#151 Podcast Guest Updates / AI / Open AI & Sam Altman / Religion, God & Vision

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Welcome to another episode of
come together

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We are live another episode
today is my third take trying to

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record a solo episode.
It's a muscle that I have not

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used in a very long time, and
it's crazy how it reflects so

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quickly and how it starts to
decay so quickly.

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I've got a lot I want to talk
about.

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I've got a lot of my mind that's
been going on.

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But first I want to just say a
couple of things about the most

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recent few podcasts that I did,
in case you missed them.

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The one of them I recorded most
recently or is least recently,

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but since my last solo episode
with an awesome journalist named

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Mark Elliott.
I really like Mark a lot.

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He's really cool.
I he, he's this, he told me an

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awesome story and how he became
a writer.

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And in the writing world, the
only real way to get published

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is to either have some kind of
obviously academic background,

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Either I have a publisher or an
agent.

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And if you don't have any of
those, it's very difficult to

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get published.
And so Mark was telling me the

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story and how he was trying to
negotiate with the publisher and

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an agent at the same time.
And the first person that showed

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interest, he showed to the other
person and the other person

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signed him and then got him the
deal that he ended up getting.

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So he brokered his own career to
begin his his literary degree,

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sorry, his literary career.
And he did, he did some amazing

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work.
We talked about 60s and 70s

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Hollywood.
We talked about Disney.

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He wrote an amazing book about
Walt Disney.

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And I'm actually, I just got in
the mail.

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I have to finish one or two
other books and then I'm going

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to be reading it.
But he told me that he hired a

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girl to her only job for two
years was to FOIA information

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from the government.
Freedom, Freedom of Information

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Act.
And that's where the government

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stores all these public records
about what they do.

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And because we're all taxpayers
and we're all buying into this

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big organization, this big
government in this big country,

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we as individuals have a right
to request information about

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whatever we feel like is being
that that is publicly.

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It's done by the government,
it's done by this collective

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collaborate entity.
And sometimes the government

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will say no and then you have to
sue them.

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And then when you sue them, they
hand over the information, but

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they try to get make as many
steps in the process in hopes

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that you kind of give up along
the way.

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And only the, the people that
really are pushing people that

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really are dedicated end up
getting, getting that

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information through.
And it could take years.

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And so, so he had FOIA all this
information about Walt Disney's

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relationship with the FBI and
found some really interesting

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stuff regarding strikes,
regarding communism regarding he

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has some employees that Disney
was concerned were communist.

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Disney was very capitalistic,
very anti communist.

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Of course, this is around the
time of World War 2 and we're

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right, right around right after
World War 2.

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And even though we beat the
Nazis, fear of the Russians,

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fear of the of the Soviet Union
and the Communists was still

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very much prevalent in American
Society.

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So we talked about a bunch of
that type of content, a lot of

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fun.
He was really awesome and he got

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a lot of pushback from the
Disney family for what he wrote

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and he stayed strong.
And, you know, we were talking

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about on camera and off camera
about the value of when you of

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having journalistic integrity
and saying the truth even when

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it hurts.
And it's really hard to do.

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I don't do it all the time, you
know, and you could say, I mean,

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and there's a, there's a middle
ground, of course, where you

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don't have to offer up the truth
if it's going to get people in

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trouble or if it isn't relevant
or whatever, unless it's, well,

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you know, again, unless it's
specifically relevant or

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specifically important.
And then you don't hide it, you

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know, Anyway, he got a ton of
pushback from Disney corporate,

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from the Disney family, and he
still published this.

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And a lot of people won't touch
him now because of this

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blacklist from this enormous,
the American entertainment

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company has pretty much
blacklisted him.

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And he's still, he's still
working hard and he's doing

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amazing work.
I also spoke with Nick Marks,

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who was a, who's a professor out
of, I believe it was Colorado

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State University, University of
Colorado.

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It's one of the two.
And he taught, he teaches media

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studies.
And when I would reach out to

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him, I initially thought that he
was actually a conservative guy

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teaching media studies in a
college.

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And I'm like, how cool is that?
That's so, so rare.

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And it turns out he's a liberal
guy teaching that, which was

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also a really interesting
conversation because I would say

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with my experience and
anecdotally, the experience of

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my friends around me that I've
spoken to is that colleges and

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universities tend to not really
be so diverse as far as

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supporting right street, right
right wing or libertarian media.

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That seems to be more of a kids
thing.

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And you kind of have to be like
a rebel kid or a Frappro or a

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sorority girl from my and my my
time on campus.

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I don't know whether whether
it's still like that or not, but

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there was, you know, there was a
type of character that was a

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concert, you know, like
libertarian, conservative on

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campus.
But most of the time it was not

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the liberal arts teachers to the
media studies professors.

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And but Nick did a really good
job putting himself in other

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people's shoes.
And, and he and I were talking

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about trying to understand his,
his, his work is trying to be

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objective despite his personal
opinions.

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And I totally get that because
I'm probably the left, as far

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left as you could be on the
right.

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I would probably say that about
myself.

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I don't really have again, of
affiliation so much.

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And I've pretty much felt like
everyone in politics has let

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everyone down.
And there's really no hope for

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that the current system as it
is.

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So I can't really put those, I
can't say I ascribe to any of

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those ideas.
And we, so he and I had a really

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interesting conversation.
I was just trying to understand

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where he was coming from.
And there's times where I

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thought I disagreed with him.
And there was times where I

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thought that he and I really
disagreed on like some

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fundamental stuff about people
and humanity and people and

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people's nature and what's right
and wrong.

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And then after asking if I
understood what he was saying

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correctly or asking to
elaborate, he, it turns out that

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we did not really disagree very
much at all in a lot of things.

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And so it was really, really a
lot of fun.

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And I learned a lot about about
at least his perspective and how

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to have this conversation.
And also it's important to

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understand what is being taught
and what the perspective of the

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teachers are because they're the
people that are raising the

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youth and they're the people
that are influencing the college

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students, especially at public
universities.

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So they tend to be much larger
collections of, of of classrooms

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and students.
So Nick was was a lot of fun.

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I did a awesome episode with a
guy named Alan Paul who's Allman

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Brothers, the which is the Great
American rock band from the late

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60s, early 70s.
And they had a 40 year career,

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45 year career with the rotation
of band members.

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Excuse me, a couple of them had
died first two within the first

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couple of years of the of the
band and then and then he and I

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talked about he spent some time
in China and Beijing and he was

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actually taking a risk trying
something new.

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His wife was in media too.
They'd and he was writing at the

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time for slam magazine and
working in music journalism and

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I could.
Hey everyone real quick.

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If you're enjoying the show,
click subscribe and rate the

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show 5 stars helps a ton.
Thanks so much.

