Latest / Core Memory / Engineering Brains - EP 09 Max Hodak

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Engineering Brains - EP 09 Max Hodak · Core Memory

0:01
SPEAKER_01: I was in fifth grade and literally saw the matrix and I was like,
0:03
SPEAKER_01: I don't know if we're living in a simulation,
0:05
SPEAKER_01: but we should build one basically.
0:08
SPEAKER_01: Look, Earth is small.
0:10
SPEAKER_01: Resources are intensely contested.
0:13
SPEAKER_01: Space is big.
0:13
SPEAKER_01: The speed of light is low.
0:15
There are real limits to building with atoms and doing things
0:18
in the physical world
0:19
SPEAKER_01: where there's these conflicts,
0:20
SPEAKER_01: like a piece of land can only be used by one person at a time.
0:24
SPEAKER_01: Building buildings is super expensive and complicated.
0:26
SPEAKER_01: But in the simulation, none of those limits are true.
0:30
SPEAKER_01: In the simulation, there's no scarcity.
0:32
SPEAKER_01: Have you heard of the Jennifer Aniston neuron?
0:33
SPEAKER_01: No.
0:34
SPEAKER_01: So there's...
0:35
SPEAKER_01: Yeah.
0:58
And so the intuition here is that if you look at all of the
1:00
millions of neurons in
1:01
SPEAKER_01: that area,
1:02
they encode a representation of architecture or of faces or of
1:07
people or of places.
1:09
SPEAKER_01: And this is embedded on a mathematical object called a manifold.
1:13
And so what you want to do is you want to access that
1:15
statistical representation somehow.
1:17
SPEAKER_01: And when these neurons grow into the brain and they wire up,
1:19
SPEAKER_01: you get all this,
1:20
SPEAKER_01: when the cells in the brain fire,
1:21
SPEAKER_01: you're getting all this partial information,
1:23
which represent information about the statistics of those representations.
1:28
And so you can access this information in and out of the brain
1:31
through this.
1:33
This is a very,
1:33
very deep well of neuroscience that we were at the very
1:36
beginning of.
1:36
SPEAKER_01: Just making these devices at all is pretty tricky.
1:40
SPEAKER_01: I would say this is up there with modern semiconductors for complexity.
1:45
SPEAKER_01: Music
1:59
SPEAKER_00: Hello everyone.
2:00
SPEAKER_00: It's Ashley Vance, your friendly neighborhood host of Core Memory.
2:04
SPEAKER_00: Our guest on this wonderful episode is Max Hodak.
2:10
SPEAKER_00: He is co-founder of Neuralink, currently CEO
2:16
SPEAKER_00: and co-founder of Science Corp, which is an amazing name.
2:20
SPEAKER_00: And we'll get to that in the podcast.
2:22
SPEAKER_00: But if you've been reading the site at all these first couple of months,
2:25
SPEAKER_00: we've written a couple of stories about Macs in science.
2:27
They're doing some of the most cutting edge research and
2:31
products imaginable in the
2:33
brain computer interface field that are helping people get
2:36
their vision back.
2:38
SPEAKER_00: And then they're pushing us
2:40
SPEAKER_00: possibly in some very weird cyborg-ish directions.
2:44
SPEAKER_00: So you're gonna have a great time listening to this.
2:46
SPEAKER_00: We went to Science's headquarters in Alameda,
2:49
SPEAKER_00: California,
2:51
SPEAKER_00: and Max was full of weird and wonderful ideas.
2:55
as ever maybe you're getting this podcast off of core memory
2:59
just want to remind
3:00
you you can get it off itunes spotify wherever you like to get
3:04
your podcast please
3:05
do us a favor leave a review a like all that stuff um be a
3:10
great help and with that
3:14
SPEAKER_00: let us dive right in to the brain and science corp with max odak
3:24
SPEAKER_00: Max Hodak.
3:24
SPEAKER_00: Hello.
3:25
SPEAKER_00: Hey, Ashley.
3:27
SPEAKER_00: I would say welcome to my office, but I'm in your office.
3:30
SPEAKER_00: Welcome to science.
3:31
SPEAKER_00: Yeah.
3:32
SPEAKER_00: So for people who don't know, where are we?
3:35
SPEAKER_01: This is our little pocket of the future in Alameda.
3:39
SPEAKER_01: When we started the company,
3:41
SPEAKER_01: the brand,
3:42
SPEAKER_01: we wanted this white mirror,
3:43
SPEAKER_01: optimistic vision of the future,
3:45
SPEAKER_01: and we created these landscape renders that are on our website now.
3:48
And we wanted this thing that people wouldn't tell if it was
3:51
like far future or ancient past.
3:53
SPEAKER_01: I think those kind of blur together as technology disappears.
3:57
SPEAKER_01: And...
3:59
when we moved here we took some photography updated the website
4:03
built some out and
4:04
people actually sometimes couldn't tell like what were the
4:06
renders and what was
4:07
alameda and so it's like this far future vision of utopian
4:10
future it's like or you
4:11
could live in alameda yeah alameda is a cool place it's uh
4:17
underrated and it's been
4:19
SPEAKER_00: transforming as a bunch of really cool startup setup shop here
4:23
Yeah,
4:24
I mean,
4:24
I have,
4:25
I think,
4:25
a fairly encyclopedic knowledge of Bay Area lab real estate.
4:30
SPEAKER_01: And it's,
4:32
SPEAKER_01: I mean,
4:32
SPEAKER_01: I say this,
4:33
SPEAKER_01: this will of course change very quickly,
4:34
SPEAKER_01: I'm sure,
4:34
SPEAKER_01: but like cheaper than a lot of everywhere else.
4:36
SPEAKER_01: And it's also a good commute for whether you're coming from the East Bay,
4:40
SPEAKER_01: SF,
4:41
SPEAKER_01: the Peninsula,
4:42
SPEAKER_01: kind of all over.
4:43
SPEAKER_01: And so employees really like it.
4:46
SPEAKER_01: It's its own power grid.
4:47
SPEAKER_01: It's not PG&E,
4:48
SPEAKER_01: which is actually underrated for a lot of things,
4:50
SPEAKER_01: especially if you need a lot of power.
4:52
It's like an idyllic community and it is very cost effective
4:55
for this type of infrastructure.
4:57
SPEAKER_00: And just to paint a picture for people who can't,
5:00
SPEAKER_00: some people will see us sitting at the stable,
5:02
SPEAKER_00: some people will just hear this,
5:04
SPEAKER_00: you know,
5:04
SPEAKER_00: what happens in this environment.
5:06
from sort of the...
5:08
What are you guys doing here from wet lab to hardware?
5:11
SPEAKER_00: The scope of what takes place?
5:14
SPEAKER_01: We do a lot.
5:16
So we have everything from a large animal vivarium to cell
5:20
engineering to a small MEMS fab.
5:23
SPEAKER_01: And we've got some tools here.
5:25
SPEAKER_01: We also have a captive MEMS fab in North Carolina.
5:27
I mean,
5:28
we make kind of,
5:30
we're like a full stack neural engineering company.
5:32
SPEAKER_01: Our main focus is on the retinal prosthesis.
5:36
SPEAKER_01: When we started the company,
5:38
we thought that the time was right to restore vision to
5:40
patients that had gone
5:41
SPEAKER_01: blind due to losing the photoreceptors,
5:44
SPEAKER_01: the rods and cones in their eye.
5:46
if you want to do that there's two layers of cells past that in
5:49
the retina the
5:50
retinal bipolar cells and the optic nerve cells and we weren't
5:54
totally sure whether
5:55
it would make sense to stimulate either the bipolar cells or
5:57
the retinal ganglion
5:58
cells the optic nerve cells but if you could figure out how to
6:02
selectively drive
6:02
one or the other with some other it's of course much more
6:05
complicated than that
6:06
then you should be able to get vision back onto the wire going
6:09
into the brain at
6:10
SPEAKER_01: like the first possible opportunity past the dead rods and cones and
6:15
SPEAKER_01: We work on gene therapies.
6:18
SPEAKER_01: We work on electrical simulators.
6:20
We work on these really cool,
6:24
pretty complicated cell-based neural interface technologies.
6:30
SPEAKER_01: But yeah,
6:31
SPEAKER_01: I mean,
6:32
SPEAKER_01: we're especially excited about the Prima retinal prosthesis,
6:35
SPEAKER_01: which is getting submitted to regulators for marketing approval.
6:38
SPEAKER_01: Now, we finished a clinical trial last summer in Europe, 38 patients.
6:43
As far as we know,
6:44
first time ever that these blind patients have been able to
6:46
read again.
6:47
And so not approved yet,
6:49
but the clinical trial results look really,
6:51
really great.
6:52
SPEAKER_01: And we're hoping to have that through the regulatory process soon.
6:56
SPEAKER_00: All right.
6:57
I want to deep dive on all the technology,
7:00
but ever since I've known you,
7:03
I mean,
7:03
you're...
7:05
SPEAKER_00: Lots of people are interested in the brain.
7:07
I would say I could feel it exuding out of you,
7:11
your interest in this field.
7:12
I remember we were talking about you actually wanted to bring
7:15
something like The Matrix,
7:17
SPEAKER_00: make it real.
7:18
You were one of the first people I had ever heard who just like
7:22
willingly admit
7:23
SPEAKER_00: this out loud and had this passion.
7:26
SPEAKER_00: Is that weird?
7:28
SPEAKER_00: I think it's...
7:29
SPEAKER_00: it's maybe a little weird.
7:31
SPEAKER_00: I don't even know if I care about that.
7:33
SPEAKER_00: I think there's like people,
7:34
SPEAKER_00: obviously people who would see the matrix,
7:36
SPEAKER_00: I think is like a dystopian sort of thing.
7:38
SPEAKER_00: Um,
7:39
SPEAKER_00: but even just,
7:39
SPEAKER_00: yeah,
7:40
SPEAKER_01: I mean,
7:40
SPEAKER_01: certainly like the,
7:41
SPEAKER_01: like the human batteries machine state,
7:43
SPEAKER_01: like that's not the part of the matrix that I'm into.
7:45
SPEAKER_00: Right.
7:45
SPEAKER_00: Yeah.
7:46
SPEAKER_00: Yeah.
7:46
SPEAKER_00: No, so that part I got.
7:47
SPEAKER_00: And then I just think, um, yeah, I don't know.
7:50
There's not a lot of people that say something like that with
7:52
such conviction,
7:53
I think.
7:54
SPEAKER_01: Yeah.
7:55
SPEAKER_01: I mean, the,
7:58
like your entire conception of reality is based in electrical
8:02
activity in your brain.
8:03
SPEAKER_01: That's like all of your perception,
8:05
SPEAKER_01: all of your thoughts,
8:06
SPEAKER_01: all your memory,
8:06
SPEAKER_01: all of your reasoning.
8:08
This is all really emergent from the electrical activity of
8:13
these billions of neurons.
8:15
SPEAKER_01: And so it just seemed like very clear to me that if you could,
8:18
SPEAKER_01: if you really believed that engineering with that substrate was possible,
8:21
SPEAKER_01: this would enable some really incredible things.
8:24
SPEAKER_00: And you know, this is what I was curious about.
8:26
Is this something young Max was into forever or is this
8:31
something you came to in college?
8:33
SPEAKER_00: Oh yeah,
8:33
SPEAKER_00: no,
8:34
SPEAKER_01: no,
8:34
SPEAKER_01: this was,
8:34
SPEAKER_01: I saw that like,
8:35
SPEAKER_01: this was a path I was on really since fifth grade,
8:37
SPEAKER_01: trying to figure out how to,
8:39
SPEAKER_01: how to work on these things.
8:39
SPEAKER_00: Like what happened in fifth grade?
8:41
SPEAKER_01: I mean,
8:41
SPEAKER_01: I mean,
8:42
SPEAKER_01: the story was,
8:42
SPEAKER_01: I was in fifth grade and literally saw the matrix and I was like,
8:45
SPEAKER_01: I don't know if we're living in a simulation,
8:47
SPEAKER_01: but we should build one basically.
8:50
SPEAKER_01: Look, Earth is small.
8:52
SPEAKER_01: Resources are intensely contested.
8:54
SPEAKER_01: Space is big.
8:55
SPEAKER_01: The speed of light is low.
8:57
There are real limits to building with atoms and doing things
9:00
in the physical world
9:01
SPEAKER_01: where there's these conflicts,
9:02
SPEAKER_01: like a piece of land can only be used by one person at a time.
9:06
SPEAKER_01: Building buildings is super expensive and complicated.
9:08
SPEAKER_01: But in the simulation, none of those limits are true.
9:11
SPEAKER_01: It is, I think...
9:16
SPEAKER_01: Like in the simulation, there's no scarcity.
9:19
SPEAKER_01: And how like it is,
9:22
SPEAKER_01: of course,
9:22
SPEAKER_01: like anything's not that simple,
9:24
SPEAKER_01: but that at least early on,
9:26
SPEAKER_01: I mean,
9:26
SPEAKER_01: I think I now have more motivations for working on this stuff.
9:28
SPEAKER_01: It is not just not just building the simulation.
