00:00:00
Peter was the person who told me this
00:00:02
really pithy
00:00:05
quote in a world that's changing so
00:00:08
quickly the biggest risk you can take is
00:00:10
not taking any risk this guy is a tough
00:00:13
nut to try to sort of explain changed
00:00:16
money with PayPal was the first outside
00:00:18
investor in Facebook uh back paler which
00:00:21
is I believe they helped find Osama Bin
00:00:23
Laden almost certainly the most
00:00:25
successful technology investor in the
00:00:28
world I don't think the future is fixed
00:00:31
I think what matters is a question of
00:00:32
agency what I think works really well
00:00:36
are sort of oneof A- kind companies how
00:00:39
do you get from Z to one what great
00:00:41
business is nobody building tell me
00:00:42
something that's true that nobody agrees
00:00:44
with you
00:00:45
on all right Peter welcome back it's
00:00:48
good to see
00:00:49
[Applause]
00:00:51
you
00:00:53
um you don't do this too often uh so we
00:00:56
do appreciate it U but when you do do it
00:00:58
you're always super candid and
00:01:00
appreciate that as well you fit right in
00:01:01
here um you're sitting this year's
00:01:04
political cycle out right politics well
00:01:08
no I mean I think this is a question we
00:01:10
all have which is you were very active
00:01:13
um you bet on Jed in a major way um he
00:01:17
delivered today it was a very impressive
00:01:18
uh discussion why aren't you involved
00:01:21
this this cycle where it's very
00:01:23
confounding to us because these are your
00:01:24
guys man how much time do we have
00:01:26
supposed talk about this for two hours
00:01:28
or something um um I I don't know look I
00:01:32
have a lot of conflicted thoughts on it
00:01:34
uh I I am still very strongly prot Trump
00:01:39
Pro uh Pro JD I've decided not to uh
00:01:43
donate any money politically but uh I'm
00:01:45
supporting them in every other way uh
00:01:48
every other way possible uh I you know
00:01:51
uh obviously uh you know I think uh I
00:01:56
think
00:01:57
there's my my pessimistic thought is
00:01:59
that uh Trump is is going to win and
00:02:02
probably will win by a big margin uh
00:02:05
he'll do better than the last time and
00:02:08
it'll still be really disappointing
00:02:09
because you know the elections are
00:02:11
always a relative Choice and then once
00:02:13
someone's president it's an absolute and
00:02:16
they you get evaluated you know do you
00:02:17
like Trump or Harris better and that
00:02:20
seems there seem to be a lot of reasons
00:02:22
you know and that one would be more
00:02:24
anti-h haris than anti-trump let's again
00:02:26
no one's Pro any of these people it's
00:02:28
all it's all negative right um and uh
00:02:31
but then after after they win there will
00:02:33
be a lot of buyers remorse and
00:02:35
disappointment that's sort of that's
00:02:36
sort of the arc that I I see of what's
00:02:38
going to happen and it's it's somewhat
00:02:40
under motivating um I don't know just to
00:02:42
describe describe it I I think you know
00:02:45
I think it's I think the odds are
00:02:47
slightly in favor of trump but it's
00:02:48
basically
00:02:49
5050 um my one contrarian view on the
00:02:52
election is that it's not going to be
00:02:53
close un you know most presidential
00:02:55
elections aren't and uh you know one
00:02:57
side just breaks you know 20 2016 2020
00:03:00
we super close but two-thirds of the
00:03:02
elections aren't and you know you can't
00:03:03
always line things up and figure it out
00:03:06
I think either the you know the comma
00:03:07
bubble will burst or you know maybe
00:03:09
maybe the Trump voters get really
00:03:11
demotivated and don't show up but I
00:03:12
think you know one side is is simply
00:03:14
going to collapse in the next uh in the
00:03:16
next two months and then you know if you
00:03:18
want to get involved you know with all
00:03:20
the headaches that come with being
00:03:21
involved if it makes a difference
00:03:23
counterfactually and if it's a really
00:03:25
close election everything makes a
00:03:26
difference if it's if it's not even
00:03:28
close I don't think it makes much of a
00:03:29
difference if if it is going to be close
00:03:31
by the way if it's if it's like going to
00:03:33
be a razor thin close election then um
00:03:35
then I'm pretty sure KLA will win
00:03:37
because um because they will cheat they
00:03:39
will fortify it they will steal the
00:03:41
ballots and so so uh so you know if we
00:03:45
if we can if we can if we can and so
00:03:47
then in the event in the event that it's
00:03:50
close I don't want to be involved in the
00:03:52
event that it's not close I don't need
00:03:54
to be involved and so that's sort of
00:03:56
that's sort of a straightforward analis
00:03:57
right there jumping off point much
00:04:00
cheating on a percentage basis do you
00:04:02
think happens every year how much and do
00:04:05
you think Trump actually careful with
00:04:07
the verb so you know um cheating
00:04:10
stealing that implies something happened
00:04:12
the dark night I think the verb you're
00:04:14
allowed to use is fortify okay yeah we
00:04:17
don't want get canell on YouTube ballot
00:04:19
harvesting I mean it was you know it's
00:04:21
all sort of there were all these rule
00:04:22
changes it was sort of done in plain
00:04:24
daylight and uh um but yeah I think I
00:04:27
think our elections are not they're not
00:04:29
perfectly clean otherwise we could
00:04:31
examine it we could have vigorous debate
00:04:33
about it well what would you change then
00:04:34
what what should change cuz we all want
00:04:36
everybody's votes to count we want it to
00:04:38
be clean um I'm I'm talking about the
00:04:41
audience here I know at a minimum you
00:04:43
you'd run them you'd try to run
00:04:44
elections the same way you do it in
00:04:46
every other Western democracy you have
00:04:47
one day voting you have practically no
00:04:50
absentee ballots um you have um and um
00:04:55
and it's you know it's it's it's it's
00:04:57
it's one day where everything happens
00:04:59
it's not this uh two two-month elongated
00:05:02
process that's what the way you do it in
00:05:04
every other country you you'd have you'd
00:05:05
have some somewhat stronger voter ID and
00:05:09
you know make sure that you know the
00:05:11
people who are voting have a right to
00:05:12
vote um make it a national holiday
00:05:15
that's that's basically that's basically
00:05:17
what you do in every other Western
00:05:18
democracy and it's it's it and it used
00:05:20
to be much more like that in the US I
00:05:21
mean it's it's it's meaningfully decayed
00:05:23
over the last 20 30 years you 20 30
00:05:26
years ago 30 40 years ago you you got
