00:00:00
my body is a wonderland
00:00:03
if that wonderland is white soft and
00:00:05
mushy sure
00:00:07
and hairy too
00:00:11
you know the worst thing about skin on
00:00:12
skin sleeping with the newborn is that
00:00:15
you know sometimes she roots and she
00:00:16
goes after the man the male nip i know
00:00:18
the problem is my nipple's covered in
00:00:20
hair
00:00:21
it's really awkward for everybody
00:00:24
she start gagging i'll tell tally that
00:00:26
story when she's 18. we're at her
00:00:27
wedding it'll be even better
00:00:46
hey everybody welcome to another episode
00:00:49
of the all-in podcast i am wearing a
00:00:51
blue shirt i am a pasty white old greek
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man
00:00:56
uh who's balding and obnoxious
00:00:59
and uh with me today
00:01:02
is uh no no no no no you have to you
00:01:04
have to say your pronoun bro am i oh and
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my pronouns are
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uh
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oh wait what are my pronouns my pronouns
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are beep beep and most people just call
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me a jerk
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with me today of course is my sri lankan
00:01:19
urkel looking wearing a furry sweater
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hello everybody my name is chamath i
00:01:24
have uh salt and pepper black hair brown
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eyes uh i am tall
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uh six foot two
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i go by the pronouns we
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king and stud muffin
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and uh uh i'm here to talk to you about
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uh internet security protocols
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i look like article i think people
00:01:46
should just come up and say well i don't
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look like girls i'm the closest i don't
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look like urkel i look like a bollywood
00:01:51
when you put your glass about
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welcome to the all-in podcast two out of
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the four of us are cancelled next up for
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cancellation socks
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yes i'm coming to you here from the
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floor of the new york stock exchange
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which was once land that belonged to the
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mohegan the montauk the oneida the erie
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and iroquois tribes
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you forgot the irish
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we own the seven points oh my god
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you literally did it you went for it
00:02:27
saks i love you i'm uh isn't it
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important that
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at any moment
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that we're successful we have to
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flagellate ourselves and remind
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ourselves
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about that at one time
00:02:41
all this land was owned by somebody else
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we stole it and also the greeks
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conquered the romans and so on
00:02:49
but you forgot to mention you're also
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wearing
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a
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other shirt that is four sizes too large
00:02:57
this is my slim fit so that's slim fit
00:02:59
oh no here we go again sax has been
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upgrading the wardrobe he's changing we
00:03:03
wait before freeburg does the intro uh
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jacob you want to tell them why we're
00:03:06
we're doing these intros like this yeah
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i gotta pause before we get okay
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yesterday on the internet emerged
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a series of videos that were clipped of
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microsoft presenting their new suite of
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developer tools yadda yadda and
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corporate people got up
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and without any explanation
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started describing their physical
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appearance their pronouns their
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ethnicity their skin tone and their hair
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styles
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and the entire internet was like oh my
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god this is crazy woke-ism like what
00:03:39
what is happening here this
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no i thought it was a skit i thought it
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was a saturday on the livestream and so
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right and so then as soon as they got
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called out by the entire internet they
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claimed that they were doing this for
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visually impaired people which kind of
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begs the question of why visually
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impaired people need to know what race
00:03:53
you are like it's still playing into
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this like crazy weight race
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consciousness
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but then on top of it it wasn't just
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that we we know it's not that because
00:04:02
then they start doing no no but hold on
00:04:03
yeah also if you if you're blind and
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technically can't see you may not even
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know what blue means
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because you will have never seen the
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color blue or blonde
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okay right right but they were also
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identifying their races which kind of
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begs the question of why that's
00:04:16
important but if you were born blind you
00:04:18
would not know what that means either
00:04:20
you're literally colorblind
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on the same footing as people who are
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not visually impaired what i'm saying
00:04:27
if you're visually impaired you're using
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the wrong language that language is for
00:04:30
the sighted people
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okay but i i'm just calling [ __ ] on
00:04:34
their stated explanation that has
00:04:36
anything to do with visually impaired
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because then they went on to basically
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recite the names of 10 tribes
00:04:43
native american tribes that no one's
00:04:44
ever heard of on on which the microsoft
00:04:46
campus it used to belong to so which is
00:04:49
why i was kind of making fun of that in
00:04:51
my initial statement but so look this is
00:04:53
just woke capitalism this is woke-ism
00:04:56
out of control obviously they didn't see
00:04:58
the election results earlier in the week
00:05:01
it's clearly there was some level of
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virtue signaling i think in their
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defense they were trying to do it i
00:05:06
think for the visually impaired the
00:05:08
problem was they didn't explain the
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context and
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they didn't give instructions to the
00:05:12
people on what to do so well
00:05:14
but jake that video that was a clip
00:05:17
pulled out of a broader context too
00:05:18
right so like apparently this is common
00:05:20
on campus or common there that this is
00:05:22
happening all over so we just know it
00:05:24
isn't common because i asked people
00:05:26
online well it was optional it was
00:05:28
optional it's optional to the common
00:05:30
point i think the reason the internet
00:05:31
reacted the way it was was i asked every
00:05:33
single person who came at me because the
00:05:35
work left came at me i just said can you
00:05:37
show me another clip of this on youtube
00:05:39
of any event where this occurred and
00:05:41
nobody could so i think this was kind of
00:05:43
a first when did you stop being a member
00:05:45
of that that woke left jkl
00:05:47
what was the mother like the hysterical
00:05:49
side i've never been for bernie i've
00:05:51
never been for elizabeth warren i've
00:05:52
always been moderate
00:05:53
always wait can i hear freeberg's intro
00:05:55
yeah free bro can we hear yours
00:05:58
my identity is an illusion
00:06:00
it's an illusion created by the viewer
00:06:03
and you can call me whatever you want i
00:06:06
sit on the ground where during the
00:06:07
haitian period there was lava and magma
00:06:11
and nothing but co2 and methane and i
00:06:13
represent those gases that are now lost
00:06:15
to the oxygenation and the cyanobacteria
00:06:18
that swarmed over this earth and took
00:06:20
everything over
00:06:21
and led to the formation of eukaryotic
00:06:23
life and here we all sit today in our
00:06:25
privileged existence thank you are you
00:06:27
saying that you want to
00:06:29
freeburger is just electrons hitting
00:06:30
neurons in interesting ways yeah
00:06:41
quantum foam is my pronoun so would you
00:06:44
like to formally apologize for
00:06:46
colonizing the dark matter during the
00:06:49
big bang now or would you like to i feel
00:06:51
it was inappropriate
00:06:54
it wasn't fair when the cyanobacteria
00:06:56
took over the the face of the earth and
00:06:58
sucked up all the co2 and created all
00:07:00
the oxygen and for that we all apologize
00:07:03
for the genocide of
00:07:05
the for the genocide
00:07:08
of co2 and methane i mean those
00:07:09
molecules were really happy and
00:07:12
you know they had a very kind of like
00:07:14
peaceful existence on this earth and you
00:07:16
know
00:07:17
we just came in and ripped it away
00:07:20
just took it all away from them and you
00:07:21
know and then the offspring ended up
00:07:24
being us and here we are so apologies
00:07:27
all right
00:07:28
all right
00:07:30
welcome to episode 54.
00:07:32
everybody's canceled the final episode
00:07:34
everybody's horrible
00:07:37
i i don't think that the microsoft thing
00:07:39
was
00:07:40
bad and when you hear the broader
00:07:41
context it was like you know that's just
00:07:43
you know i think it's a reasonable thing
00:07:44
that visually impaired people
00:07:47
heard i'm still long microsoft and
00:07:48
google and short the rest of the big
00:07:50
tech so i'm fine with it there you go
00:07:51
back to the stock price
00:07:53
actually jamal do you think that the
00:07:54
google long netflix short play is the
00:07:56
right play
00:07:58
i think the best trade on the best trade
00:08:00
on the internet the most obvious simple
00:08:01
money making trade is long microsoft
00:08:03
google short big tech short the rest of
00:08:05
the big tech short ibm short netflix no
00:08:07
no no no short one meaning you can you
00:08:10
can very comfortably short apple
00:08:12
facebook amazon netflix and belong
00:08:14
microsoft google so as a spread trade
00:08:16
right right it's the most it's the best
00:08:18
risk parity trade on the internet right
00:08:20
now i mean period in the markets can you
00:08:22
explain explain a spreadsheet so look
00:08:23
look i i tweeted this a while ago but
00:08:25
it's like and and again the
00:08:28
i i think like
00:08:30
well let me be constructive and say the
00:08:32
people on twitter that respond to these
00:08:34
treads are not totally stupid although i
00:08:35
think they're kind of idiotic
00:08:37
um i said you know here's how you can
00:08:39
effectively you know i i said something
00:08:41
about
00:08:42
you know big tech and i said oh i can
00:08:43
comfortably put my short on
00:08:46
and i'm kind of trolling people when i
00:08:48
do that because i'm not telling them the
00:08:49
full trade and the real trade whenever
00:08:51
you put anything on in my opinion is all
00:08:54
about managing risk
00:08:55
and the best thing about the internet
00:08:57
and the stock market is that you know
00:08:59
when you're betting on internet stocks
00:09:01
you don't necessarily have to be naked
00:09:03
long or naked short which comes with a
00:09:05
lot more risk than if your
00:09:07
long one security and short another
00:09:10
against it so for example
00:09:12
over the last 10 years you would have
00:09:14
made a lot of money by being long amazon
00:09:17
and short a basket of traditional
00:09:19
commerce companies offline commerce i'm
00:09:22
going to make up a basket but macy's
00:09:23
jcpenney you know kmart sears right so
00:09:27
if you're short those and long amazon
00:09:29