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Tar World, I believe.
And he and he and his wife and

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and he and his wife ended up
going to Beijing.

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They were there while the
Olympics were there.

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He turned out to he he got a gay
guy as an Olympic journalist for

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a little while and then he ended
up starting a rock band, a rock

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band, I guess, and really was
pretty big in in Beijing.

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And he had this whole couple of
years stint where he and a

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couple of Chinese guys had
built, you know, made a band and

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we're very popular.
It's really cool.

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So that that we had he had a
great story.

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We had a ton of fun in our
conversation.

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And finally, Doctor Karen
Barrett is a musician and

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studies creativity and studies
the impact of music on our

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brain, studies dementia and our
aging brain and how music can

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help activate different parts of
our brain, recall different

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associations.
And those are important to

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exercise because when we get
when God forbid, and we

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shouldn't know about this, but
if people get dementia or some

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kind of form of that, it's the
neural pathways are decaying or

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they're completely breaking off
at certain points.

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And so our brain isn't really
isn't speaking to itself in the

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best way that it could.
And music actually helps

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maintain that.
So we had a really interesting

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conversation about where
creativity comes from and

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improvising and different neural
pathways and reward systems and

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youth and children, sorry, and
adults that they get activated

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when we improvise and when we
play around.

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And this doesn't have to be with
music.

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It could also be with speaking.
It could also be with poetry.

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It could also be with art and
painting.

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So check out that episode.
It was really, really, really

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cool.
I was, I was talking to a friend

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of mine, Ari and all right,
Mendelow, friend of the podcast,

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friend of the show, great dude.
He lives in Seattle and he and I

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are extremely close.
We were talking the other day

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and he sent me a Diary of the
CEO podcast with Karen Howe.

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I want to say is her name and
I'm going to look it up while

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I'm saying this.
And Empire of AI is the book and

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Karen is yeah, Karen Howe and
she was on Diary of the CEO

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warning and talking a little, a
little bit about open AI and AI

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in general.
And so I listened to the

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podcast.
I immediately bought the book.

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I got to be honest, the topic is
such an interesting topic and

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she really does provide a lot of
incredible information and

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context to people that don't
know about the whole world of

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AI.
Because like any other world,

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and I've talked about this in
the podcast in a lot of

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different capacities, As for
example, like I've gone into UFC

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and MMA world, you find out that
there's, you know, a million,

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there's a whole universe within
this.

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There's the body trainers,
there's the dietitians, there's

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the recovery people, there's the
functional medicine people,

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there's the actual, you know,
the, the, the actual martial

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artists and the people that, and
the, and the different forms of

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fighting and then the cardio
people and the strength people.

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And, and then you have the
actual drama and the stories of

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the people of where the
backgrounds are from and where

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they came from and what the
fighting history is.

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And, and everyone's got a story.
And he, he cut 30 lbs to fight

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and he cut 10 lbs to fight or
he's going up or down a weight

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class.
And you have all these

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incredible, incredible stories
and details, this whole little

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world in and of itself.
And it turns out obviously, that

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you have this with AI.
But the AI world is old and rich

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and a lot more impactful than I
think any of us realize.

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Then I think most of us realize.
And this book Empire of AI does

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an amazing job at least outlying
to to the basic reader, to the

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regular relatively uninformed
reader about how about different

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concepts to generally be aware
of.

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So, for example, Open AI
started, always started as a

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safety company, but as a safety
company has some kind of

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paradoxical relationship with
making money.

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Because in order to be the lead
safety company, the lead safety

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company of the world, you need
to be at the top, you need to be

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at the head of the game, right?
Open AI, which is a start, which

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is a startup was competing with
AI companies like Meta or like

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Google or like Apple or Amazon.
And these companies have been

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developing AI for years as these
enormous conglomerations that

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have the GDP of countries at a
time.

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And not only and, and these
corporations, these, these tech

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companies are so powerful and so
wealthy and so influential that

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they really could basically take
control over whole countries at

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00:13:41,440 --> 00:13:44,920
a time or mass parts of
populations of countries.

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00:13:44,920 --> 00:13:48,840
So, for example, Karen Howe
talks in the in this book about

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00:13:49,480 --> 00:13:54,280
there's parts, you know, an
enormous and really crucial part

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00:13:54,280 --> 00:13:59,080
of safe AI is training the AI
properly, right?

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00:13:59,080 --> 00:14:03,040
Meaning you have you're creating
a personality, you're creating a

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00:14:03,040 --> 00:14:08,080
kid, you know, you're giving it
access to more information than

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00:14:08,080 --> 00:14:11,600
we can even be aware of.
Then we can even know what to do

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00:14:11,600 --> 00:14:13,120
with.
You're giving AI all this

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information and then you're
asking it a question and asking

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it to summarize all that
information, all this compute

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00:14:20,160 --> 00:14:24,320
into a one word answer, into a
one sentence answer, into one

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00:14:24,320 --> 00:14:28,280
paragraph answer.
And what that ends up doing, we

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00:14:28,280 --> 00:14:32,000
can't predict what it's going to
say or what information it's

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00:14:32,000 --> 00:14:35,840
going to draw from because we
don't know all the information

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00:14:35,840 --> 00:14:38,400
it's drawing from.
It's like take all of Twitter,

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00:14:38,400 --> 00:14:43,320
take all of Facebook, take all
of Google and tell me how to

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00:14:43,320 --> 00:14:47,600
water my tree.
And like imagine all the context

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00:14:47,640 --> 00:14:50,400
in which anyone could say water
your tree appropriately,

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00:14:50,480 --> 00:14:54,040
inappropriately as far as
gardening, as far as as far as

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00:14:54,040 --> 00:14:56,320
tree maybe be a reference to
something else.

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00:14:56,720 --> 00:15:02,280
And all of Google, all of
YouTube, all of X, all of

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00:15:02,280 --> 00:15:05,440
Twitter, whatever it is, all of
Core and all of Reddit and give

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00:15:05,440 --> 00:15:07,480
me that information in the
paragraph you can.

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00:15:07,480 --> 00:15:09,040
We can't predict what that's
going to say.

250
00:15:09,040 --> 00:15:10,720
So we have to train it.
We have to train it what's

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appropriate.
We have to train it what's

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00:15:11,880 --> 00:15:15,760
acceptable.
And there's the more advanced

253
00:15:15,760 --> 00:15:19,680
training and then there's the
more lower level but equally

254
00:15:19,680 --> 00:15:24,080
important training, which is
basically manually teaching it.

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00:15:24,080 --> 00:15:26,200
This is acceptable.
This is not this considered

256
00:15:26,200 --> 00:15:29,080
inappropriate?
This considered OK for those

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00:15:29,080 --> 00:15:34,440
jobs for the lower the, the
bottom tier of training AI and

258
00:15:34,600 --> 00:15:36,400
this industry has been around
for a long time.

