Latest / Come Together with Ephraim Herschmann / #151 Podcast Guest Updates / AI / Open AI & Sam Altman / Religion, God & Vision

Transcript

#151 Podcast Guest Updates / AI / Open AI & Sam Altman / Religion, God & Vision · Come Together with Ephraim Herschmann

0:01
Welcome to another episode of come together
0:15
We are live another episode today is my third take trying to
0:21
record a solo episode. It's a muscle that I have not
0:25
used in a very long time, and it's crazy how it reflects so
0:30
quickly and how it starts to decay so quickly.
0:34
I've got a lot I want to talk about.
0:35
I've got a lot of my mind that's been going on.
0:36
But first I want to just say a couple of things about the most
0:40
recent few podcasts that I did, in case you missed them.
0:44
The one of them I recorded most recently or is least recently,
0:48
but since my last solo episode with an awesome journalist named
0:51
Mark Elliott. I really like Mark a lot.
0:54
He's really cool. I he, he's this, he told me an
0:59
awesome story and how he became a writer.
1:00
And in the writing world, the only real way to get published
1:04
is to either have some kind of obviously academic background,
1:09
Either I have a publisher or an agent.
1:11
And if you don't have any of those, it's very difficult to
1:13
get published. And so Mark was telling me the
1:16
story and how he was trying to negotiate with the publisher and
1:23
an agent at the same time. And the first person that showed
1:25
interest, he showed to the other person and the other person
1:28
signed him and then got him the deal that he ended up getting.
1:32
So he brokered his own career to begin his his literary degree,
1:38
sorry, his literary career. And he did, he did some amazing
1:42
work. We talked about 60s and 70s
1:44
Hollywood. We talked about Disney.
1:48
He wrote an amazing book about Walt Disney.
1:51
And I'm actually, I just got in the mail.
1:53
I have to finish one or two other books and then I'm going
1:56
to be reading it. But he told me that he hired a
1:59
girl to her only job for two years was to FOIA information
2:02
from the government. Freedom, Freedom of Information
2:06
Act. And that's where the government
2:09
stores all these public records about what they do.
2:11
And because we're all taxpayers and we're all buying into this
2:15
big organization, this big government in this big country,
2:18
we as individuals have a right to request information about
2:21
whatever we feel like is being that that is publicly.
2:25
It's done by the government, it's done by this collective
2:28
collaborate entity. And sometimes the government
2:33
will say no and then you have to sue them.
2:34
And then when you sue them, they hand over the information, but
2:36
they try to get make as many steps in the process in hopes
2:39
that you kind of give up along the way.
2:41
And only the, the people that really are pushing people that
2:44
really are dedicated end up getting, getting that
2:46
information through. And it could take years.
2:48
And so, so he had FOIA all this information about Walt Disney's
2:53
relationship with the FBI and found some really interesting
2:57
stuff regarding strikes, regarding communism regarding he
3:02
has some employees that Disney was concerned were communist.
3:05
Disney was very capitalistic, very anti communist.
3:08
Of course, this is around the time of World War 2 and we're
3:12
right, right around right after World War 2.
3:14
And even though we beat the Nazis, fear of the Russians,
3:19
fear of the of the Soviet Union and the Communists was still
3:23
very much prevalent in American Society.
3:26
So we talked about a bunch of that type of content, a lot of
3:29
fun. He was really awesome and he got
3:31
a lot of pushback from the Disney family for what he wrote
3:33
and he stayed strong. And, you know, we were talking
3:36
about on camera and off camera about the value of when you of
3:41
having journalistic integrity and saying the truth even when
3:46
it hurts. And it's really hard to do.
3:50
I don't do it all the time, you know, and you could say, I mean,
3:53
and there's a, there's a middle ground, of course, where you
3:55
don't have to offer up the truth if it's going to get people in
3:58
trouble or if it isn't relevant or whatever, unless it's, well,
4:02
you know, again, unless it's specifically relevant or
4:04
specifically important. And then you don't hide it, you
4:09
know, Anyway, he got a ton of pushback from Disney corporate,
4:14
from the Disney family, and he still published this.
4:16
And a lot of people won't touch him now because of this
4:19
blacklist from this enormous, the American entertainment
4:24
company has pretty much blacklisted him.
4:27
And he's still, he's still working hard and he's doing
4:31
amazing work. I also spoke with Nick Marks,
4:34
who was a, who's a professor out of, I believe it was Colorado
4:38
State University, University of Colorado.
4:41
It's one of the two. And he taught, he teaches media
4:43
studies. And when I would reach out to
4:44
him, I initially thought that he was actually a conservative guy
4:46
teaching media studies in a college.
4:49
And I'm like, how cool is that? That's so, so rare.
4:52
And it turns out he's a liberal guy teaching that, which was
4:54
also a really interesting conversation because I would say
4:58
with my experience and anecdotally, the experience of
5:02
my friends around me that I've spoken to is that colleges and
5:07
universities tend to not really be so diverse as far as
5:12
supporting right street, right right wing or libertarian media.
5:17
That seems to be more of a kids thing.
5:18
And you kind of have to be like a rebel kid or a Frappro or a
5:21
sorority girl from my and my my time on campus.
5:24
I don't know whether whether it's still like that or not, but
5:28
there was, you know, there was a type of character that was a
5:33
concert, you know, like libertarian, conservative on
5:35
campus. But most of the time it was not
5:37
the liberal arts teachers to the media studies professors.
5:40
And but Nick did a really good job putting himself in other
5:45
people's shoes. And, and he and I were talking
5:47
about trying to understand his, his, his work is trying to be
5:51
objective despite his personal opinions.