that's what's called a spread trade
00:09:31
you're you're basically playing the gap
00:09:34
between your longs and your shorts it's
00:09:36
independent of where the market
00:09:38
generally trades it's one of the
00:09:39
irrelevant of the market you're
00:09:41
basically saying those stocks could go
00:09:42
up but just not everything could work
00:09:44
near amazon yeah
00:09:47
when you put that trade on for example
00:09:49
it's i'm going to bet that if everything
00:09:51
goes up amazon will go up more than
00:09:54
kmart walmart sears and if the stock
00:09:57
market goes down
00:09:58
amazon won't go down that much but these
00:10:00
ones will go down a lot and you you're
00:10:02
playing the spread so just just to be
00:10:04
very explicit
00:10:06
you know there was a very and i talked
00:10:08
about this last week but uh i that this
00:10:10
idea wasn't mine it's a borrowed trade
00:10:12
from somebody who's a very well-known
00:10:13
hedge fund manager
00:10:15
who put it on in massive size and you
00:10:17
know to be honest not knowing much of
00:10:19
anything i just copied it but he's his
00:10:21
initial trade
00:10:22
was long google short facebook
00:10:25
and that trade basically was at parity
00:10:28
which meant that the long and the short
00:10:29
canceled each other out for about the
00:10:31
last four years
00:10:33
until the last year it completely blew
00:10:36
out and it returned about 80 85 percent
00:10:39
so if you had put 100 and you would have
00:10:40
made about 85 uh 85 bucks on this trade
00:10:43
by being long google short facebook
00:10:47
the the bigger trade at scale is
00:10:49
actually long google and microsoft and
00:10:51
short the rest of big tech and there's a
00:10:53
lot of vague reasons why
00:10:55
that this idea makes a lot of sense but
00:10:57
what you're saying is they'll outperform
00:10:58
the other basket of texas on a relative
00:11:00
basis on a relative basis so so it's not
00:11:02
like you're saying airbnb can't go up or
00:11:05
facebook can't go up it could it's not
00:11:07
going to go as well
00:11:10
he's saying that the the trillion dollar
00:11:12
market cap companies yeah not the airbnb
00:11:14
oh okay and the reason and the reason
00:11:16
why focusing there makes sense is there
00:11:18
hyper liquid markets
00:11:21
they have tremendous ways in which you
00:11:23
can have massive size on so you could
00:11:25
put a trade of
00:11:26
10 billion long versus 10 billion short
00:11:29
i mean you can put mega size on on these
00:11:31
things if you if you have real
00:11:33
conviction
00:11:35
and then the third thing is when the
00:11:36
banks look at that kind of position
00:11:38
they actually from a risk management
00:11:40
perspective treat it differently than if
00:11:43
you were just naked long any one of
00:11:44
these things or make it long would be
00:11:46
just making one bet yeah or you know or
00:11:48
naked short which is even more dangerous
00:11:50
so because if the market collapses by 30
00:11:54
both stocks might go down 30 roughly but
00:11:57
one will go down 32 and the other one
00:11:58
will go down 28 and so you're really
00:12:00
only getting two percent two percent as
00:12:02
opposed to the 30 percent of the so all
00:12:04
the market risk is taken out when you
00:12:05
make trades like that yeah the reason
00:12:08
it's possible also today to do so at
00:12:10
such a scale right chemoth is interest
00:12:12
rates are so low
00:12:13
so when you borrow on margin to go long
00:12:15
the rate is very low and when you short
00:12:17
the stock if it's a highly liquid stock
00:12:19
it doesn't cost a lot to borrow too
00:12:21
short that's so your actual you know uh
00:12:24
carrying cost on that trade ends up
00:12:26
being pretty low relative to the upside
00:12:28
you expect so just to just to give you a
00:12:30
sense of it my um you know when i
00:12:32
tweeted that tweet out to complete the
00:12:34
picture i was actually long something
00:12:36
against my proposed short
00:12:38
and i put it on in pretty meaningful
00:12:40
leverage and um it's worked out really
00:12:42
well because i was playing the spread i
00:12:45
was basically betting that you know the
00:12:47
the safest company on the internet today
00:12:49
is google because they're both a
00:12:50
platform company and to the extent that
00:12:53
they're at risk at being an app company
00:12:56
the risk is to apple but because they
00:12:58
pay apple so much for search they're
00:13:01
inoculated and so in many ways google is
00:13:03
the safest and it's also as we've said
00:13:06
before the purest money making machine
00:13:07
on the internet you're referring of
00:13:09
course to
00:13:10
google paying apple 10 billion dollars
00:13:12
to be the default search they own
00:13:14
android so one platform and on the other
00:13:16
platform they they pay them so much that
00:13:18
they're going to be always protected and
00:13:20
the second best company is microsoft and
00:13:23
you we even saw it by the way this past
00:13:25
week i don't know if you guys saw that
00:13:26
but microsoft decided to take a
00:13:27
broadside attack against notion yeah
00:13:30
which is a productivity app that's been
00:13:32
growing very well i felt this when i was
00:13:35
on the board of slack when microsoft put
00:13:37
its gun sights on us we always thought
00:13:38
that they could not
00:13:40
out compete with us and what it turns
00:13:42
out is when you have a massive
00:13:44
distribution advantage
00:13:46
feature parity is enough and you can
00:13:48
actually be
00:13:49
slightly less than good enough on the
00:13:51
features because distribution and
00:13:53
bundling and packaging overpower a
00:13:55
customer's desire to adopt a product so
00:13:57
in the case of slack
00:13:58
it was very difficult i think for us to
00:14:00
compete against microsoft's bundling
00:14:03
of teams
00:14:04
with all this other software that they
00:14:06
were selling and all the discounting
00:14:07
that they could do made it very
00:14:08
difficult for us to compete because we
00:14:10
had a single product and lo and behold
00:14:12
18 months later the only real long-term
00:14:15
protective solution for slack
00:14:16
shareholders was to basically get bought
00:14:18
by salesforce so that you could be part
00:14:20
of a bigger hole
00:14:21
this past week microsoft decided to go
00:14:23
after notion and it's going to be i
00:14:25
think a very similar story where
00:14:27
you know once they decide to sort of go
00:14:29
after this a product experience
00:14:32
they only need to be eighty percent as
00:14:34
good and then the distribution and
00:14:35
bundling and packaging will take care of
00:14:37
the other twenty percent it doesn't kill
00:14:38
the other company but it creates
00:14:40
headwinds that massive headwinds because
00:14:42
because a company like notion cannot be
00:14:44
fully valued over long periods of time
00:14:46
simply being an smb company at a minimum
00:14:48
you'll have to move into the mid-market
00:14:50
you may necessarily never have to go to
00:14:52
the enterprise but you probably have to
00:14:54
go to the mid-market and in that is a
00:14:55
very troublesome path because microsoft
00:14:58
has so much
00:15:00
you know uh
00:15:01
so many tentacles inside of those
00:15:02
businesses so anyways basically
00:15:04
microsoft long google is a pretty
00:15:06
obvious kind of like monopolistic
00:15:09
you know
00:15:10
pair trade the question is what do you
00:15:12
short against it so that you can take up
00:15:14
the market volatility and you can play
00:15:16
spread
00:15:17
again apple has severe you know
00:15:19
headwinds with respect to inflation
00:15:21
pressures um and margins and supply
00:15:24
chain issues amazon has pretty
00:15:26
meaningful headwinds now
00:15:28
relative to uh pricing power and
00:15:31
competition facebook has pressure with
00:15:34
respect to regulatory oversight i just
00:15:35
came up with one what about airbnb
00:15:37
versus the airlines
00:15:40
you're talking about small or
00:15:42
rinky dink ideas well listen i'm not
00:15:44
playing the same chip stack issue i
00:15:45
wasn't there on tuesday night i'm on a
00:15:47
thursday night so no no that'll be a
00:15:49
good spread for me no that's a stupid
00:15:50
idea and i'll tell you why okay if
00:15:52
you're gonna put these things on go to
00:15:54
where the deepest liquid markets are
00:15:55
because those are the safest
00:15:57
okay
00:15:58
right like like don't try to be
00:16:00
different
00:16:01
being the same here tell me why airbnb
00:16:04
which is a incredible margin business
00:16:06
that's incredibly well run and growing
00:16:08
versus airlines which are horribly run
00:16:10
and low margin why wouldn't that be a
00:16:12
good spread trade i'm just thinking
00:16:14
i think it's a very very too you're
00:16:16
picking two random companies out of a
00:16:19
hat well no they're both in
00:16:21
uh transportation and vacation and
00:16:23
traffic they're completely different
00:16:24
businesses with completely different
00:16:25
motivations with different capital pools
00:16:27
with different people that own the stock
00:16:29
there's no point trying to get cute on
00:16:31
these things my point is if you really
00:16:33
want to be hedged
00:16:34
against market risk got it
00:16:37
go to where it's safest
00:16:39
find the simplest most obvious thing
00:16:42
don't overthink it or don't put it on
00:16:45
so another obvious one here's here's so
00:16:47
obvious is within big tech figure out
00:16:50
which ones you want to be long which
00:16:51
ones you want to be short that's a
00:16:52
spread trade that over the next four or
00:16:54
five years where if you expect a lot of
00:16:56
market volatility
00:16:57
it makes sense to maybe put some of this
00:16:59
kind of stuff on right
00:17:01
a different version of this idea which
00:17:03
makes sense is in autos again trillions
00:17:06
of dollars of market cap and you can
00:17:08
make a decision do i want to be long
00:17:11
tesla lucid and
00:17:13
rivian and short the traditional autos
00:17:16
that could be a trade
00:17:18
you know but trying to like trying to go
00:17:20
after like let me pick airbnb versus
00:17:22
united airlines is too random for me and
00:17:24
i don't think they're correlated enough
00:17:26
for it to make any sense right speaking
00:17:28
of the stock market uh saks um you've
00:17:31
got the background of the new york stock
00:17:32
exchange as your zoom background today
00:17:34
what's that about
00:17:36
yeah so bird listed on the new york
00:17:38
stock exchange today this is a company
00:17:41
that i've been involved in pretty much
00:17:42
since the beginning we led the series a
00:17:44
round back in 2017 it was actually the
00:17:46
first
00:17:47
check i wrote as a vc to lead around
00:17:50
at kraft and four years later public
00:17:52
company on the new york stock exchange
00:17:54
is pretty amazing
00:17:56
and so you're literally at the new york
00:17:58
stock exchange we speak first remote
00:18:00
bestie yes and you can see behind me um
00:18:05
that is the floor of the new york stock
00:18:06
exchange it's not like you know if you
00:18:08
see the movie trading places it's not
00:18:10
like that anymore there are no stock
00:18:12
brokers there's no like paper flying
00:18:13
around got it i'm not really sure what
00:18:16
the purpose of all those monitors are
00:18:17
down there it feels to me a little bit
00:18:19
like a movie set
00:18:20
yeah it's like a movie setting yes yeah
00:18:22
and some people guys come here to record
00:18:24
things but
00:18:26
as we all know the all the trades are
00:18:28
really happening inside giant machines
00:18:30
can you turn around and just start
00:18:32
yelling booyah
00:18:35
and let's see if security comes and
00:18:38
no i remember i'm in i'm i'm elevated
00:18:40
above the floor no one could really hear
00:18:42
me here i'm in like this sort of
00:18:44
broadcast booth
00:18:45
uh so take us behind the decision to go
00:18:47
public as a four year old company we
00:18:50
were expecting
00:18:51
you know uh airbnb ubers and lyfts took
00:18:55
over 10 years to go public now here we
00:18:56
are sitting on a four-year-old public
00:18:58
company
00:18:59
is that a good thing a bad thing
00:19:01
something in between and how does the
00:19:03
board and the management team make that
00:19:04
decision to go public
00:19:05
i think it's a good thing um because the
00:19:08
company well the company wanted to i
00:19:09
think it had the opportunity to it um it
00:19:12
grew very very quickly before covid then
00:19:15
you had covid was like sort of a huge
00:19:16
setback they i mean basically the
00:19:18
scooter industry just stopped for at
00:19:20
least six months because of lockdowns
00:19:22
but then coming out of kova they bounced
00:19:24
back really strongly they kind of
00:19:25
pivoted
00:19:27
their model to what's called a fleet
00:19:29
manager model where basically they're
00:19:30
putting a business in a box for a local
00:19:33
operator a local entrepreneur to buy the
00:19:36
scooters with financing and manage the
00:19:38
fleet themselves so it's a much more
00:19:40
highly virtualized model
00:19:42
and so as a result of that in q2 they
00:19:45
just did 60 million in revenue in the
00:19:47
last quarter
00:19:49
and i think
00:19:51
it was a gross profit of something like
00:19:53
27
00:19:54
and
00:19:56
uh it was had a loss of like 12 million
00:19:59
so they're very very close to getting to
00:20:01
profitability
00:20:03
and uh you know the company's only four
00:20:05
years old you know it took uber 12 years
00:20:07
or whatever to get through public so
00:20:09
it's been pretty it's been a pretty
00:20:10
amazing ride there's been a lot of big
00:20:12
ups and downs but uh so it's kind of a
00:20:15
pretty sweet event what is it
00:20:17
i know it was switchback was like the
00:20:19
spat name right so it's it today was the
00:20:21
first day it started trading under the
00:20:22
ticker symbol brds i guess all birds
00:20:25
took
00:20:26
bi rd so we took brds
00:20:30
and um
00:20:31
you know if there's a total number of
00:20:34
shares outstanding of i want to say
00:20:35
roughly 300 million so it's about a 2.4
00:20:39
uh billion dollar market cap you know as
00:20:41
it stands right now
00:20:43
which you know for a series a investor
00:20:44
is pretty great really happy for you sex
00:20:46
yeah congratulations it's great congrats
00:20:49
dude we heard last week sequoia is going