259
00:15:36,440 --> 00:15:42,240
Meta and Facebook famously,
infamously have people.

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00:15:42,760 --> 00:15:45,880
It's, it's a, it's, it's a
completely inhumane job because

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00:15:45,880 --> 00:15:51,520
what you're doing is you're,
you're subjecting people to 10s

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00:15:52,120 --> 00:15:57,600
to, to to days, months, years of
I mean these people, you know,

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00:15:57,600 --> 00:16:00,280
if you're in Venezuela or you're
in Kenya and you're worried and

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00:16:00,280 --> 00:16:04,880
you're getting hired by open AI
to, to, to to teach AI what's

265
00:16:04,880 --> 00:16:11,320
considered a sexually explicit
or gory or violent image, right?

266
00:16:11,560 --> 00:16:15,480
You're looking at all this
stuff, all these images or all

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00:16:15,480 --> 00:16:17,440
these.
Text descriptions and sentences.

268
00:16:17,440 --> 00:16:20,440
And, and, and quotes and
paragraphs and essays even at a

269
00:16:20,440 --> 00:16:25,000
time, and you're reading and
seeing the most repulsive,

270
00:16:25,000 --> 00:16:30,840
disgusting, terrible, terrible
stuff, the darkest stuff on the

271
00:16:30,840 --> 00:16:33,120
internet's there.
And we're paying people a dollar

272
00:16:33,120 --> 00:16:39,960
to $4.00 an hour to spend 20
hours a day trying to teach

273
00:16:39,960 --> 00:16:42,720
training AI what's acceptable or
not.

274
00:16:45,760 --> 00:16:50,120
So that's just one component of
the AI world and AI safety.

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00:16:50,840 --> 00:16:56,120
And in order to train the AI to
do this, we need to make money.

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00:16:56,800 --> 00:16:59,720
In order to be able to make
money, we have to sell our

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00:16:59,720 --> 00:17:02,240
products or at least have to
commercialize our products

278
00:17:02,240 --> 00:17:04,040
because that's the way that
America works.

279
00:17:04,520 --> 00:17:07,480
You could get people to invest
in you, but then they expect

280
00:17:07,480 --> 00:17:08,640
something out of that
investment.

281
00:17:08,640 --> 00:17:12,000
So for example, when Open AI
made a partnership with

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00:17:12,000 --> 00:17:15,040
Microsoft and they, Microsoft
initially I think gave them a

283
00:17:15,040 --> 00:17:19,640
billion dollars, then 10, and I
think I believe they're up to

284
00:17:19,640 --> 00:17:22,960
$100 billion.
But double check me on that.

285
00:17:25,000 --> 00:17:26,359
Microsoft's not doing that for
free.

286
00:17:26,680 --> 00:17:29,880
They're expecting returns.
They're expecting, hey, I gave

287
00:17:29,880 --> 00:17:31,880
you a billion dollars.
What do you have to show me for

288
00:17:31,880 --> 00:17:35,400
that?
And Open AI has an enormous

289
00:17:35,400 --> 00:17:38,080
amount of pressure to show them,
hey, we created this new

290
00:17:38,080 --> 00:17:39,520
product, We created this great
product.

291
00:17:39,720 --> 00:17:42,280
But if they're so focused on
safety and they're so focused on

292
00:17:42,280 --> 00:17:45,200
wait, we can't advance until we
make sure that this machine,

293
00:17:45,200 --> 00:17:48,880
that this software, that this
code, that this bot, whatever

294
00:17:48,880 --> 00:17:53,320
this is, this AI is operating in
a way that is safe and

295
00:17:53,320 --> 00:17:56,000
predictable and within the
confines of the restrictions

296
00:17:56,000 --> 00:17:59,680
that we set for it.
If they don't have time to do

297
00:17:59,680 --> 00:18:04,600
that, then Open AI is
essentially it is it at a

298
00:18:04,600 --> 00:18:10,920
constant state of civil war over
but whether to be safe or not,

299
00:18:10,960 --> 00:18:13,440
and this is supposed to be the
safety company too.

300
00:18:16,360 --> 00:18:20,600
It's all too crazy.
It's all too crazy then, you

301
00:18:20,600 --> 00:18:23,640
know, there's obviously the
economic potential issues of AI

302
00:18:23,640 --> 00:18:27,040
and there's something else that
that Karen Howe talks about

303
00:18:27,360 --> 00:18:33,520
where for example, there I
actually don't remember if she

304
00:18:33,520 --> 00:18:34,680
talked about this in the book
yet.

305
00:18:35,440 --> 00:18:37,320
She talks about the environment.
I'll get to that in a minute,

306
00:18:39,240 --> 00:18:45,360
but I think I read online maybe
then about an AI tax.

307
00:18:45,440 --> 00:18:48,640
And so this would be that we're
going to switch.

308
00:18:48,960 --> 00:18:53,240
The government would switch
taxing labour from people to

309
00:18:53,240 --> 00:18:58,320
taxing labour of AI.
If AI is going to take jobs away

310
00:18:58,320 --> 00:19:01,160
from people and going to
generate so much productivity,

311
00:19:01,400 --> 00:19:06,560
it doesn't make sense to tax the
citizens that are working on a

312
00:19:06,560 --> 00:19:11,800
much smaller scale at this point
in time and humanity for

313
00:19:11,800 --> 00:19:15,720
America.
And instead we should be taxing

314
00:19:15,720 --> 00:19:20,120
the companies and the
corporations whose AI are

315
00:19:20,800 --> 00:19:24,040
creating those values and taking
those jobs and generating that

316
00:19:24,040 --> 00:19:26,120
value.
And then you take a common pool

317
00:19:26,320 --> 00:19:29,360
and you just when you
redistribute it to people who

318
00:19:29,360 --> 00:19:32,640
don't have jobs anymore because
they lost all those jobs to AI.

319
00:19:32,640 --> 00:19:35,680
And then you wonder, what, what
are you going to do when we're

320
00:19:35,680 --> 00:19:39,480
on, when we have no jobs?
And what are we going to do when

321
00:19:39,480 --> 00:19:43,200
our jobs are meaningless or
useless and everyone's on social

322
00:19:43,200 --> 00:19:47,800
media all day or on drugs all
day or constantly consuming

323
00:19:48,080 --> 00:19:51,920
something or buying something.
And then the humanity ends up

324
00:19:51,920 --> 00:20:02,080
like in Wall-e, Yeah, you don't
want that either, really, You

325
00:20:02,080 --> 00:20:04,080
know, So you got to think about
those repercussions.

