wrong. Whereas here, because

we're adding the only thing that has

been edited are the graft cells that we

add. And if if those die off, then like

you're really not worse off than you

were before for the most part. Um, but

it comes with the potential of growing

throughout the brain, forming biological

connections all over the place. Um, and

I mean that's what we've seen in the

animal models. That's not in humans yet,

but have you seen James Cameron's Avatar

movies?

>> Definitely.

>> Like you know the ponytails that the

aliens have. That's how I think about

it. Basically, it's like it's a big new

cranial nerve with a connector at the

end. I think that's actually the the

Avatar Q. I think is like a pretty

direct reference for how I think about

our biohybrid neural interfaces. So

earlier you were saying sort of this how

do we find a USB port? I mean obviously

an avatar that's uh you know one of the

manifestations in the blue creatures the

optic nerve in a way is like a port. Um

and then you know jumping to Neurolink

uh when you were co-founding it that you

know sort of enters the brain and then

you there is no not necessarily like an

obvious port like how do you think about

that you know you know where where do

you attach and how does it work and what

did what did you learn from Neurolink

that you know was useful here? Well, I

mean a lot of what I learned from

Neuralink was like just like the in many

ways it was kind of the ultimate startup

PhD and so that was more about like how

do you execute a technically complex

company that requires this type of like

multi-disiplinary team and

infrastructure

>> like I'm very curious from those days

like what was the V1 and then you know

there's the hypothesis and then you know

the outcome and then here like the

outcome is very very awesome with

science so far not done obviously.

>> Yeah. Yeah, when you think about the

brain, like cuz I I remember it being

like totally magical to me, like what is

like how do you even understand what the

brain's doing? Like what is like what

language is it speaking? How do we

understand what's going on there? That

seems like impossibly complicated. The

way that I would think about like the

brain from this information processing

perspective is the brain is full of

these these things that we call

representations. And so you can have a

representation of like hand activity. So

there's like a like a geometric object

in the brain. Like if you record from

some neurons, then when your finger is

is like held open, a neuron will be

firing. When it's closed, another neuron

will be firing. There's neurons that

kind of correspond to every possible

state here. And often in prim primary

motor cortex, which is where many of the

other BCI companies record from, primary

motor cortex is a couple synapses, often

two synapses from the muscle. So it

projects all the way from the top of the

head down to the spine, and then there's

another synapse from the spine out to

the muscle. And so the representation

that you get in primary motor cortex um

is kind of easy to understand because it

looks like like it it directly

corresponds to things that we can easily

reason about like hand state and

specifically often joint joint torques.

One of the things that I like to do

sometimes with the LLMs is like I'll

pick like a neuron to start from for

example like the retinal ganglion cell

and I'll be like okay go forward one

synapse like what are all the cells that

we're connected to? I'll pick another

one be like okay go forward one synapse

like what are all the cells that we're

connected to just kind of try to walk

through the brain and each generation of

model your ability to do this gets

better but one of the things that you

see is that when you're close to like an

input or an output like a muscle or a

coclear hair cell or a retinal ganglen a

roer cone like in these cases we think

of the representations as being concrete

because they correspond to things that

are intuitive for us like colors and

like image intensities or frequencies of

sound or uh muscle control. But as you

go deeper into the brain, it very

quickly kind of blows up into these very

abstract things. And so um like there's

a part of the brain called infratemporal

cortex where the representation that it

has is a map of face like a map of

objects or a map of another area right

next to is a map of faces. We think

about this like map of object space this

normal representation of general

objects. There's like one point you can

think of as like a long list of numbers

and there's some point in that that's

like a vase. There's some point that's

like the Eiffel Tower. There's some

point that's a car. There's some point

that's a person. There's some point

that's like a zebra. And as you move

around in this on this like manifold,

you get um kind of the percept of any

possible object. And there's millions of

neurons there that are representing this

like this space of possible objects that

the brain could be identifying. Sounds

like latent space.