00:20:51
to do the sequoia fund this evergreen
00:20:53
fund keep owning shares now as a vc
00:20:56
um do you distribute after four years of
00:20:59
this investment and you made multiple
00:21:01
investments or do you make the decision
00:21:03
hey we think it's undervalued we have
00:21:05
you know conviction in the company we
00:21:06
were going to be in it for 10 years or
00:21:08
do you just take the quick win and give
00:21:10
everybody their shares well i've i'm
00:21:12
gonna i've agreed to be on the board for
00:21:13
the next year so
00:21:14
you know i'm planning to do that and
00:21:18
we have a traditional six month lockup
00:21:20
and so at that point we'd have to make a
00:21:22
decision about when or how much to
00:21:24
distribute the shares and this is the
00:21:27
first time we've been confronted with
00:21:28
the decision i mean craft ventures is
00:21:30
only a four-year-old firm and like i
00:21:31
said this is actually the first
00:21:33
round that i led as a vc so it's the
00:21:35
first time we've been confronted with a
00:21:37
distribution of this magnitude we've had
00:21:39
some smaller distributions
00:21:41
so yeah we still have to make those
00:21:42
decisions we haven't decided yet what
00:21:44
we're going to do if you if the stock is
00:21:46
up let's say meaningfully in the next
00:21:48
six months and you get to that you know
00:21:49
six months and a day and you have the
00:21:51
ability to distribute and it's up 25
00:21:55
and you're looking at it business is
00:21:57
thriving you're on the board
00:21:59
do you consider holding for a year or
00:22:00
two so that you can distribute it at 16
00:22:04
25 or whatever your price target is
00:22:07
maybe i mean we haven't we haven't
00:22:08
gotten to that point yet so yeah i mean
00:22:10
i guess what i would say is that our
00:22:12
bias
00:22:13
would be to distribute
00:22:15
shares to our lps so that they can make
00:22:19
their own decisions about whether to
00:22:21
hold it or not
00:22:22
um as long as we think the stock is you
00:22:24
know priced fairly if for some reason we
00:22:26
thought it wasn't
00:22:28
then would there be an additional reason
00:22:29
to hold on to it and make the
00:22:30
distribution later
00:22:32
chamoth what are your thoughts on this
00:22:33
given it's come up before
00:22:36
and a number of us are going to be faced
00:22:37
with this decision and then we see
00:22:38
sequoia has got lp buy-in for an
00:22:41
evergreen fund well i think an evergreen
00:22:43
fund is different from having to figure
00:22:45
out how to do distributions so
00:22:47
um they're they're solving for two
00:22:49
different ideas
00:22:50
the evergreen fund is really good
00:22:52
because you don't have to do this
00:22:54
continual
00:22:56
fundraising process and you can
00:22:57
basically roll gains back into
00:23:00
the next tranche of invested companies
00:23:02
in an easier way i like that idea it was
00:23:04
pretty
00:23:05
rare at the time i remember when i was
00:23:07
starting social capital the only fund
00:23:09
that did it really well was sutter hill
00:23:11
um and for a whole host of reasons i
00:23:13
decided to not do an evergreen fund
00:23:16
in hindsight i think for me
00:23:18
that turned out to be better because
00:23:19
then it was easier for me to wind down
00:23:22
and have a clear demarcation of when
00:23:24
it was just myself and other lps
00:23:27
versus
00:23:28
when it was just my capital
00:23:31
but there were some really good reasons
00:23:32
to do it
00:23:34
the hardest thing i think that sequoia
00:23:35
is going to find
00:23:37
in this new iteration is
00:23:40
at some point somebody's reputation will
00:23:42
be on the line for judging public
00:23:45
equities
00:23:46
and
00:23:48
it's still not clear to me that people
00:23:49
who live and breathe venture
00:23:51
can context switch well enough to then
00:23:53
live and breathe
00:23:55
public equity so just the best example i
00:23:57
would say is like tiger global when you
00:23:58
look inside that
00:24:00
organization which is incredibly well
00:24:02
run there are two superb investors that
00:24:05
carve the universe up right you have
00:24:07
chase coleman that runs the public book
00:24:08
and you have scott schleifer that runs a
00:24:09
private book
00:24:11
what does it prove to me it proves that
00:24:13
it's just very hard to find a person
00:24:14
that can do both
00:24:16
and the context switching is very
00:24:17
complicated so maybe sequoia finds
00:24:20
an incredible public market strategist
00:24:22
that can then manage these positions
00:24:24
otherwise but
00:24:26
they've done this for a few years right
00:24:27
they've um sequoia i don't know people
00:24:29
realize this they set up
00:24:31
the heritage fund and they set it up
00:24:32
with only gp's money it's got billions
00:24:35
under management and it's been making
00:24:37
late stage private but mostly public
00:24:39
equity investing
00:24:41
i know but that's a fun to fund what i'm
00:24:43
saying is
00:24:44
i'll be very honest with you if i was an
00:24:46
lp of sequoia
00:24:48
i would want the money back
00:24:50
and the reason is i'm not sure that
00:24:52
sequoia can compound money in the public
00:24:54
markets anywhere near what i could
00:24:56
so do you buy the point that they make
00:24:58
that like exiting some of these left
00:25:00
most of the you know kind of value
00:25:02
creation on the table i think what
00:25:04
they're saying something much more
00:25:05
subtle which is they exited and they
00:25:08
have regrets for selling you have to
00:25:09
remember
00:25:10
when sequoia distributed google
00:25:13
every single partner got google shares
00:25:17
now had they held those shares they
00:25:19
wouldn't be saying any of this and
00:25:20
famously i'll tell you when they held
00:25:22
their shares
00:25:24
i actually do
00:25:25
fair enough but maybe they did maybe
00:25:27
they didn't but let's just let's just
00:25:28
put it out there that for example i know
00:25:30
explicitly when i almost merged social
00:25:32
capital with kleiner perkins like six
00:25:34
years ago
00:25:35
i spent so much time with john dore the
00:25:37
most incredible thing that i was so
00:25:38
impressed with dora was he was he told
00:25:40
me he had never sold a single share of
00:25:43
amazon that was distributed to him and
00:25:46
he had only sold a handful of shares of
00:25:48
google
00:25:49
only to fund future capital requirements
00:25:51
at kleiner at the time
00:25:53
so
00:25:54
i just think that ultimately
00:25:56
i think probably what sequoia was saying
00:25:58
is man i wish i had not sold my google
00:26:00
shares when they were distributed to me
00:26:02
because otherwise they wouldn't make
00:26:03
that claim no i think what they're
00:26:04
saying is more subtle i think they're
00:26:05
saying you as our lps should have held
00:26:08
them we are on the board of these
00:26:09
companies from day one we have better
00:26:12
insights in the second decade than in
00:26:13
the first production board uh founder
00:26:16
david friedberg how do you think about
00:26:18
early exits distributing capital because
00:26:21
you do have also with a startup studio
00:26:23
structure which you should explain to
00:26:24
the audience how a startup studio works
00:26:26
because you create companies which is
00:26:29
you know was a terrible place to be
00:26:30
maybe five or ten years ago but it turns
00:26:32
out you're in the best place because
00:26:33
zero to one is where all the values
00:26:34
created explain the two things
00:26:37
what a startup studio is for people who
00:26:38
don't know
00:26:40
and then what's your view of selling
00:26:41
early if a company of yours goes uh
00:26:45
publicly i think there's a big um
00:26:47
there's a bigger kind of framing here
00:26:49
which is a lot of um
00:26:51
investors
00:26:53
you know professional money managers
00:26:54
have tried to find ways to create what
00:26:57
is called permanent capital which is a
00:26:59
vehicle whereby they can
00:27:01
continuously make investments decide
00:27:03
when to sell those investments and
00:27:04
recycle the capital into new investments
00:27:06
with the idea being that over time
00:27:08
they're not at risk of capital outflows
00:27:10
meaning investors pull their money out
00:27:12
and they're not at risk of
00:27:15
uh you know needing to kind of go out
00:27:17
and raise more money and they can they
00:27:18
can share in the value creation as they
00:27:20
grow their book value over time
00:27:22
years ago a bunch of hedge funds set up
00:27:25
public reinsurance companies
00:27:27
dan loeb did this um uh what's his name
00:27:30
einhorn did this blackman did it and
00:27:32
basically bill ackman did it what they
00:27:34
did is they set up a public company a
00:27:36
new public company a reinsurer
00:27:38
and then they used that that reinsurer
00:27:40
to underwrite reinsurance and when you
00:27:42
underwrite reinsurance you get all this
00:27:43
capital that you can then go invest and
00:27:45
then the hedge fund manage that
00:27:46
investment and because it's actually a
00:27:48
public company it's got a balance sheet
00:27:50
the um
00:27:52
the shareholders can't pull their money
00:27:53
out right it's just got a balance sheet
00:27:55
and the hedge fund was managing that
00:27:56
balance sheet
00:27:58
and you know generating good returns and
00:27:59
this is effectively what warren buffett
00:28:01
does and everyone looks to berkshire
00:28:02
hathaway and warren buffett it's kind of
00:28:04
the
00:28:04
you know the the the key kind of long
00:28:07
term here
00:28:08
um which is uh hey look if you can keep
00:28:10
investing and keep compounding value
00:28:12
this thing can grow
00:28:13
you know exponentially over time
00:28:16
so you know the way we set up the
00:28:18
production board i had the option of
00:28:20
raising a fund and being a fund manager
00:28:21
i chose to set up the production board
00:28:23
because i was much more interested in i
00:28:25
think the similar sort of vein of what
00:28:26
sequoia is saying which is like how do
00:28:27
you become a longer term uh builder and
00:28:30
a longer term holder and where you don't
00:28:32
have these incentives to return capital
00:28:34
because you only get paid if and when
00:28:35
you return capital
00:28:37
and um
00:28:39
you know and then you're kind of making
00:28:40
these decisions to you know because your
00:28:41
shareholders are saying well you had a
00:28:43
good return quickly give me the shares
00:28:44
back and let me and mark your profit and
00:28:46
take your share and i was also more
00:28:48
interested in look the fact is over time
00:28:50
there's always going to be opportunities
00:28:52
to chase with the capital so if we have
00:28:54
a great gain if something works out
00:28:55
really well we can take the the gain and
00:28:58
we can reinvest that capital in building
00:29:00
new things there's no shortage of
00:29:01
opportunities to pursue for the rest of
00:29:03
my life
00:29:04
so that's why i set up the production
00:29:05
board initially in partnership with
00:29:07
alphabet and then later on we brought in
00:29:08
you know bill gates and other allen and
00:29:11
co and other kind of investors that have
00:29:13
a similar sort of mindset which is like
00:29:14
let's just if we have an exit recycle
00:29:17
that capital and continuously they're
00:29:19
not looking for a quick win they don't
00:29:21
have pension payments to make right they
00:29:22
don't have a reason to distribute cash
00:29:25
and so same with me like i don't have a
00:29:26
reason to take cash out so the objective
00:29:28
was just build this thing over time and
00:29:30
grow value over time and that's why i
00:29:33
set it up the way i did and i think it
00:29:34
allows us to make you know really
00:29:36
long-term bets that are super risky
00:29:38
most of what we're doing is super
00:29:40
technical and and difficult and maybe
00:29:42
very hard to pull off uh many of which
00:29:44
are still after many years in a very
00:29:46
early you need very patient capital
00:29:48
patient capital and also the you know
00:29:50
the preference for
00:29:51
not trying to find exits but i have
00:29:54
found this i'll tell you one thing i
00:29:55
have been through a number of
00:29:56
circumstances where i have seen
00:29:58
businesses i've been an investor in or
00:29:59
involved in that have traded long-term
00:30:02
value for short-term opportunity meaning
00:30:05
there's an opportunity to make a
00:30:06
business that you can then go raise
00:30:08
capital against you change your strategy
00:30:10
to do that then you go raise vc funding
00:30:12
and now the business looks like it's
00:30:13
working but the 10x or 100x opportunity
00:30:16
was taken off the table because you
00:30:18
ended up going down this different path
00:30:20
that was a sure thing that was more
00:30:22
likely to work that created value in the
00:30:24
short term that allowed you to mark up
00:30:26
your investment or raise capital against
00:30:27
that but you gave up the big long term
00:30:29
thing and i think that's something i've
00:30:30
been trying to avoid with the structure
00:30:32
and it certainly makes sense with some
00:30:34
of these other folks and what they're
00:30:35
trying to do so what we're getting at
00:30:37
here saks is decision making by capital
00:30:40
allocators
00:30:41
and on behalf of their lps or letting
00:30:44
the lps make those decisions inevitably
00:30:47
the crypto world says well why aren't
00:30:48
you just doing this in a dow
00:30:51
and you know having some decentralized
00:30:54
authority make the decisions
00:30:57
i had vanillin i've had a conversation
00:30:59
with our friend vinnie lingam uh after
00:31:00
the solana stuff and and multi-coin
00:31:03
capital
00:31:04
and we were talking about dows for early
00:31:06
stage investing or syndicates and just
00:31:08
brainstorming hey is there a way to do
00:31:10
this
00:31:12
and the problem i came to every time was
00:31:14
should a bunch of folks be making
00:31:16
decisions who are not meeting with the
00:31:18
companies or meeting with 2000 companies
00:31:20
a year
00:31:21
what are your thoughts on a dao
00:31:24
representing sort of what we
00:31:27
collectively do but we all do it
00:31:28
obviously in different flavors
00:31:30
this actually exist yep
00:31:33
well there have been dows that have
00:31:35
existed to vote on buying nfts so yes
00:31:37
for collectibles i mean i kind of feel