00:05:28
the results on the day of of the vote
00:05:30
and that sort of stopped happening a
00:05:32
while ago what would make you not
00:05:34
disappointed so Trump gets elected how
00:05:37
do you what's your counternarrative on
00:05:40
you know where a year or two years past
00:05:43
the election Trump is president what
00:05:45
what makes you say I'm surprisingly not
00:05:47
disappointed what takes place man it's
00:05:52
um you know it's I I I think there are
00:05:55
some extremely difficult problems that
00:05:57
it's it's it's really hard to know how
00:05:59
how to how how to solve them I wouldn't
00:06:01
know what to do but uh we have you know
00:06:03
we have an incre incredibly big deficit
00:06:07
and uh and yeah if you can if you can
00:06:11
find some way to meaningfully reduce the
00:06:13
deficit with no tax hikes and without
00:06:16
without GDP contraction well you you
00:06:19
would do it if you got a lot of GDP
00:06:21
growth maybe right but um if you could
00:06:23
if you could meaningfully reduce the
00:06:24
deficit with with um with no with no tax
00:06:28
hikes that would be that would be very
00:06:30
impressive you know I I think we're sort
00:06:32
of sleepwalking into Armageddon with uh
00:06:35
you know the Ukraine and um the conflict
00:06:38
and Gau are just sort of the warm-ups to
00:06:40
the China Taiwan war and uh and so if uh
00:06:45
if if Trump can find a way to head that
00:06:47
off that would be incredible if they
00:06:49
don't go to war in four years that that
00:06:50
would be that would be better than I
00:06:52
would expect possibly in relation to
00:06:54
Taiwan if Trump called you and asked
00:06:56
should we defend it or not in this acute
00:06:59
case
00:07:00
would you advise to let Taiwan be taken
00:07:03
by China in order to avoid a nuclear
00:07:07
Holocaust in World War II or would you
00:07:10
believe that we should defend it and
00:07:11
defend free countries like that well I I
00:07:14
I think um I think you're probably not
00:07:17
supposed to
00:07:18
say no no no if you no if you um you I I
00:07:23
I think look I think there's so many
00:07:24
ways our our policies are messed up but
00:07:26
probably you know the one the one thing
00:07:29
that's roughly correct on the Taiwan
00:07:31
policy is that uh uh we don't tell China
00:07:34
what we're going to do um and what we
00:07:36
tell them is we don't know what we'll do
00:07:38
and we'll figure it out when you do it
00:07:39
which is probably has the virtue of
00:07:41
being correct and uh and then I think if
00:07:43
you had yeah if you had a red line at
00:07:45
quoy Matsu the the island you know five
00:07:48
miles off the coast of China that's
00:07:50
unbelievable if you um if you um if you
00:07:53
say we want some guard rails and we
00:07:55
won't defend Taiwan then they'd get
00:07:57
invaded right away so I think I think I
00:07:59
think policy of um not say policy is and
00:08:04
maybe not even having a policy you know
00:08:07
in some ways is relatively the best I I
00:08:09
I think anything anything anything
00:08:11
precise you say that's going to just
00:08:13
lead to war right away but what do you
00:08:15
believe I um worth defending or not
00:08:18
worth starting the conflict democracy in
00:08:20
this tiny Island worth going to war over
00:08:23
or not according to Peter teal it's um
00:08:26
it's not worth uh it's not worth World
00:08:28
War III
00:08:29
um and I I still think it's it's uh
00:08:32
quite catastrophic if it uh if it gets
00:08:35
taken over by the Communists how does
00:08:36
the world those can both be true how
00:08:37
does the world
00:08:38
divide if we end up in a heightened
00:08:42
escalation is China Russia Iran friends
00:08:46
is that an Alli is that an axis that
00:08:48
forms you know think out the next decade
00:08:51
in kind of your base case and I don't
00:08:53
know what happens how the world I don't
00:08:55
know what happens militarily if there's
00:08:57
a China Taiwan Invasion I mean may maybe
00:09:00
we roll over maybe it
00:09:02
escalates you know all the way to
00:09:04
nuclear war probably it's it's you know
00:09:07
some very messy in between thing sort of
00:09:10
like what what you have in in the
00:09:11
Ukraine uh what what I think happens
00:09:13
economically is very straight forward I
00:09:15
think uh I think basically um you know
00:09:18
you have with Russia and Germany you had
00:09:20
one northstream Pipeline and we have the
00:09:23
equivalent of a 100 pipelines between
00:09:25
the US and China and they they all blow
00:09:27
up you I I met the tick tock CEO about
00:09:30
about a year ago and um you know I not
00:09:33
maybe I wouldn't have said this now but
00:09:35
what I told him and I felt was very
00:09:37
honest advice was you know you don't
00:09:39
need to worry about the us we're never
00:09:41
going to do anything about Tik Tok we're
00:09:42
too incompetent um but um but but if I
00:09:46
were in your place I would still get the
00:09:48
business out of China I would get the
00:09:50
computers out the people out I'd
00:09:51
completely decouple it from bike Dan
00:09:54
because um Tik Tok will be banned 24
00:09:57
hours after the Taiwan invasion
00:10:00
and if you think there's a 50/50 chance
00:10:02
this happens and that will destroy you
00:10:04
know 100% of the value of the Tik Tok
00:10:07
franchise what was his reaction
00:10:09
um you know uh he said that they had
00:10:12
done a lot of simulations and the bunch
00:10:15
of companies in World War I and World
00:10:16
War II that managed to sell things to
00:10:18
both sides he doesn't seem so bright to
00:10:20
me do you think he's um he no he donly
00:10:23
what your take on him he he didn't
00:10:25
disagree with my frame and so I always I
00:10:27
always find that flattering if someone
00:10:28
basically framing so he seemed he seemed
00:10:31
perfectly bright to me even
00:10:35
though lot of bright people I saw you
00:10:37
give this I saw you give a talk last
00:10:39
summer with Barry Weiss and you talked
00:10:41
about this decoupling should be
00:10:43
happening you weren't saying should you
00:10:45
were recommending that every industry
00:10:47
leader consider decoupling from China I
00:10:50
think your comment was it's like picking
00:10:51
up nickels in front of a freight train
00:10:53
you remember saying that the well I I I
00:10:57
think like it's it's there a lot of
00:10:58
different there lot of different ways in
00:11:01
which businesses are coupled to China
00:11:03
that were investors that tried investing
00:11:06
there are people who tried to compete
00:11:08
within China they people who built
00:11:09
factories in China for export um and um
00:11:12
you know there different parts of that
00:11:14