9:31
SPEAKER_01: I also think.
9:33
SPEAKER_01: AI is real, making that not an other, merging with that.
9:36
SPEAKER_01: That's the thing that I didn't necessarily...
9:38
It was not really in my initial motivation for working in
9:41
neural engineering,
9:42
SPEAKER_01: but it is increasingly so.
9:43
And so I think there's many different paths to this,
9:47
but that was part of my origin story.
9:49
SPEAKER_00: And you're...
9:51
SPEAKER_00: Look, you're super bright.
9:53
SPEAKER_00: When you had that impulse in fifth grade,
9:55
SPEAKER_00: did that mean you started reading tons of science fiction?
9:59
SPEAKER_00: Did you get into computer science?
10:01
SPEAKER_00: Did you get into biology?
10:03
SPEAKER_00: Or did you not really take action as a fifth grader on that?
10:06
SPEAKER_01: Well, I mean, I started programming when I was really little.
10:09
My parents tell me that I sat on the floor of a Barnes & Noble
10:11
and cried until they
10:12
bought me a Learn Visual Basic book or like a basic .NET book
10:17
or something,
10:17
SPEAKER_01: or well before .NET,
10:18
SPEAKER_01: like a QBasic book.
10:21
SPEAKER_01: And they were very skeptical I would actually make anything.
10:26
SPEAKER_01: And now, 30 years later, I've written many programs.
10:30
SPEAKER_01: But I've always been around computers.
10:32
SPEAKER_01: I think when I was a kid,
10:34
it was like the compiler was the thing that didn't care how old
10:36
you were and would
10:37
SPEAKER_01: take you seriously regardless.
10:38
SPEAKER_01: Yeah.
10:40
SPEAKER_01: But no,
10:41
SPEAKER_01: I mean,
10:41
there's not a lot that a fifth grader in the late nineties can
10:44
do to really work on neural,
10:46
SPEAKER_01: like to work on brain computer interfaces.
10:49
SPEAKER_01: So it was reading, it was being an enthusiast.
10:51
I mean,
10:51
I certainly wanted to make stuff,
10:53
but that wasn't really practical.
10:56
SPEAKER_01: Ultimately,
10:57
one of the reasons I went to the college I did Duke was because
11:00
there was a lab
11:00
SPEAKER_01: that at the time was doing some of the best work in the field.
11:04
SPEAKER_01: Miguel Nicolales' group in Duke Med Center.
11:07
SPEAKER_01: And when I showed up to Duke as a freshman, I like...
11:12
SPEAKER_01: pretty quickly figured out how to get into that lab.
11:15
So I remember my freshman year advisor,
11:18
there's like,
11:18
is there a lab that you want to work in?
11:20
SPEAKER_01: Is there some internship?
11:21
SPEAKER_01: And I suggested Nicholas's group and got immediately rejected.
11:25
SPEAKER_01: They're like, they don't take undergrads.
11:26
SPEAKER_01: It's like, that's the medical center.
11:28
SPEAKER_01: That's not accessible.
11:29
And so I eventually figured out that I could do an independent
11:32
study through the
11:33
SPEAKER_01: chemistry department.
11:34
SPEAKER_01: There's a class called Chem26S.
11:36
SPEAKER_01: but didn't actually require you to work in the chemistry department.
11:39
SPEAKER_01: And I was able from there to get into the Nicholas lab.
11:42
SPEAKER_01: And that was really where most of my education happened in college.
11:45
SPEAKER_00: Okay.
11:45
SPEAKER_00: So,
11:46
SPEAKER_00: but even at that point,
11:47
SPEAKER_00: were you thinking,
11:48
were you thinking I'm going to be an entrepreneur or are you
11:52
thinking I'm going to
11:53
SPEAKER_00: get like a PhD in neuroscience?
11:55
SPEAKER_01: I don't think at that point I had a particularly strong experience.
12:00
SPEAKER_01: sense of that.
12:03
SPEAKER_01: I was always kind of an entrepreneur.
12:05
SPEAKER_01: When I was in high school,
12:07
SPEAKER_01: I did web design consulting with some friends,
12:09
kind of figured out how to make some money come out of the
12:11
internet to buy myself a laptop.
12:14
and then i didn't really enjoy school i was never really um
12:19
like i was a fine
12:20
student i went to a fine school graduated with a degree in
12:24
biomedical engineering
12:24
from a pretty good program for that but i never like liked
12:27
college or liked school
12:29
for the matter um and so i'd always been somewhat
12:33
entrepreneurial but i don't know
12:35
i mean the reason that i ended up going into industry was
12:37
really more driven by the
12:39
SPEAKER_01: logic that um
12:42
SPEAKER_01: if in academia,
12:43
SPEAKER_01: when you're applying for grants,
12:45
SPEAKER_01: if you apply for a grant,
12:46
SPEAKER_01: these are these philanthropic funders that if they don't fund you,
12:50
SPEAKER_01: like,
12:51
SPEAKER_01: fine,
12:52
SPEAKER_01: it's their money.
12:52
SPEAKER_01: Who are you to say that they're wrong?
12:54
SPEAKER_01: They can pick what they're interested in.
12:56
SPEAKER_01: And in industry,
12:57
SPEAKER_01: there was,
12:57
SPEAKER_01: if you,
12:58
it just made more sense to me why someone would give you money deterministically,
13:02
SPEAKER_01: because if you can create this closed economic cycle,
13:04
SPEAKER_01: create this return,
13:04
SPEAKER_01: it didn't,
13:06
SPEAKER_01: it just,
13:06
SPEAKER_01: it made me feel like I'd have more agency over my life.
13:09
SPEAKER_01: And ultimately,
13:10
SPEAKER_01: when things work industrially,
13:12
you can marshal much larger amounts of resources than you can
13:16
in really any other way.
13:18
SPEAKER_01: Although back in 2011,
13:19
SPEAKER_01: 2012,
13:19
SPEAKER_01: when I was graduating from college,
13:22
SPEAKER_01: it was clear that BCIs were still a ways from translation.
13:27
SPEAKER_01: I figured when I was graduating from college that
13:30
SPEAKER_01: You'd probably need like $100 million in 10 years to build a BCI company,
13:34
SPEAKER_01: which I didn't have at that time.
13:35
And so I started a company and somebody thought was more
13:37
accessible and building
13:39
SPEAKER_01: automation for drug discovery,
13:41
SPEAKER_01: which was also interesting.
13:42
SPEAKER_00: Was that transcriptic?
13:43
SPEAKER_01: That was transcriptic.
13:44
SPEAKER_00: Okay.
13:44
And just for people who might not know,
13:46
a BCI is a brain-computer interface?
13:48
SPEAKER_00: Yeah.
13:48
SPEAKER_00: Yeah.
13:50
SPEAKER_01: And I considered going to grad school, but I figured...
13:54
that if BCI is 20,
13:58
2012,
13:58
BCI is probably 10 years away from clinical translation.
14:00
SPEAKER_01: You go get a PhD,
14:02
SPEAKER_01: graduate six or seven years later,
14:04
SPEAKER_01: random postdoc,
14:05
SPEAKER_01: don't have access to real resources.
14:07
SPEAKER_01: BCI would probably still be 10 years away from clinical translation.
14:10
SPEAKER_01: And so I just,
14:11
I thought that I'd have more agency over my life learning to
14:14
build companies,
14:15
SPEAKER_01: get access to those resources,
14:16
SPEAKER_01: and then be able to deploy them towards,
14:18
SPEAKER_01: figure out how to do it profitably,
14:19
SPEAKER_01: basically.
14:19
SPEAKER_00: Did you grow up in North Carolina?
14:21
SPEAKER_00: No, I grew up in Manhattan.
14:22
SPEAKER_00: Yeah.
14:23
in manhattan so was obviously an entrepreneurial place with
14:27
where these ideas might
14:28
be floating around but had you had you thought about silicon
14:32
valley were there
14:33
people you kind of looked up to or anything like that i was
14:37
growing up i was like
14:38
vaguely dimly aware of silicon valley um i was a kid through
14:43
the dot-com era i was
14:45
i think i had like a pretty dim awareness of it new york was a
14:47
totally different
14:48
SPEAKER_01: culture subculture
14:50
SPEAKER_01: No, I mean, I drove out.
14:51
SPEAKER_01: So I did two years of college.
14:53
SPEAKER_01: I actually took a year off.
14:55
SPEAKER_01: So when I was in high school,
14:56
SPEAKER_01: I was concerned that,
14:57
SPEAKER_01: like I think many high school students,
14:59
SPEAKER_01: I had no future,
14:59
SPEAKER_01: was never going to get into a good school.
15:02
SPEAKER_01: I got a bunch of statistics from my guidance counselor's office,
15:05
SPEAKER_01: entered those into Excel,
15:07
SPEAKER_01: built a model,
15:08
SPEAKER_01: and kind of you can –
15:11
SPEAKER_01: or this at least used to be this kind of interesting,
15:14
SPEAKER_01: like there's some game theoretic interesting elements there.
15:18
And so I built a model that predicted like if I applied early
15:21
decision versus early
15:22
action and made like what was the best school that I could get
15:25
into that aligned
15:25
SPEAKER_01: with my interests.
15:26
And one of those interests,
15:27
of course,
15:28
was wanting to work in a good BCI lab.
15:30
SPEAKER_01: I ended up working out that my,
15:32
what I thought my optimal move there was to apply to Duke early
15:35
decision where I
15:36
SPEAKER_01: thought I'd have a very high chance of getting in.
15:37
SPEAKER_01: You can of course only do that.
15:38
SPEAKER_01: I got in, I was committed.
15:40
SPEAKER_01: And then that eventually,
15:42
that model eventually turned into a small SaaS company that I
15:45
took a year off college,
15:47
SPEAKER_01: moved out to California,
15:48
SPEAKER_01: ran that for a little over a year.
15:50
SPEAKER_01: That got pretty quickly a very small acquisition.
15:53
SPEAKER_01: But no,
15:54
SPEAKER_01: I showed up,
15:55
I kind of drove across the country as a sophomore in college
15:57
with a friend and
15:59
SPEAKER_01: Got an apartment in Mountain View and didn't know anybody.
16:02
And it was like very lonely for the first year and eventually
16:05
started making some friends.
16:06
And then like 15 years later,
16:08
you look around and like your friends are everywhere.
16:10
SPEAKER_01: But that was not where I started.
16:12
So in this year off,
16:13
you just took a year off from college,
16:15
started a company and sold it.
16:17
SPEAKER_01: Yeah,
16:17
SPEAKER_01: I mean,
16:18
SPEAKER_01: it wasn't like a big success,
16:19
SPEAKER_01: but it was a really interesting...
16:22
SPEAKER_01: I mean,
16:22
SPEAKER_01: that was really my introduction to Silicon Valley.
16:24
And I think...
16:25
I remember my co-founder from that was...
16:29
He's a product guy.
16:32
But we ended up at this house party once in,
16:35
I want to say,
16:36
somewhere in South Bay.
16:37
SPEAKER_01: I forget exactly where.
16:38
SPEAKER_01: But when we went, it was advertised as like a hackathon-type party.
16:44
SPEAKER_01: And...
16:46
SPEAKER_01: I didn't really know what to expect.
16:47
He thought that there's,
16:48
like,
16:49
no way that people are going to be on laptops.
16:50
SPEAKER_01: It's like,
16:50
SPEAKER_01: you're going to be,
16:51
SPEAKER_01: like,
16:51
SPEAKER_01: it's going to be in the backyard by the pool,
16:53
SPEAKER_01: like,
16:53
SPEAKER_01: people are going to have beers.
16:54
SPEAKER_01: And you walk in, there's just, like, fold-out tables of rows of laptops.
16:58
SPEAKER_01: And I was like, these are my people.
17:01
Okay,
17:02
one last question along those lines,
17:04
because I was wondering this as you were talking.
17:06
SPEAKER_00: I mean, are your parents engineers at all?
17:10
SPEAKER_00: Is there any reason for you to be wired this way from your background?
17:14
SPEAKER_01: I guess, like, my...
17:17
My dad has a degree in aerospace engineering undergrad,
17:20
and then they met at business school.
17:22
SPEAKER_01: They both went to, they met in their MBA at Wharton.
17:26
SPEAKER_01: And so I grew up around like a business sense.
17:30
SPEAKER_01: Okay.
17:30
SPEAKER_01: My dad's a management consultant.
17:33
SPEAKER_01: My mom does like ESG and philanthropy stuff.
17:39
SPEAKER_01: She was actually at Lehman.
17:41
SPEAKER_01: in 2008, which was a really interesting form.
17:44
SPEAKER_01: I have this list in my mind of like impossible things.
17:47
SPEAKER_01: And like the failure of Lehman was like entry one on that list is like,
17:50
SPEAKER_01: there's things that you never think.
17:51
SPEAKER_01: I mean,
17:51
SPEAKER_01: this sounds simple now because it's so long ago,
17:53
SPEAKER_01: but like as a kid growing up around these institutions,
17:55
SPEAKER_01: you see these things happen that you're like,
17:57
SPEAKER_01: there's no way that would happen.