326
00:20:04,880 --> 00:20:07,200
And you got to think about what
to do financially.

327
00:20:07,200 --> 00:20:14,240
You got to think about the fact
that AI in order to work on the

328
00:20:14,240 --> 00:20:17,480
scale that it is working, in
order to grow on the scale that

329
00:20:17,480 --> 00:20:19,560
it's growing, it needs data
centers.

330
00:20:19,760 --> 00:20:23,800
And for data set and data
centers take reason require,

331
00:20:23,800 --> 00:20:30,520
excuse me, resources.
And resources include all the

332
00:20:30,520 --> 00:20:34,920
resources that humans need like
real estate and land.

333
00:20:35,000 --> 00:20:40,120
For example, Chile is example of
a company that sorry, a country

334
00:20:40,520 --> 00:20:48,040
that is basically being used to
mine AI components, minerals.

335
00:20:48,560 --> 00:20:54,800
And the real estate and land is
being used as as as as Centers

336
00:20:54,800 --> 00:20:57,840
for data.
And they it has to take clean

337
00:20:57,840 --> 00:20:59,320
water.
The data centers they have to

338
00:20:59,320 --> 00:21:03,880
take clean water because water
from pipes and water from in the

339
00:21:03,880 --> 00:21:05,720
minerals in waters that are
used.

340
00:21:05,720 --> 00:21:08,560
So sorry context you need water
for cooling.

341
00:21:09,640 --> 00:21:12,040
The reason why you need to cool
these certain these sensors is

342
00:21:12,040 --> 00:21:14,680
imagine if you have a computer
and you're overworking the

343
00:21:14,680 --> 00:21:17,680
computer gets warm gets hot.
Imagine you have 100 computers

344
00:21:17,680 --> 00:21:21,760
or 1000 computers.
Imagine that with all these data

345
00:21:21,760 --> 00:21:26,160
centers that are required to
compute and store and power all

346
00:21:26,160 --> 00:21:31,120
the and generate all everything
that all the AI companies, Meta,

347
00:21:31,160 --> 00:21:35,320
Apple, Instagram, sorry
Instagram, whatever Google, Open

348
00:21:35,360 --> 00:21:41,480
AI, Enthropic, Clod, the whole
everything.

349
00:21:42,760 --> 00:21:50,000
Those all need servers which all
need to be cooled with water by

350
00:21:50,000 --> 00:21:54,840
using water that needs to be
clean water because the bacteria

351
00:21:54,840 --> 00:21:58,680
in the mineral and the minerals
in tap water or from the pipes

352
00:21:58,680 --> 00:22:02,840
or from sewage, much like humans
where it's not great for us to

353
00:22:02,840 --> 00:22:06,040
drink that and we generally need
a filter or some kind of form of

354
00:22:06,040 --> 00:22:10,320
filter to clean our water.
It actually would impact the

355
00:22:10,320 --> 00:22:14,520
hardware and the data centers
and caused decay and actually

356
00:22:14,520 --> 00:22:17,160
caused them to break.
So the cooling centers need to

357
00:22:17,160 --> 00:22:19,480
use clean water.
They need real estate, they need

358
00:22:19,480 --> 00:22:22,880
electricity, they need power.
And like all these things that

359
00:22:22,880 --> 00:22:25,680
like we need that, like these
things that would bring people

360
00:22:25,680 --> 00:22:28,680
out of poverty.
Remember, the question isn't

361
00:22:28,680 --> 00:22:30,800
whether or not this technology
exists.

362
00:22:30,800 --> 00:22:33,600
The technology certainly exists.
And the reason why we know that

363
00:22:33,880 --> 00:22:38,120
is because China, who America
hopes is still ahead of I, you

364
00:22:38,120 --> 00:22:40,800
know, we'll see.
I hope so.

365
00:22:40,800 --> 00:22:45,600
I don't know if I believe that,
but China who is our famous

366
00:22:45,600 --> 00:22:52,720
infamous competitor, they
they're doing pretty good.

367
00:22:56,720 --> 00:23:01,400
They're doing pretty good and
they are working on alternative

368
00:23:01,400 --> 00:23:03,880
fuels that we're sources that
we're not using.

369
00:23:03,880 --> 00:23:10,720
And they are they're just,
they're stepping up in ways.

370
00:23:12,800 --> 00:23:16,640
They lifted 650 million people
out of poverty.

371
00:23:16,720 --> 00:23:19,360
That's what I was going at.
They lifted 6.

372
00:23:19,360 --> 00:23:23,800
They lift, they lifted almost
double the population of the

373
00:23:23,800 --> 00:23:26,240
United States out of complete
poverty.

374
00:23:27,440 --> 00:23:29,760
So we have the resources and the
technology to do it.

375
00:23:31,080 --> 00:23:33,600
And the question is what we're
going to focus our efforts on

376
00:23:33,960 --> 00:23:37,680
the AI companies and the AI
world and the leadership this

377
00:23:37,840 --> 00:23:45,040
these tech Bros in Silicon
Valley, their excuse for using

378
00:23:45,040 --> 00:23:48,760
all these resources for AI and
not for people at the moment is

379
00:23:48,760 --> 00:23:52,120
because down the line, AI is
going to be such a great tool

380
00:23:52,120 --> 00:23:54,080
that no one's going to need
anything.

381
00:23:54,080 --> 00:23:57,760
And so we're just making it
short term pain for a long term

382
00:23:57,760 --> 00:24:03,800
gain.
And I don't know why we can't

383
00:24:03,800 --> 00:24:07,920
have some short term gain and
long term gain sometimes,

384
00:24:08,120 --> 00:24:10,680
especially if we worked hard
enough to create that technology

385
00:24:13,040 --> 00:24:18,920
that we know that has been put
in practice within the last 20

386
00:24:18,920 --> 00:24:24,600
years on planet Earth, should be
able to lift millions of people

387
00:24:24,600 --> 00:24:32,000
out of poverty, should be able
to create a higher scale, higher

388
00:24:32,000 --> 00:24:34,080
quality of life than ever
before.

389
00:24:34,880 --> 00:24:38,560
And even if you want to say we
do, which I do think we do,

390
00:24:38,560 --> 00:24:42,360
obviously I think most of the
world, even in the worst parts

391
00:24:42,360 --> 00:24:45,360
of it, was probably better off
than they were 50 years ago or

392
00:24:45,360 --> 00:24:48,240
100 years ago.
I, I got to believe I, I, I

393
00:24:48,240 --> 00:24:57,000
think so.
We seem to be spending an awful

394
00:24:57,000 --> 00:25:02,680
lot of resources on AI and we
only think that it's worth the

395
00:25:02,680 --> 00:25:05,280
trade off because Sam Altman
thinks so.