that worked to um to to varying degrees
00:11:17
but uh but yeah
00:11:19
my um my I I certainly would not try to
00:11:24
um to invest in a company that competed
00:11:27
domestically inside China I think that's
00:11:30
that's virtually impossible um I think
00:11:34
it's probably quite tricky even to
00:11:37
invest in Chinese Chinese businesses um
00:11:40
uh and uh and then and then there is
00:11:43
there is sort of this model of you know
00:11:45
building factories in China uh for uh
00:11:48
for export uh to the west and um it was
00:11:51
it was a very big Arbitrage these things
00:11:53
do work you know I me I visited the
00:11:55
foxcon factory nine years ago and it's
00:11:58
you know you have people get paid a
00:11:59
dollar and a half $2 an hour and they
00:12:01
work 12 hours a day and they live in a
00:12:03
dorm room with two bunk beds where uh
00:12:06
you know you get eight people in the
00:12:07
dorm room someone's sleeping in your bed
00:12:08
while you're working and vice versa and
00:12:11
uh and you sort of realize they're
00:12:13
really far behind us or they're really
00:12:14
far ahead of us and either way you know
00:12:16
it's it's not that straightforward to
00:12:18
just uh shift the um the iPhone
00:12:20
factories to the United States um so I I
00:12:23
sort of understand you know why a lot of
00:12:27
businesses ended up there and why why
00:12:30
this is the the arrangement that we have
00:12:32
but uh but yeah my my my intuition for
00:12:36
you know what is going to happen without
00:12:38
making any normative judgments at all is
00:12:40
it is going to decouple how inflationary
00:12:42
will that
00:12:44
be it presumably is it's presumably
00:12:48
pretty inflationary yeah that that's
00:12:50
that's probably the you know I I don't
00:12:53
know it's and you'd have to sort of look
00:12:55
at you know what the in elasticities of
00:12:57
all these goods are so that's true
00:12:59
what's the policy re probably not that
00:13:02
it may not be as inflationary as people
00:13:03
think because um people always model
00:13:06
trade in terms of uh pairwise in terms
00:13:09
of two countries so if you literally
00:13:11
have to move the people back to the US
00:13:13
that's that's insanely expensive I don't
00:13:15
you know I don't know how much would
00:13:16
cost people to build an
00:13:18
iPhone you just you just well I think
00:13:20
India is sort of too messed up but you
00:13:22
shift it to like Vietnam Mexico there
00:13:24
are you know there there 5 billion
00:13:26
people living in countries where the
00:13:28
incomes are lower than China and so um
00:13:31
and so you know probably the um the
00:13:34
negative sum trade policy we should have
00:13:36
with China is um you know we should just
00:13:39
shift it to other countries which is a
00:13:41
little bit bad for the US extremely bad
00:13:44
for China and let's say really good for
00:13:46
Vietnam that's kind of um and that's
00:13:49
kind of the the negative sum policy um
00:13:53
that uh that's going to manifest as this
00:13:55
sort of uh decoupling happens let's talk
00:13:58
about avoiding it for a second here
00:14:00
Trump seems to be extremely good with
00:14:02
dictators and authoritarians uh Kim
00:14:04
Jong-un seems like a big fan I mean that
00:14:06
in like as a compliment as a superpower
00:14:08
right like he doesn't have a problem
00:14:10
talking to them he connects with them
00:14:12
and they seem to like him so what would
00:14:16
be the path to him working with XI to
00:14:18
avoid this is there a path to avoid this
00:14:21
because we were sitting here last year
00:14:23
talking about this and it just seems
00:14:25
mindboggling that if everybody agrees
00:14:28
that this is going to happen happen that
00:14:30
we can't figure out a way to make it not
00:14:33
happen well it's it's not just up to us
00:14:37
so um yeah there's there's and so I
00:14:41
don't know it's it's obviously somewhat
00:14:42
of a black box we don't exactly we we I
00:14:46
I I feel we just have no clue what
00:14:48
people in in in China think but um but I
00:14:52
I I think it's sort of the the sense of
00:14:55
history is is strongly the sort of thus
00:14:58
trap idea that you have a rising power
00:15:00
against an existing power and it tends
00:15:02
to you know it's it's willham mean
00:15:05
Germany versus Britain before World War
00:15:07
I and you know it's um you know Athens
00:15:10
against Sparta the rising power against
00:15:12
the existing power you you tend to um
00:15:15
get conflict that's that's probably what
00:15:18
deep down I think is is really really
00:15:22
far in the China DNA so so I'd say maybe
00:15:24
maybe the first I don't know the meta
00:15:27
version would be the first the first
00:15:28
step avoiding the conflict would be we
00:15:30
have to we have to start by admitting
00:15:32
that China believes the conflict's
00:15:34
happening right and then if if if if
00:15:37
people like you are constantly saying um
00:15:40
well we just need to have some happy
00:15:41
talk right um that's that is a recipe
00:15:44
that's a recipe for world I'm not
00:15:46
advocating happy Jo necessarily
00:15:49
um I'm I get accused of being a bit more
00:15:52
hawkish obviously obviously um in in
00:15:54
general you know I don't know I I'm not
00:15:57
I'm not sure Trump should talked to the
00:15:59
North Korean dictator but yeah in
00:16:01
general um it's probably a good idea to
00:16:03
to try to um talk to people even if
00:16:06
they're they're really bad people most
00:16:08
of the time and uh and uh you know it's
00:16:10
it's certainly um a very odd Dynamic
00:16:13
with the US and and uh and Russia at
00:16:15
this point where um I I think it is
00:16:18
impossible for anybody in the Biden
00:16:21
Administration even to have a back
00:16:22
Channel communication with uh with
00:16:24
people like I I don't think Tucker
00:16:26
Carlson counts as an emissary from the
00:16:28
Biden Administration and if anybody gets
00:16:30
tuckered or I don't know what the verb
00:16:32
is who talks you know that's that's that
00:16:35
seems that seems worse than the
00:16:37
alternative can we um talk about
00:16:40
technology um you have this you you you
00:16:44
have a speech where you talk about some
00:16:46
of the misguided things we've done in
00:16:47
the past in the name of technology and
00:16:49
use like big data as an example of that
00:16:52
um what is
00:16:54
AI um oh man that's that's sort of a
00:16:59
big question I
00:17:01
um it's um yeah I I always I I always
00:17:07
had this riff where I I don't like the
00:17:09
buzzwords and um you know machine
00:17:12
learning learning Big Data cloud
00:17:14
computing you know I'm going to build a
00:17:16
mobile app bring the cloud to um you