17:59
SPEAKER_01: Um, but, uh,
18:01
SPEAKER_01: Yeah, I mean, my dad knows a good program.
18:08
SPEAKER_01: We grew up building model rockets and doing stuff like that.
18:12
SPEAKER_01: So I was a bit exposed to it.
18:14
SPEAKER_00: And when you were a freshman, what year did you go to college?
18:17
SPEAKER_01: That was fall of 2007.
18:19
SPEAKER_00: Fall of 2007,
18:20
SPEAKER_00: and you're already thinking about brain-computer interfaces,
18:23
SPEAKER_00: because,
18:23
SPEAKER_00: you know,
18:24
SPEAKER_00: they were not the most exciting,
18:27
SPEAKER_00: very academic.
18:28
SPEAKER_00: This field is a lot older than that.
18:30
SPEAKER_01: Like, the Utah Array was invented in the mid-90s.
18:33
SPEAKER_01: Right, but you'd even... Cyberkinetics had been a startup.
18:35
SPEAKER_00: Yeah.
18:35
SPEAKER_00: Yeah, at that point.
18:36
SPEAKER_00: You'd been following even stuff like that.
18:38
SPEAKER_01: Oh, yeah, yeah.
18:39
SPEAKER_00: You would...
18:41
SPEAKER_00: I mean,
18:41
SPEAKER_00: I definitely never heard of a Utah Array,
18:43
SPEAKER_00: you know,
18:44
SPEAKER_00: until,
18:44
SPEAKER_00: I would say,
18:45
SPEAKER_00: relatively recently.
18:46
SPEAKER_00: But so you were like...
18:48
genuinely into,
18:50
even as a teenager pursuing brain-computer interface stuff and
18:54
SPEAKER_01: Yeah, I mean, I also had played sports and did other things.
18:59
But yeah,
19:00
I mean,
19:00
I definitely knew about,
19:02
was following the field and reading about it.
19:05
SPEAKER_01: There wasn't a lot that I could do at the time on that.
19:07
SPEAKER_01: I was reading and being interested in it and dreaming about it.
19:11
SPEAKER_01: But I mean, this is pretty cool.
19:13
SPEAKER_01: It is pretty cool to be here in 2025 getting to do this.
19:18
SPEAKER_01: That, yeah, I don't think was necessarily given.
19:20
SPEAKER_00: So that was my next question.
19:21
SPEAKER_00: I mean,
19:21
SPEAKER_00: you happen to be coming of age is probably not the right phrase,
19:27
but getting into your professional career right as money starts
19:31
to come into this technology,
19:33
as it starts to transform from the mostly academic pursuit to
19:38
lots of brain implant
19:40
SPEAKER_00: and BCI startups.
19:43
I mean,
19:44
like you just said,
19:45
that's sort of fortuitous for somebody who's into this stuff.
19:48
SPEAKER_01: Yeah,
19:48
SPEAKER_01: I mean,
19:48
SPEAKER_01: I think that this is also,
19:50
SPEAKER_01: I mean,
19:50
this is like a narrow slice of just the craziness that we all
19:56
seem to be here right
19:57
now getting to do this in what appears increasingly to me like
20:00
to be the takeoff era.
20:02
And you can see how in some people this kind of tugs at the
20:05
sense of like,
20:06
SPEAKER_01: are we living in a simulation?
20:07
Like we're here getting to do this stuff in this time when
20:10
every like AI is happening,
20:11
SPEAKER_01: BCIs are happening.
20:14
SPEAKER_01: The internet has matured.
20:17
SPEAKER_01: It is definitely, I think, the most exciting time in human history.
20:22
SPEAKER_01: And I think that that will continue to be true.
20:25
SPEAKER_00: So I can never tell because I think like you,
20:27
SPEAKER_00: you probably hang out with even,
20:29
SPEAKER_00: I don't know,
20:30
SPEAKER_00: I spend my whole life hanging out with people at the frontier of science.
20:33
SPEAKER_00: And so it starts to really skew my sense of reality or,
20:37
SPEAKER_00: or,
20:37
SPEAKER_00: or what other people get to encounter on a day to day basis.
20:42
SPEAKER_00: You probably even have a more extreme version of that.
20:45
SPEAKER_00: So I,
20:45
cause I have a similar feeling to what you're describing
20:47
sometimes as this takeoff point,
20:49
SPEAKER_00: um,
20:51
SPEAKER_00: And then I try to put myself in the shoes of someone,
20:53
SPEAKER_00: I don't know,
20:54
SPEAKER_00: whatever it is,
20:54
SPEAKER_00: like 40 years ago.
20:55
It's like,
20:56
if you're inclined this way,
20:58
do you always sort of feel like this to some degree?
21:02
SPEAKER_01: Well,
21:02
SPEAKER_01: I mean,
21:02
SPEAKER_01: have you seen,
21:03
SPEAKER_01: like we think of it as like the graph,
21:05
SPEAKER_01: have you seen the GDP over time going back 2,000 years?
21:09
uh yes yeah yeah so i mean it is it's the hawk it's a
21:14
exponential it's a hockey
21:15
stick and i think the thing that i only i think i realized
21:19
maybe a year ago but i
21:20
hadn't really appreciated before is this acceleration didn't
21:23
start five years ago
21:26
or in 2001 this started in the late 1800s this really started
21:30
with the industrial
21:30
revolution and the acceleration has been has been continuous um
21:36
and the uh
21:38
SPEAKER_01: And the doomers have always been there,
21:40
SPEAKER_01: like the Malthusians were kind of the OG doomers on this.
21:43
Because they look at this and they're like,
21:44
this can't possibly be sustainable.
21:46
SPEAKER_01: But it all just gets so much bigger.
21:49
And that is what is possible with technology,
21:53
basically,
21:53
and engineering applications of it.
21:55
SPEAKER_01: And that has all just gotten so much further.
21:57
I mean,
21:57
it just breaks intuition constantly because it's tough to think
22:02
that way.
22:02
SPEAKER_01: But yeah,
22:03
SPEAKER_01: I mean,
22:03
SPEAKER_01: I think in the early 2000s or like in the 2010s,
22:07
SPEAKER_01: people were saying like,
22:08
SPEAKER_01: oh,
22:08
SPEAKER_01: there's a generation that went from horse and buggy to man on the moon.
22:12
SPEAKER_01: Are we ever going to match that?
22:14
SPEAKER_01: Because can you imagine going from like pre-car to jet planes routinely?
22:21
And I think now the feeling of like,
22:23
yes,
22:23
that has not stopped is coming back.
22:25
SPEAKER_00: Yeah,
22:26
SPEAKER_00: I remember distinctly somewhere around 2012,
22:29
there was a paper from a physicist who I think worked at China
22:34
Basin Lake,
22:36
SPEAKER_00: and he wrote this paper looking at patents over time,
22:39
SPEAKER_00: and he was arguing that all the big ideas had been found,
22:43
SPEAKER_00: and then,
22:44
SPEAKER_00: you know,
22:45
SPEAKER_00: since then it does feel like...
22:47
we and this was like in an era when when like the iphone had
22:51
come out but then a
22:54
lot of tech was kind of boring because it was like facebook and
22:57
things like that
22:58
and and so it sort of by the way these are only like it's crazy
23:02
that we thought
23:02
that these were boring at the time because the i like the two
23:05
things you said the
23:06
iphone and facebook have dramatically reshaped the world well i
23:09
meant the iphone
23:10
SPEAKER_00: was a bit
23:10
one that was a big one but then things had kind of gotten a
23:12
little a little uh i
23:14
think the iphone even is more dramatic in retrospect yeah like
23:17
we talk about like
23:19
opioids and the effect of um the just how strong an effect on a
23:26
human brain a
23:26
connection to a phone is is like it's not it's not that it's
23:30
under people get this
23:31
but we still don't really get how dramatic that is oh no i mean
23:35
i think it's like
23:36
SPEAKER_01: people get so anxious being away from it for a couple minutes
23:38
SPEAKER_00: Yeah.
23:39
And then you,
23:40
we were just with a group of four people today and everyone's
23:43
had this experience.
23:44
SPEAKER_00: It's like, you have small talk for a second, everybody gets bored.
23:47
SPEAKER_00: Checking your phones.
23:48
SPEAKER_00: Checking your phones together.
23:50
SPEAKER_00: That is a crazy technology.
23:52
SPEAKER_01: Yeah.
23:52
SPEAKER_01: Yeah.
23:53
SPEAKER_01: And then Facebook,
23:54
SPEAKER_01: I mean,
23:55
SPEAKER_01: not Facebook specifically,
23:56
SPEAKER_01: but social media,
23:58
SPEAKER_01: it was less of a technical innovation as a social one,
24:00
SPEAKER_01: but it has profoundly reshaped the world.
24:02
right right no but i mean okay no point taken and agree i think
24:06
it was that sense
24:07
of like like you were talking about of uh the light bulb or uh
24:11
um yeah we wanted we
24:13
wanted flying cars and we got uh 140 characters yeah but the
24:18
140 characters
24:18
reshaped earth yeah and i think this is really underrated in in
24:22
this communications
24:23
worldwide yeah yeah yeah no that's true i think sometimes like
24:27
hardware things are
24:28
SPEAKER_00: easier to for people to immediately identify that
24:32
SPEAKER_00: Yesterday, we didn't have a semiconductor.
24:34
SPEAKER_00: Now we do, and it unlocks all these things.
24:38
SPEAKER_00: Obviously not instantly,
24:39
SPEAKER_00: but you feel like in this particular moment,
24:42
SPEAKER_00: because I think there are people who would argue,
24:45
SPEAKER_00: yes,
24:46
SPEAKER_00: something like BCIs are exciting,
24:48
SPEAKER_00: gene therapies are exciting,
24:52
SPEAKER_00: all kinds of stuff that I cover,
24:54
SPEAKER_00: energy.
24:55
SPEAKER_00: All of these things are exciting.
24:56
SPEAKER_00: Right, but still feel like not guaranteed at all.
25:02
SPEAKER_01: I agree with that.
25:03
SPEAKER_01: I think BCI in particular,
25:04
SPEAKER_01: there's been a lot of capital and a lot of interest,
25:08
but there's still no BCI company making a couple hundred
25:11
million dollars a year
25:12
SPEAKER_01: more in revenue.
25:13
SPEAKER_01: Until that is true, there will always be a risk of winter.
25:18
SPEAKER_01: I think that that risk,
25:20
SPEAKER_01: AI is through the looking glass on this,
25:23
SPEAKER_01: but BCI is still on that side,
25:26
which is I think one of the reasons that our focus is so
25:28
strongly on get the visual
25:29
SPEAKER_01: prosthesis to market,
25:31
SPEAKER_01: get profitable,
25:33
SPEAKER_01: and then have capital markets start to see,
25:38
SPEAKER_01: oh,
25:39
SPEAKER_01: there's actually economic return here.
25:40
Because the flip side of getting to deploy these types of
25:42
resources is you have to
25:43
SPEAKER_01: close the economic cycle that cannot be forgotten.
25:46
SPEAKER_00: But if I go down the list of DCI,
25:51
SPEAKER_00: vertical takeoff,
25:53
SPEAKER_00: you know,
25:54
SPEAKER_00: taxis,
25:57
SPEAKER_00: partial cell reprogramming,
25:59
my sense is you're like net positive on this kind of bucket of
26:04
things that we're on
26:05
SPEAKER_00: the cusp of.
26:05
SPEAKER_01: Yeah, I mean, I think for a lot of these, it's really the...
26:11
SPEAKER_01: they're really held back by regulatory decisions.
26:14
SPEAKER_01: And I don't mean that dismissively.
26:15
SPEAKER_01: I mean,
26:16
SPEAKER_01: like we can make decisions that give us a clean,
26:19
SPEAKER_01: healthy society with all kinds of nuance and trade-offs there.
26:22
SPEAKER_01: But absolutely,
26:24
SPEAKER_01: if you had no environmental or airspace regulations,
26:27
SPEAKER_01: we would have flying cars all over the place.
26:30
SPEAKER_01: You'd have eVTOL everywhere.
26:32
SPEAKER_01: Yeah.
26:33
SPEAKER_01: But these are societal-level conversations.
26:37
I think that you'll start seeing these things deployed
26:39
differentially in different
26:40
SPEAKER_01: regions that make different trade-offs about these things.
26:42
SPEAKER_01: But I think it's more than just the technology.
26:47
SPEAKER_01: I think that the technology is great.
26:48
SPEAKER_01: And even on the drug discovery side,
26:50
SPEAKER_01: like gene or cell therapies,
26:51
SPEAKER_01: I think that you've got a knob.
26:54
SPEAKER_01: Society is a knob,
26:54
which is how quickly and how much do you do in human subjects
27:00
research versus...
27:02
SPEAKER_01: how fast do you get new drugs?
27:04
SPEAKER_01: And we have largely turned that down to minus five, um, societally.
27:08
SPEAKER_01: And this isn't like the, this isn't like the fault of the FDA.