396
00:25:08,920 --> 00:25:13,160
Because Dario, whatever his name
is over at Anthropic thinks so.

397
00:25:14,680 --> 00:25:18,120
I even know if you think so.
Bra or Brockman, Greg Brockman.

398
00:25:19,800 --> 00:25:25,240
It's a very small AI world and
most of these guys keep on

399
00:25:25,240 --> 00:25:29,720
branching off and starting their
own companies, not because it's

400
00:25:29,720 --> 00:25:32,360
such an amazing environment and
everyone's thriving.

401
00:25:32,360 --> 00:25:34,320
It's because no one trusts each
other and because the

402
00:25:34,320 --> 00:25:36,880
competition is so intense and
the and they feel, everyone

403
00:25:36,880 --> 00:25:44,400
feels that the threat that's so
existential to life is so

404
00:25:44,400 --> 00:25:49,160
prevalent that they need to take
matters into their own hands

405
00:25:49,800 --> 00:25:53,840
instead of collaborating,
instead of working together.

406
00:25:55,160 --> 00:25:58,320
And it seems that unfortunately,
that's it, that Sam Altman is at

407
00:25:58,320 --> 00:26:02,680
the root of all this because
most of these people have come

408
00:26:02,680 --> 00:26:07,520
and gone through him and come
and gone as a consequence of him

409
00:26:07,520 --> 00:26:10,720
or because of him or stated that
he was the reason why.

410
00:26:10,720 --> 00:26:15,040
They feel that there is no
transparency or minimal trust or

411
00:26:16,680 --> 00:26:20,560
murkiness in the vision of what
AI is going to be.

412
00:26:22,800 --> 00:26:25,840
And that's crazy, and that's
crazy.

413
00:26:25,960 --> 00:26:28,240
That's crazy.
So I don't think that, you know,

414
00:26:28,240 --> 00:26:31,520
and I think there's a lot of
amazing avenues of science for

415
00:26:31,520 --> 00:26:34,400
us to be able to go down.
I think there's a lot of avenues

416
00:26:34,840 --> 00:26:40,520
of life, of technology that we
can go down to improve

417
00:26:40,600 --> 00:26:45,400
everything without having to
necessarily make these enormous

418
00:26:45,400 --> 00:26:47,360
sacrifices on such a grand
scale.

419
00:26:47,800 --> 00:26:50,640
Or at least have a little bit
more of a diverse perspective as

420
00:26:50,640 --> 00:26:53,800
to who, you know, what the
actual end goal is and who's

421
00:26:53,800 --> 00:26:59,840
going to accomplish it.
And 25% chance that it's

422
00:26:59,840 --> 00:27:04,560
existential to humanity.
One out of four.

423
00:27:06,920 --> 00:27:09,760
I think that like we don't need
to continue down.

424
00:27:09,760 --> 00:27:12,480
Like we could hit the brakes
with that and we could focus on

425
00:27:14,640 --> 00:27:17,760
other sciences, we can focus on
implementing nuclear, we could

426
00:27:17,760 --> 00:27:19,720
focus on and that, you know, I
mean, we could catch up.

427
00:27:19,720 --> 00:27:22,200
We can catch up on what it
actually means.

428
00:27:22,200 --> 00:27:24,400
And this is actually an
important part of AI too, What

429
00:27:24,400 --> 00:27:26,800
it means to be a human, what it
means to be a person.

430
00:27:27,080 --> 00:27:28,560
What does it mean to be
creative?

431
00:27:28,560 --> 00:27:30,880
What does it mean to work?
What's the purpose of working?

432
00:27:30,880 --> 00:27:34,040
And when our jobs are gone, when
we don't need to work, when

433
00:27:34,040 --> 00:27:36,880
there is universal basic income,
when we are all living on that

434
00:27:36,880 --> 00:27:40,800
Wally ship, what are we going to
do?

435
00:27:42,160 --> 00:27:44,920
Are we going to be distracted?
How do you find meaning?

436
00:27:45,480 --> 00:27:48,640
Every Elon Musk is so concerned
about preserving consciousness,

437
00:27:51,560 --> 00:27:55,440
but we're not focusing on
exercising consciousness.

438
00:27:55,480 --> 00:27:58,680
We're not focusing on building
on exercising its muscles.

439
00:27:58,680 --> 00:28:04,160
In fact, everything around us
has been put here to decay it,

440
00:28:05,000 --> 00:28:08,320
including the things that I'm
habitually doing on a regular

441
00:28:08,320 --> 00:28:10,000
basis.
I'm on social media a lot.

442
00:28:10,000 --> 00:28:14,840
I'm on my screens a lot.
I am not present a ton.

443
00:28:14,840 --> 00:28:18,240
I am not looking around my
backyard and thinking I should

444
00:28:18,240 --> 00:28:21,560
play, you know, I should play
with my kid there often enough.

445
00:28:21,560 --> 00:28:23,800
I'm not looking around at my
neighbors, like someone to talk

446
00:28:23,800 --> 00:28:28,080
to and a relationship to have
and a band to start and, you

447
00:28:28,080 --> 00:28:32,720
know, and a bonfire to have and
concert to go to often enough.

448
00:28:32,720 --> 00:28:34,880
Because I'm in my own head
listening to the podcast about

449
00:28:34,880 --> 00:28:39,440
about how the world's ending.
So is humanity going to be

450
00:28:39,440 --> 00:28:41,240
preserved?
Probably.

451
00:28:41,240 --> 00:28:43,840
But what does it mean to be a
person?

452
00:28:43,840 --> 00:28:45,720
What does it mean to have value?
What does it mean to have

453
00:28:45,720 --> 00:28:52,160
meaning?
I'm happy we have religion.

454
00:28:52,920 --> 00:28:54,440
I'm really, really happy in
times like this.

455
00:28:54,440 --> 00:28:56,560
We have religion.
And I'm really, really happy

456
00:28:56,880 --> 00:29:04,880
times like this that I have
Judaism and that the Western

457
00:29:04,880 --> 00:29:09,520
world has done so much to
divorce itself from religion

458
00:29:09,520 --> 00:29:13,640
because, and I actually do
understand this, there was,

459
00:29:13,640 --> 00:29:19,320
there is for a lot of people and
historically was an enormous

460
00:29:19,320 --> 00:29:21,000
amount of dogma that goes with
religion.

461
00:29:21,480 --> 00:29:26,920
That is to say that a lot of
times if someone says why, you

462
00:29:26,920 --> 00:29:28,320
say shut up because I told you
so.

463
00:29:29,000 --> 00:29:32,480
And a lot of times they really,
and every time, every time there

464
00:29:32,480 --> 00:29:36,160
is a why and every time there is
a how and every time there is a

465
00:29:36,160 --> 00:29:39,520
So what.
And the question just is, are

466
00:29:39,520 --> 00:29:41,040
you willing to ask those
questions?