00:17:19
know if you have sort of a concatenation
00:17:21
of buzzwords um you know my my first
00:17:23
instinct is just to run away as fast as
00:17:25
possible some really bad group think and
00:17:29
um and for many years I I my bias is
00:17:31
probably that AI was one of the worst of
00:17:33
all these buzzword it meant you know the
00:17:36
next generation of computers the last
00:17:37
generation of computers you know
00:17:39
anything in between so it's meant all
00:17:41
these all these very different things if
00:17:43
we if we roll the clock back to the
00:17:46
2010s you know the um probably the AI to
00:17:50
the extent you concretize I would say
00:17:52
the AI debate was maybe framed by by two
00:17:56
the two books the two canonical books
00:17:57
that framed it was there was the the
00:17:58
Bostrom book super intelligence 2014
00:18:01
where AI was going to be this super
00:18:03
human super duper intelligent um thing
00:18:07
and then um the anti- um Boston book was
00:18:10
the Kaiu Lee 2018 AI superpowers you can
00:18:13
think of the CCP rebuttal to Bostrom
00:18:16
where basically AI was going to be
00:18:18
surveillance Tech face recognition and
00:18:20
China was going to win because they had
00:18:22
no qualms about uh applying this
00:18:24
technology and um and then um if we now
00:18:28
think about what actually happened let's
00:18:29
say with the llms and and chat GPT it
00:18:32
was really neither of those two um and
00:18:35
it was this in between thing which was
00:18:37
actually what people would have defined
00:18:39
AI as for the previous 60 or 70 years
00:18:42
which is passing the touring test which
00:18:44
is you know this the somewhat fuzzy line
00:18:46
it's a computer that can pretend to be a
00:18:48
human um or that can fool you into
00:18:51
thinking it's a human and um and uh you
00:18:54
know even with the fuzziness of that
00:18:56
line you could say that pre chat GPT
00:18:59
wasn't passed and then chat GPT passed
00:19:02
it and that seems that seems very very
00:19:05
significant um and um and then obviously
00:19:08
leads to all these questions what does
00:19:10
it mean you know is it going to is it
00:19:12
going to complement people is it going
00:19:14
to substitute for people you know what
00:19:16
does it do to the labor market do you
00:19:17
get paid more paid less you know so
00:19:19
there all these all these questions but
00:19:21
uh it um it seems extremely it seems
00:19:25
extremely important um and um
00:19:29
and it's probably you know certainly the
00:19:32
the big picture questions which I think
00:19:34
Silicon Valley is always very bad at
00:19:35
talking about is like you know what does
00:19:37
it mean to be a human being right um
00:19:38
sort of the I don't know the stupid 2022
00:19:42
answer would be that humans differ from
00:19:43
all the other animals because we we're
00:19:45
good at languages if you're a
00:19:46
three-year-old or an 80-year old you
00:19:48
speak you communicate we tell each other
00:19:50
stories this this this is what makes us
00:19:53
different and so um so yeah I think
00:19:55
there's something about it that's uh
00:19:57
incredibly important and and very
00:19:59
disorienting you know the question I
00:20:00
always have as a I know the narrower
00:20:02
question I have as an investor is sort
00:20:03
of how do you make money with this stuff
00:20:06
and um how do you make money I it's um
00:20:09
it's pretty confusing and I think I I
00:20:13
don't know this is always where I'm
00:20:14
anchored on the late 90s is sort of the
00:20:16
formative period for me but uh I I I I
00:20:19
keep thinking that uh AI in 20123 2024
00:20:24
is like the internet in
00:20:26
1999 um it's it's really big it's going
00:20:29
to be very important it's going to
00:20:32
transform the world not you know in 6
00:20:34
months but in 20 years and then um there
00:20:37
are probably all kinds of incredibly uh
00:20:40
catastrophic approximations where you
00:20:43
know uh what businesses are going to
00:20:45
make money you know who's going to have
00:20:47
the Monopoly who's going to have pricing
00:20:48
power is um you know is is is is super
00:20:52
unclear um probably you know one one
00:20:54
layer deeper of analysis you know if
00:20:56
attention is all you need and if you're
00:20:58
you're not post economic you need to pay
00:21:00
attention to who's making money and in
00:21:02
AI it's basically one company is making
00:21:04
Nvidia is making over 100% of the
00:21:07
profits everybody else is collectively
00:21:08
losing money and so um and so there's
00:21:11
sort of a you have to do some sort of
00:21:13
you should do you should try to do some
00:21:15
sort of analysis you do you go long
00:21:18
Nvidia do you go short you know is it um
00:21:20
you know My Monopoly question is it a is
00:21:22
it a really durable Monopoly you know
00:21:25
and and then I it's it's hard for me to
00:21:27
know because I'm in Silicon Valley and I
00:21:28
haven't done anything we haven't done
00:21:29
anything in semiconductors for a long
00:21:31
time so I have no clue do you um if you
00:21:33
let's debz word the word Ai and say it's
00:21:35
a bunch of process automation let's just
00:21:37
say that's version 0.1 where brains that
00:21:40
are roughly the equivalent of a teenager
00:21:42
can do a lot of manual stuff what do you
00:21:45
have you thought about what it means for
00:21:48
you know 8 billion people in the world
00:21:50
if there's an extra billion that
00:21:52
necessarily couldn't work or like
00:21:54
whether that in political or economic
00:21:56
terms
00:21:59
I don't know the the the
00:22:01
um I I I don't know if this is the same
00:22:04
but this is you know the the history of
00:22:06
2050 years the Industrial Revolution
00:22:09
what was that it you know it adds to GDP
00:22:12
it frees people up to do more more
00:22:14
productive things um you know maybe
00:22:17
there's you know there was yeah there
00:22:18
was a I know there was a lite critique
00:22:20
in the 19th century of the factories
00:22:23
that people were going to be unemployed
00:22:24
and wouldn't have anything to do because
00:22:25
the machines would replace the people
00:22:27
you know maybe the Lites are right this
00:22:30
time around I'm I'm I'm probably I'm
00:22:32
probably pretty pretty skeptical of it
00:22:34
but uh but yeah it's it's it's extremely
00:22:36
confusing you know uh where where the
00:22:39
gains and and losses are there there
00:22:42
probably are um you know there there's
00:22:45
always sort of a hobby you can always
00:22:47
just use it on your hobby horses so I
00:22:49
don't know the you know my anti-
00:22:50
Hollywood or anti- university hobby
00:22:52
horse is that uh it seems to me that you