27:11
SPEAKER_01: This is, um, this is the culture of, of, um,
27:18
it's this is there's no like magic bullet here there's it's
27:21
tough because nobody
27:22
you don't you as a patient you want things that are safe you
27:27
don't want anything to
27:27
be made worse especially if it's a family member like you see
27:30
how you get there i
27:30
can tell you on the other side of this at the point where
27:34
you're doing a brain
27:35
surgery for the first time or you're dosing a human with a new
27:37
thing for the first
27:38
time that is a very stressful experience like that is not
27:41
something that is done
27:42
SPEAKER_01: lightly and so there's just a lot of
27:45
SPEAKER_01: concern around that, which is justified.
27:48
SPEAKER_01: But at the same time,
27:49
SPEAKER_01: if you look at what is possible in the animal models,
27:52
SPEAKER_01: we have amazing technologies.
27:55
It's that translation because of our concern for other humans
27:59
creates a lot of friction.
28:00
SPEAKER_01: And I don't have a magic bullet for that, but I think that's the tension.
28:04
SPEAKER_00: And you outlined some of your
28:07
SPEAKER_00: I want to get to your idealistic,
28:10
SPEAKER_00: your optimum future,
28:12
whether it's even like in your lifetime or possibly a couple
28:16
more generations.
28:19
SPEAKER_00: You said some of it when you were talking about
28:22
matrix of living in this virtual world that's bountiful and and
28:26
if we were watching
28:28
you got me to start watching uh pantheon in which you know in
28:31
in that show people
28:32
are able to upload their minds and into a computer and and
28:36
except for a glitch
28:37
otherwise we'd be able to live forever maybe with their
28:40
personality i don't know i
28:41
was just kind of curious yeah i mean where you want to start
28:44
it's tough to talk
28:45
SPEAKER_01: about this stuff without like sounding like a lunatic
28:49
SPEAKER_01: I'll be honest,
28:49
I don't at this point have like a concrete vision for how I
28:52
think 2040 or 2045 is
28:53
SPEAKER_01: going to look.
28:55
SPEAKER_01: There's like,
28:55
SPEAKER_01: I always,
28:57
SPEAKER_01: like growing up for a lot of my life,
28:58
I always felt like I could kind of see the future and this guy
29:01
did what I did.
29:03
SPEAKER_01: And now I just have this event horizon at like 2035.
29:06
SPEAKER_01: maybe even 2030.
29:08
SPEAKER_01: And it's just impossible to see past that.
29:12
And I think part of it is when you look at a lot of the
29:14
depictions of the future in
29:18
SPEAKER_01: science fiction,
29:19
SPEAKER_01: like another one of my favorite stories is The Expanse,
29:22
SPEAKER_01: which is fundamentally a political drama.
29:26
SPEAKER_01: And the thing that is missing from so many of these stories is AI.
29:30
And that is often intentionally left out because at the point
29:34
where you've got AGI,
29:34
there's no longer a story about humans and the humans want to
29:37
see stories about
29:38
SPEAKER_01: each other.
29:39
SPEAKER_01: But that can't be left out.
29:42
SPEAKER_01: It won't be left out of the future.
29:43
I think the only story that I think really gets this that I
29:47
feel is compelling is
29:49
SPEAKER_01: Ian Banks' The Culture.
29:52
SPEAKER_01: And that is a very optimistic vision,
29:55
SPEAKER_01: but a very like also grounded one where it's not like this utopia,
29:58
SPEAKER_01: but it's not all good.
29:59
Like they could spend a lot of their time dealing with really
30:02
complex moral and
30:02
SPEAKER_01: ethical trade-offs that you get in that type of society.
30:06
But I think that there's that huge transition from a pre-AGI to
30:13
post-AGI society
30:15
SPEAKER_01: how does that impact on scarcity?
30:17
SPEAKER_01: Obviously,
30:17
SPEAKER_01: I mean,
30:18
SPEAKER_01: one of the lessons of Bitcoin for me is like,
30:20
SPEAKER_01: there's no scarcity information.
30:22
SPEAKER_01: The internet can make as many copies as you want.
30:24
SPEAKER_01: And so we created a new source of scarcity.
30:27
SPEAKER_01: And that is a transition that I...
30:32
I think is just so out of distribution that is still pretty
30:35
hard for me to reason about.
30:37
SPEAKER_01: But I remain optimistic.
30:39
SPEAKER_01: I think that there's going to be a lot of uncertainty,
30:42
SPEAKER_01: but success is absolutely one of the possible outcomes here.
30:46
It is very possible that that future is amazing and we have to
30:50
figure out how to
30:50
SPEAKER_01: get there,
30:51
SPEAKER_01: but that's going to be...
30:52
Um,
30:53
way beyond,
30:54
I mean,
30:54
I'm just often feel buffeted along by much larger forces.
30:57
SPEAKER_00: I feel like you're holding back.
30:59
SPEAKER_00: I know you, I've heard you riff on the future.
31:04
SPEAKER_00: The, when you started science in 22?
31:06
SPEAKER_00: Uh, mid 21.
31:06
SPEAKER_00: Mid 21.
31:06
SPEAKER_00: Um, yeah.
31:11
SPEAKER_00: We hadn't, LLMs had not, like, why around?
31:14
SPEAKER_00: They were around, but not, you know, sort of after that chat, GPT moment.
31:18
SPEAKER_00: It was before that.
31:19
SPEAKER_00: Like, why start a brain company as opposed to an AI company?
31:25
SPEAKER_01: I mean,
31:26
SPEAKER_01: I,
31:28
SPEAKER_01: every now and then,
31:28
SPEAKER_01: I mean,
31:28
SPEAKER_01: I think that my life would be in some ways easier if I was doing AI.
31:32
SPEAKER_01: AI has a lot of nice structural advantages.
31:34
SPEAKER_01: You can do it with a laptop.
31:35
SPEAKER_01: You can inspect the weights.
31:36
SPEAKER_01: It's like, you can, it's really more engineerable than biology.
31:40
SPEAKER_01: It grows a lot faster.
31:41
SPEAKER_01: You don't have these time constants in biology.
31:48
SPEAKER_01: You have to actively prevent engineers from re-implementing cryptographic
31:52
SPEAKER_01: primitives in ways that are totally dangerous,
31:54
SPEAKER_01: because it's just like you've got an F-16 sitting there,
31:56
SPEAKER_01: and you can see it,
31:57
SPEAKER_01: but you can't touch the F-16.
31:58
SPEAKER_01: It's very tough.
31:59
SPEAKER_01: It's this glittering...
32:01
uh the um thing and so a working on ai is obviously very
32:09
alluring but also i felt
32:11
like it wasn't the thing like these are not these fields are
32:15
not just really driven
32:16
by people that come into them later on later on i think the
32:19
people that have been
32:20
SPEAKER_01: doing this like ilia like andre like um
32:25
uh like the people that are like like demes like they've spent
32:28
their life working
32:28
on in the same way that i've spent my life really interested in
32:30
bci and i think
32:32
that there's a lot of judgment and intuition that gets built
32:35
doing that that i
32:36
didn't have they were clearly better positioned this is i felt
32:40
like my contribution
32:41
to the world it was a thing that i think i know much better
32:43
than almost anybody
32:44
SPEAKER_01: else um and that also then like capital followed that like you could
32:49
SPEAKER_01: I could kind of start my career over switching to AI.
32:52
But one of the things I found in 21 was a bunch of my friends
32:56
had seen what I'd
32:57
done previously and were willing to put up a pretty large
33:00
amount of capital,
33:01
SPEAKER_01: like basically $150 million from day one.
33:03
SPEAKER_01: Those are good friends.
33:04
SPEAKER_01: To say, like, we believe in your understanding of how to build this.
33:09
SPEAKER_01: And that wouldn't have been possible if I changed careers.
33:11
SPEAKER_01: And I also didn't want to.
33:12
SPEAKER_01: I think that this still hasn't been done
33:14
SPEAKER_01: It is important to me that it happens.
33:16
SPEAKER_00: Did you know it was going to be called Science Corp?
33:19
SPEAKER_00: And how did you possibly get the name Science Corp?
33:22
SPEAKER_01: Well, I mean, there's no trademark.
33:23
SPEAKER_01: Like nobody gets to exclusively do science.
33:26
SPEAKER_01: Like everybody should get to do science.
33:29
SPEAKER_01: The .com is not available.
33:32
SPEAKER_01: It's owned by AAAS, the American Academy for Advancement of Science.
33:35
SPEAKER_01: They just redirected to the .org.
33:38
SPEAKER_01: Someday we'll get it.
33:40
SPEAKER_01: The XYZ was kind of the...
33:43
SPEAKER_01: Like it kind of gets grouped with crypto.
33:47
And people think that's like a crypto company or people call it
33:49
science XYZ.
33:50
SPEAKER_01: It's definitely not science XYZ.
33:53
SPEAKER_01: But I thought that that domain was going to go mainstream.
33:56
SPEAKER_01: I think it kind of has.
33:59
SPEAKER_01: It was good enough.
34:00
SPEAKER_01: It was available.
34:01
SPEAKER_01: I'm not very good at naming things,
34:03
and I just felt like the future needed a big multinational
34:08
biomedical technology
34:09
SPEAKER_01: company called Science.
34:11
There's like some VC in LA or something that was a science something,
34:15
right?
34:15
SPEAKER_00: There's an incubator, Science Inc.
34:16
SPEAKER_01: We're a science corporation.
34:17
SPEAKER_01: Delaware had no problem with this.
34:20
SPEAKER_00: They invested in like totally non-science.
34:23
SPEAKER_00: They invested in like, what's that?
34:25
SPEAKER_00: I think Dollar Shave Club.
34:26
SPEAKER_00: Yeah, Dollar Shave Club and that...
34:29
What's the water that everybody drinks with the weird can that
34:33
looks like beer?
34:33
SPEAKER_00: Liquid death.
34:36
SPEAKER_00: Liquid death, yeah.
34:37
SPEAKER_00: I was like, this is not...
34:39
SPEAKER_01: Yeah.
34:39
SPEAKER_01: I mean, look, there's plenty of science to go around.
34:41
SPEAKER_01: Everybody should get to do some science.
34:44
And I think it's basically like the branding for this is just
34:46
pure mimetic warfare.
34:48
SPEAKER_01: It's like if we build things that matter to people that they like,
34:50
then there will be the representation of their brain will split
34:54
off a little bit
34:54
SPEAKER_01: and it will become less confusing.
34:56
SPEAKER_01: And if we don't, then then that won't.
34:58
SPEAKER_01: And that's that we deserve it.
35:01
SPEAKER_00: So when you start out,
35:02
SPEAKER_00: there's all kinds of things you could have done in BCI land,
35:07
SPEAKER_00: and you had this very focused first approach.
35:10
SPEAKER_00: So yeah,
35:11
SPEAKER_00: tell me the thinking,
35:11
SPEAKER_00: right,
35:12
SPEAKER_00: when you're starting the company of what you think makes the most sense.
35:15
Yeah,
35:16
so we had,
35:16
there were kind of two ideas at the beginning of the company.
35:18
SPEAKER_01: Well, there were a couple ideas.
35:20
SPEAKER_01: The first,
35:24
SPEAKER_01: So spring of 21, I didn't really have a plan.
35:28
I got out of the last thing I was doing,
35:32
started reading a bunch of papers.
35:33
SPEAKER_01: Actually,
35:33
SPEAKER_01: it would have been the first time,
35:35
SPEAKER_01: that spring was like the first time in my life,
35:37
SPEAKER_01: really,
35:37
SPEAKER_01: that I hadn't been working.
35:38
And so I just had a couple months of not doing anything,
35:40
which was pretty weird and interesting.
35:42
SPEAKER_01: By the end of that, I definitely needed to get back to work.
35:45
SPEAKER_01: But I...
35:47
I really took it as an opportunity to reset and second-guess
35:50
what I was doing,
35:51
SPEAKER_01: and that was a big opportunity for a change.
35:54
SPEAKER_01: And I looked at AI,
35:55
SPEAKER_01: I thought about other things,
35:56
SPEAKER_01: I kind of made a very intentional decision not to do those.
36:02
And part of that was I became really convinced that it would be
36:05
possible to restore
36:05
SPEAKER_01: vision through the retina.
36:08
SPEAKER_01: in cases where the optic nerve was intact,
36:11
SPEAKER_01: the patient grew up with vision,
36:12
SPEAKER_01: they'd lost it in adulthood,
36:14
SPEAKER_01: and they just lost the rods and cones in their eye.
36:16
That seemed to me to be with the technology that was becoming
36:19
available and that
36:24
SPEAKER_01: that would be doable.
36:25
SPEAKER_01: We didn't know exactly the right approach.
36:27
We didn't know whether this was like an optogenetic cell
36:30
therapy or an electrical
36:31
SPEAKER_01: stimulator or something else.
36:34
And we didn't know whether you should target the bipolar cells
36:36
or the RGCs.
36:38
SPEAKER_01: But
36:38
SPEAKER_01: It seemed clear that that would be possible.
36:40
SPEAKER_01: And I think that that has basically been borne out.