00:31:39
like i'll let you know when it actually
00:31:41
gets here
00:31:42
so open-minded to it but who knows yeah
00:31:44
but i mean we talk about these things as
00:31:45
if they already are here and they're not
00:31:47
quite here i mean technically i know
00:31:49
they they exist but people haven't
00:31:50
really figured out how to
00:31:52
use them to you know to be a fund
00:31:55
manager for example i think david's
00:31:57
right i think the
00:31:58
look i i there there are these three
00:32:02
immutable features of web 3.0 that we're
00:32:04
going to have to figure out over the
00:32:06
next few years so the obvious ones are
00:32:08
decentralization right that makes sense
00:32:11
the second obvious one is the level of
00:32:13
composability which means that you're
00:32:15
plug and play with everything
00:32:17
um but the third one is this idea of
00:32:19
democratization and governance right and
00:32:21
that's where dows come in and david's
00:32:23
right we don't really know what the
00:32:25
boundaries of that feature is
00:32:29
i think it exists in some small level
00:32:31
scale
00:32:33
but we need to have many iterations of
00:32:35
companies get built
00:32:37
to figure out what it'll mean
00:32:40
so i don't know i'm taking a pretty
00:32:41
traditional approach jason which is that
00:32:44
you know it's kind of like a crawl walk
00:32:45
run strategy right now i'm in the
00:32:47
crawling phase and
00:32:49
i'm kind of saying how did
00:32:51
web 1.0 and web 2.0 develop and i'm
00:32:54
trying just copying it so you know in
00:32:56
web 1.0 and 2.0
00:32:58
you needed companies like sun
00:33:00
microsystems and cisco and you know all
00:33:02
of the plumbers foundational stuff to
00:33:05
build plumbing for the internet to allow
00:33:08
the thousand flowers to bloom at the
00:33:09
application level
00:33:11
and you know we had a very good
00:33:13
reference model by the way for web 1.0
00:33:15
for most people if you want to look at
00:33:16
it it's called the osi reference stack
00:33:18
and if you actually look at that osi
00:33:19
stack you can translate that
00:33:22
to
00:33:23
all kinds of value creation over the
00:33:25
first you know two arcs of the internet
00:33:27
over 20 years trillions of dollars was
00:33:29
created by just following each of those
00:33:31
substrates
00:33:32
um and in those transitional layers was
00:33:34
where these great beautiful companies
00:33:36
were built
00:33:37
and i think similarly we're going to do
00:33:38
that again but we need a different stack
00:33:40
to represent what web pre is so
00:33:43
yeah you know this week we did something
00:33:45
which was pretty straightforward which
00:33:46
was this idea that if you're going to
00:33:48
build all these apps you're going to
00:33:50
need a distributed compute
00:33:52
infrastructure which means you're going
00:33:53
to need very simple building blocks like
00:33:55
remote procedure calls rpc
00:33:57
that exists in web 2.0 it's kind of a
00:34:00
not something you don't really think
00:34:01
about but in web 3 doesn't exist and so
00:34:03
it's all this
00:34:05
aws you know gcp like infrastructure
00:34:07
that has to get built and
00:34:09
that's what syndicate does and i almost
00:34:11
i think that's um a really very
00:34:13
interesting uh observation there because
00:34:16
everybody is trying to go to the
00:34:18
application level and talk about the
00:34:19
consumer experience
00:34:21
but before you even have the ability you
00:34:23
know
00:34:24
we're talking about cars before we've
00:34:25
even made a transmission or you know
00:34:28
that's exactly right this is why crypto
00:34:30
comes across as so delusional and
00:34:31
strange sometimes they wrote 000 ico
00:34:33
papers
00:34:34
none of them were about infrastructure
00:34:36
they were all about some sort of end
00:34:38
game but the thing is it's a very
00:34:39
delicate balancing act right you need a
00:34:41
handful of companies that capture
00:34:43
consumer imagination right that then
00:34:45
incentivize all of the plumbing
00:34:47
companies to come in and build
00:34:48
underneath it right so it's a customer
00:34:50
it's a very delicate balancing act right
00:34:52
so you needed compuserve
00:34:54
in order to enable a bunch of companies
00:34:55
then you needed aol in order to enable
00:34:57
another set then you needed yahoo then
00:35:00
you needed google and in all of that
00:35:02
what happened was people were pulled
00:35:03
through
00:35:04
right you needed amazon commerce to
00:35:07
justify aws
00:35:09
so we're in that world where it's going
00:35:11
to be a little back and forth where the
00:35:12
pendulum will swing back and forth
00:35:14
between consumer experiences that
00:35:15
capture imagination get to some level of
00:35:17
scale that then create incentives for
00:35:20
the developer ecosystem and the
00:35:22
technology infrastructure to catch up uh
00:35:24
zillow which we talked about previously
00:35:26
became an eye buyer what's an eye buyer
00:35:28
that means you buy a bunch of single
00:35:30
family homes in all likelihood
00:35:33
like open door and redfin have been
00:35:35
doing and then you hope to flip them uh
00:35:37
maybe improve them and uh maybe lower
00:35:41
cost to the consumers by taking out real
00:35:43
estate brokers this has created a lot of
00:35:46
bad feelings amongst real estate brokers
00:35:48
a tick tock video trended a couple of
00:35:51
months ago where a broker said or
00:35:53
accused zillow
00:35:55
of buying up these homes in order to do
00:35:57
price fixing and to corner the market on
00:35:59
homes well
00:36:00
uh it turns out that zillow which has an
00:36:03
incredible ceo uh in rich barton and has
00:36:06
done tremendously over the decades
00:36:08
according ahead of their earnings call
00:36:10
this week bloomberg reported zillow is
00:36:12
trying to offload seven
00:36:14
thousand seven thousand homes for 2.8
00:36:16
billion that's about a 400k average per
00:36:19
home
00:36:20
and zillow shares dropped 37 this week
00:36:23
alone from 100 to 66. their market cap
00:36:26
has dropped nine billion throughout the
00:36:28
week
00:36:29
uh and they're down 70 from a peak
00:36:31
valuation of 48 billion just in february
00:36:33
about six months ago
00:36:35
zillow is going to reduce its workforce
00:36:37
by 25 over the next few months i'm
00:36:39
assuming that's all those eye buyers
00:36:41
anecdotally a lot of what i'm hearing is
00:36:44
they bought homes indiscriminately the
00:36:46
anecdotal stories that are breaking on
00:36:48
twitter and other forums with real
00:36:49
estate brokers are they would look at a
00:36:51
home
00:36:52
they didn't know that it had a noisy
00:36:54
neighbor or it was near power lines or
00:36:56
whatever the people who came in bought
00:36:57
them indiscriminately maybe too fast
00:36:59
whereas some other companies maybe open
00:37:01
door or redfin were more considered i
00:37:03
actually had glenn from redfin on the
00:37:05
pod not long ago and he said it's a very
00:37:07
hard operational business you have to be
00:37:08
very careful on what you buy in your
00:37:10
entry price that seems to have turned
00:37:12
out to be true what do you think
00:37:14
friedrich rich barton who runs zillow is
00:37:17
considered a legend in silicon valley
00:37:20
you know he um uh has been involved in
00:37:23
some of the most successful internet
00:37:25
companies um and you know when he
00:37:28
stepped back in as the founder of zillow
00:37:29
stepped back in to run the business a
00:37:31
few years ago it was viewed as kind of a
00:37:33
second
00:37:35
you know resurrection of this business
00:37:37
and he was going to take it into new
00:37:38
areas and then three and a half years
00:37:39
ago he announced the cyber program which
00:37:41
everyone thought was such a you know
00:37:43
incredibly strong move and obviously
00:37:45
chased open door which champ is involved
00:37:47
in and i'm sure we'll share more on but
00:37:49
it was such an obvious opportunity that
00:37:51
if you could add liquidity to the real
00:37:53
estate market the residential real
00:37:55
estate market there's an incredible
00:37:56
amount of value to be had
00:37:58
now the way that they wrote about it
00:38:00
when they talked about it initially and
00:38:02
then the way that they've kind of talked
00:38:03
about in their earnings report this week
00:38:04
was that they were trying to be a quote
00:38:06
market maker in the business
00:38:07
and it turned out that what they were
00:38:09
really doing was being more of a
00:38:11
speculator right a market maker looks at
00:38:13
bids and asks in the spread and then
00:38:14
tries to to create a gap in that spread
00:38:16
and make and take some share of it
00:38:20
and by adding that liquidity the idea is
00:38:22
the spreads can narrow and they can make
00:38:23
money in this case they were looking at
00:38:26
the historical
00:38:28
velocity of selling prices of homes and
00:38:31
using that as a way to kind of project
00:38:33
what was going to happen which makes
00:38:35
them much more of a speculator than a
00:38:37
market maker
00:38:39
and they clearly got this wrong and
00:38:41
their kind of quote-unquote models on
00:38:43
you know where prices headed ended up
00:38:45
getting them in trouble there's also the
00:38:47
inherent conflict where they are now
00:38:48
competing in a way with the brokers that
00:38:50
generate a lot of revenue for them and
00:38:52
are a big part of their core business
00:38:54
and they were clearly um
00:38:56
you know cannibalizing their own
00:38:57
business where the zestimate and some of
00:38:59
the other scoring that they provide as a
00:39:00
data and analytics platform to both
00:39:02
sides of the existing market
00:39:04
starts to get blown up because they're
00:39:05
coming in and saying we're going to put
00:39:06
our you know our foot down and say this
00:39:08
is what the value is and it inevitably
00:39:10
kind of cannibalizes the core product
00:39:12
that they provide to both sides of the
00:39:14
market so you know one could argue this
00:39:16
was flawed from the beginning the
00:39:18
execution clearly was way off and it
00:39:19
begs the question you know where was
00:39:21
leadership and kind of tracking what was
00:39:23
going on here is these guys were buying
00:39:25
homes at market prices that are well
00:39:27
above what they were actually selling
00:39:28
for in the market no one was actually
00:39:30
doing on-the-ground work they were all
00:39:32
doing kind of speculative models and
00:39:33
saying this is what we think will happen
00:39:35
and then they woke up way too late and
00:39:38
um lost way too much money i think they
00:39:40
lost 300 million dollars in the quarter
00:39:42
so um you know really a lot of questions
00:39:44
and a lot of challenges on this um i'm
00:39:46
sure chemat has a point of view on you
00:39:48
know what makes opendoor distinct from
00:39:50
from zillow um but there's a really
00:39:52
important kind of you know um underlying
00:39:55
here you know
00:39:57
yeah the maturity of a silicon valley
00:39:59
uh entrepreneur who's crushed it so many
00:40:01
times uh doesn't mean that they're
00:40:03
perfect and you know this was a big mess
00:40:05
you can go really too fast into a turn
00:40:07
here and clearly they flip the car
00:40:09
chamoth i i don't know how comfortable
00:40:11
you are talking about this interesting
00:40:12
very comfortable okay well then here we
00:40:14
go
00:40:16
number one you know i'm not on the board
00:40:18
um of open door of open door maybe tell
00:40:21
us about your history with open door
00:40:22
chim off would be super look i
00:40:24
look i am one of the largest individual
00:40:26
shareholders of that company i think
00:40:28
somewhere between three and four percent
00:40:29
of the business i own
00:40:31
we you know i came to own those shares
00:40:33
with a large investment uh as well as
00:40:37
through the transaction uh where we
00:40:39
merged
00:40:42
one of our specs into it and took it out
00:40:44
ipob
00:40:46
yes
00:40:47
couple things to say the first is about
00:40:49
the ceo and founder of opendoor
00:40:52
eric wu
00:40:54
is
00:40:55
special special special so let me just
00:40:57
leave it at that
00:40:59
on that topic the second is i think that
00:41:02
rich barton is very special
00:41:04
but it speaks to
00:41:06
two big mistakes that zillow made
00:41:09
the first is that
00:41:11
catching
00:41:13
a wave of disruption
00:41:15
is very difficult when you have an old
00:41:17
line business that is fundamentally
00:41:19
competitive with the new line of
00:41:21
business
00:41:22
and zillow as david said had this thing
00:41:24
called zestimate
00:41:25
whose entire job was to directionally
00:41:27
drive
00:41:28
top of funnel traffic into the rest of
00:41:30
their media business
00:41:32
now imagine you go to a website to look
00:41:34
up your house value or somebody else's
00:41:36
house value
00:41:38
accuracy is a bug
00:41:40
the feature that makes this estimate
00:41:42
work is a highly inflated house price
00:41:46
right like if you go and you see a crazy
00:41:48
house price number that's interesting
00:41:50
that's more um
00:41:53
click-worthy than if you go in there and
00:41:55
it shows some depressed value you think
00:41:57
the sight sucks that's the unfortunate
00:41:58
psychological reaction so i think
00:42:00
whether we believe it or not or whether
00:42:03
zillow knew it or not
00:42:05
zestimate over time basically calcified
00:42:08
this idea of price inflation
00:42:11
so the accuracy was never a goal
00:42:14
so then if you take that business and
00:42:15
then you try to orient it towards home
00:42:17
buying and you use
00:42:18
probably zestimate or some version of it
00:42:20
to underpin how you buy and take risk
00:42:23
it creates a lot of risk and i think
00:42:24
this is essentially what played out
00:42:26
where they were over buying homes and
00:42:28
they didn't know how to price this stuff
00:42:29
accurately so you know my partner ravi
00:42:32
tweeted this out but
00:42:33
you know uh the open door margin on
00:42:36
average is about ten percent the zillow
00:42:38
margin on average was three percent so
00:42:39
they had a much more razor thin margin
00:42:42
of safety here which again speaks to
00:42:44
pricing and then it speaks to this third
00:42:46
thing which is that
00:42:48
if you start doing one thing and do it
00:42:50
really well with software
00:42:53