00:22:55
know the um the AI is quite good at the
00:22:57
woke stuff
00:22:59
and um it'll and and so you know if you
00:23:01
want to if you want to be a successful
00:23:03
actor you should be maybe a little bit
00:23:04
racist or a little bit sexist or just
00:23:06
really funny uh and you won't have any
00:23:09
risk of the AI replacing
00:23:11
you everybody else will get everybody
00:23:14
else will get replaced and then probably
00:23:17
I don't know
00:23:18
um I don't know uh Claudine gay the
00:23:21
plagiarizing Harvard University
00:23:23
president um you know the AI is going to
00:23:26
you know the AI will produce end amounts
00:23:29
of um of these sort of I don't even know
00:23:32
what to call them uh woke um papers and
00:23:36
um they they were all already sort of
00:23:38
plagiarizing one another they were
00:23:40
because they were always saying the same
00:23:41
thing over and over again they were
00:23:43
using their own version of is just going
00:23:44
to flood the Zone with with even more of
00:23:46
that and that you know I don't know
00:23:48
obviously they've been able to do it for
00:23:49
a long time and no one's noticed but uh
00:23:52
but I think I think at this point um
00:23:54
that it it doesn't seem promising from a
00:23:56
um compet compe Point obviously my hobby
00:24:00
horses so I'm I'm just maybe just
00:24:02
wishful thinking on my part what are the
00:24:03
areas of technology that um you're
00:24:06
curious about that your mind is like wow
00:24:07
this is really I have to learn more pay
00:24:11
attention you know I'm always I always
00:24:14
think uh you you want to instantiate it
00:24:18
more in companies than than um things or
00:24:21
you know you ask sort of like where is
00:24:23
where is innovation happening you um you
00:24:27
know it it it
00:24:29
in our society it doesn't have to be
00:24:30
this way but it's it's um it's mostly in
00:24:34
in um in a certain subset of relatively
00:24:37
small companies where we have these
00:24:39
relatively small teams of people that
00:24:41
are really pushing the envelope and
00:24:43
that's that's sort of you know that
00:24:45
that's sort of what I find you know
00:24:47
inspiring about about venture capital
00:24:50
and then you and then obviously you
00:24:52
don't just want Innovation you also want
00:24:54
it to sort it to it to um to translate
00:24:57
into into good businesses but that's
00:24:59
that's where it happens it it somehow it
00:25:01
doesn't happen in universities it
00:25:03
doesn't happen in government you know
00:25:05
there was a time it did I mean you know
00:25:07
somehow in this very very weird
00:25:09
different country that was the United
00:25:11
States in the 1940s you had you know
00:25:13
somehow the Army organized the
00:25:15
scientists and got them to produce a
00:25:16
nuclear bomb in Los Alamos in three and
00:25:18
a half years and you know the way the
00:25:20
New York Times editorialized after that
00:25:23
was you know it's it's you know it was
00:25:24
sort of an anti-libertarian write up it
00:25:26
was you know there were um you know
00:25:27
obvious Maybe you'd left the Primadonna
00:25:29
scientists to their own would have taken
00:25:31
them 50 years to build a bomb and uh the
00:25:33
Army could just tell them what to do and
00:25:35
this will should silence anybody who
00:25:37
doesn't believe the government can do
00:25:38
things and uh they don't write
00:25:40
editorials like that in the New York
00:25:42
Times anymore but I think um yeah but I
00:25:45
think that's sort of that that's that's
00:25:47
sort of where where when where when
00:25:49
should look I think it I think I think a
00:25:51
crazy amount of it still happens in the
00:25:52
United States you know there sort of you
00:25:55
know we've we've you know episodically
00:25:57
tried to all this investing we probably
00:25:59
tried to do tooo much investing in
00:26:00
Europe over the years it's always sort
00:26:02
of a junk it sort of it's a nice place
00:26:04
to go on vacation as an investor and um
00:26:07
and it's it's it is it is very it's it's
00:26:10
very and I don't have a great
00:26:12
explanation but it's a very strange
00:26:15
thing that uh so much of it is still the
00:26:17
US is somehow still the country where
00:26:19
people do new things Peter is that is
00:26:21
that a team organizational social
00:26:24
evolutionary problem in the United
00:26:26
States what is the root cause of the
00:26:28
failure to innovate in the United States
00:26:30
relative to the expectation going back
00:26:34
70 years 50 years Etc from you know the
00:26:37
the rocket shift and we're all going to
00:26:39
live yeah well this is always this is
00:26:40
always this always one of the big
00:26:42
picture and claims I have that we've
00:26:44
been in an era of relative Tech
00:26:46
stagnation the last 40 or 50 years or
00:26:48
the you know the tagline um that we
00:26:51
had they promis flying cars all we got
00:26:54
was 140 characters which is not an anti-
00:26:56
Twitter antix commentary even though the
00:26:58
the way the way I used to always qualify
00:27:00
it was that uh at least you know at
00:27:02
least it was at least a good company you
00:27:04
had you know 10,000 people who didn't
00:27:06
have to do very much work and could just
00:27:08
smoke marijuana all day very similar to
00:27:10
Europe and so I I think that actually
00:27:11
that part actually did get corrected but
00:27:14
um um but the um very but I think I I
00:27:19
think um like what went wrong because
00:27:21
you you point out that it's not a
00:27:22
technology Trend tracker that you think
00:27:24
about it's about people and teams that
00:27:26
innovate and drive to outcomes B on
00:27:28
their view of the world and and what's
00:27:30
gone wrong with our view of the world
00:27:32
and our ability to organize to achieve
00:27:35
the seemingly unachievable with very
00:27:37
rare exceptions obviously elon's here
00:27:38
later but yeah you know it's it's it's
00:27:40
it's overdetermined um the um the the
00:27:44
the rough frame I always have and again
00:27:46
it's not that there's been no innovation
00:27:48
there's been there's been a decent
00:27:49
amount of innovation in the world of
00:27:51
bits computers internet mobile internet
00:27:54
you know crypto AI so there sort of all
00:27:57
these um world of bits uh places where
00:28:01
there was you know a sign significant
00:28:04
but sort of somehow narrow cone of
00:28:06
progress but it was everything having to
00:28:07
do with atams that was slow this was
00:28:09
already the case When I Was An
00:28:10
undergraduate at Stanford in the late
00:28:12
80s in retrospect any applied
00:28:14
engineering field was a bad idea it was
00:28:16