467
00:29:41,840 --> 00:29:48,240
And what does that mean?
And the people that are dogmatic

468
00:29:48,240 --> 00:29:50,360
are the people that don't want
to answer those questions or

469
00:29:50,360 --> 00:29:52,200
don't want to look into those
questions, or the different

470
00:29:52,200 --> 00:29:54,920
dogmatic people are the people
that don't that, that that tell

471
00:29:54,920 --> 00:29:59,040
you to be quiet.
And to no, it can't be right.

472
00:29:59,120 --> 00:30:01,280
What you're saying isn't right.
If it conflicts with my

473
00:30:01,280 --> 00:30:04,360
perception, with my perception
of reality, it cannot be the

474
00:30:04,360 --> 00:30:09,040
case.
And Judaism, from my

475
00:30:09,040 --> 00:30:12,640
understanding and from my school
of thought is the shattering of

476
00:30:12,640 --> 00:30:14,080
that.
That's what Abraham represents,

477
00:30:14,080 --> 00:30:18,200
Avraham, the forefather, and
it's the end.

478
00:30:18,280 --> 00:30:21,120
Shimsunafal Hirsch, Samsonafal
Hirsch, who is I've spoken about

479
00:30:21,120 --> 00:30:23,920
before, but is lived in the
1800s in Germany.

480
00:30:24,400 --> 00:30:30,160
Incredible Rabbi reading his
stuff has reading a lot of his

481
00:30:30,160 --> 00:30:33,720
stuff has changed my life as far
as his views on education, on

482
00:30:33,720 --> 00:30:38,080
his views on family, on his
views on just just really,

483
00:30:38,080 --> 00:30:45,240
really extremely thoughtful and
reason God views on Torah and

484
00:30:45,240 --> 00:30:46,760
views on personal
responsibility.

485
00:30:47,320 --> 00:30:50,800
And one thing that he is
constantly, constantly

486
00:30:50,800 --> 00:30:53,760
emphasizing, and I think that
this is something that we

487
00:30:53,760 --> 00:31:00,960
sorely, sorely need in our
society, is the idea that there

488
00:31:00,960 --> 00:31:10,440
is a greater moral objective
good and humanity is objectively

489
00:31:10,440 --> 00:31:14,840
flawed.
And we are constantly on the

490
00:31:14,840 --> 00:31:19,080
search to get closer to that
objective good.

491
00:31:21,440 --> 00:31:25,960
Not easier, not comfort, not
comfort.

492
00:31:26,760 --> 00:31:30,680
We're trying to get better,
we're trying to get good, we're

493
00:31:30,680 --> 00:31:33,000
trying to grow.
We're trying to get closer to

494
00:31:33,000 --> 00:31:37,800
the divine truth of the capital
T in God that is God and not

495
00:31:37,800 --> 00:31:41,440
gods, and the oneness that is
reality.

496
00:31:44,520 --> 00:31:50,480
And when we just reject
information because of dogma, we

497
00:31:50,480 --> 00:31:53,760
can't get closer to there.
Abraham started as an

498
00:31:53,760 --> 00:31:56,200
iconoclast.
That was the way that he found

499
00:31:56,200 --> 00:31:58,440
God was by breaking down
perceptions.

500
00:31:58,440 --> 00:32:02,000
The way he found God was
breaking down dogma and saying

501
00:32:02,000 --> 00:32:04,400
that doesn't make sense, that
doesn't make sense, something

502
00:32:04,400 --> 00:32:12,080
must make sense and then
communicates with the universe

503
00:32:12,800 --> 00:32:19,960
in some kind of manner.
And again, there is so many

504
00:32:19,960 --> 00:32:24,680
layers to reality.
There's so many layers to

505
00:32:24,680 --> 00:32:27,120
consciousness.
There's so many layers to the

506
00:32:27,120 --> 00:32:30,960
world around us.
And we've been talking about

507
00:32:30,960 --> 00:32:34,640
this forever, forever.
All religions, ancient

508
00:32:34,640 --> 00:32:39,080
religions, modern technology.
The story of the matrix is just

509
00:32:39,080 --> 00:32:42,200
another story of the story of
God, you know, and this world is

510
00:32:42,440 --> 00:32:46,240
is is is something that you
know, is some kind of

511
00:32:46,280 --> 00:32:47,880
preparation for the world to
come.

512
00:32:48,160 --> 00:32:51,520
And reality is layered and God
created the world and with

513
00:32:51,520 --> 00:32:56,320
different, different stages of
development and evolution and,

514
00:32:56,720 --> 00:33:02,400
and, and I mean, just let layers
of reality and layers of

515
00:33:02,400 --> 00:33:06,400
meaning.
And we have to try to get

516
00:33:06,400 --> 00:33:11,880
better, not to confuse ourselves
for the end all be all.

517
00:33:13,000 --> 00:33:18,640
And what it seems to me be and
what Sam Altman and what these

518
00:33:20,400 --> 00:33:25,000
tech billionaires, Peter Thiel,
who's his mentor, by the way,

519
00:33:26,520 --> 00:33:30,880
original backer introduced him
to his boyfriend or husband in

520
00:33:30,880 --> 00:33:34,400
the hot tub, 3:00 in the
morning, ketamine parties and

521
00:33:34,400 --> 00:33:38,760
stuff like that.
These are people that are more

522
00:33:38,760 --> 00:33:42,240
interested in preserving
themselves forever than

523
00:33:42,240 --> 00:33:44,920
elevating themselves to be a
part of a greater truth of

524
00:33:44,920 --> 00:33:50,560
reality.
And Sam Altman.

525
00:33:50,560 --> 00:33:57,760
Oh crap, I forgot.
The company signed up to be part

526
00:33:57,760 --> 00:33:59,840
of this, to be part of this
company.

527
00:33:59,840 --> 00:34:01,720
Hang on.
I think he was fun helping fund

528
00:34:01,720 --> 00:34:07,920
it and brain upload that there
was going to upload his digital

529
00:34:07,920 --> 00:34:20,840
consciousness and his brain.
Ah. 02018 but Sam Altman just

530
00:34:20,840 --> 00:34:24,600
dropped $10,000 deposit on a
brain upload paying a start load

531
00:34:24,600 --> 00:34:27,840
a start up to you to euthanize
you so for so that it can one

532
00:34:27,840 --> 00:34:30,239
day maybe bring back a digital
copy of your mind.

533
00:34:31,120 --> 00:34:36,360
According to Here's the MIT Tech
Review in 2018, Sam Altman tells

534
00:34:36,360 --> 00:34:37,520
MIT Technology.
Review.