the gains over years really compound and
00:42:56
so when somebody else shows up and tries
00:42:58
to pivot their business to try to copy
00:43:00
it it's very very difficult the classic
00:43:03
example is google versus yahoo yahoo had
00:43:05
a beautiful directory driven business
00:43:08
but when larry and sergey really larry
00:43:10
invented pagerank and then invented that
00:43:12
first version of a google search index
00:43:15
as we saw it play out over the next 10
00:43:17
or 15 years it was impossible for yahoo
00:43:20
to really invest the technology the
00:43:22
technical capital necessary to catch up
00:43:24
with google and every day and every week
00:43:27
and every year as friedrich talked about
00:43:29
last week
00:43:30
those technical gains compound and
00:43:32
compounded now google is completely
00:43:34
unassailable with respect to search
00:43:37
i suspect we will look back
00:43:39
and the ability to accurately forecast
00:43:42
price and volatility
00:43:44
and the ability to sell these assets
00:43:48
at a defined margin of safety in a
00:43:50
predictable way
00:43:52
is something software can solve
00:43:55
and it seems that open door is the first
00:43:58
it doesn't necessarily mean it'll be the
00:44:00
only one
00:44:02
but it has an enormous head start now
00:44:04
and as long as they can keep iterating
00:44:06
those gains will compound
00:44:08
um so that's what i think i just think
00:44:10
this is a wonderful business
00:44:12
run by an incredible ceo to wrap up this
00:44:15
uh zillow story saks uh any thoughts on
00:44:18
you know jamaat's point here you know
00:44:20
you're the rating agency and you add
00:44:22
this business and the business it might
00:44:24
be orthogonal to the existing money
00:44:27
printing machine on a strategic basis
00:44:29
what do you think
00:44:30
any lessons or mistakes here uh in terms
00:44:33
of when you handicap zillow or do you
00:44:35
want to just move on to truck politics i
00:44:36
mean look i'm a i was a c investor in
00:44:38
open door because rabbi invited me to
00:44:40
the seed round so
00:44:42
you know i'm a little biased here but i
00:44:44
think it's pretty obvious what happened
00:44:46
zillow tried to copy them the business
00:44:48
is much more operationally complicated
00:44:50
than they realized it's a low business
00:44:52
low margin business with the which
00:44:54
requires a ton of capital so if you're
00:44:57
off a little bit the losses can be huge
00:45:00
and zillow couldn't figure it out they
00:45:01
underestimate the difficulty that's what
00:45:03
frequently happens when a big company
00:45:04
tries to
00:45:05
copy a smaller sort of upstart company
00:45:08
so i mean that to me is what happened in
00:45:09
a nutshell quite frankly we're an hour
00:45:11
into this pod we haven't discussed
00:45:13
issues any issue that i think is broadly
00:45:15
relevant to most americans i think this
00:45:17
is one of our worst episodes we're going
00:45:18
to bore everyone to tears i frankly
00:45:20
don't understand what the [ __ ] you're
00:45:21
doing i don't even know why we have a
00:45:22
topic list when you start pulling it out
00:45:24
of your ass like dolls and i don't know
00:45:26
what the [ __ ] else all right all right
00:45:28
fine we'll talk about politics i thought
00:45:29
the dow question sucked all right i'm
00:45:32
just giving you the opportunity
00:45:36
that we shouldn't even be talking about
00:45:37
cut it out of the show this whole
00:45:39
episode should be cut jesus christ
00:45:43
episodes
00:45:44
yeah i agree i think we should cut all
00:45:45
that it's going great
00:45:47
what do you know jason
00:45:48
jason i agree that that part where we
00:45:50
cut it that's all right fine you got
00:45:52
some [ __ ] loser i'm trying to give
00:45:54
you guys the benefit of the doubt to
00:45:56
just because it was like no one cares
00:45:58
all right fight calm down everybody you
00:46:00
want to talk about politics we talk
00:46:02
about politics okay saks go ahead tell
00:46:04
us about the election okay i'll just
00:46:05
rattle off some of the key results here
00:46:07
from blue states we have a woke lash
00:46:09
going on all across the country that's
00:46:12
the important thing
00:46:13
in virginia a state that biden one by
00:46:16
ten he's cranking a huge upset
00:46:17
republican glenn younkin beat terry
00:46:19
mcauliffe a former governor there he was
00:46:22
this was a huge upset mcauliffe was
00:46:23
supposed to win younkin won
00:46:26
51-48 so that's a
00:46:29
13 point swing
00:46:31
uh versus where biden was
00:46:34
just a year ago in new jersey a state
00:46:36
that biden won by 16 points the democrat
00:46:38
held on to it but only by 1.5 points and
00:46:41
i bet you anything the rnc is kicking
00:46:43
itself they didn't give any money to
00:46:45
chaturelli who's the challenger who i
00:46:47
think almost became very very close
00:46:50
and there were
00:46:51
down ticket seats that
00:46:53
went republican so the the um
00:46:57
this is really interesting in
00:46:59
south jersey which is a blue-collar
00:47:01
bastion for democrats sweeney versus
00:47:03
burr that's right the democratic state
00:47:05
senate leader steve sweeney lost to a
00:47:07
truck driver named ed durr who spent a
00:47:10
grand total of 153 dollars on his
00:47:12
campaign
00:47:13
okay so those were some and then we had
00:47:15
someone say write in like he was
00:47:17
printing on others to say write me in i
00:47:19
think i don't think he's a writer but
00:47:21
but any event so so implications for
00:47:23
2022 dave wasserman of cook political
00:47:25
report calculates somewhere between a 44
00:47:28
and 51 c game from the gop they only
00:47:31
need five seats to win the majority so
00:47:33
it's looking very bleak for the
00:47:34
democrats in 2022 and then i think you
00:47:37
also had some very interesting local
00:47:39
elections in minneapolis voters rejected
00:47:42
a proposal to defund the police with 56
00:47:45
percent of the vote
00:47:46
uh they there was a ballot proposition
00:47:49
to change the police department into
00:47:51
some sort of larger public safety group
00:47:53
voters were having none of it
00:47:56
in seattle which is a very liberal city
00:47:58
they voted for a literal republican as
00:48:01
city attorney which is the office that
00:48:03
prosecutes misdemeanors so
00:48:06
against a police abolitionist who said
00:48:08
she would stop prosecuting misdemeanors
00:48:11
you're forgetting that in virginia it
00:48:12
wasn't just glenn younkin that won but
00:48:14
basically it was terry mcauliffe
00:48:17
and then a lieutenant governor who is
00:48:19
some milk toast individual
00:48:21
and an attorney general candidate who
00:48:24
was caught in blackface
00:48:26
which by the way there is no more racist
00:48:28
thing you can do just to let you guys
00:48:30
let
00:48:31
everybody in
00:48:32
all the non-colors okay that guys please
00:48:35
don't do blackface or brown face it's
00:48:36
such a bad it's it's not it's not you're
00:48:38
right it was a sweep so the lieutenant
00:48:40
and
00:48:40
junkin and it was a it was a black
00:48:42
female lieutenant governor and a latino
00:48:44
attorney general that's right and they
00:48:46
swept right so that's right that's right
00:48:48
so the lieutenant governor was winston
00:48:49
sears uh she's a a black woman
00:48:52
republican if you've seen the photo of
00:48:54
her she's frequently photographed with a
00:48:55
giant assault rifle in her hands uh
00:48:58
that's her and then the hispanic
00:49:00
attorney general jason miyari's uh one
00:49:03
as well so yeah it was a huge sweep
00:49:06
and then you know in long island and
00:49:07
staten island which again are blue
00:49:09
counties you had two republican
00:49:11
prosecutors
00:49:12
beat the local sort of incumbent
00:49:15
democrat decarceration
00:49:17
rad just i think i think this is very
00:49:19
clear
00:49:20
which is um
00:49:23
trump was
00:49:24
behaviorally extreme and after four
00:49:27
years people were sick of it
00:49:29
nobody wanted that behavioral extremism
00:49:31
because it was unpredictable and people
00:49:33
felt frankly in danger and i think that
00:49:35
that was legitimate he also turned out
00:49:37
to be extremely lazy and probably pretty
00:49:39
dumb
00:49:41
now what we're realizing is the
00:49:43
different form of extremism which is
00:49:44
policy extremism will also be met with
00:49:47
the same response which is that you you
00:49:48
can't sustain election results and wins
00:49:51
right so people care consistently
00:49:53
about three things they care about the
00:49:55
economy
00:49:56
they care about the education of their
00:49:58
children and they care about safety
00:50:01
and the thing that glenn younkin did
00:50:03
which i thought was
00:50:06
at least a playbook for
00:50:08
centrists and the right and it's also a
00:50:10
playbook for the democrats if they
00:50:12
choose to embrace it is to understand
00:50:14
that these things are reaching a tipping
00:50:16
point where you know again we've said
00:50:18
this before
00:50:19
it is possible to live in a state of
00:50:21
mind where you believe in black lives
00:50:23
matter and you believe in law and order
00:50:26
right
00:50:27
and and when you try to pit those two
00:50:29
things against each other for example
00:50:31
like you would have thought the one
00:50:32
place
00:50:33
where they would have basically defunded
00:50:35
the police in its entirety would have
00:50:37
been minneapolis after george floyd but
00:50:39
instead even they drew the line and said
00:50:41
no
00:50:42
or new york
00:50:44
or new york there was a there was a
00:50:45
really compelling quote actually by this
00:50:47
woman i think it was in the new york
00:50:48
times um
00:50:50
and what she said was i didn't elect joe
00:50:52
biden to be fdr i elected him to tack to
00:50:56
the middle and just calm things down so
00:50:58
that everybody could exhale so that we
00:51:01
could reset same with me and what's up
00:51:03
that was abigail spamberger actually
00:51:05
she's a virginia democrat yeah she's a
00:51:07
virginia democrat who won a seat in one
00:51:09
of those blue counties that just flipped
00:51:11
red to vote for yunkan and since she got
00:51:14
elected i guess she got elected last
00:51:16
year she's been telling the democratic
00:51:18
party she's the one who called out
00:51:19
pelosi
00:51:20
in that you know caucus meeting saying i
00:51:23
don't ever want to hear the words defund
00:51:24
the police again that is electoral
00:51:25
poison and then she said yes nobody
00:51:28
elected biden to be fdr they elect him
00:51:29
to be normal and stop the chaos
00:51:32
and so certainly my vote yeah yeah
00:51:34
there's a big backlash going on because
00:51:36
biden has decided to start governing
00:51:37
like bernie sanders no one elected him
00:51:39
to do that so sax is the lesson dems
00:51:43
learned this time around is it's very
00:51:45
easy to beat
00:51:46
trump but it's very hard to beat a
00:51:48
moderate republican
00:51:50
no no it's not that it's that you just
00:51:52
have to be a rational normal person
00:51:54
that's what i mean by a moderate
00:51:56
republican well you just have to be
00:51:58
moderate i don't think it matters when
00:51:59
this is but this is the key to the
00:52:01
condems it was so easy for them to use
00:52:03
trump
00:52:04
you know but these three topics are not
00:52:06
a republican tent pole nor are they a
00:52:08
democratic temple they are the tentpole
00:52:11
of reasonable people yes meaning which
00:52:13
most people are reasonable hey guys get
00:52:15
out of the way so that we can you know
00:52:17
have a reasonable life in an economy
00:52:19
hey folks please make sure my kids when
00:52:21
i send them to school for eight hours a
00:52:23
day come back reasonably educated and
00:52:25
please keep my streets safe and i'm not
00:52:27
really willing to decarcerate
00:52:29
ad hoc to such a degree that all of a
00:52:31
sudden crime gets out of control those
00:52:33
are not democratic or republican tent
00:52:35
poles those are just moderate centrist
00:52:37
rational things to believe in yeah being
00:52:39
and also behave normally like i i think
00:52:42
whatever happened with these progresses
00:52:43
where they couldn't pass you know the
00:52:45
stimulus bills and things that almost
00:52:47
everybody agreed on glenn younkin was
00:52:49
not behaviorally extremist yes and and
00:52:53
from a policy perspective was pretty
00:52:55
much down the middle eric adams eric
00:52:58
adams is not behaviorally extreme and he
00:53:01
is politically down the middle the mayor
00:53:03
of buffalo who got reelected is not
00:53:05
behaviorally extreme and he's
00:53:08
politically down the middle do you start
00:53:09
to see a pattern here yeah nobody wants
00:53:11
aoc bernie elizabeth warren or trump i
00:53:15
think it's not it's not a question of
00:53:16
aoc or bernie or trump it's just that
00:53:18
right now
00:53:19
the temperature of america is let's just
00:53:22
all exhale and just re-center ourselves
00:53:25
as a country yeah and so moderation and
00:53:28
centrism is actually what calls for
00:53:30
today i don't know how to predict what
00:53:32
happens in 15 or 20 years and maybe aoc
00:53:34
is the canary in the coal mine for where
00:53:37
the country goes by a plurality of
00:53:39
people in 15 or 20 years but what's
00:53:42
clear is it's not where it goes today
00:53:44
and i think that we it all behooves us
00:53:46
to just take a real step back and exhale
00:53:48
and just read the tea leaves because
00:53:50
every single thing
00:53:52
that the democrats tried to do to sort
00:53:54
of like make this extreme really didn't
00:53:56
work the race-baiting all of that stuff
00:53:58
really kind of failed and i think that
00:54:00
that's important to listen to you know
00:54:03
because you had a lot of black indian
00:54:05
chinese families that just showed up
00:54:07
hispanics
00:54:08
you know that again reliable democratic
00:54:11
voters
00:54:12
and voted for glenn younkin in a way
00:54:14
that was surprising to me right and then
00:54:17
so if you compare new jersey and and um
00:54:20
virginia
00:54:21
biden won virginia by 10.
00:54:25
he the the democratic nominee lost biden
00:54:28
won new jersey by 16
00:54:31
and phil murphy barely sweeped by it was
00:54:33
like 10 000 votes here she's always had
00:54:35
a a republican kind of uh leaning group
00:54:38
uh they're very uh tuned in one by 16.