a bad idea to become a chemical engineer
00:28:18
you know a mechanical engineer aeroastro
00:28:20
was terrible nuclear engineering
00:28:22
everyone KN I mean I no one did that you
00:28:25
know and um and and there's something
00:28:28
about yeah the world of Adams that um
00:28:31
you know from a Libertarian point of
00:28:32
view you'd say got regulated to death um
00:28:35
there probably uh you know there's
00:28:38
there's some there's some set of
00:28:39
arguments where um the lwh hanging fruit
00:28:42
got picked and got harder to find new
00:28:44
things to do although I always I always
00:28:46
think that was just a sort of baby
00:28:48
boomer excuse for for covering up for
00:28:50
the the failures of that generation um
00:28:53
and um and then um and then I think but
00:28:57
I think maybe maybe um maybe a very big
00:29:00
picture part of it was that uh at some
00:29:03
point in the 20th century the idea got
00:29:06
took hold that not all forms of
00:29:09
technological progress were simply good
00:29:12
and simply for the better and there's
00:29:13
you know there's something about the two
00:29:15
world wars and the you know the
00:29:17
development of nuclear weapons that uh
00:29:19
that that gradually pushed people into
00:29:21
this this more uh risk ofers society and
00:29:23
it didn't happen overnight but um you
00:29:26
know maybe a quarter century
00:29:28
you know after the nuclear bomb it's
00:29:29
like by Woodstock it happened by
00:29:31
Woodstock it happened yeah cuz that was
00:29:33
the same summer we landed on the moon
00:29:35
yeah Woodstock was three weeks after
00:29:36
that yeah that's that was the Tipping
00:29:39
Point progress stopped in the took over
00:29:41
sex can we shift gears just to the
00:29:43
domestic economy what what do you
00:29:44
think's happening in the domestic
00:29:45
economy and just say backdrop we've had
00:29:47
something like 14 straight months of
00:29:49
downward revisions to jobs the revisions
00:29:52
are supposed to be completely random but
00:29:53
somehow they've all been down um prob
00:29:56
doesn't mean anything um
00:29:58
there's also what's happening with with
00:30:00
the yield curve but I'll stop there what
00:30:02
what's your take on what's happening in
00:30:03
the
00:30:04
economy
00:30:07
um you know it's
00:30:09
it's man it's always hard hard to know
00:30:12
exactly yeah I I I suspect we're close
00:30:14
to a recession i' I've probably thought
00:30:16
this for a while uh it's it's being
00:30:20
stopped by really big government
00:30:22
spending so um you know in May of 2023
00:30:27
the projection for the deficit in 20
00:30:30
fiscal year 24 which is October of 23 to
00:30:33
September 24 was something like 1.5 1.6
00:30:37
trillion um the deficit is going to come
00:30:39
in about 400 billion higher and so um
00:30:42
which you know was a sort of a crazy
00:30:44
deficit was projected and it was way off
00:30:46
and then somehow um and so if if we had
00:30:50
not found another 400 billion um to add
00:30:54
to you know this this crazy deficit at
00:30:56
the top of the economics cycle you know
00:30:59
you're supposed to you're supposed to
00:31:00
increase deficits in a recession not at
00:31:02
the not at the top of the cycle um you
00:31:05
know think things would be probably very
00:31:07
shaky there's yeah there's there's
00:31:08
there's there's some way where um we
00:31:11
yeah we have a um too much debt not
00:31:14
enough sustainable growth um you know
00:31:17
again I always think it comes back to
00:31:19
you know Tech Innovation there probably
00:31:21
are other ways to grow an economy
00:31:23
without Tech um or intensive progress um
00:31:28
but I think they we we we don't have
00:31:31
those don't seem to be on offer and then
00:31:32
that's that's where it's very deeply
00:31:34
stuck if you if you wind back over the
00:31:35
last 50 years you there's always a
00:31:37
question why did people not realize that
00:31:39
this Tech stagnation had happened sooner
00:31:41
and I think there were two one-time
00:31:43
things people could do economically that
00:31:45
had nothing to do with science or tech
00:31:47
there was a 1980s Reagan Thatcher move
00:31:51
which was to massively cut taxes
00:31:53
deregulate allow lots of companies to
00:31:55
merge and combine and and it was sort of
00:31:58
a one-time way to make the economy a lot
00:32:02
bigger even though it had it was not
00:32:04
something that really had the sort of
00:32:05
compounding effect so it led to one
00:32:08
great decade and then there was um you
00:32:10
know and that was sort of the right-wing
00:32:12
capitalist move and then um in the 90s
00:32:15
there was sort of a Clinton Blair um
00:32:18
Center left thing which was sort of
00:32:19
Leaning into globalization and there was
00:32:21
a giant Global Arbitrage you could do
00:32:24
which also had you know a lot of
00:32:25
negative externalities that came with it
00:32:27
but um it sort of was a one-time move I
00:32:29
think both of those are are not on offer
00:32:33
you know I don't necessarily think you
00:32:35
should undo globalization I don't think
00:32:36
you should raise taxes like crazy but um
00:32:39
you can't you can't do more
00:32:41
globalization or more tax cuts here
00:32:43
that's not going to be the win and and
00:32:45
so I I think you have to somehow get
00:32:46
back to the future um we have time for a
00:32:48
couple more questions you um I think saw
00:32:52
that maybe this ivy league institutions
00:32:55
maybe weren't producing the best and
00:32:56
brightest or weren't exactly um hitting
00:32:59
their mandate um and you created the
00:33:01
teal fellows and you've been doing that
00:33:03
for a while and I meet them all because
00:33:04
they all have crazy ideas and they pitch
00:33:06
me for Angel investment what have you
00:33:08
learned getting people to quit school
00:33:10
giving them $100,000 and then how many
00:33:12
parents call you and get really upset
00:33:14
that their kids are quitting
00:33:16
school uh
00:33:20
it's well I I don't know I've I've I've
00:33:23
learned a lot I mean it's it's um
00:33:30
I don't know I I I I think I think the
00:33:32
universities are far worse than I even
00:33:33
thought when I started this thing um I
00:33:37
think um yeah it's um you know I I I I
00:33:41
did this uh I did this debate at Yale
00:33:45
last week um you know resolved higher
00:33:46
education's a bubble and um and uh you
00:33:51
sort of go through all the different
00:33:53
numbers and um the and then you know and
00:33:57
again I I was ful to word it in such a
00:33:58
way that I I didn't have to you know and
00:34:00
then people kept saying well what's your
00:34:01
alternative what should people do
00:34:02
instead and I said nope that's not was