36:43
SPEAKER_01: And then there was another idea that I had back in college.
36:45
SPEAKER_01: This is the bio-hybrid idea,
36:47
SPEAKER_01: where the problem of,
36:49
SPEAKER_01: like,
36:49
SPEAKER_01: if you place wires into the brain,
36:51
SPEAKER_01: there's no space there.
36:51
SPEAKER_01: You're going to displace them.
36:52
SPEAKER_01: You're going to damage some tissue.
36:56
SPEAKER_01: How do you get things into the brain?
36:57
SPEAKER_01: Like, what can you add?
36:58
SPEAKER_01: Like, what happens if you culture some neurons on the brain?
37:01
The answer is they grow in and wire up and form new synapses,
37:03
and you get tons of them.
37:06
SPEAKER_01: That was also really interesting,
37:07
SPEAKER_01: but it was clear that that had to be paired with a near-term business.
37:10
That was too much of a research project for too long to kind of
37:13
stand alone.
37:14
So I want to break this down for people who haven't heard of
37:18
bio-hybrid technology
37:20
SPEAKER_00: at all or seen what you guys are doing.
37:24
SPEAKER_00: Okay, we'll take a step back for a second.
37:26
SPEAKER_00: You kind of create neurons that...
37:30
SPEAKER_00: that are outside of the skull.
37:32
SPEAKER_00: I mean,
37:32
SPEAKER_00: you create these man-made,
37:34
SPEAKER_00: human-made...
37:34
SPEAKER_01: Well,
37:35
SPEAKER_01: I mean,
37:35
SPEAKER_01: you start with a skin punch from a patient.
37:38
SPEAKER_01: So you start with a skin punch,
37:39
SPEAKER_01: you turn those back into stem cells,
37:42
SPEAKER_01: and then we do a lot of editing on those stem cells.
37:45
SPEAKER_01: We try to hide them from the immune system.
37:48
SPEAKER_01: We add in a bunch of safety mechanisms.
37:49
Now that you've hidden these cells from the immune system,
37:51
you have to worry about that.
37:53
SPEAKER_01: We add a bunch of other stuff to them, make them light sensitive.
37:58
SPEAKER_01: We make them specific types of neurons.
38:00
SPEAKER_01: And then you've got this culture of cells.
38:02
SPEAKER_01: And what we do is we embed those in an electronic device in a dish,
38:06
SPEAKER_01: and then you engraft that into the brain.
38:08
So there's no part of the device other than the biological
38:11
axons and dendrites that
38:12
SPEAKER_01: grow into the brain.
38:13
SPEAKER_01: The device just sits on the surface.
38:15
SPEAKER_01: But these grow in and form millions of synapses.
38:18
SPEAKER_00: Right.
38:18
SPEAKER_00: So you create this.
38:19
SPEAKER_00: Okay.
38:20
SPEAKER_00: When you talk about taking a skin cell,
38:22
you're talking about using Yamanaka transcription factors to
38:27
take it back.
38:27
You take a skin cell,
38:28
take it back to a stem cell,
38:29
then you turn it into this modified neuron.
38:33
SPEAKER_00: And then you're putting these in a gel, in a device.
38:38
SPEAKER_00: make a little hole in the skull,
38:40
SPEAKER_00: and then the neurons in that device are able to connect,
38:44
SPEAKER_00: send dendrites and axons into your brain.
38:46
And so you're getting like extra horsepower from this device
38:49
that's connected.
38:50
SPEAKER_01: Well,
38:50
SPEAKER_01: yeah,
38:50
SPEAKER_01: I mean,
38:50
SPEAKER_01: if you don't just get extra horsepower for just adding the neurons,
38:53
like the intuition here is not like we're adding neurons that
38:55
are then making your
38:56
SPEAKER_01: brain bigger.
38:58
SPEAKER_01: but you're being able to access these representations.
39:01
SPEAKER_01: So the brain is an information processing organ.
39:04
SPEAKER_01: It has,
39:05
SPEAKER_01: like if you record from lots of different,
39:07
SPEAKER_01: have you heard of the Jennifer Aniston neuron?
39:10
SPEAKER_01: So there's a well-known result that there's some,
39:12
SPEAKER_01: in some part of the brain,
39:13
SPEAKER_01: if you record from these cells,
39:15
SPEAKER_01: if you show them pictures of different people,
39:17
SPEAKER_01: they,
39:18
SPEAKER_01: in some cases will respond very selectively.
39:19
SPEAKER_01: And so there was a nature paper a while ago that showed that if you,
39:24
SPEAKER_01: If you showed pictures of different people,
39:26
SPEAKER_01: there was a cell that would fire just for pictures of Jennifer Aniston.
39:30
SPEAKER_01: Or if they showed you types of different houses,
39:33
SPEAKER_01: they would fire for just specific types of architecture.
39:36
And so the intuition here is that if you look at all of the
39:38
millions of neurons in that area,
39:40
they encode a representation of architecture or of faces or of
39:45
people or of places.
39:47
SPEAKER_01: This is embedded on a mathematical object called a manifold.
39:52
What you want to do is you want to access that statistical
39:56
representation somehow.
39:58
SPEAKER_01: When these neurons grow into the brain and they wire up,
40:01
SPEAKER_01: when the cells in the brain fire,
40:02
you're getting all this partial information which represents
40:06
information about the
40:06
SPEAKER_01: statistics of those representations.
40:09
And so you can access this information in and out of the brain
40:11
through this.
40:13
SPEAKER_01: This is a very,
40:14
very deep well of neuroscience that we are like at the very
40:16
beginning of just
40:17
SPEAKER_01: making these devices at all is pretty tricky.
40:20
I would say this is like up there with like modern
40:24
semiconductors for complexity.
40:26
SPEAKER_01: Because of all the steps of different things you have to do and...
40:29
SPEAKER_01: yeah, I mean, making these cells at all is really annoying.
40:31
Getting them to survive and be healthy in the microenvironment
40:34
of these devices is
40:35
SPEAKER_01: pretty tricky.
40:36
Getting them to get through the hypoxic and glycemic injury of
40:39
surgery is really tricky.
40:40
SPEAKER_01: Dealing with all of the electronics on these devices is all custom.
40:45
SPEAKER_01: And a lot of this is like for the cells,
40:49
SPEAKER_01: it's not,
40:49
there's no like file on a computer that somebody can download
40:51
and like make more of
40:52
SPEAKER_01: these cells.
40:53
SPEAKER_01: It's like these cells are in
40:55
unbroken lineage of cell divisions through these edits for
40:58
several years from back
40:59
SPEAKER_01: to the original donor skin cells to make them.
41:03
SPEAKER_01: And in a lot of cases,
41:04
the way that you do these edits is you construct basically like
41:07
a test that you can
41:08
evaluate what's the cell doing and you pick the ones that do
41:11
the right thing.
41:12
And you don't have total detail on exactly what's going on
41:15
inside the cell.
41:16
SPEAKER_01: You just can qualify that they're safe,
41:17
SPEAKER_01: that they have these properties,
41:19
SPEAKER_01: they behave this way,
41:20
SPEAKER_01: and they can do the function.
41:20
SPEAKER_01: It's a lot of science.
41:24
SPEAKER_01: Yeah, and ironically, we really try to do mostly engineering.
41:27
Yeah,
41:28
well,
41:28
I was going to say,
41:28
I mean,
41:29
there's a lot of engineering,
41:30
manufacturing.
41:30
SPEAKER_01: We very selectively take on our science.
41:33
SPEAKER_00: Okay,
41:35
SPEAKER_00: we've had this conversation about this a couple times,
41:38
SPEAKER_00: and I always bring up that you get extra horsepower,
41:40
SPEAKER_00: I think maybe because I'm just...
41:42
Simple,
41:43
and that's what resonates with me,
41:45
but you always push back on it.
41:46
SPEAKER_00: And then just in your description,
41:48
I'm not sure if the lay audience would get exactly then what
41:53
these extra neurons
41:54
SPEAKER_00: are supposed to be doing.
41:55
SPEAKER_01: Have you seen James Cameron's Avatar movies?
41:58
SPEAKER_00: No.
41:58
SPEAKER_01: No, okay.
41:59
SPEAKER_01: Well, I think that is actually a really useful analogy here.
42:02
So in there,
42:03
the aliens have these blue ponytails with these fibers at the end.
42:08
SPEAKER_01: And this ponytail is...
42:10
So all of the information that flows in or out of the brain
42:13
goes through a pretty
42:14
SPEAKER_01: small number of wires.
42:15
SPEAKER_01: There's 12 cranial nerves.
42:16
SPEAKER_01: The optic nerve is cranial nerve two.
42:19
The vestibular cochlear nerve that carries hearing imbalance is
42:21
cranial nerve eight.
42:22
And then there's about 30 spinal nerves that go down and come
42:25
out of the vertebrae that carry...
42:28
motor commands up to the muscles and sensory information up to
42:31
the brain.
42:32
SPEAKER_01: And so the brain,
42:35
all of the information that flows in or out of the brain goes
42:38
through one of the 12
42:39
SPEAKER_01: cranial nerves and one of the 31 spinal nerves.
42:42
So the ponytails in Avatar are basically a big externalized
42:46
cranial nerve with like
42:47
SPEAKER_01: a connector at the end that you can plug into,
42:49
SPEAKER_01: in the movie,
42:50
SPEAKER_01: other brains.
42:51
SPEAKER_01: And I think that is actually, like imagine if that was a tech product.
42:55
I think is the simplest way to conceptualize a biohybrid neural interface.
42:58
Even this part about like sort of connecting to another person
43:02
or you're just connecting to you?
43:03
SPEAKER_01: I mean, and there's like existence proofs of this.
43:06
So there's a pair of twins that are conjoined in the brain,
43:11
Tatiana and Krista Hogan in Canada.
43:13
SPEAKER_01: I don't,
43:15
SPEAKER_01: I've never met them,
43:15
SPEAKER_01: but I've read the case studies and they,
43:19
SPEAKER_01: so it's one skull with four hemispheres linked at the thalamus
43:24
SPEAKER_01: And we know that this must be possible.
43:26
And we know that they share significant elements of their
43:28
conscious experience.
43:30
But this takes you to all kinds of really interesting places
43:34
that I think get at
43:35
SPEAKER_01: fundamental questions.
43:36
And one of them was because these neurons are a little more
43:41
accessible because
43:42
SPEAKER_00: they're external from the brain and you're manufacturing them,
43:45
SPEAKER_00: that...
43:47
SPEAKER_00: I'm sure,
43:48
SPEAKER_00: please correct me as I butcher this,
43:49
SPEAKER_00: but you know,
43:51
SPEAKER_00: for certain sorts of ideas where we know the shape of those ideas,
43:55
SPEAKER_00: the neuronal patterns that you could put,
43:58
SPEAKER_00: you could put ideas into these,
44:01
SPEAKER_00: like sort of like inception,
44:03
SPEAKER_00: sort of like downloading kung fu.
44:05
SPEAKER_01: We're like super early in this research.
44:07
SPEAKER_01: Yeah.
44:07
SPEAKER_01: So making the devices,
44:09
what we know right now is that you can culture the cells on
44:12
these devices,
44:13
SPEAKER_01: they survive,
44:14
SPEAKER_01: they integrate,
44:14
SPEAKER_01: you get functional synapses into the brain.
44:17
SPEAKER_01: To be clear, that's where we are.
44:19
Exactly how you use this and what it feels like and the capabilities,
44:23
that is at early stages.
44:27
SPEAKER_01: But if you think about this from a representational perspective,
44:30
SPEAKER_01: the brain has these representations that correspond to...
44:34
SPEAKER_01: Visual processing and language and monologue.
44:39
SPEAKER_01: I mean,
44:39
it's weird and interesting that you see the representations
44:43
that you see in these
44:44
SPEAKER_01: big transformers.
44:46
These big AI models look a lot like the surfaces that you see
44:49
in the brain.
44:50
SPEAKER_01: And so in what sense?
44:53
Like the way that they compress information often looks like
44:56
they find similar
44:57
SPEAKER_01: statistical structure in many cases.
44:59
And so there's a question of if you're thinking about using
45:01
this as like a
45:02
SPEAKER_01: brain-to-brain technology,
45:03
SPEAKER_01: you could go between human brains.
45:05
SPEAKER_01: You could also potentially go between a human brain and an AI model.
45:11
SPEAKER_01: And it's a very profound sense where this begins to feel like one brain.
45:15
SPEAKER_00: And you,
45:15
SPEAKER_00: I know you said it's early days,
45:16
SPEAKER_00: but I mean,
45:18
SPEAKER_00: this is stuff you think about all the time.
45:20
SPEAKER_01: Yeah,
45:21
SPEAKER_01: I mean,
45:21
I think there's a misconception that we get a lot of people
45:24
applying to work here
45:25
SPEAKER_01: and at the place I was before who are really motivated.
45:29
I don't spend a lot of my time sitting around thinking about
45:31
the future of humanity.
45:32
We spend a lot of our time debugging Linux drivers and
45:36
wondering why the cells are contaminated.