>> It is a latent space. Exactly. And so

there's this huge unification going on

between AI and and neuroscience. And you

know, one of the most interesting things

is that um when you train AI models like

like image models or and even language

models, um the representations that you

get inside them look a lot like the

representations you see in the brain.

>> Fascinating. And so this is like a real

hint that the AI people I mean that's

really good are on the right track.

Yeah. No, I mean the whole idea like

there's these things are like stochastic

parrots or glorified autocompletes like

these people just don't know what

they're talking about. Many people in

neuroscience have gone over to AI

because they're basically still doing

neuroscience but it's just way easier to

do it on the models.

>> It sounds like it's very good news for

you in that like there is actually some

kind of latent space mapping and then

the job of science in terms of being

sort of like the API to the brain.

>> Totally. Exactly.

like entirely possible

>> the neural activity that you when you

record neural activity from the brain

this is just another this is just

another latent and if you can translate

this into another model then you can do

we think really cool stuff with that

>> so you have input now and then you

earlier saying I mean a lot of the

earlier BCI uh experiments involved

figuring out like

>> motor yeah so motor decoding is kind of

this very classic task and you can do it

any number of ways um but getting like

cursor control or keyboard control in a

human. That was first done in the late

'9s. And so I think a lot of the BCI

companies are doing that now just

because like we know it definitely

works. Um you know there's some patient

need and it really is just like an

electronics problem. Like if you can

shrink the electronics so they're small

enough and low power enough so they they

don't dissipate a lot of heat so you can

close the skin then that is like a big

advance. And that I think is really the

first thing that Neuralink has done.

There were prior devices that could do

that type of motor decoding but they

required a connector coming out through

the scalp. And as long as the skin is

open, there's a risk that like an

infection will climb down that and then

you're going to have a really bad day.

So being able to close the skin is

really important. But that was really

difficult because it required really

efficient electronics that were small

enough to fully implant and also were

power efficient enough that they

wouldn't get hot. And so I think the

thing that made this possible is is what

we call the smartphone dividend. Like

BCI couldn't have done this on its own,

but Apple and Samsung and others have

poured epic amounts of money onto making

these types of electronics exist in the

world so that people like us can use

them. And then it feels like you have um

a really significant advantage around

being a biohybrid. I mean there are all

these issues uh famously about you sort

of trying to electrically stimulate uh

brain cells for a long period of time.

Yeah. I mean I think that there are

different products here. I think that on

the like on the one hand I mean I that's

why I'm doing it. I think that's a good

idea. On the other hand I think some

people look at this and they're like

that is now you have a cell to deal with

like you took a device and you added a

bunch of biology to it. And I think we

have a good handle on that. that's why

we're doing it. But there's definitely a

trade-off there. And I think that BCI

we're going to come to see is not is not

a specific product in the way that like

pharma is not a product. I think they're

going to be a bunch of BCI companies

going after different applications where

different types of probes will make

sense. And I think biohybrid in

particular is only really necessary for

some of like the very highest end

things. And on the flip side, it will be

harder to deploy for many other

important medical needs and important

applications along the way. Um, and will

probably be a little backloaded relative

to some other things in in that scalable

impact. So earlier you're referring to

uh, you know, there's a third part of

science which is vessel. Talk more about

that because it feels like you're

applying a lot of the first principles

thinkings that got you here to this

thing that is also like pretty pretty

groundbreaking. So this is this is our

smallest project. So there's this field

of profusion. You can think of it as

they're kind of like heart and lung

machines. And I I was first clued into

the need here about a decade ago when I

read an article in in a medical journal

called the Lancet, which was this case

study of a the 17-year-old living in

Boston who was waiting for a lung

transplant. And while he was waiting for

this lung transplant, he was being kept

alive on a on an ECMO circuit. ECMO is

sacra corporeal membrane oxygenation.

this fancy word for like heart lung

machine. And in his case, his heart was

okay, but his lungs had failed. And so

this was keeping him alive. And after a

while on the transplant list, he was

diagnosed with a complication that made

him no longer a priority recipient for

donor lungs. And so they took him off

the transplant list. And so this article

is kind of about the ethical dilemmas of

like, what do we do with him?