00:34:04
not the debate I'm not you know I'm not
00:34:06
your guidance counselor I'm not your
00:34:07
career counselor I I don't know how to
00:34:09
solve your problems but um if
00:34:11
something's a bubble you know the first
00:34:13
thing you should do is probably not you
00:34:15
know lean into it in too crazy a way and
00:34:19
you know the student debt was 300
00:34:20
billion in 2000 it's uh it's basically
00:34:24
uh close to two trillion at this point
00:34:25
so it's just been the sort of runaway um
00:34:28
this runaway process and um and then if
00:34:30
you look at it by cohort if you
00:34:33
graduated from college in 1997 12 years
00:34:36
later um people still had student debt
00:34:39
but most of the people had sort of paid
00:34:40
it down um but the first by 2009 we
00:34:44
started the teal Fellowship in 2010 and
00:34:47
it you know it felt uh two by 2009 was
00:34:51
the first cohort where this really
00:34:53
stopped if you take the people graduated
00:34:54
from college in 2009 and you fast for
00:34:57
forward 12 years to
00:35:00
2021 the median person had more student
00:35:04
debt 12 years later than they graduated
00:35:07
with because it's actually just it's
00:35:09
just compounding faster and it was you
00:35:11
know partially partially the global
00:35:13
financial crisis the people had less
00:35:15
well-paying jobs they stayed in college
00:35:17
longer um and the colleges they it's
00:35:20
just sort of been this background thing
00:35:22
where it's it's decayed in these in
00:35:25
these really significant ways and um you
00:35:27
know again I I think it's on some level
00:35:30
um there are sort of a lot of um debates
00:35:33
in our society that are probably
00:35:34
dominated by sort of a boomer narrative
00:35:37
and maybe the Baby Boomers were the last
00:35:39
generation where College really worked
00:35:41
and you know they think well you know I
00:35:43
I worked my way through college and why
00:35:45
can't why can't um why can't you know an
00:35:48
18-year-old going to college do that
00:35:49
today and um and so I I I think the
00:35:53
bubble will will will be done once the
00:35:56
Boomers have exited stage left but does
00:35:58
the government to it would be good if we
00:36:00
figured something out before then you
00:36:02
know does does the government need to
00:36:03
stop underwriting the loans because it's
00:36:06
the lending I think the 90 plus perc of
00:36:09
the the the capital in the student loan
00:36:11
programs is funded by federal uh Federal
00:36:14
the federal government and there's if
00:36:17
you're an accredited University you can
00:36:18
take out a loan and go to it and
00:36:20
accreditation in in a in a in a rigid
00:36:23
kind of free market system you would
00:36:25
have an underwriter that says are you
00:36:27
going to be able to Gra graduate make
00:36:28
enough money to pay your loan off is
00:36:29
this a good school are you going to get
00:36:31
a good job and then the market would
00:36:32
figure out whether or not to give you a
00:36:33
loan would figure out what the rate
00:36:34
should be and so on but in this case the
00:36:36
government simply provides Capital to
00:36:38
support all this and as a result
00:36:39
everything's gotten more expensive and
00:36:42
the rigidity in the system that
00:36:44
basically qualifies schools and the
00:36:46
quality of those schools relative to the
00:36:47
earning potential over time is gone we
00:36:49
need the government to get out of
00:36:51
student loan business yeah but look the
00:36:53
the place where I'm I I know I'm sort of
00:36:56
some ways I'm rightwing some ways I'm
00:36:57
left wing on this so the place where I'm
00:36:58
leftwing is I do think a lot of the
00:37:01
students got ripped off and uh and so I
00:37:04
think there should be some kind of broad
00:37:06
um debt forgiveness at this point um who
00:37:09
should pick up the T but it's not just
00:37:11
the taxpayers it's the universities and
00:37:14
it's the the the the bond holders got it
00:37:17
the bond take a little bit out of those
00:37:18
ends the universities and um and then
00:37:22
obviously if you just make it the
00:37:24
taxpayers then um then you'll just then
00:37:26
the universities can just charge more
00:37:28
and more no incentive to reform what
00:37:30
whatsoever but uh had me you know it's
00:37:33
in 2005 uh it was under Bush 43 that the
00:37:36
bankruptcy laws got Rewritten in the US
00:37:39
where you cannot discharge student debt
00:37:41
even if you go bankrupt and if you
00:37:43
haven't paid it off by the time you're
00:37:44
65 your Social Security wages checks
00:37:47
will be garnished it's crazy so um so
00:37:50
you know I I I I do think um but should
00:37:52
we stop lending should the federal
00:37:54
government get out of the the student
00:37:55
lending business well if if if we if we
00:37:58
say that uh if we if we start if we
00:38:01
start with my place where you know a lot
00:38:03
of the student debt should be forgiven
00:38:05
and then and then and then reform the
00:38:07
then we'll see how many people are
00:38:09
willing to lend you know how how much
00:38:11
how many of the colleges can um pay for
00:38:13
all the student what's your sense if if
00:38:15
it was a totally free market system how
00:38:17
many colleges would shut down because
00:38:20
they wouldn't be able to S there's no
00:38:21
tuition
00:38:24
support it it probably would be a lot
00:38:27
smaller it it might it might you might
00:38:30
not have to shut them down because
00:38:33
there's you know a lot of them have
00:38:34
gotten extremely a blow it's like Bal
00:38:36
Mall's cost disease where you know I
00:38:38
don't know if I have no idea like a
00:38:40
place like UCLA it probably has you know
00:38:43
twice or three times as many bureaucrats
00:38:45
as they had 30 40 years ago so there's
00:38:48
sort of all there's sort of all these
00:38:49
sort of um parasitic people that have
00:38:52
sort of uh gradually approved and uh and
00:38:55
um and and so there's probably a lot of
00:38:57
would be a lot of rational ways to dial
00:38:59
this back but um but yeah um you know
00:39:01
maybe we're to a new
00:39:03
location if the only if the only way to
00:39:05
lose weight is to cut off your thumb
00:39:07
that's kind of a difficult way to go on
00:39:08
a DI he um Peter three of your
00:39:11
collaborators longtime collaborators
00:39:13
Elon Musk um Mark Zuckerberg and uh Sam
00:39:18
mman are arguably the three leading AI
00:39:22
language model um
00:39:25
leaders which one is going to win rank
00:39:27
in order and tell us a little bit about
00:39:33
each Peter said he would answer any
00:39:35
question I I I I I said I would take any
00:39:37