535
00:34:37,520 --> 00:34:39,400
He's pretty.
Sure, mines will be digitized in

536
00:34:39,400 --> 00:34:44,840
his lifetime.
And then on Instagram over here.

537
00:34:44,840 --> 00:34:48,679
Who's this account?
Artificial intelligence In 2018,

538
00:34:48,679 --> 00:34:51,600
Sam Waltman paid a $10,000
deposit to join a wait.

539
00:34:51,600 --> 00:34:54,199
List for a Nectome.
That's the company Nectome, a

540
00:34:54,199 --> 00:34:57,920
startup offering 100% Fatal
Brain 100.

541
00:34:57,920 --> 00:35:00,160
Percent fatal brain preservation
procedure.

542
00:35:05,480 --> 00:35:09,120
And he thinks it's worth it to
die today, to have his

543
00:35:09,120 --> 00:35:11,080
consciousness or his brain live
forever.

544
00:35:11,080 --> 00:35:14,680
I don't know that we're supposed
to be doing that with our

545
00:35:14,680 --> 00:35:18,160
bodies.
I don't know human life.

546
00:35:18,560 --> 00:35:23,080
There seems to be something
particularly unique about our

547
00:35:23,080 --> 00:35:30,680
consciousness with our flesh
that is even biblical.

548
00:35:31,200 --> 00:35:32,280
I mean, that's not even
biblical.

549
00:35:32,280 --> 00:35:37,440
It's specifically biblical that
God created, that we took, God

550
00:35:37,440 --> 00:35:39,160
took.
I was just reading this today

551
00:35:39,680 --> 00:35:43,800
actually.
If anyone wants the sources hit

552
00:35:43,800 --> 00:35:51,800
me up because these are Jewish
sources, Midrash Tantuma and one

553
00:35:51,800 --> 00:35:54,400
of the things it talks about is
layered reality where God

554
00:35:54,400 --> 00:35:58,160
created our spirits, our souls
before he created our bodies,

555
00:35:59,720 --> 00:36:01,840
which is why our consciousness
seems to be something that we

556
00:36:01,840 --> 00:36:06,720
can't like locate in our bodies.
And actually, one thing I hope

557
00:36:06,720 --> 00:36:12,840
that we do discover from AI is
we're going to understand a

558
00:36:12,840 --> 00:36:15,920
remarkable amount about how our
our brains work, because our

559
00:36:15,920 --> 00:36:22,040
brains mostly work like LLMS
most of the time, large language

560
00:36:22,040 --> 00:36:25,720
models, most of the time our
brains work.

561
00:36:26,800 --> 00:36:31,200
We talk to people, we're in
different contexts, we're in

562
00:36:31,200 --> 00:36:33,640
social situations, we're in work
situations.

563
00:36:34,160 --> 00:36:39,720
We scroll through our library of
associations and compute in

564
00:36:39,720 --> 00:36:43,440
order to best guess and
approximate what the most

565
00:36:43,440 --> 00:36:48,120
valuable response is.
That's exactly how AI works.

566
00:36:48,120 --> 00:36:50,920
And when we're talking to
people, we even like to even

567
00:36:50,920 --> 00:36:52,400
guess what they're starting to
say.

568
00:36:53,040 --> 00:36:55,480
Like when you're using that
e-mail where it's using the

569
00:36:55,480 --> 00:36:57,800
e-mail where it starts typing,
you start typing words and it

570
00:36:57,840 --> 00:36:59,280
guesses the rest of your
sentence for you.

571
00:36:59,280 --> 00:37:01,480
And sometimes it's awesome and
sometimes it's terrible.

572
00:37:02,120 --> 00:37:03,720
We're like that in written in
person too.

573
00:37:04,960 --> 00:37:11,760
But if we can find the ways that
our brains are similar, but the

574
00:37:11,760 --> 00:37:14,040
ways that humans are different,
and you say, you know what?

575
00:37:15,080 --> 00:37:18,800
We see how memory works, but how
does creativity work?

576
00:37:20,080 --> 00:37:26,480
How does the process of
generating new information and

577
00:37:26,480 --> 00:37:28,560
not regurgitating old
information work?

578
00:37:29,400 --> 00:37:32,320
We don't really understand that.
And I think that's actually

579
00:37:32,320 --> 00:37:37,320
what's that's, I think what is
I, I believe what is puzzling

580
00:37:38,280 --> 00:37:44,640
people the most is when you give
AIA document and say A50 page

581
00:37:44,640 --> 00:37:48,120
document and say, summarize it
for me in the paragraph.

582
00:37:48,600 --> 00:37:54,960
It can do that.
If you say, what do you think is

583
00:37:54,960 --> 00:37:57,840
now going to be a consequence of
this 50 page document?

584
00:37:59,120 --> 00:38:01,640
We have no idea where it comes
up with that, with that, with

585
00:38:01,640 --> 00:38:03,560
those kind of answers.
And we have no idea how people

586
00:38:03,560 --> 00:38:04,760
come up with those kind of
answers.

587
00:38:08,320 --> 00:38:12,200
All this, I think, is to say
that we have a lot to look

588
00:38:12,200 --> 00:38:15,520
forward to, I believe.
But I think we have to tread

589
00:38:15,520 --> 00:38:26,400
very carefully because we are
hurtling towards an AI Cliff

590
00:38:29,800 --> 00:38:35,240
that could affect all of us, our
perceptions of reality, what

591
00:38:35,240 --> 00:38:39,520
reality is, what news is, what
work is, what work means, what

592
00:38:39,520 --> 00:38:43,280
life means without necessarily
having those answers.

593
00:38:43,280 --> 00:38:47,760
And we're going to be forced to
confront it a lot sooner than I

594
00:38:47,760 --> 00:38:49,280
think.
I think it's happening now.

595
00:38:50,240 --> 00:38:53,560
It has to be happening now.
Most people's day.

596
00:38:53,560 --> 00:38:55,960
Tim Dylan said this the other
day and it was another week,

597
00:38:55,960 --> 00:38:57,120
another month.
And it was so true.

598
00:38:57,120 --> 00:39:00,240
Like most jobs are BS.
Most jobs are not real.

599
00:39:00,680 --> 00:39:03,680
Most jobs you don't need to be
doing, and the reason why you're

600
00:39:03,680 --> 00:39:06,960
doing is to make you feel good.
Now, that's it.

601
00:39:08,600 --> 00:39:11,720
That's it.
But then we got to identify

602
00:39:12,520 --> 00:39:17,800
what's worth quitting your job
for, what's worth building on

603
00:39:17,800 --> 00:39:23,160
the side that you love, that you
want to create, that you need to

604
00:39:23,160 --> 00:39:25,600
create.
So interesting.