>> But he's alive because he's Yeah. He's

like playing video games. He's doing

homework, hanging out with friends. If

we turn off the circuit, he will

immediately die.

>> Well, don't do that then. On the other

hand, he's consuming a half a million

dollar a month ICU suite. And so there

are these quotes in this article from

the doctors being like his family and

friends derived benefits from his

continued survival and how this raised

fairness questions because if we like

support him for a longer period of time

than why would we do this for everybody?

And so I saw this I'm like those were

great questions. I need answers to those

questions because there seemed to be

this big gap between what was

technically possible and what was

economic to deploy for some reason. I

mean that's exactly what being a founder

is about.

>> Yeah. Yeah. So I saw this and I there's

this database of medical literature

called PubMed and I realized that if I

searched PubMed for the phrase ECMO

ethical dilemma, there were multiple

pages of results. So this was not like a

one-off. And when I looked at this

literature there, it was often a lot of

it was talking about how ECMO shouldn't

be used as a as a quote bridge to

nowhere and how many doctors were

basically trying to discourage families

from like even pursuing it in these

critical care cases because it would

create this bridge nowhere and then like

what do we do? And it creates these

dilemmas. And then I went and asked some

some doc, this was a long time ago. This

was almost a decade ago now. Like, oh

well, like why don't we consider it as a

destination? That the phrase is like a

destination therapy versus a bridge

therapy. What if the technology just

isn't good enough yet and it needs to be

improved?

>> It needs to be improved definitely. But

that wasn't even the response that I

got. The response that I got was just

like shouting and throwing things. And

so I was like something feels wrong

here. But I wasn't really in a position

then to pursue it. But this was always a

thing that was kind of I saw that there

was a really important unification here.

It also this the same fundamental type

of technology has really transformed

organ transplantation. So there they

call it NMP normotheric machine

profusion rather than ECMO but it's the

same idea. Um so 20 years ago if you

needed a like a kidney transplant or a

liver if the car crash happened at 3 in

the morning the surgery would happen at

4:00 or 5 in the morning. But now it

gets scheduled for like the afternoon or

the next day. And over 75% of liver

transplants in the US use this type of

profusion technology now. But like the

the systems that exist for this are like

$500,000. They can only be moved by

private jet. Like one of the big

companies in the space, it turns out

that their like private jet logistics

business is bigger than their medical

device business. And it just like there

was just like clearly an engineering

that could refine this. And so we looked

at this and we thought like, well, what

if you could refine this to the point

where you could check a kidney's luggage

on a United flight to the East Coast? Or

what if you could make a thing that that

17-year-old could have brought home as a

backpack um instead of just what they

did in his case is they stopped changing

the oxygenator filter and a week later

it clotted and he died. And that's what

happened. There are other problems here

like like being able to close the skin

around the brain implant. also need to

make it so that the the tubes that

connect the the blood supply to the

circuit can the skin can heal to it. So

that's not an infection risk. You can

otherwise you have to clean it very

carefully. But just overall there's this

huge gap between like clearly like where

the scientific breakthroughs like were

put were pointing and like what was

being done like I think I think that

people don't appreciate is that in many

cases like there's like if you want to

be a brand in a vat like this basically

already exists like you can keep a like

an end life like patient alive in an ICU

almost indefinitely but this is very

poor quality of life and so patients

like ask for that to be withdrawn like

nobody wants to be basically like a

brain and like a hospital bed connected

to tubes. you need to be able to provide

a high quality of life. And so you need

something that people can like live

with. And I think to see this like if

you can get vision, hearing, balance,

motor control, um the ability to like be

out in the world and doing things, I

just saw this like very fundamental way

to reframe the problems of medicine

here. And so that like I said like at

science even though there's these

several different projects, I really see

them as like as one project over the

next 10 years. So you know started as an

engineer um first principles thinking

which often now is quite associated with

Elon Musk. Uh how did Neurolink start?