45:38
But yeah,
45:40
I mean,
45:40
it's definitely undeniably interesting neuroscience to do.
45:44
Well,
45:44
I ask because you said you started the company with these two
45:49
places you wanted to go.
45:50
SPEAKER_00: Yeah,
45:52
SPEAKER_01: there's actually a smaller third program,
45:54
SPEAKER_01: which has been there from the beginning,
45:55
SPEAKER_01: but is also much smaller and is a little bit different.
45:57
SPEAKER_01: But yeah, go ahead.
45:59
SPEAKER_00: Well,
45:59
SPEAKER_00: but two pretty large,
46:02
SPEAKER_00: massive efforts,
46:03
SPEAKER_00: one to restore vision and the other we're just talking about.
46:06
SPEAKER_00: Yeah.
46:08
SPEAKER_00: I mean, it's important to you.
46:09
This is why you kind of started the company,
46:10
was to get to this place,
46:12
right?
46:12
Yeah,
46:12
and I think that also there's a misconception that these are
46:14
really very different.
46:16
SPEAKER_01: They build on,
46:16
SPEAKER_01: I think,
46:17
one of the other underrated effects here is a lot of the
46:20
medical device industry
46:21
SPEAKER_01: and biotech generally,
46:22
SPEAKER_01: like...
46:23
15 years ago,
46:24
all of the drug companies were moved to being virtual biotech.
46:27
SPEAKER_01: So it's a very small core office.
46:29
SPEAKER_01: All the research was done through contrast research organizations.
46:32
SPEAKER_01: In medical devices, you almost never see multi-product companies.
46:36
SPEAKER_01: They're almost always these single purpose,
46:39
SPEAKER_01: single asset companies,
46:40
SPEAKER_01: an asset licensed out of a university.
46:42
SPEAKER_01: There's a playbook.
46:43
SPEAKER_01: You get it through market approval.
46:45
SPEAKER_01: You go public, you get acquired, and you end up with these big
46:49
SPEAKER_01: marketing players like Medtronic and Boston Scientific,
46:52
SPEAKER_01: whose real business is actually sales and distribution and support.
46:57
SPEAKER_01: And this makes it actually really difficult to innovate.
47:02
SPEAKER_01: So most of these companies,
47:04
SPEAKER_01: you'll get a version one to market or maybe a version two,
47:07
but it usually things get really interesting and exciting at
47:10
versions four,
47:10
SPEAKER_01: five,
47:10
SPEAKER_01: and six.
47:11
SPEAKER_01: But to do that, you need to be able to iterate.
47:13
And you just can't iterate through CROs,
47:17
through contract research organizations.
47:19
SPEAKER_01: If every time you need to do an animal study,
47:21
you're calling a contract research organization and putting
47:23
together a $700,000
47:25
SPEAKER_01: contract that's going to last for 8 to 12 months,
47:28
SPEAKER_01: or every time you want to make a new version of your cell line,
47:31
SPEAKER_01: you're calling a
47:33
SPEAKER_01: a contract manufacturer and sending them $2 million.
47:35
You're thinking in like these multi-year cycles where it's just
47:39
very hard to move
47:40
SPEAKER_01: or learn or iterate anything,
47:41
SPEAKER_01: but you also get to incrementally use this very expensive infrastructure.
47:47
SPEAKER_01: This type of work is really limited by infrastructure,
47:49
SPEAKER_01: much more so than genius scientific insights.
47:52
And so I,
47:53
from my prior boss,
47:54
fully received the gospel of vertical integration.
47:57
SPEAKER_01: And that is absolutely essential.
47:59
Being able to go from a design change to surgery in a couple of
48:01
weeks or being able
48:02
to make like we routinely void the warranty on million dollar
48:07
fab tools because you
48:08
SPEAKER_01: like to put these atoms in these particular locations.
48:13
SPEAKER_01: And if you call up a commercial fab and say,
48:15
SPEAKER_01: hey,
48:15
SPEAKER_01: can you like put this gas and this material in your sputter?
48:18
SPEAKER_01: They'll be like, who let you in the building?
48:20
SPEAKER_01: How did you get here?
48:21
SPEAKER_01: And so that is absolutely essential.
48:24
SPEAKER_01: But that infrastructure is very expensive.
48:28
SPEAKER_01: It can consume.
48:28
SPEAKER_01: It's like carrying that cost is like hugely capital intensive.
48:32
SPEAKER_01: And so a couple ideas.
48:34
SPEAKER_01: One,
48:35
SPEAKER_01: our foundry,
48:36
we sell commercial wafer services to others to defray part of
48:40
the cost of ownership
48:41
SPEAKER_01: of that.
48:42
SPEAKER_01: That is a complicated business.
48:44
SPEAKER_01: That is like,
48:45
SPEAKER_01: that comes with a bunch of other pros and cons,
48:48
but we hope allows us to get more scale over time than we'd be
48:51
able to otherwise.
48:54
And the incremental cost of these programs is actually quite
48:57
low relative to each other.
48:58
SPEAKER_01: If we only had one or the other,
48:59
SPEAKER_01: you could make either one look more expensive,
49:02
but it's actually building on the same underlying platforms
49:04
that we need anyway.
49:05
SPEAKER_01: If we want to go from where we actually go to things that work
49:10
really well okay and and so there's this interlinking between
49:15
these different
49:16
technologies and the substrates of things that you need but you
49:19
you did so but you
49:20
saw um that you needed to make some money and uh the retinal
49:27
technology was that
49:28
that was kind of the first clearest path for you on on getting
49:32
the business going
49:33
Yeah,
49:33
but I mean,
49:33
I think it's a little too dismissive just to say we need to
49:35
make some money.
49:36
SPEAKER_01: I think the question is like,
49:38
what was the most value that we could create with the state of
49:41
the field and our resources,
49:43
SPEAKER_01: including our team as a resource and what we knew and our differentiated,
49:46
SPEAKER_01: I think,
49:47
SPEAKER_01: perspective on the world.
49:48
SPEAKER_01: And the revenue is downstream from the value.
49:51
SPEAKER_01: And I don't at all want to,
49:52
SPEAKER_01: like,
49:52
I think one of the things that becomes an issue when we talk
49:55
about the different,
49:57
SPEAKER_01: our interests,
49:57
SPEAKER_01: which are not diversification.
49:58
SPEAKER_01: We think that each of these are really important.
50:01
SPEAKER_01: is it sells short the fact that AMD patients are reading.
50:06
SPEAKER_01: Like this is an end in itself.
50:07
If that was the only thing that Science,
50:09
the company did,
50:09
we would be very proud of that.
50:11
SPEAKER_01: And so I think that there was an opportunity.
50:13
SPEAKER_01: We saw that, I mean, I grew up around blindness.
50:15
My mom's dad had retinitis pigmentosa when I told her that this
50:18
was like gonna be
50:19
SPEAKER_01: the first major focus of the company.
50:20
SPEAKER_01: She was like pretty, pretty excited.
50:22
Um,
50:23
and so that we thought what we needed to do was create value
50:27
for the world.
50:28
And I think that this restoration of site is like an incredible,
50:33
um,
50:34
opportunity on that.
50:35
SPEAKER_01: Um,
50:36
SPEAKER_01: the revenue follows,
50:37
SPEAKER_01: um,
50:38
SPEAKER_01: but with the value at the heart of that,
50:40
SPEAKER_01: that would be believed would give us a platform to go on,
50:43
to continue to innovate and do these other things through the
50:46
takeoff era that we
50:47
SPEAKER_01: thought would not,
50:48
SPEAKER_01: um,
50:50
SPEAKER_01: we thought would be really important and have an impact on the world.
50:53
You got more offended for being called a capitalist than I
50:56
thought you were going to,
50:57
man.
50:57
SPEAKER_01: You have to embrace capitalism.
50:58
SPEAKER_01: That's like a key.
51:00
SPEAKER_01: That's why we get to do this.
51:02
SPEAKER_01: Don't, like, for someone, don't break capitalism.
51:06
SPEAKER_01: But that's, I mean, there's lots of
51:08
SPEAKER_01: I don't know, I talk to companies in the PCI space all the time.
51:12
SPEAKER_01: I was just having a meeting with one the other day.
51:14
SPEAKER_01: And I think we feel strongly that these things are used for good.
51:19
SPEAKER_01: And I don't know,
51:20
SPEAKER_01: there's a lot of companies out there that are thinking like,
51:22
SPEAKER_01: oh,
51:22
SPEAKER_01: we're going to get all this recording data.
51:23
SPEAKER_01: How do we monetize it?
51:24
SPEAKER_01: Do we have subscriptions?
51:25
SPEAKER_01: I'm like, why are you gathering this at all?
51:28
SPEAKER_01: You don't need any of this.
51:30
SPEAKER_01: This should just run it all locally.
51:31
SPEAKER_01: It should belong to the patient.
51:33
SPEAKER_01: And so I think that there's nuance there.
51:36
SPEAKER_00: For the layperson,
51:38
can you explain how the retinal technology works and where we
51:42
are with your trials
51:43
and where we will get to with other people being able to get
51:47
this technology?
51:48
SPEAKER_01: Yeah, so we have two retinal technologies.
51:51
SPEAKER_01: The one that is for this long that is coming to market next year,
51:54
SPEAKER_01: hopefully,
51:56
SPEAKER_01: submitting for approval very,
51:56
SPEAKER_01: very soon.
51:57
SPEAKER_01: In the US?
51:59
SPEAKER_01: In Europe.
52:00
SPEAKER_01: Also, hopefully the US.
52:01
We're waiting on a response from FDA on a question that we sent
52:03
them recently.
52:07
SPEAKER_01: So the product is called Prima.
52:09
SPEAKER_01: It's a little chip that's inserted in the back of the eye.
52:11
SPEAKER_01: It's an hour outpatient procedure.
52:14
SPEAKER_01: Just...
52:14
SPEAKER_01: You insert it to the front of the eye.
52:15
SPEAKER_01: You leave it under the retina.
52:17
SPEAKER_01: And the chip has all these little,
52:19
SPEAKER_01: if you see a picture of it,
52:20
SPEAKER_01: it has all these little hex grids.
52:22
SPEAKER_01: And each one of these hex grids is a little solar cell, basically.
52:25
SPEAKER_01: So the patient wears glasses that have a laser projector and a camera.
52:29
SPEAKER_01: The camera is looking out at the world.
52:31
SPEAKER_01: It converts it.
52:32
SPEAKER_01: It simplifies it, converts it to an infrared image.
52:34
SPEAKER_01: And then it uses the laser projector to project this infrared image.
52:40
image onto the implant and wherever the implant absorbs
52:43
infrared light,
52:44
it stimulates.
52:45
And so this is actually a really elegant idea because that's
52:48
the whole implant.
52:49
There's no wires,
52:49
there's no battery,
52:50
there's no cable coming out of the eye.
52:52
You send it energy and information simultaneously in the laser projection.
52:56
SPEAKER_01: And so there's something really elegant about that.
52:58
SPEAKER_01: And we didn't invent that here.
53:01
SPEAKER_01: The original inventor of this technology is a professor at Stanford,
53:04
SPEAKER_01: Daniel Planker,
53:05
SPEAKER_01: in the electrical engineering department.
53:07
SPEAKER_01: And he's great, super smart guy.
53:11
SPEAKER_01: And we're fortunate to be able to own and commercialize that idea now.
53:17
SPEAKER_01: And so the current device has 100 micron pixels.
53:21
SPEAKER_01: So it stimulates that first layer of cells, the bipolar cells.
53:26
SPEAKER_01: and each pixel simulates a bunch of bipolar cells.
53:30
So the next step is to shrink those to make it smaller and
53:32
smaller until you get
53:33
SPEAKER_01: towards native acuity,
53:35
SPEAKER_01: like the native resolution of the eye,
53:37
SPEAKER_01: which we think we can get to in a couple device generations.
53:41
SPEAKER_01: Right now,
53:41
SPEAKER_01: it's just black and white because when you stimulate all of these cells,
53:44
SPEAKER_01: you average their representations together,
53:46
SPEAKER_01: and one of the things you lose in that is color.
53:50
SPEAKER_01: There's no such thing as a white photon.
53:53
SPEAKER_01: If you look on the color spectrum, there's no white.
53:55
White is when your brain loses spatial temporal resolution to
53:59
distinguish what
54:00
SPEAKER_01: colors the photons actually were.
54:02
SPEAKER_01: And so when you stimulate a bunch of bipolar cells,
54:04
SPEAKER_01: this averages them together and you lose the color resolution,
54:07
SPEAKER_01: so it shows up as white or black.
54:09
But we think that in the next device generation,
54:12
we might be able to get red and green.
54:13
SPEAKER_01: Blue is a little bit trickier, but there's a path there.
54:17
SPEAKER_00: What's the difference between what somebody obviously they can't see?
54:21
SPEAKER_00: What can they make out like letters on a page?
54:25
SPEAKER_01: Yeah.
54:25
SPEAKER_01: I mean, there's videos online from the trial.
54:27
SPEAKER_01: There's patients can intuitive.
54:31
SPEAKER_01: Some patients can intuitively read.