605
00:39:25,600 --> 00:39:31,520
I've been playing guitar for
five years and I think it was

606
00:39:31,520 --> 00:39:32,800
really valuable because I had
to.

607
00:39:32,800 --> 00:39:35,000
I never was crazy about the
guitar, but I taught myself the

608
00:39:35,000 --> 00:39:36,960
discipline.
The discipline of practicing

609
00:39:36,960 --> 00:39:39,840
something and playing and
getting better at it, even if it

610
00:39:39,840 --> 00:39:42,600
wasn't natural or even something
that didn't necessarily always

611
00:39:42,600 --> 00:39:44,680
speak to me because guitar was
not the instrument that spoke to

612
00:39:44,680 --> 00:39:45,840
me.
It was always piano.

613
00:39:46,200 --> 00:39:49,200
And then this couple of days
ago, I sat down, I was ChatGPT

614
00:39:49,200 --> 00:39:53,320
and I gave me a couple of finger
exercises and a couple of scales

615
00:39:53,320 --> 00:39:56,000
and chords to practice and learn
and start to coordinate a new

616
00:39:56,000 --> 00:39:58,480
skill and learn piano in my
head.

617
00:39:58,880 --> 00:40:06,320
And just the I, I, I got this
incredible feeling of passion

618
00:40:06,320 --> 00:40:14,320
and appreciation and awe and
depth that a guitar never gave

619
00:40:14,320 --> 00:40:19,560
me from playing the piano, even
though is rudimentary, even the

620
00:40:19,560 --> 00:40:22,640
beginning, I had the, the, the
basics understanding of music

621
00:40:22,640 --> 00:40:25,120
and the basic understanding of
theory that I can understand

622
00:40:25,120 --> 00:40:27,400
what I'm doing on the piano and
I'm playing just a little bit.

623
00:40:27,400 --> 00:40:30,120
I'm just.
I'm just twinkling away, but

624
00:40:30,520 --> 00:40:34,280
there's something inside me that
that that shares with the piano,

625
00:40:34,280 --> 00:40:38,480
that speaks piano.
What is that?

626
00:40:39,440 --> 00:40:42,800
What is that that speaks piano
over guitar or over saxophone?

627
00:40:43,760 --> 00:40:46,560
What is that that does that that
that makes writing work for me

628
00:40:47,400 --> 00:40:52,360
instead of math and losing
myself in writing and losing

629
00:40:52,360 --> 00:40:56,720
myself in a podcast and losing
myself in a conversation with

630
00:40:56,720 --> 00:40:59,520
someone and just seeing where
things go or just just in a flow

631
00:40:59,520 --> 00:41:02,360
in a basketball game or, or in
jiu jitsu and you and you're

632
00:41:02,360 --> 00:41:04,640
just gone and you're in the
moment and you're just, and you

633
00:41:04,640 --> 00:41:08,720
have no idea where this creative
explosion comes from.

634
00:41:10,920 --> 00:41:14,040
We're going to, we have the
potential to start to figure out

635
00:41:14,040 --> 00:41:18,240
how to identify that.
Now that's what we should be

636
00:41:18,240 --> 00:41:20,680
focusing on.
That's what AI could help us do.

637
00:41:20,680 --> 00:41:22,120
It's not going to help us
listen.

638
00:41:22,360 --> 00:41:25,760
It could help preserve you in
the way that you are in your

639
00:41:25,760 --> 00:41:28,800
ridiculously limited form
forever if you want.

640
00:41:30,560 --> 00:41:32,160
But you can use it to discover
so much more.

641
00:41:32,840 --> 00:41:35,480
You can use it to do.
We, we, we could focus on so

642
00:41:35,480 --> 00:41:37,640
many different things.
We could use it to focus on

643
00:41:37,640 --> 00:41:45,400
different sciences.
There's a, you know, I, I think

644
00:41:45,400 --> 00:41:46,640
there's a lot of potential for
good.

645
00:41:46,640 --> 00:41:50,360
I don't like to be doomsday,
even though I am scared.

646
00:41:50,480 --> 00:41:52,920
I think that being scared does
not mean you have to be glass

647
00:41:52,920 --> 00:41:55,440
half empty, just means you have
to be vigilant, just means you

648
00:41:55,440 --> 00:42:01,440
have to be thoughtful.
And I think I think that we can

649
00:42:01,440 --> 00:42:04,000
do great things.
I have a lot of, I've been

650
00:42:04,000 --> 00:42:06,480
reaching out to a lot of people
about the economics of AI and

651
00:42:06,480 --> 00:42:08,640
the downstream potential
implications of what it would

652
00:42:08,640 --> 00:42:13,800
mean for a society and money.
And we know that economics tends

653
00:42:13,800 --> 00:42:20,360
to drive everything, war, civil
war, you know it even, I mean,

654
00:42:20,640 --> 00:42:24,600
countries that are rich have a
lot or tend to be a lot more

655
00:42:24,600 --> 00:42:27,560
morally or socially, quote UN
quote developed.

656
00:42:27,560 --> 00:42:31,200
I don't know if I agree
necessarily, but I think that

657
00:42:31,200 --> 00:42:36,960
people would say that, you know,
if it comes to, if you go to the

658
00:42:36,960 --> 00:42:42,320
supermarket and there's only
it's, and it's get food or your

659
00:42:42,320 --> 00:42:46,160
kid dies, their supermarket,
your supermarket experience is

660
00:42:46,160 --> 00:42:48,240
going to be very different about
letting the person go ahead of

661
00:42:48,240 --> 00:42:50,960
you in line or take that last
piece of chicken in the in the

662
00:42:50,960 --> 00:42:54,720
supermarket.
So, you know, abundance leads to

663
00:42:54,720 --> 00:42:59,080
a potential of flexibility for
morality and abundance leads to

664
00:43:00,040 --> 00:43:01,880
potential for creativity and
meaning.

665
00:43:03,760 --> 00:43:06,240
But that means that we have to
really study that and we have to

666
00:43:06,240 --> 00:43:08,160
really understand it.
And then we have to implement it

667
00:43:08,160 --> 00:43:12,240
on a mass scale and fix a lot of
the damage that we've done by

668
00:43:12,240 --> 00:43:14,680
keeping people isolated and
keeping people glued to social

669
00:43:14,680 --> 00:43:17,640
media and keeping people
addicted to smartphones and

670
00:43:17,640 --> 00:43:20,040
addicted to chemicals and
addicted to food and addicted to

671
00:43:20,040 --> 00:43:26,680
drugs and addicted to alcohol.
And be instead driven by the

672
00:43:26,680 --> 00:43:34,880
spirit of adventure and love and
enthusiasm that that is what

673
00:43:34,880 --> 00:43:39,320
makes humanity so special.
More episodes coming this week.