How did you get to know him? And how did

all of this sort of come together?

Because I first met you when you were uh

doing Y Combinator many years ago, my

first stint at YC. So, I um

got an email one night in early 2016 um

from Sam uh subject line crazy question

be like Alon starting a brain computer

interface company like who should who

should run it and I assumed they're

talking to a lot of people and my first

reaction was actually I I had some

friends at MIT that I thought I'm like

well these guys are really smart you

should talk to them but then like an

hour later I was like wait a second and

so I I emailed him back I'm like can I

like

and uh Sam introduced me to Elon and

Elon was going around he'd already had

the idea like on his own that he wanted

to start a company and he had the name

Neurolink. I also think that he heard my

name from enough people that he was

talking to at the time and kind of over

the second half of 2016 there was just

this group of people that was kind of

some some degree ever shifting that

would meet once a week or so in the

evening and that snowballed into into

Nurlink and of the the initial group a

bunch of them were people that I knew

from Duke. So Tim Hansen, the guy who

had originally had the the sewing

machine idea, he was in the lab that I

came from at Duke, he was a a grad

student, um I was an undergrad working

for him and then the professor that he

and one of our other friends had gone to

at UCSF and then a collaborator of

theirs. So it was kind of a very small

community.

>> What was that like initially to talk

about the idea of like you know

connecting a computer to a human being's

brain? Elon he I mean he saw what was

coming in AI like very much more clearly

than many other people much earlier and

I think the implications of like if like

you got to this this can't be a separate

thing from humanity and that needs to

merge somehow I think that implication

was just very clear to him and so that

was the genuine motivating factor of

like how do we make it so that this

allows us to upgrade humanity rather

than get left behind. I mean if you look

at the natural history of earth um it's

not like this is a totally speculative

thing. Humanity has totally dominated

the planet and we keep our closest

living relatives in glass boxes so they

don't go extinct. And so there's a real

history here of of greater intelligence

being very dangerous. Like in the

beginning there wasn't like a specific

technical idea necessarily, but there

was that motivating force and then the

idea is we'd pull together like the

smartest group of people that he could

find and and enough resources to to do

whatever made sense and eventually got

consensus around what you see now is the

uh as the thin film polymer threads.

You're one of the best examples of

someone who came from a pure software

world and then went into hard- techch

and now is actually doing real

breakthrough type of research and work

that is also commercializable. The

people watching, they might be on a

similar track. Knowing what you know

now, like what would you tell to the

sort of 2016 version of yourself? So, I

think there's two things. The first is

um like the thing that I did and then

there's the thing I didn't do. The thing

that I did I think was I had I had a a

clear sense of what I wanted and then I

was very high agency towards that. When

I was in college I knew that I wanted to

work in brain computer interfaces. There

was a great lab that was doing that work

at Duke where I went and I was pretty

persistent in figuring out how to like

place myself into that lab. It was in

the medical center. They didn't usually

take undergrads. They're like it took me

a little while to get in there. I

eventually figured out that I could

sneak in by taking an independent study

in the chemistry department that would

like be a back door into this like

primate neuroscience group. But then

really most of my education in college

happened in that lab. So yeah, I grew up

programming in my my deepest hard skill

is software, but I I've been doing

primate brain computer interface like

closely neural decoding stuff since

2008. And so that was just like you had

to be pretty high agency and and like um

persistent in trying to like if like

follow through on that. But that only

works if you have a sense of where you

want to go. And so the first is like

figure out what you want. The thing I

didn't do was my so after college I

started a company um called transcryptic

that was a the it was a robotic cloud

laboratory. So the idea was and I also

in college had the experience of working

in a synthetic biology group where I

needed to go press a button on a device

called a plate reader every 3 hours for

3 days to take a measurement that I

wanted. And I was like in software like

this doesn't we wouldn't do this. Like

this just clearly doesn't make sense.

Like we would automate it. This was also

the time when AWS was just emerging and

cloud computing was becoming a thing.