54:33
So I think it's important to draw a distinction because people
54:35
have been working on
54:35
SPEAKER_01: retinal prostheses,
54:36
SPEAKER_01: visual prostheses generally,
54:37
SPEAKER_01: whether into the retinal or into cortex.
54:39
SPEAKER_00: Yeah,
54:40
SPEAKER_00: like when I've seen stuff historically,
54:42
it's kind of amazing because people can't see and then they can
54:45
see these blurry shapes.
54:46
SPEAKER_00: Yeah,
54:47
I think it's important to really distinguish what they're
54:49
talking about because
54:50
SPEAKER_01: when we talk about form vision,
54:53
SPEAKER_01: this is vision that is apprehensible to the brain as a coherent whole,
54:57
SPEAKER_01: like a letter at a time or a word at a time.
54:59
SPEAKER_01: Yeah.
55:01
SPEAKER_01: that is distinct from these things called phosphenes.
55:05
SPEAKER_01: And all of the earlier devices they would get,
55:07
like if you put an electrode array on the optic nerve or in
55:11
cortex and you
55:12
SPEAKER_01: stimulate it,
55:13
SPEAKER_01: you'll get these flashes of light.
55:14
SPEAKER_01: Those are phosphenes.
55:15
SPEAKER_01: But you can't look to them.
55:18
SPEAKER_01: They don't add up to a hole.
55:20
You'll see these artistic representations of these flashes that
55:23
form a pattern.
55:24
SPEAKER_01: But when you actually have a patient,
55:26
SPEAKER_01: we know this because 10 years ago,
55:27
there was a company called Second Sight that had a stimulator
55:30
that activated the
55:31
SPEAKER_01: optic nerve that got these phosphine fields.
55:35
SPEAKER_01: And it was,
55:36
patients could like kind of read in the sense that they could
55:38
like look at letters
55:39
SPEAKER_01: and kind of make out letters,
55:39
SPEAKER_01: but it was,
55:41
SPEAKER_01: it wasn't intuitive.
55:41
SPEAKER_01: Like the brain didn't assemble it into a hole.
55:43
SPEAKER_01: You'd have to see like,
55:44
SPEAKER_01: oh,
55:44
SPEAKER_01: there's like a line and it's like,
55:45
SPEAKER_01: it's an E.
55:46
SPEAKER_01: Then it's like,
55:46
SPEAKER_01: I see,
55:47
SPEAKER_01: oh,
55:47
SPEAKER_01: it's an A.
55:48
SPEAKER_01: And you'd go that way.
55:49
SPEAKER_01: Whereas the results from the Prima,
55:51
SPEAKER_01: they're reading off words.
55:55
SPEAKER_00: But like if I had these glasses on and I was sitting here,
55:58
SPEAKER_00: what would I see versus what I...
56:01
SPEAKER_00: So this isn't for people who are completely blind.
56:04
SPEAKER_00: It's kind of degraded condition.
56:06
SPEAKER_01: So the trial was done in age-related macular degeneration.
56:09
SPEAKER_01: And so they have some residual peripheral vision.
56:12
SPEAKER_01: They've lost the...
56:14
It's only like the central six or seven degrees of the field of
56:18
your vision are
56:19
SPEAKER_01: high-resolution color vision.
56:20
SPEAKER_01: This is a part of the retina called the fovea.
56:23
SPEAKER_01: and then the macula around the fovea.
56:26
SPEAKER_01: And so these patients,
56:27
SPEAKER_01: they can walk around,
56:29
they can generally kind of navigate the environment because
56:31
they've got this
56:32
SPEAKER_01: peripheral vision,
56:33
SPEAKER_01: but they can't recognize faces,
56:35
SPEAKER_01: they can't read,
56:36
SPEAKER_01: they can't,
56:37
SPEAKER_01: it's really very debilitating to lose your central vision.
56:39
SPEAKER_01: You don't notice it because your eyes are constantly darting around.
56:42
SPEAKER_01: These are called saccades, saccadic eye movement.
56:46
And so even though only the central few degrees of your visual
56:49
field are high
56:50
SPEAKER_01: resolution and in color,
56:52
SPEAKER_01: Um,
56:52
your eyes are constantly filling in information and your brain
56:55
more fundamentally
56:55
SPEAKER_01: has a model of the world,
56:57
SPEAKER_01: which is being updated by this weak sensory input.
56:59
This is one of the reasons that like optical illusions can be
57:02
so strong because
57:03
SPEAKER_01: it's not really,
57:03
SPEAKER_01: your eyes are not a camera.
57:05
SPEAKER_01: They're an information channel to the world model in your brain.
57:08
SPEAKER_01: and that, um, gets these updates.
57:11
SPEAKER_01: And so actually in the beginning,
57:12
SPEAKER_01: like when you lose sight or lose hearing for that matter,
57:14
SPEAKER_01: um,
57:15
SPEAKER_01: your brain tries to turn up the gain to say like,
57:18
SPEAKER_01: I'm trying to looking for something.
57:19
SPEAKER_01: And so hallucinations are very common in blind patients.
57:22
And so the first couple hours with the device are just learning
57:25
to separate the
57:26
phantom percepts from the real percepts and distinguish what's
57:29
real coming in from
57:30
SPEAKER_01: the optic nerve again.
57:31
SPEAKER_01: And then once that's broken and they get it,
57:33
SPEAKER_01: then they can,
57:33
SPEAKER_01: they can figure it out pretty quickly from there.
57:36
SPEAKER_01: But, um,
57:37
SPEAKER_01: Yeah, but to your question, what does it look like?
57:42
Another task that's done,
57:44
there's videos online of patients filling in crossword puzzles.
57:49
SPEAKER_01: And this is, so most motor control is not visually guided.
57:53
It's like you don't need to look at your fingers to type or to
57:55
catch a baseball.
57:57
SPEAKER_01: Most motor control is proprioceptively guided.
57:59
There's nerves in the muscles that give you feedback so that
58:02
you know where your
58:03
SPEAKER_01: limbs are when you're not looking at them.
58:06
SPEAKER_01: And depending on how you try to stimulate vision of the brain,
58:09
you may or may not get for free this connection to motor
58:12
control because your brain
58:13
has to correlate the visual signal with the proprioceptive
58:15
signal back together.
58:17
SPEAKER_01: And there's these videos of a patient filling in a crossword puzzle
58:22
And this is interesting and really not to be underrated because
58:25
that is a visually
58:26
SPEAKER_01: guided fine motor task.
58:28
SPEAKER_01: They have to see the grid squares on the page.
58:30
SPEAKER_01: They need to see the letters.
58:32
SPEAKER_01: They need to control the tip of the pen within it.
58:34
And so that I think is very strong evidence that it shows up as
58:38
vision for
58:38
SPEAKER_01: everything that vision is useful for.
58:40
And what about just looking at someone across from the distance
58:45
that we would be at?
58:47
SPEAKER_01: So there's different modes in the software.
58:50
We actually were planning to do more of a study on facial
58:53
recognition that wasn't
58:53
SPEAKER_01: actually carefully studied in this clinical trial,
58:56
SPEAKER_01: but it's definitely a thing that we're going to be characterizing better.
59:00
SPEAKER_00: And...
59:02
where does this technology go in terms of,
59:05
um,
59:05
somebody who was born completely blind?
59:07
SPEAKER_00: I mean, it's not really meant for that.
59:10
SPEAKER_00: Yeah.
59:10
SPEAKER_00: That's not meant for that.
59:11
SPEAKER_01: Okay.
59:11
SPEAKER_01: Um, that's at least, I'll just say a different problem.
59:13
SPEAKER_01: Okay.
59:14
SPEAKER_01: I think there for a long time,
59:16
SPEAKER_01: there's a conventional wisdom that,
59:18
SPEAKER_01: um,
59:19
SPEAKER_01: if you didn't form this vision circuitry in childhood,
59:21
SPEAKER_01: it wasn't even because you miss these critical periods in development.
59:25
SPEAKER_01: Um, um,
59:26
SPEAKER_01: And there are some case studies from like,
59:29
SPEAKER_01: I don't know,
59:30
like decades ago where patients would get like if their retina
59:36
developed fine,
59:36
SPEAKER_01: but maybe they had a genetic cataract or something that would be removed.
59:40
The patients would find it totally overwhelming and their
59:42
brains were not at all
59:43
SPEAKER_01: prepared for it.
59:44
SPEAKER_01: And some of these patients committed suicide.
59:46
SPEAKER_01: But there's also,
59:47
SPEAKER_01: but I'm not sure that I find this like,
59:49
SPEAKER_01: I think these anecdotes are not totally convincing.
59:52
SPEAKER_01: There was a case, I don't know, 10 years ago, maybe.
59:54
SPEAKER_01: I don't remember exactly when where,
59:58
SPEAKER_01: There's a group called Project Prakash that went to,
1:00:00
SPEAKER_01: I think,
1:00:00
rural India and treated this population of teenagers with
1:00:06
genetic cataracts and
1:00:08
SPEAKER_01: repaired them,
1:00:09
SPEAKER_01: which is a very easy surgical fix.
1:00:11
SPEAKER_01: And then these teenagers got sight for really the first time.
1:00:14
SPEAKER_01: And within a couple of weeks, many of them could catch a baseball.
1:00:17
And so I think that the brain stays plastic really throughout
1:00:20
life more than is
1:00:21
SPEAKER_01: commonly appreciated.
1:00:23
Um,
1:00:23
the critical periods are definitely important,
1:00:25
but,
1:00:26
um,
1:00:27
anyway,
1:00:28
that's like,
1:00:28
that's loss.
1:00:31
No vision from childhood is just very different in the impacts
1:00:33
on the brain.
1:00:33
SPEAKER_00: It was maybe like too specific of a question.
1:00:36
SPEAKER_00: I was just wondering if,
1:00:37
SPEAKER_00: if this is step one of curing a wider variety of visual issues or,
1:00:43
SPEAKER_00: or how far this technology can stretch.
1:00:45
SPEAKER_01: There's many different types of reasons that people go blind.
1:00:48
SPEAKER_01: If you have like cataracts, um,
1:00:51
SPEAKER_01: are easily fixed, not a problem.
1:00:53
Corneal abrasions also,
1:00:54
I mean,
1:00:54
you need some donor tissue there,
1:00:56
but can be repaired.
1:01:00
SPEAKER_01: So we're focused on diseases where the rods and cones have degenerated,
1:01:04
SPEAKER_01: but they grew up with vision,
1:01:05
SPEAKER_01: lost it in later life.
1:01:07
SPEAKER_01: And the optic nerve importantly is still there.
1:01:10
SPEAKER_01: when you lose the optic nerve, that is more difficult.
1:01:13
SPEAKER_01: The most common cause for that is glaucoma,
1:01:15
SPEAKER_01: which is high pressure in the eye,
1:01:16
SPEAKER_01: which squeezes the blood supply to the optic nerve,
1:01:18
SPEAKER_01: and then you lose that.
1:01:19
If a patient has glaucoma or has otherwise lost the optic nerve,
1:01:22
Prima would not work for them.
1:01:25
SPEAKER_01: But...
1:01:25
SPEAKER_01: There's a lot of reasons why people lose the rods and cones.
1:01:29
SPEAKER_01: Beyond macular degeneration, there's also retinitis pigmentosa.
1:01:32
There's Stargardt's disease,
1:01:34
which is kind of a young person's age-related macular degeneration.
1:01:37
SPEAKER_01: It's genetically driven.
1:01:37
SPEAKER_01: Diabetic retinopathy.
1:01:41
SPEAKER_01: there's a lot of reasons that people can lose rods.
1:01:43
SPEAKER_01: There's all kinds of idiopathic, uh, uh, photoreceptor losses.
1:01:47
SPEAKER_01: Um, there's not as much.
1:01:49
SPEAKER_01: So people, um, we've obviously had cochlear implants for 50 years.
1:01:54
Um,
1:01:54
sensory neural hearing loss is much more common than,
1:01:57
uh,
1:01:58
rod cone degenerations.
1:02:00
SPEAKER_01: Um, a common, a common,
1:02:04
A major reason that people have sensorineural hearing loss is
1:02:07
an autoimmune reaction.
1:02:08
SPEAKER_01: So your immune system attacks those cells and then causes them to die.
1:02:14
My intuition here is that there's just clearly a much weaker
1:02:16
evolutionary pressure
1:02:17
SPEAKER_01: on protecting those.
1:02:18
SPEAKER_01: And sometimes people talk about the eye being immune-privileged.
1:02:22
There's definitely immune cells in the eye,
1:02:24
but they tend to hang out on the periphery.
1:02:25
I think evolution learned a long time ago that if you overreact
1:02:28
in the eye and kill
1:02:29
SPEAKER_01: the photoreceptors,
1:02:30
SPEAKER_01: this is really bad and you must not do that,
1:02:33
SPEAKER_01: which is one of the reasons the eye ends up immune privileged.
1:02:35
And you also don't have as much spontaneous loss of these cells
1:02:40
than you do in,
1:02:41
SPEAKER_01: for example,
1:02:41
SPEAKER_01: the ear.