00:54:41
this should have been a cakewalk yeah
00:54:42
but i think that's 16 how much of that
00:54:44
is get trump out of office is what we i
00:54:47
think the democrats need to parse
00:54:50
we're repudiating behavioral extremism
00:54:53
and policy extremism so i think we just
00:54:55
need to realize
00:54:56
rational normal chill people
00:54:59
who can do reasonable things get our
00:55:01
kids educated so for example on the
00:55:03
education front
00:55:04
i don't know if you guys saw this
00:55:05
because i tweeted and you can put this
00:55:07
nick in the group chat but in california
00:55:09
right now there's a battle over math
00:55:11
class ridiculous right where the title
00:55:14
i'm just going to read the title because
00:55:15
it sets it up california tries to close
00:55:17
the gap in math but sets off a backlash
00:55:19
proposed guidelines in the state would
00:55:21
de-emphasize calculus
00:55:23
reject the idea that some children are
00:55:25
naturally gifted
00:55:27
and build a connection to social justice
00:55:29
critics say math shouldn't be political
00:55:32
well of course the way that those
00:55:34
articles are always written it's always
00:55:35
about the backlash you know they don't
00:55:37
talk about what what the people in
00:55:39
charge are trying to do to basically
00:55:41
degrade the curriculum of course there's
00:55:42
a backlash because parents don't like
00:55:44
what the people on these school boards
00:55:45
are doing this was the sleeper issue in
00:55:48
virginia was the school board issue you
00:55:50
had
00:55:52
you know parents were already angry that
00:55:53
the teachers unions had kept the schools
00:55:55
close for a year and a half during covet
00:55:57
and while their kids were at home you
00:56:00
know work doing classes over zoom
00:56:02
parents got a good look at what some of
00:56:03
their kids were learning and then like
00:56:05
what they saw i mean we're talking about
00:56:07
lessons plans that incorporated crt
00:56:09
and you know the 16-19 project view of
00:56:12
america singling out kids by their race
00:56:14
making them focus on difference and then
00:56:16
there were some you know rather explicit
00:56:19
materials at young grade levels about
00:56:21
you know lgbt issues and so this led to
00:56:24
a whole bunch of confrontations that
00:56:25
school board memes were parents of all
00:56:27
races
00:56:28
objected to you know the lease lesson
00:56:31
plans for for their kids and the school
00:56:33
boards and administrators just dismissed
00:56:35
their complaints out of hand and you
00:56:37
know their message was we're not
00:56:38
teaching cr teacher kids uh but if we
00:56:41
were it's a good thing and only white
00:56:42
supremacists would object
00:56:45
so you know that was sort of what was
00:56:47
happening in the background and then
00:56:48
mcauliffe comes along and makes this
00:56:50
gigantic gaffe
00:56:52
in the last debates about two weeks
00:56:53
before the election where he says i
00:56:55
don't think parents should be telling
00:56:56
the schools what to teach
00:56:58
and what yes this is the customer
00:57:01
no he said that he said that on a debate
00:57:03
and he said that debate about two weeks
00:57:04
for the election mcauliffe was leading
00:57:06
through this whole thing until that
00:57:08
debate
00:57:09
where and this was sort of a kinsley
00:57:10
gaffe in the sense that you know michael
00:57:12
kinsley set a gaffe is when a candidate
00:57:14
inadvertently uh
00:57:16
says something true you know this is
00:57:17
mccalla's view is that the teachers
00:57:19
union should be controlling the schools
00:57:21
not the parents well
00:57:22
um
00:57:24
yes so this is what yanking uh jumped
00:57:26
all over all of his ads in the last
00:57:28
weeks of the campaign really focused on
00:57:31
this issue
00:57:32
you know poured gasoline on a fire and
00:57:34
then the most tone-deaf thing mcauliffe
00:57:36
did is he had randy weingarten who was
00:57:38
the head of the the big teachers union
00:57:41
come in and campaign for him at the 11th
00:57:42
hour well of course that's not going to
00:57:44
save him because people are sick and
00:57:45
tired of the teachers unions so you know
00:57:49
this was basically the big sleeper issue
00:57:51
crt and the schools
00:57:53
in virginia
00:57:55
and
00:57:56
you know this is this i think
00:57:58
specifically is what the democratic
00:58:00
party has to wake up to is that these
00:58:01
progressive ideologies are not popular
00:58:04
the other thing i'll say about glen
00:58:05
yonkin is that this is another thing
00:58:07
that the that the republicans should
00:58:09
hopefully pay attention to which is
00:58:12
you can look normal act normal
00:58:15
be normal
00:58:17
you know this is not an extremist in any
00:58:18
way this guy was the co-ceo of carlisle
00:58:21
which is a huge and very successful
00:58:23
private equity firm so this is a very
00:58:25
rational reasonable person who um
00:58:29
you know didn't embrace anything that
00:58:31
was really that pro-trump
00:58:33
and that should be a real wake-up call
00:58:35
to the republicans which is hey let's
00:58:37
just run a fleet of normal people i
00:58:39
think what you saw i think chamath is
00:58:41
right that what you saw in virginia is
00:58:43
that the playbook that gavin newsom just
00:58:45
used to defeat the recall in california
00:58:47
did not work
00:58:49
in virginia which is he tried to
00:58:52
paint yunkan as a trump proxy
00:58:55
and young can very definitely you know
00:58:58
avoided that he got trump's yes he got
00:59:00
trump's endorsement but very early in
00:59:02
the process he did not have trump come
00:59:04
to the state
00:59:05
um and you'd have to say it also helped
00:59:07
younken a lot that social media that
00:59:09
trump wasn't all over social media
00:59:10
because he's been banned
00:59:12
so you know in a weird way facebook and
00:59:14
twitter deserve an assist here
00:59:16
because they help keep trump out of the
00:59:18
virginia race
00:59:19
so you know this playbook that that
00:59:22
newsom defined that would work very
00:59:23
effectively from california which is
00:59:25
simply to keep running against trump i
00:59:27
think democrats thought they'd be able
00:59:28
to win elections for years based on that
00:59:30
that playbook didn't even last two
00:59:32
months so you know so i think
00:59:35
democrats are gonna have to find a new
00:59:37
playbook here
00:59:38
okay so friedberg on this california
00:59:40
issue around education one of the key or
00:59:43
most controversial
00:59:45
concepts is detracting in other words
00:59:48
instead of having high performing
00:59:49
students go to a high performing track
00:59:51
and then everybody else stay behind
00:59:53
maybe keep in not all cases but keep
00:59:55
some of the students together because
00:59:57
there is some research that shows if
00:59:59
done right
01:00:00
if you track people together the higher
01:00:03
performing students will pull up the
01:00:05
ones who are slightly behind other
01:00:07
people say we're basically
01:00:10
uh throttling people who could be the
01:00:11
next einstein or the next world-class
01:00:14
leader in science math etc uh any
01:00:17
thoughts on the concept of detracting
01:00:19
since i'm assuming you were
01:00:20
in the high-speed track in science and
01:00:23
math
01:00:25
maybe we should get rid of like jv and
01:00:28
varsity sports teams as well and you
01:00:31
know triple a baseball and major league
01:00:33
baseball as well and you know any
01:00:35
distinction of performance um or
01:00:38
exceptionalism goes away
01:00:41
you know and and that is kind of the the
01:00:43
key
01:00:44
social question is are we going to give
01:00:46
up exceptionalism
01:00:48
um to minimize uh the distance uh
01:00:51
between the exception on the average and
01:00:53
that seems to me if it makes people it
01:00:55
makes people feel bad but i've said this
01:00:57
point before you know we're doing it
01:00:59
when we try and think about you know the
01:01:00
billionaire attacks or what have you
01:01:02
as soon as you start to limit progress
01:01:05
um you
01:01:06
reduce inequality
01:01:08
but you limit progress and the same will
01:01:10
be true not just in science not just in
01:01:13
business
01:01:14
uh but also in sports and athletics and
01:01:17
um and any other kind of system
01:01:19
where you will have exceptionalism you
01:01:21
will have an average you will have a
01:01:23
distribution
01:01:24
amongst human performance and as soon as
01:01:27
we try and limit the difference in that
01:01:29
distribution
01:01:30
um we move the entire curve to the left
01:01:34
here's the uh counterfeit bird
01:01:37
what some studies have shown is yes you
01:01:39
will uh throttle the high performers but
01:01:42
we're seeing uh along race lines certain
01:01:44
demographics being left behind other
01:01:46
ones excelling
01:01:48
and that you can get yeah it's an ethics
01:01:50
and values question right like do you
01:01:52
think that individual freedom and the
01:01:53
opportunity to pursue your opportunity
01:01:56
your your exceptionalism
01:01:58
um should be taken away from you such
01:02:01
that others who aren't as exceptional as
01:02:03
you
01:02:04
are given um you know greater progress
01:02:06
than they would have had on their own um
01:02:08
and that's the key crux of what all of
01:02:10
these social systems are grappling with
01:02:12
whether it's in sports or business or
01:02:14
finance or or um
01:02:16
or education is what's the right thing
01:02:19
to do and that ethics question is going
01:02:22
to be defined by the social agenda of
01:02:23
the moment and you know the means of the
01:02:25
moment and what we all think is is the
01:02:27
right thing to do and it's different all
01:02:28
over the world and it's different within
01:02:30
political systems but it's a very
01:02:32
divisive point
01:02:33
that i think folks who find themselves
01:02:35
on one end of that exceptional spectrum
01:02:37
in different aspects are going to have
01:02:39
one point of view and folks on the other
01:02:40
end of that exceptional spectrum are
01:02:42
going to have other points of view and
01:02:43
everyone's going to be sensitively tuned
01:02:45
to where they fall in that spectrum i
01:02:46
will say one thing though
01:02:47
on that spectrum exceptionalism is rarer
01:02:51
than the average therefore it is likely
01:02:53
the case that over the next years and
01:02:55
decades we will see
01:02:56
the um the idea that we should remove
01:02:58
exceptionalism in business and
01:03:00
exceptionalism and education and
01:03:01
exceptionalism in sports
01:03:04
because it benefits the majority
01:03:06
and um and no one kind of recognizes and
01:03:09
a lot of folks don't recognize the
01:03:11
progress that is made by exceptionalism
01:03:13
and um and that's and then we're gonna
01:03:15
wake up one day and be like oh wait a
01:03:17
second we don't have the the best sports
01:03:19
teams winning all the gold medals we
01:03:20
don't have the smartest kids we don't
01:03:22
have the best businesses china and
01:03:24
europe and brazil and whoever else the
01:03:26
emerging markets are gonna india are
01:03:28
gonna start to have them such a good
01:03:29
point i think this is a very old debate
01:03:32
it's the debate between a quality of
01:03:33
opportunity and a quality of results
01:03:35
yeah and the progressive left is
01:03:37
absolutely obsessed with a quality of
01:03:40
results or outcomes which they now call
01:03:42
equity which is we're going to take
01:03:44
people at the finish line and we're
01:03:45
going to move them around we're going to
01:03:47
redistribute the outcomes to achieve a
01:03:50
more proportional representation or
01:03:51
something more fair as opposed to
01:03:54
giving everybody as much opportunity at
01:03:57
the outset as possible that is the
01:03:59
fixation right now that is why they're
01:04:01
taking out advanced math in the schools
01:04:03
they're trying to level people it's not
01:04:05
going to work it doesn't lead to a more
01:04:07
we want to have an exceptional society
01:04:09
where i think we should be focusing is
01:04:10
creating as much opportunity for
01:04:11
everybody the way to do that would be to
01:04:13
let every child go to the school of
01:04:16
their choosing so that we would stop
01:04:18
trapping kids in bad schools but back to
01:04:21
kind of to bring this back to the
01:04:22
election for a second because i think it
01:04:24
was a very clear repudiation of this
01:04:26
progressive mindset and i think there's
01:04:28
essentially two sets of reactions to it
01:04:31
if you look at sort of all the left-wing
01:04:33
commentators the the one who i thought
01:04:35
seemed to
01:04:37
get
01:04:37
it the most was cnn's uh van jones
01:04:41
actually had i thought you know
01:04:44
a rare moment of introspection where he
01:04:45
said this was the the results were a
01:04:48
five alarm fire he said it was a big big
01:04:50
wake-up call for the democrats to stop
01:04:52
annoying voters with woke hectoring
01:04:54
um he actually advised biden to start
01:04:56
triangulating against awoke left in the
01:04:59
way that bill clinton did i mean which
01:05:01
is something that i've been suggesting
01:05:02
on this pod so you're saying something
01:05:04
super important the game theory now is
01:05:06
for biden to put to the test
01:05:09
the progressive left because now he can
01:05:11
go firmly to the center
01:05:13
and he can put all of the pressure
01:05:16
on the progressive left in the house and
01:05:19
uh warren and
01:05:22
bernie sanders in the senate well he's
01:05:24
right that's the first thing he should
01:05:25
do is he should
01:05:27
he should pull a sister soldier on
01:05:28
bernie sanders he can't keep delegating
01:05:31
the domestic agenda to bernie sanders he
01:05:34
if he wants to save his presidency he'll
01:05:35
start triangulating in the way that bill
01:05:36
clinton did i'm not sure he's going to i
01:05:39
think there's already a misperception
01:05:41
that the reason why they lost selection
01:05:43
is because they didn't deliver the
01:05:45
goodies in this house reconciliation
01:05:48
bill um that in other words i don't
01:05:50
think the public cares about the goodies
01:05:52
i mean they care about this normalcy and
01:05:53
centrism yeah there there's a part of
01:05:55
the democratic base that does want the
01:05:57
what's in that house reconciliation bill
01:05:59
but but here's the thing democratic
01:06:01
turnout in this election was extremely
01:06:03
high the democratic turnout for
01:06:05
mcauliffe was higher
01:06:07
than the democratic turnout four years
01:06:09
ago for the democrat who won
01:06:11
the turnout that
01:06:12
in new jersey was higher than what
01:06:14
murphy got four years ago when he won
01:06:16
the problem that democrats have is that
01:06:18
republican turnout was extremely high
01:06:20
even without trump showing that trump
01:06:22
doesn't matter that much
01:06:24
to turn out and the independence came
01:06:26
out in a big way for republicans so this
01:06:29
idea that democrats can just win
01:06:32
elections by delivering
01:06:33
you know programs for their base
01:06:36
that's not going to work so i think
01:06:38
that's a misperception i think van jones
01:06:40
has the right idea they need to
01:06:41
triangulate but you turn the channel to
01:06:43
msnbc and they were just blaming the
01:06:45
whole thing on white supremacy basically
01:06:47
hysterical um just on the de-tracking
01:06:49
thing this shows to me a severe lack of
01:06:52
creativity
01:06:53
you if you look at what happened in the
01:06:55
nba they had this developmental league
01:06:57
which they didn't kind of run then
01:06:58
became the g league they now have the
01:07:00
ability to bring players fluidly
01:07:02
from the warriors g league team up to
01:07:04
the warriors or the next team up to the
01:07:06
knicks what this means is
01:07:08
you don't have to say there's two
01:07:09
different tracks
01:07:10
and the the two never shall meet in the
01:07:13
season they can move up and down in math
01:07:15
a very easy solution to this would be to
01:07:18
have the high track for high performers
01:07:20
have the regular track and then spend
01:07:22
with all this money we have say hey
01:07:24
every school is going to be open from
01:07:25
three to five o'clock four days a week