question I didn't say to answer any
00:39:39
question you said you would honestly you
00:39:41
said today you felt extremely honest and
00:39:43
candid Let's uh I I yeah but Ive already
00:39:46
been extremely honest and candid so I
00:39:48
think qu it's it's it's whoever I talked
00:39:52
to last okay they're they're all very
00:39:55
very convincing people so you know I cre
00:39:58
I I talk a little bit I talked to Elon a
00:40:02
while ago and and you know and it was it
00:40:04
was just um how ridiculous it was that
00:40:08
Sam Alman was getting away with turning
00:40:10
open AI from a nonprofit into a
00:40:12
for-profit that was such a scam if
00:40:15
everybody was allowed to do this
00:40:17
everybody would do this that it has to
00:40:19
be totally illegal what Sam's doing and
00:40:22
it shouldn't be allowed at all and that
00:40:24
seemed really really convincing in the
00:40:26
moment and then then sort of half an
00:40:27
hour later I I thought to myself but you
00:40:30
know actually um man it was it's been
00:40:33
such a horrifically mismanaged place at
00:40:37
open AI with this Preposterous nonprofit
00:40:40
board they had nobody would do this
00:40:42
again and so there actually isn't much
00:40:44
of a moral hazard from it so but yeah
00:40:46
who whoever whoever I talk to I find
00:40:48
very convincing in the
00:40:49
moment well will that spaces get
00:40:52
commoditized I mean do you see a path to
00:40:53
Monopoly there well again this is this
00:40:56
is again where you know you should you
00:40:58
know attention is all you need you need
00:41:00
to pay attention to who's making money
00:41:02
it's Nvidia it's it's the hardware the
00:41:04
chips layer and um and um and then
00:41:09
that's just it's just what we you know
00:41:11
it's not what we've done in tech for for
00:41:13
30 years you are they making 120% of the
00:41:17
profits they're they're make they're I
00:41:19
think everybody else is losing money
00:41:21
collectively yeah everyone else is just
00:41:23
spending money on on the computer so
00:41:24
it's it's one it's one company that's
00:41:25
making I mean maybe there's a few other
00:41:27
people are making some money I mean I
00:41:28
assume tsmc and asml but but uh but uh
00:41:32
yeah I think everyone else is
00:41:33
collectively losing money what do you
00:41:34
think of Zuckerberg's approach to say
00:41:36
I'm so far behind this isn't cour in my
00:41:38
business I'm going to open source it um
00:41:41
is that going to be the winning strategy
00:41:44
handicap that for
00:41:46
us um again I I I I I I I would say um
00:41:53
my again my my my big my my big
00:41:55
qualification is you know my my model is
00:41:57
AI feels like it does feel uncomfortably
00:42:00
close to the bubble of 1999 so I'm we
00:42:04
haven't invested that much in it um and
00:42:08
uh I I I'd want to have more clarity in
00:42:11
investing but uh but the the uh the
00:42:14
simple simplistic question is you know
00:42:17
who who's going to make money um you
00:42:19
know I think a year ago two years ago in
00:42:21
retrospect Nvidia would have been a good
00:42:22
buy you know I think at this point
00:42:24
everybody it's it's it's sort of too
00:42:26
obvious that they're making too much
00:42:27
money everyone's going to try to copy
00:42:29
them on on the chip side maybe that's
00:42:32
straightforward to do maybe it's not but
00:42:34
but that's you know I'd say probably um
00:42:38
you should you should if you if you want
00:42:39
to figure out the AI thing you you
00:42:41
should not be asking this question about
00:42:42
um you know meta or um open air or any
00:42:46
of these things you should really be
00:42:47
focusing on the Nvidia question the
00:42:49
chips question and the the fact that
00:42:50
we're not able to focus on that that
00:42:52
that tells us something about how we've
00:42:53
all been trained you know I think Nvidia
00:42:55
got started in 1993 yeah I believe that
00:42:57
was the last year where anybody in their
00:43:00
right mind would have studied electrical
00:43:02
engineering over computer science right
00:43:03
94 Netscape takes off and then yeah it's
00:43:06
probably a really bad idea to start a
00:43:08
Semiconductor Company even in '93 but
00:43:10
the benefit is there was going to be no
00:43:12
one would come after you no no talented
00:43:15
people started semiconductor companies
00:43:17
after 1993 because they all went into
00:43:20
you know into software score their
00:43:22
Monopoly
00:43:23
power um it's
00:43:30
I I I think it's quite strong because
00:43:33
this this this history that I just gave
00:43:35
you where none of us know anything about
00:43:37
chips um and then I think the you know I
00:43:41
think the risk it's always you know if
00:43:44
attention is all that you need um the
00:43:47
qualifier to that is you know when you
00:43:49
get started as an you know actress as a
00:43:51
startup as a as a company you need
00:43:54
attention then it's desirable to get
00:43:56
more and at some point attention becomes
00:43:59
the worst thing in the world and and
00:44:01
there was the one day where Nvidia had
00:44:03
the largest market cap in the world
00:44:05
earlier this year and I do think that
00:44:08
represented a phase transition once that
00:44:10
happened they probably had um more
00:44:13
attention than was good hey Peter as we
00:44:15
wrap here um your brain works in a
00:44:18
unique way you're an incredible
00:44:20
strategist you think you know very
00:44:22
differently than uh a lot of the folks
00:44:25
um that we get to talk to um with all of
00:44:28
this are you optimistic for the
00:44:32
future uh I I always man I always push
00:44:35
back in that question I I um I think I
00:44:40
think extreme optimism and extreme
00:44:42
pessimism are both really bad attitudes
00:44:46
and they're the somehow the same thing
00:44:48
you know extreme pessimism nothing you
00:44:50
can do extreme optimism the future will
00:44:53
take care of itself so if if you have to
00:44:55
have one it's probably you want to be
00:44:57
somewhere in between maybe mildly
00:44:59
optimistic mildly pessimistic but uh you
00:45:02
know I I believe in human agency and
00:45:04
that it's up to us and it's not you know
00:45:06
it's not some sort of winning a lottery
00:45:08
ticket or some astrological chart that's
00:45:11
going to decide things and I believe in
00:45:13
human agency and that's sort of an axis
00:45:16
that's very different from optimism or
00:45:18
pessimism what a great extreme optimism
00:45:19
extreme pessimism they're both excuses
00:45:21
for laziness what an amazing place to
00:45:24
end ladies and gentlemen give it up for
00:45:26
Peter J thank you thank you Peter come
00:45:28
on
00:45:29
now wow all right Peter ch