1:02:42
um but there's but still it happens every now and then um
1:02:45
there's viral cases
1:02:46
sometimes um and so really for any of those like if you can
1:02:50
bypass those dead cells
1:02:51
and just get the visual signal back into the brain as early as
1:02:54
possible um we hope
1:02:57
to provide mechanisms for doing that that get better and better
1:03:01
over time i do
1:03:02
SPEAKER_01: think that it
1:03:03
SPEAKER_01: down the road, a biohybrid type device could work for glaucoma.
1:03:08
SPEAKER_01: People have done,
1:03:09
SPEAKER_01: not us,
1:03:09
but like the academic community has done experiments where
1:03:12
they've engrafted cells
1:03:15
into the eye and they've seen that they've path found down
1:03:18
along the remaining
1:03:20
SPEAKER_01: optic nerve track into the thalamus.
1:03:22
SPEAKER_01: And that is really intriguing, but it's also a big science project.
1:03:27
SPEAKER_01: And so is for the future.
1:03:29
SPEAKER_00: Okay,
1:03:30
SPEAKER_00: so if you look at something like what you guys are doing there,
1:03:33
SPEAKER_00: and then I look at the BCI field more broadly,
1:03:37
SPEAKER_00: you know,
1:03:37
SPEAKER_00: this technology is first hitting with people in quite dire straits.
1:03:41
SPEAKER_00: They have vision problems.
1:03:42
SPEAKER_00: They have ALS.
1:03:44
SPEAKER_00: They're paralyzed.
1:03:46
SPEAKER_00: Well, so, I mean, my big question is, you know, we...
1:03:50
SPEAKER_00: hear all the time of where this technology might be going.
1:03:55
SPEAKER_00: I mean,
1:03:57
what is your best guess on how long we're in this phase where
1:04:04
BCI-type technology
1:04:06
is being used really as a medical treatment versus when it gets
1:04:10
to something closer to,
1:04:12
SPEAKER_00: like,
1:04:12
an elective kind of consumer thing that people are choosing to
1:04:17
take advantage of?
1:04:18
SPEAKER_01: Yeah, I mean, I...
1:04:20
SPEAKER_01: My view on this is that everybody eventually becomes a patient.
1:04:25
SPEAKER_01: I think that this body is great for a long time, but eventually fails.
1:04:31
And so I think we take a perspective here of it's like we're
1:04:33
going to restore loss functionality,
1:04:35
SPEAKER_01: eventually extend.
1:04:36
But I think what you're going to see first are people that
1:04:38
become patients anyway,
1:04:40
SPEAKER_01: get capabilities that are differentiated.
1:04:43
SPEAKER_00: Or that they lost or...
1:04:46
Yeah,
1:04:47
definitely restore things that they lost and eventually go further.
1:04:51
SPEAKER_01: But I think, I mean, I don't know.
1:04:53
SPEAKER_01: It's just so hard to bet against progress in technology right now.
1:04:57
SPEAKER_01: And just two days ago, we had a meeting where...
1:05:01
SPEAKER_01: a thing that I thought was going to take years,
1:05:03
SPEAKER_01: it might,
1:05:03
SPEAKER_01: it's like,
1:05:04
SPEAKER_01: might happen much faster now.
1:05:06
SPEAKER_01: And I, just the timelines keep compressing.
1:05:09
Um,
1:05:10
and so I don't know,
1:05:11
like who,
1:05:12
like I said,
1:05:12
I've got this event horizon at 2035.
1:05:14
SPEAKER_01: Right.
1:05:15
SPEAKER_00: Okay.
1:05:15
SPEAKER_00: But the end goal of your company is what it's to help people in need,
1:05:21
SPEAKER_00: but is it also to give,
1:05:23
SPEAKER_00: uh,
1:05:23
SPEAKER_00: special powers to the rest of us at some point.
1:05:27
SPEAKER_01: Well,
1:05:27
SPEAKER_01: I mean,
1:05:27
SPEAKER_01: so part of,
1:05:28
I think the reason that I'm having trouble with this question
1:05:31
is that BCI is not a product.
1:05:35
SPEAKER_01: BCI is a field in the same way that like social media is a field.
1:05:39
SPEAKER_01: But if you're just like,
1:05:40
SPEAKER_01: I'm gonna build a social media company,
1:05:41
SPEAKER_01: you're like,
1:05:41
SPEAKER_01: what does that mean?
1:05:42
SPEAKER_01: Like, what is the interaction here?
1:05:43
SPEAKER_01: that is compelling, that people are into?
1:05:45
SPEAKER_01: Is it photo sharing?
1:05:46
SPEAKER_01: Is it 140-character updates?
1:05:49
SPEAKER_01: Is it family?
1:05:50
SPEAKER_01: You've got to be more specific.
1:05:51
And you're going to have many different products within that
1:05:54
that are all different
1:05:55
SPEAKER_01: ecological niches that are compelling.
1:05:57
SPEAKER_01: And so I think when you look at motor,
1:06:00
SPEAKER_01: BCI has become kind of synonymous with motor decoding,
1:06:03
SPEAKER_01: I think,
1:06:03
SPEAKER_01: in many people's minds.
1:06:04
SPEAKER_01: I think that generalizes into communication.
1:06:06
SPEAKER_00: Yeah.
1:06:07
SPEAKER_00: Okay.
1:06:08
SPEAKER_00: Well, I mean...
1:06:11
SPEAKER_00: Okay,
1:06:12
SPEAKER_00: tell me,
1:06:12
SPEAKER_00: next 20,
1:06:14
SPEAKER_00: 30 years,
1:06:14
SPEAKER_00: sort of like a mind meld,
1:06:17
SPEAKER_00: I can express a thought directly to you.
1:06:20
SPEAKER_01: Yeah, probably.
1:06:21
Yeah,
1:06:22
I think like direct,
1:06:23
I mean,
1:06:23
so first of all,
1:06:24
language is pretty good at this.
1:06:25
SPEAKER_01: Like evolution did a pretty good job of this.
1:06:27
SPEAKER_01: Sure.
1:06:27
SPEAKER_00: Sure,
1:06:28
but when I'm at a concert and I feel this sort of joy during
1:06:34
the best moment of the concert,
1:06:36
SPEAKER_00: yes,
1:06:36
SPEAKER_00: I could describe that in words.
1:06:38
SPEAKER_00: It would be a little slow,
1:06:39
SPEAKER_00: really,
1:06:40
SPEAKER_00: for what I'm actually feeling,
1:06:41
SPEAKER_00: but I'm definitely not conveying.
1:06:43
But this is why you have the other 10 cranial nerves of your
1:06:46
face and your
1:06:47
SPEAKER_01: expressions and things.
1:06:48
SPEAKER_01: But yes,
1:06:48
SPEAKER_01: I think that 20 years for this technology,
1:06:52
SPEAKER_01: I would say,
1:06:52
is for many of the things that you could imagine is a
1:06:55
sufficiently long time horizon.
1:06:56
SPEAKER_00: Yeah, even words are slow.
1:06:57
SPEAKER_00: If I wanted to convey,
1:06:59
SPEAKER_00: like,
1:06:59
SPEAKER_00: a paragraph to you in an instant,
1:07:01
SPEAKER_00: I mean,
1:07:01
SPEAKER_00: I guess that's kind of what I'm...
1:07:03
SPEAKER_00: Almost like an LLM.
1:07:04
Like,
1:07:04
am I sending a block of tokens,
1:07:06
you know,
1:07:07
from my brain to your brain?
1:07:08
SPEAKER_01: Yeah.
1:07:09
SPEAKER_01: So, generate production of language.
1:07:11
SPEAKER_01: I think that...
1:07:12
SPEAKER_01: there's a myth that we could just think faster.
1:07:16
SPEAKER_01: Perception is a lot faster than production.
1:07:19
So getting information into the brain can be done at much
1:07:22
higher bandwidth.
1:07:22
SPEAKER_01: So you can get vision in and you can see an image,
1:07:26
SPEAKER_01: you can read much faster than you can produce the tokens.
1:07:30
SPEAKER_01: So I'm not sure that it's just like talking faster,
1:07:33
SPEAKER_01: but I think that it's,
1:07:36
SPEAKER_01: so all communication is about creating correlations between brains.
1:07:40
SPEAKER_01: We can have this conversation because we both speak English.
1:07:43
SPEAKER_01: We picked this up during childhood.
1:07:45
We can talk about ideas about brains because we both had an
1:07:47
education about what our brains are.
1:07:49
If there's a concept that we don't both share,
1:07:51
then we can't convey it to each other.
1:07:53
SPEAKER_01: I think the same thing is going to be true over these BCIs.
1:07:56
SPEAKER_01: It's no matter what the link is,
1:07:57
you need the concept spaces present on both sides in order to
1:08:01
light them up.
1:08:03
SPEAKER_01: Now, where you get into more interesting territory is...
1:08:10
SPEAKER_01: How do you add a new cortical area?
1:08:12
How do you add representations to the brain that you didn't
1:08:15
have before so that you
1:08:17
SPEAKER_01: can communicate these things very efficiently?
1:08:21
Or how do you decode into a pre-trained model that allows you
1:08:24
to get out more complex?
1:08:26
SPEAKER_01: You can get information into the brain very efficiently.
1:08:28
SPEAKER_01: Getting information out is limited to muscle control and language.
1:08:32
SPEAKER_01: You can't get vision out of the brain.
1:08:34
SPEAKER_01: You can't get hearing out of the brain.
1:08:36
SPEAKER_01: And so that type of stuff, I think, might be possible.
1:08:39
SPEAKER_00: Okay.
1:08:40
SPEAKER_00: I want to be mindful of your time.
1:08:41
As we were setting up for this,
1:08:46
you're like,
1:08:46
oh,
1:08:46
there's all this crazy stuff.
1:08:48
SPEAKER_00: I wish I could tell you, but I can't wait.
1:08:51
SPEAKER_00: So I'm probably not going to get those details out of you.
1:08:53
SPEAKER_00: But what does that even mean?
1:08:54
That just means you're seeing things out in the world that are
1:08:57
fascinating and fascinating.
1:08:59
SPEAKER_01: Yeah, I mean, I don't mean that.
1:09:00
SPEAKER_01: And like, I mean, I wouldn't over I wouldn't overthink that.
1:09:03
SPEAKER_01: It's just there's like a lot of cool stuff.
1:09:04
SPEAKER_01: And I think it's also.
1:09:06
SPEAKER_01: Yeah, I mean.
1:09:14
SPEAKER_01: I think that it's the most exciting time in human history,
1:09:16
SPEAKER_01: and I think that that will continue to be true.
1:09:19
SPEAKER_01: The world is also...
1:09:20
SPEAKER_01: I think that as these things accelerate,
1:09:22
SPEAKER_01: there'll definitely be some instability.
1:09:26
SPEAKER_01: But I don't know.
1:09:30
SPEAKER_01: There's the only way out is through.
1:09:32
SPEAKER_00: So there's the stuff you're working on,
1:09:33
but then you're hearing from your friends and you're just
1:09:36
hearing that things are
1:09:37
SPEAKER_00: clicking and interesting.
1:09:38
SPEAKER_00: Yeah.
1:09:38
SPEAKER_01: I mean, I'd say Silicon Valley is buzzing.
1:09:42
SPEAKER_01: Like there's, um, there's just so much, I don't know.
1:09:46
SPEAKER_01: Like I,
1:09:47
SPEAKER_01: yeah,
1:09:47
SPEAKER_01: two days ago,
1:09:48
SPEAKER_01: I think,
1:09:48
SPEAKER_01: uh,
1:09:48
SPEAKER_01: Celine's company loyal announced that they got through a major update,
1:09:52
SPEAKER_01: a major milestone with the FDA for dog longevity.
1:09:55
SPEAKER_01: Yeah.
1:09:55
SPEAKER_01: Like all like the,
1:09:56
SPEAKER_01: I just refer, I'm not speaking specifically.
1:09:58
SPEAKER_01: There's no like one thing that I'm like, oh man, I wish I could say.
1:10:01
SPEAKER_01: It's just like,
1:10:02
there's the sense that like a lot of cool stuff is happening
1:10:04
and we're going to get
1:10:05
SPEAKER_01: a lot of it.
1:10:06
SPEAKER_00: Okay.
1:10:07
SPEAKER_00: That seems like a good place to stop for the optimists.
1:10:11
SPEAKER_00: Thank you so much for your time.
1:10:12
SPEAKER_00: Thanks for letting us come to your company.
1:10:14
SPEAKER_00: And yeah, thanks.
1:10:15
SPEAKER_01: Yeah, cool.
1:10:16
SPEAKER_01: Good to see you.
1:10:20
SPEAKER_00: Core Memory is hosted by me, Ashley Vance.
1:10:24
SPEAKER_00: Today's guest was Max Hodak.
1:10:27
SPEAKER_00: The show is produced by me and David Nicholson.
1:10:31
SPEAKER_00: Our theme song is by James Mercer and John Sortland.
1:10:35
SPEAKER_00: And the show is edited by the tremendous John Sortland.