01:07:27
if anybody wants to
01:07:29
attempt to get into a higher track of
01:07:31
math just stay after school for two
01:07:34
hours anybody can go and get one-on-one
01:07:35
tutoring and just don't change the
01:07:37
number of teachers the whole country
01:07:40
wants excellence they don't want
01:07:42
leveling they don't want equity they
01:07:43
don't want a quality of results they
01:07:44
want to have a quality volunteer david
01:07:47
wants people to move up they do want to
01:07:48
see that's true and brown students and
01:07:51
immigrants do better at math that's what
01:07:53
you're missing yes and that's about a
01:07:54
quality of opportunity absolutely no
01:07:56
it's not just about equal opportunity
01:07:57
they're so far behind statistically that
01:08:00
you need to do something new what we're
01:08:01
doing is not working david that's why
01:08:03
people are picking this bad
01:08:05
they're
01:08:06
they are eliminating advanced math
01:08:09
because they don't want to actually look
01:08:10
at the the problem what do you see the
01:08:12
problem is well if there's another
01:08:14
performance a certain group then you
01:08:15
should work harder to raise them up not
01:08:17
eliminated
01:08:18
give me a suggestion it's charters and
01:08:21
school choice
01:08:22
okay look i mean if you're if you if
01:08:24
you're gonna define structural racism as
01:08:27
conditions that that trap people of
01:08:29
color in poverty across generations
01:08:31
seems like a pretty fair definition then
01:08:33
you have to say the number one cause of
01:08:35
structural racism is the school system
01:08:38
school system education yeah it's the
01:08:39
school system because we know poor kids
01:08:42
are trapped in schools that aren't very
01:08:43
good why because they're controlled by
01:08:45
the education unions they don't have
01:08:47
your choices
01:08:49
so who is making that argument uh on the
01:08:51
on the side of the left no one why
01:08:53
because everyone knows the unions
01:08:55
especially the education unions are the
01:08:57
number one donor to the democratic party
01:08:58
so the democrats won't even look at this
01:09:00
problem although this is the way
01:09:02
white supremacy could build their base
01:09:04
is by saying we want to fix education
01:09:07
that would be if you've seen education
01:09:09
what do you think young industry in
01:09:10
virginia by the way 55
01:09:12
of hispanics in virginia voted for
01:09:14
yunkan so minorities are shifting on
01:09:17
this
01:09:18
issue and school choices
01:09:22
these are the new quality of life issues
01:09:24
if yunkan has a a good four years in
01:09:26
virginia he can run for president and
01:09:28
crush this thing can i show you just one
01:09:30
one chart and then we can get off the
01:09:31
politics thing which is it was this
01:09:33
chart from this guy patrick uh raffini
01:09:36
who's a pollster and i think it really
01:09:38
illustrates the problem that progresses
01:09:40
the democratic party
01:09:41
for the listener okay so
01:09:43
what this chart shows
01:09:45
is
01:09:46
it basically shows where the democratic
01:09:49
the democratic party is and the senate
01:09:50
republican party is in relation to the
01:09:53
center of the country okay and basically
01:09:55
as you'd expect in a democracy whichever
01:09:58
party is closer to five wins okay so
01:10:01
in 1994 when bill clinton was president
01:10:04
the democratic party the center of it
01:10:06
was smack dab as five the republicans
01:10:08
weren't that far away they were six so
01:10:10
the party even though there is a lot of
01:10:12
partisan warfare the
01:10:15
the political differences actually
01:10:16
weren't that great and clinton i think
01:10:19
more accurately found that dead center
01:10:21
okay fast forward to 2004. so george w
01:10:24
bush is president now the democrats are
01:10:26
at four republicans are at five that's
01:10:28
why republicans won okay now go to 2017
01:10:32
these poll numbers he did and this is a
01:10:34
few years ago the democrats are all the
01:10:36
way at two
01:10:38
okay and the republicans are at six and
01:10:39
a half so it's true that both parties
01:10:42
have moved away from the center but
01:10:44
republicans are one and a half points
01:10:45
away from the center whereas democrats
01:10:47
are three points away so the democrats
01:10:49
have actually moved further away from
01:10:51
the center if you look at who are the
01:10:53
activists in the democratic party who is
01:10:55
the base who is the energy who does all
01:10:57
the work who does the contributions it
01:11:00
is the progressives right this is why
01:11:02
mcauliffe ran as mcauliffe is not a
01:11:04
progressive he was the clinton democrat
01:11:07
you know going way back to the 90s okay
01:11:09
he was bill clinton's you know uh
01:11:11
right-hand man in the party back in the
01:11:13
90s but he nevertheless ran
01:11:15
as a progressive in virginia who
01:11:18
supported the teachers unions why
01:11:20
because he was appealing to the base of
01:11:21
the party gavin newsom did the same
01:11:23
thing in california gavin was never a
01:11:25
bernie bro i mean he's always been
01:11:27
liberal but he he has moved very far
01:11:29
left and biden has moved very far left
01:11:32
as president why is that because the
01:11:34
base of the party has moved very far
01:11:36
left so unless that gets fixed i see
01:11:40
maybe it's going to the party's base but
01:11:42
not the countries exactly so you're
01:11:44
going to need a strong democrat who can
01:11:46
basically give the heisman to that part
01:11:49
of the base
01:11:50
or they're going to keep losing
01:11:52
elections i think this could be a
01:11:53
republican decade i know it doesn't seem
01:11:55
like it right now because you had trump
01:11:57
and the republicans lost but look how
01:11:59
quickly the republicans turned around
01:12:01
their electoral fortunes so with trump
01:12:02
on the sidelines then that's just a huge
01:12:07
trump is the nominee in 2024 all bets
01:12:10
are off but in 2022 he's not the nominee
01:12:12
he's still
01:12:13
censored from social media
01:12:15
he's really nowhere in sight and people
01:12:18
people have a very short um memory it
01:12:21
turns out they've moved on very quickly
01:12:24
young can check the box because he felt
01:12:26
he had to to get the nomination and to
01:12:28
run on the republican
01:12:29
platform but then you think yunkan's
01:12:32
going to talk to trump once no
01:12:34
not once and i think and i honestly
01:12:36
think this election is going to help
01:12:38
republicans move past trump because what
01:12:40
republican believes in um
01:12:42
in like that the electoral system is
01:12:44
rigged now
01:12:45
right i mean all these blue cities and
01:12:47
states just delivered big results for
01:12:49
republicans so where exactly is the
01:12:51
ballot stuffing where exactly
01:12:53
is the stall where are the stolen
01:12:55
elections that's going to that's going
01:12:56
to stop now too they're going to stop
01:12:57
it's going to stop overnight right
01:12:58
because i mean by the way kristen cinema
01:13:01
probably knows this like you know the
01:13:02
the the funny thing about all of this is
01:13:04
when peter thiel put in 10 million
01:13:06
dollars into this pack for blake masters
01:13:08
who used to work for him and said you
01:13:10
know in arizona i'm going to run this
01:13:12
guy against you cinema attacked heart to
01:13:14
the center
01:13:16
instantly
01:13:17
so she she knew too yeah well so so just
01:13:20
this small point of course so blake is
01:13:21
running against uh the other guy um the
01:13:24
astronaut guy i'm spacing on his name
01:13:26
but but yeah but but cinema is up so to
01:13:28
speak uh in the next election cycle so
01:13:30
she got a little bit more time but
01:13:32
you're right like cinema is attuned and
01:13:34
mansion is attuned there are some of the
01:13:36
few democrats that are attuned to where
01:13:39
the center of the country is you heard a
01:13:41
mansion in the wake of this election
01:13:42
said this is a center-right country
01:13:44
these guys better wake up um you know
01:13:46
they should really now look i think i
01:13:48
think what's going to happen in the wake
01:13:49
of this election is
01:13:51
that this infrastructure bill is going
01:13:52
to sail through because one of the
01:13:54
crazier things that the progressives
01:13:55
were doing was holding that bill hostage
01:13:57
it might have helped mcauliffe i don't
01:13:59
think would a i don't think mcauliffe
01:14:00
would have won but it might have helped
01:14:02
him by a point or two if they had gotten
01:14:03
that infrastructure bill done because a
01:14:05
lot of those programs are going to be
01:14:06
popular in a state like virginia okay
01:14:09
but i mean but but i think that you know
01:14:11
this house reconciliation bill they just
01:14:13
seemed hell-bent on jamming it through
01:14:14
with all these tax increases
01:14:16
i don't think that's not popular you
01:14:18
know what the big issue in new jersey is
01:14:20
for them yeah one of the big issues in
01:14:22
new jersey where you almost had this
01:14:23
upset within one point was taxes you
01:14:26
know um there was a a gaffe by murphy
01:14:30
who said something like you know he said
01:14:32
he said that if if taxes are someone's
01:14:34
chief concern he said quote maybe we're
01:14:36
not your state can you imagine that wow
01:14:38
and he almost lost the election because
01:14:41
of that so i don't think all these big
01:14:43
tax increases are what the country wants
01:14:45
and you know if biden insists on
01:14:47
allowing
01:14:48
bernie to dominate the agenda and warren
01:14:51
i think it's gonna you're gonna see
01:14:53
40 to 50 seat losses by the democrats in
01:14:56
2022
01:14:57
okay moving on to our final topic crazy
01:15:00
update out of china a research team
01:15:03
has developed a method of converting
01:15:06
carbon dioxide into starch science
01:15:08
magazine published this paper
01:15:10
from a research team 100 grams of
01:15:12
catalysts converting 5 grams of co2 per
01:15:15
hour into starch
01:15:18
and freeberg i'm sure you tweeted that
01:15:20
this is 10 times more efficient than
01:15:22
corn plants uh what's the impact of
01:15:25
something like this could it hit scale
01:15:27
would it have an impact on food security
01:15:31
carbon
01:15:33
global warming yeah so i tweeted this
01:15:35
paper app because it's just it's a
01:15:37
fantastic demonstration of what's
01:15:39
possible in this new emerging not
01:15:42
emerging it's been around for a long
01:15:43
time but kind of you know in the state
01:15:45
of art in um in biomanufacturing
01:15:48
you know photosynthesis is the system by
01:15:51
which most starch is produced on planet
01:15:53
earth today that is plants convert
01:15:55
sunlight
01:15:56
and use water and carbon dioxide to make
01:15:59
uh starches and starches um and
01:16:02
sugars which are what carbohydrates are
01:16:04
account for 60
01:16:06
of human calories and we get all those
01:16:08
calories from rice wheat potatoes which
01:16:10
you know are grown on about 60 of our
01:16:12
acres uh that we farm on planet earth
01:16:15
so you know in in plants there's a
01:16:17
series of these chemical reactions and
01:16:18
what these guys did is they um
01:16:21
isolated and
01:16:23
created a couple of specific proteins
01:16:26
um which are a class of proteins called
01:16:29
enzymes and what an enzyme is is it's a
01:16:31
protein that can take different
01:16:32
molecules and combine them and re
01:16:34
enforce them to react and make something
01:16:36
new and they identified a couple of
01:16:38
enzymes and engineered a few enzymes and
01:16:40
put them together in a cell-free system
01:16:42
meaning there's no cells involved it's
01:16:44
just a tank with a bunch of fluids in it
01:16:47
and and they stick in some carbon
01:16:49
dioxide that they can suck in from the
01:16:51
atmosphere and they um
01:16:53
they can and they have to drive it with
01:16:54
some hydrogen gas which we can just get
01:16:57
from water
01:16:58
and the system basically converts that
01:17:00
carbon dioxide into starch
01:17:03
which is uh being done at a rate that's
01:17:05
almost 10 times higher than what we see
01:17:06
with
01:17:07
with corn plants so it's it's an
01:17:10
incredible demonstration there's there's
01:17:11
several steps to this system like six
01:17:13
steps
01:17:14
and i did some back of the envelope math
01:17:16
and my back of the envelope math on what
01:17:17
they've demonstrated and by the way
01:17:19
everything they did is publicly
01:17:20
available for reproducibility so people
01:17:23
are going to try and resource
01:17:24
open source so people going to try and
01:17:25
copy this now but my back of the
01:17:27
envelope math
01:17:29
is um you know
01:17:31
this system can produce about 10 grams
01:17:34
of starch per liter per day
01:17:36
which would mean it would take about 2.7
01:17:38
trillion liters
01:17:40
to suck up all of the carbon dioxide
01:17:43
that all of humans are putting in the
01:17:45
atmosphere every year from all of
01:17:46
industry that would require
01:17:48
um about 27 million tanks that are about
01:17:51
40 feet tall and about 8 feet wide
01:17:54
that whole all of those tanks could fit
01:17:55
in an area about 25 by 25 miles you
01:17:58
could attach one nuclear reactor to it
01:18:00
to suck up the uh
01:18:02
the water and convert it into hydrogen
01:18:04
gas and feed the system and those tanks
01:18:07
25 miles by 25 miles would take out all
01:18:10
of the carbon dioxide on planet earth
01:18:13
and convert it into usable starch and
01:18:15
that starts by the way that system could
01:18:16
be tuned not just to make starch for
01:18:18
consumption it could be used to make
01:18:20
biofuels it could be used to make
01:18:22
bioplastics it could be used to make
01:18:24
anything that's hydrocarbon-based
01:18:26
um and so you can kind of think about
01:18:27
this being the entry point to a series
01:18:30
of production systems that we could use
01:18:31
to make stuff why freeberg why did they
01:18:34
open-source it
01:18:35
so they're a research team of scientists
01:18:37
from china and they've been iterating on
01:18:39
this this process
01:18:41
this isn't the only process right and so
01:18:44
what they're showing is that this is
01:18:46
possible
01:18:47
and what i think we will see is a lot of
01:18:49
people rattling their brains now saying
01:18:51
not only do we use proteins and enzymes
01:18:53
that we find in nature but we're going
01:18:55
to start to engineer our own proteins
01:18:57
and our own enzymes that are even more
01:18:58
efficient than what we see in nature and
01:19:01
that's what's starting to happen this
01:19:02
system alone what i just described this
01:19:04
25 mile by 25 mile system which is tiny
01:19:07
is the equivalent of starch production
01:19:09
from 42 u.s corn belts if you took all
01:19:12
the corn growing in the united states
01:19:14
it's 42 times that um is what it would
01:19:16
produce that's my back of the envelope
01:19:17
map of kind of what these guys did
01:19:19
um and so i think what they're showing
01:19:21
is this is what's incredibly yeah yeah
01:19:23
and and the implications we could go in
01:19:25
100 directions and we could talk for an
01:19:26
hour
01:19:27
about what this means and what you could
01:19:29
do with it but i think it it really
01:19:31
catalyzes this point that that that
01:19:34
we're kind of everyone's always like how
01:19:35
are we going to get all this carbon out
01:19:36
of the atmosphere what are we going to
01:19:37
do with this where there's a will
01:19:39
there's a way the science is here today
01:19:42
27 million tanks made out of plastic you
01:19:44
could probably get that stuff produced
01:19:45
you know a couple billion dollars find a
01:19:47
piece of land that's 25 by 25 miles it's
01:19:49
near some water and put a nuclear power
01:19:51
plant there and you could suck up all
01:19:53
the co2 in the atmosphere anybody want
01:19:55
to take anyone would want to take a
01:19:56
guess of how many people on the team
01:19:58
were in advanced math courses
01:20:01
the funny thing about this that i think
01:20:02
is really interesting is that it came at
01:20:04
the same week where we were ending you
01:20:06
know what was this political theater of
01:20:08
cop 26.