And it seemed very obvious to me that

instead of every researcher having their

own lab and spending millions of dollars

for all their equipment and then like

needing to press these buttons, like

what we should build is a central

robotic cloud laboratory that expose

APIs that scientists can use to run

experiments over the internet. I did

that, raised a bunch of money when I

stepped down as CEO in in 20 uh

beginning of 2017 to to join Neuralink.

Um it had millions of dollars in revenue

like I felt like we got it to kind of an

early promising point. Um, and then

since then, over the last decade, um, it

that I don't that promise was not

fulfilled. That was still that was hard

mode. That was like a slog. That era

from 2012 to like 2016, I strongly

identified with Ben Horus's essay, The

Struggle. And I think the thing that I

should have done earlier is go work for

somebody like Elon cuz that just like so

dramatically leveled up like my ability

to do this and and know how the game is

played. And um, and I think that often

you'll see these really promising kids

who are just like, I'm going to do it

myself. like I don't want to work for

anybody else. I'm going to start my own

company. I'm going to plow through it.

And like sometimes that works. Like who

am I to say? But I can tell you that

very often startup like running a

startup is an oral tradition. There have

been a couple nucleating times in

history where like a really remarkable

group of people have kind of figured it

out from scratch. Like I think PayPal

was like this. But almost always beyond

that, it's like it's an oral tradition

that you pass down from one of like this

handful of Silicon Valley cultures that

can make a huge difference on the

trajectory of your career to get that

right when you're 20 versus when you're

26 or 28.

>> Well, science is the next. And it sounds

like you're assembling, you know, you've

already assembled a really accomplished

crew of people. And then what we've

learned from startups over the years is

that um once something works like more

and more resources, more and more smart

people sort of come together and then

you know zooming out that's what we

really hope happens uh a whole lot more

in exactly the spaces that you're in

right now. So you know science sounds

like one of those places to go to right

now.

>> It's pretty cool. Yeah. I mean, I'm I

definitely feel pretty lucky that I get

to that I get to do this because it's

such an interdiciplinary problem and the

to innovate on it, you need all these

different areas and really great people

in each of them, but at the same time,

it's there's the the things that you can

do today were unimaginable a few years

ago and and yeah, I mean, I think that I

think we have the best team in the in

the field. So I mean next 10 20 years of

you know science BCI like I guess where

do you see this going and you know what

are you most excited about? I have this

like event horizon at 2035 now like when

I was earlier in my life I always kind

of prided myself on the ability to see

the future and that is the next few

years I think I have a sense of but like

by 2035 it's just like impos there's

like I can't see past it. I think it is

very possible that the first people to

live to a thousand are alive right now.

And I think it might be many more people

than you think. It's not going to be

like one or two people on Earth today.

Earth as a whole is at a not not unique

like this moments in history like have

happened all the time before, but right

now it's a time of exceptional change.

This is going to be really really

influenced by the technological changes

that are happening. And I the the twin

plot lines of brain computer interfaces

and artificial intelligence. People are

are beginning to get that artificial

intelligence is real. It is still not

priced in. People still don't appreciate

it. I agree.

>> But they really don't get what's coming

in in what's possible with brain

computer interfaces. And those are

really parallel but very distinct

stories. Intelligence is going to become

widely available for those that have the

agency to deploy it. And I am generally

pretty optimistic about that. Like I

don't my my pdoom is pretty it's not

zero but it's it's not 50%. It's well

below that. Yeah. Yeah, I don't know if

we'll have cured um all disease. In

fact, I definitely wouldn't use that

term. I wouldn't say we'll have cured

all diseases by 2035. But I think that

there will be kind of new lateral

options that that totally reframe how we

think about the human condition on that

time scale

>> and totally reconfiguring basically that

sort of interface between computers and

humans. It's

>> Yeah. and humans and each other. If a

brain computer interface is equivalent

to a a braintobrain interface in many

cases, this takes you to like totally

new territory. Max, thank you so much

for joining us. Thanks for building the

future and we can't wait to see what you

build next.

>> Thanks, Gary.