01:20:10
you know greta thundberg uh who's
01:20:13
you know how dare you how dare you
01:20:18
she had this very funny comment which is
01:20:19
like uh you know it was a bunch of
01:20:21
corporate nonsense and the same old blah
01:20:23
blah blah what's your description of cop
01:20:25
26. you know we had this great
01:20:28
trickle of like you know agreements
01:20:30
there was like on monday there was an
01:20:31
agreement to stop
01:20:33
deforestation uh and then you realized
01:20:36
it's a non-binding agreement and you're
01:20:37
like oh okay well i guess we're not
01:20:39
gonna stop deforesting we're just gonna
01:20:41
keep you know doing that
01:20:43
and all of this stuff just kind of like
01:20:44
took a lot of my enthusiasm
01:20:47
um and i was a little despondent about
01:20:50
what was going on and then when i saw
01:20:51
this thing i was i was really quite
01:20:53
impressed
01:20:54
i will say that
01:20:55
there's a very tricky thing happening
01:20:57
right now which is that developing
01:20:59
countries basically said listen if you
01:21:01
want us to go after climate change
01:21:03
um we want 1.3 trillion dollars in here
01:21:06
to support us
01:21:07
and so you know the western world will
01:21:09
have to figure out whether we're willing
01:21:11
to pay
01:21:12
you know what is the equivalent of you
01:21:13
know six or seven percent of us gdp to a
01:21:15
whole bunch of other countries every
01:21:17
year
01:21:18
for them to slow down and if we don't
01:21:20
make these payments to india and china
01:21:22
and a bunch of other developing nations
01:21:24
they they have said we're just going to
01:21:26
continue to do what we're going at
01:21:27
here's an idea take half of that money
01:21:28
and put it towards science yeah take
01:21:30
half that money and go build a plant
01:21:32
that uses this system that was just
01:21:34
demonstrated and put it in south texas
01:21:36
and suck up ocean water and convert that
01:21:38
ocean water into hydrogen gas
01:21:40
by the way ocean water can be turned
01:21:42
into hydrogen gas by running electricity
01:21:44
through it so you're putting a nuclear
01:21:45
power plant to make the electricity you
01:21:46
run it through ocean water you create
01:21:48
hydrogen gas you pump it into these
01:21:49
friggin tanks and it sucks up all the
01:21:51
co2 and it makes stuff that humans can
01:21:53
consume and that we can use and suddenly
01:21:55
you have this abundance of material you
01:21:57
have this abundance of food and
01:22:00
you can turn this in jobs and you can
01:22:02
turn this into a lot of different things
01:22:03
and you know this kind of goes to the
01:22:05
point i've been making for a while if we
01:22:06
want to invest in infrastructure this is
01:22:08
the sort of thing that both solves
01:22:10
climate change creates jobs and has
01:22:12
extraordinary economic return potential
01:22:15
built into it so how do you get
01:22:17
politicians re-elected
01:22:19
you know i think the private market may
01:22:21
come after this stuff i'll be honest i'm
01:22:22
you know i'm like i'm talking to people
01:22:24
looking at this being like why don't we
01:22:25
make a plant that we can make biofuels
01:22:26
and bioplastics and food and other stuff
01:22:28
out of this this technique and there's
01:22:30
going to be other iterations of this
01:22:31
technique
01:22:32
um but it's such a no-brainer cost like
01:22:35
a functional prototype of this
01:22:37
like a small prototype nothing right i
01:22:39
mean couple million bucks yeah like
01:22:40
nothing so um
01:22:42
you know the other thing that happened
01:22:43
this week beyond this request for 1.3
01:22:46
trillion dollars is that you know we're
01:22:47
now seriously considering carbon tariffs
01:22:49
and we talked about this on a pod before
01:22:50
but
01:22:52
you know i've said i think this is the
01:22:54
most disruptive thing in the capital
01:22:55
markets and and geopolitics that can
01:22:58
happen in the next 10 or 20 years is an
01:22:59
effective carbon tariff which is to say
01:23:01
that when a good or service
01:23:03
enters the borders of a country
01:23:05
they will levy some tax that they think
01:23:07
represents
01:23:09
its drag on the environment
01:23:12
and so you know the simple example would
01:23:14
be a car you know you make a car you
01:23:16
make a tesla
01:23:18
in texas but the minute it crosses the
01:23:21
border to canada
01:23:23
canada says well here's the true carbon
01:23:25
intensity of this car all of the energy
01:23:27
that you put into the aluminum to the
01:23:29
batteries
01:23:31
you know to the to the buildings where
01:23:33
the engineers sat that were that were
01:23:34
building fsd
01:23:36
and uh you know i'm gonna charge an
01:23:37
eight thousand dollar tax on this car
01:23:40
or iphones coming out of china yeah
01:23:42
that's happening i think that's coming
01:23:44
so i think that you know the combination
01:23:45
of tariffs
01:23:47
and these transfer payments
01:23:49
is going to create a real economic
01:23:50
incentive for folks to make these kinds
01:23:52
of big technological leaps so i'm pretty
01:23:55
bullish on all of that i'm less bullish
01:23:57
on
01:23:58
politicians ability to organize because
01:24:00
unfortunately again this is the first
01:24:01
time i really paid attention to cop
01:24:04
and it just looked like a bunch of
01:24:05
really
01:24:06
you know useless political theater
01:24:08
it's just a lot of political theater
01:24:10
saks does this uh science conversation
01:24:12
about saving the planet do anything for
01:24:13
you would you like to get back i mean i
01:24:14
think it's the way to solve the problem
01:24:16
is you have to figure out new
01:24:18
technologies to actually take carbon out
01:24:20
of the atmosphere because you're not
01:24:21
going to do it through you know these
01:24:23
political
01:24:25
programs i mean
01:24:26
you know china india paying them
01:24:29
and and other developing nations 1.3
01:24:31
trillion a year i mean foreign aid
01:24:33
already is one of the least popular
01:24:35
parts of of the uh government's budget
01:24:38
you're going to now pay 1.3 trillion to
01:24:40
these countries so that they it's
01:24:42
nonsense and you're gonna pay put that
01:24:44
money into our education system nobody's
01:24:46
creating science and technology that
01:24:47
solves the problem nobody's gonna stand
01:24:49
for that yeah and you know the the the
01:24:51
tactical education system right pour it
01:24:53
in
01:24:54
yeah i don't think there's a political
01:24:56
solution to this problem that's gonna be
01:24:57
palatable to people i think it's gonna
01:24:59
have to be solved through new technology
01:25:02
now let me ask you a question freeburg
01:25:03
you said there's a six step process
01:25:06
given your experience building science
01:25:08
and technology products is it possible
01:25:10
for each of those six steps to get but
01:25:13
20 percent more efficient a year
01:25:15
yeah look i mean um i just say that to
01:25:17
describe that there's a series of steps
01:25:19
in the system it you know um but uh at
01:25:22
the end of the day this is a
01:25:23
demonstration of science
01:25:25
that has been you know probably funded
01:25:27
to some small amount but you know if you
01:25:29
start to iterate on this approach and
01:25:31
think big picture and think
01:25:32
infrastructure solution here uh there's
01:25:35
a lot of room for improvement i'm sure
01:25:36
so in other words you're back of the
01:25:38
envelope 25 by 25 mile if this is
01:25:40
getting 50 more efficient 25 more
01:25:43
efficient year over year we could see it
01:25:45
becoming you know uh twice as efficient
01:25:48
every two to three years and your 25
01:25:50
mile might be a five mile radius city i
01:25:52
mean think about going to mars right
01:25:54
what are we going to do in mars we're
01:25:55
not going to grow friggin fields of corn
01:25:57
and grow cows and stuff right you're
01:25:59
going to need a system that literally
01:26:01
takes the molecules that are in the
01:26:03
atmosphere there uses some electricity
01:26:04
that's probably going to be produced by
01:26:06
a nuclear power plant and convert those
01:26:08
molecules into what you want to make and
01:26:09
consume and that's what we can do on
01:26:11
earth today the systems are going to get
01:26:13
better they're going to get cheaper
01:26:14
they're going to get faster and that's
01:26:16
why i'm highly optimistic about
01:26:18
solutions to climate change in the
01:26:19
century it's not about an if it's about
01:26:22
a when and you know the when is going to
01:26:24
be defined by the willpower of how we
01:26:26
are going to allocate our people and our
01:26:27
capital resources to solve these
01:26:29
problems and then your term we have the
01:26:31
tools to do it i love the fact that
01:26:33
we're sort of hitting this fork in the
01:26:34
road where it's like do we just want to
01:26:36
give the money to a bunch of governments
01:26:38
to pretend they're going to solve this
01:26:39
and grifters or do we want to put it
01:26:41
into science technology
01:26:43
innovation and entrepreneurial
01:26:45
entrepreneurship
01:26:46
that execute execute right
01:26:52
yeah let's give it to politicians who
01:26:54
don't know what the [ __ ] they're doing
01:26:55
i mean it really is like when you know i
01:26:57
don't know if you saw elon say like yeah
01:26:59
if you want to solve world hunger can
01:27:01
you make us can you oh my god
01:27:02
let's talk about that that's just so
01:27:04
beautiful i thought that was like the
01:27:05
greatest that's dunk of the week nothing
01:27:07
nothing gets me up in the morning like
01:27:08
funding shenanigans right go ahead jake
01:27:11
out tell the stories i mean just
01:27:12
somebody was like oh elon you know made
01:27:14
more money tesla stocks no not an
01:27:16
article it was an article that was
01:27:17
written sure and then he's like well if
01:27:19
you want to solve world hunger i'm
01:27:20
willing to sell sheriff jason can you
01:27:22
describe it you're doing such a shitty
01:27:23
job today as a moderator what are you
01:27:25
talking about
01:27:26
all i did was put a sis in your hands
01:27:28
you guys dunked everything but dude
01:27:33
yeah uh hey guys and there was an
01:27:35
article
01:27:37
there was an article that was written
01:27:39
that basically said you know um
01:27:42
you know 6.8 billion dollars uh which is
01:27:46
you know what elon made like in a day or
01:27:48
something
01:27:50
could cure world hunger
01:27:52
and
01:27:53
then the head of the you know uh un
01:27:55
world food program retweeted that
01:27:58
again trying to further dunk on elon
01:28:01
and then um
01:28:03
elon responded well if you can just show
01:28:05
me a plan and just please reply online
01:28:06
here on twitter
01:28:08
and it's credible and detailed i'll just
01:28:10
sell
01:28:10
this talk and i'll give it to you
01:28:13
and uh everybody was like oh my god
01:28:15
there was this oh my god moment like wow
01:28:18
can this really happen ending world
01:28:20
hunger sounds like a beautiful idea it
01:28:22
can only only cost
01:28:23
you know 6.8 billion dollars and
01:28:25
obviously it went nowhere because the
01:28:26
guy didn't have a plan and it was just a
01:28:28
complete joke
01:28:30
but that's what happened
01:28:31
yeah and he's like yeah just put all of
01:28:33
your
01:28:34
uh put all of your
01:28:37
expenses out there show us your plan and
01:28:39
it was like oh crickets
01:28:41
nothing all right everybody on behalf of
01:28:44
the dictator chamoth paulie hoppetea the
01:28:46
queen of quinoa the sultan of science
01:28:49
david friedberg and
01:28:51
for the rain man himself reporting from
01:28:54
definitely reporting from yeah he's
01:28:56
reporting from the new york stock
01:28:57
exchange congratulations again my bestie
01:29:00
david sacks on the triumphant ipl of
01:29:03
bird we'll see you all next time on the
01:29:05
allman podcast bye bye
01:29:17
and they've just gone crazy with it
01:29:36
oh
01:29:38
we should all just get a room and just
01:29:39
have one big huge orgy because they're
01:29:41
all just useless it's like this like
01:29:43
sexual tension that they just need to
01:29:44
release
01:29:49
your
01:29:50
feet we need to get
01:29:53
back