5:56
And I totally get that because I'm probably the left, as far
6:00
left as you could be on the right.
6:04
I would probably say that about myself.
6:07
I don't really have again, of affiliation so much.
6:11
And I've pretty much felt like everyone in politics has let
6:13
everyone down. And there's really no hope for
6:15
that the current system as it is.
6:17
So I can't really put those, I can't say I ascribe to any of
6:22
those ideas. And we, so he and I had a really
6:26
interesting conversation. I was just trying to understand
6:28
where he was coming from. And there's times where I
6:29
thought I disagreed with him. And there was times where I
6:32
thought that he and I really disagreed on like some
6:36
fundamental stuff about people and humanity and people and
6:39
people's nature and what's right and wrong.
6:41
And then after asking if I understood what he was saying
6:45
correctly or asking to elaborate, he, it turns out that
6:48
we did not really disagree very much at all in a lot of things.
6:52
And so it was really, really a lot of fun.
6:55
And I learned a lot about about at least his perspective and how
6:59
to have this conversation. And also it's important to
7:01
understand what is being taught and what the perspective of the
7:05
teachers are because they're the people that are raising the
7:08
youth and they're the people that are influencing the college
7:12
students, especially at public universities.
7:14
So they tend to be much larger collections of, of of classrooms
7:17
and students. So Nick was was a lot of fun.
7:21
I did a awesome episode with a guy named Alan Paul who's Allman
7:25
Brothers, the which is the Great American rock band from the late
7:31
60s, early 70s. And they had a 40 year career,
7:35
45 year career with the rotation of band members.
7:41
Excuse me, a couple of them had died first two within the first
7:45
couple of years of the of the band and then and then he and I
7:48
talked about he spent some time in China and Beijing and he was
7:53
actually taking a risk trying something new.
7:55
His wife was in media too. They'd and he was writing at the
7:59
time for slam magazine and working in music journalism and
8:04
I could. Hey everyone real quick.
8:06
If you're enjoying the show, click subscribe and rate the
8:08
show 5 stars helps a ton. Thanks so much.
8:12
Tar World, I believe. And he and he and his wife and
8:18
and he and his wife ended up going to Beijing.
8:20
They were there while the Olympics were there.
8:21
He turned out to he he got a gay guy as an Olympic journalist for
8:24
a little while and then he ended up starting a rock band, a rock
8:28
band, I guess, and really was pretty big in in Beijing.
8:35
And he had this whole couple of years stint where he and a
8:38
couple of Chinese guys had built, you know, made a band and
8:42
we're very popular. It's really cool.
8:43
So that that we had he had a great story.
8:46
We had a ton of fun in our conversation.
8:49
And finally, Doctor Karen Barrett is a musician and
8:56
studies creativity and studies the impact of music on our
9:00
brain, studies dementia and our aging brain and how music can
9:05
help activate different parts of our brain, recall different
9:10
associations. And those are important to
9:11
exercise because when we get when God forbid, and we
9:15
shouldn't know about this, but if people get dementia or some
9:19
kind of form of that, it's the neural pathways are decaying or
9:23
they're completely breaking off at certain points.
9:25
And so our brain isn't really isn't speaking to itself in the
9:30
best way that it could. And music actually helps
9:34
maintain that. So we had a really interesting
9:37
conversation about where creativity comes from and
9:39
improvising and different neural pathways and reward systems and
9:43
youth and children, sorry, and adults that they get activated
9:47
when we improvise and when we play around.
9:49
And this doesn't have to be with music.
9:51
It could also be with speaking. It could also be with poetry.
9:53
It could also be with art and painting.
9:55
So check out that episode. It was really, really, really
9:57
cool. I was, I was talking to a friend
10:02
of mine, Ari and all right, Mendelow, friend of the podcast,
10:07
friend of the show, great dude. He lives in Seattle and he and I
10:14
are extremely close. We were talking the other day
10:19
and he sent me a Diary of the CEO podcast with Karen Howe.
10:26
I want to say is her name and I'm going to look it up while
10:29
I'm saying this. And Empire of AI is the book and
10:37
Karen is yeah, Karen Howe and she was on Diary of the CEO
10:42
warning and talking a little, a little bit about open AI and AI
10:46
in general. And so I listened to the
10:49
podcast. I immediately bought the book.
10:52
I got to be honest, the topic is such an interesting topic and
10:56
she really does provide a lot of incredible information and
11:01
context to people that don't know about the whole world of
11:03
AI. Because like any other world,
11:05
and I've talked about this in the podcast in a lot of
11:07
different capacities, As for example, like I've gone into UFC
11:11
and MMA world, you find out that there's, you know, a million,
11:17
there's a whole universe within this.
11:19
There's the body trainers, there's the dietitians, there's
11:22
the recovery people, there's the functional medicine people,
11:25
there's the actual, you know, the, the, the actual martial
11:29
artists and the people that, and the, and the different forms of
11:32
fighting and then the cardio people and the strength people.
11:35
And, and then you have the actual drama and the stories of
11:38
the people of where the backgrounds are from and where
11:40
they came from and what the fighting history is.
11:42
And, and everyone's got a story. And he, he cut 30 lbs to fight
11:46
and he cut 10 lbs to fight or he's going up or down a weight
11:48
class. And you have all these
11:50
incredible, incredible stories and details, this whole little
11:54
world in and of itself. And it turns out obviously, that
11:59
you have this with AI. But the AI world is old and rich
12:04
and a lot more impactful than I think any of us realize.
12:11
Then I think most of us realize. And this book Empire of AI does
12:15
an amazing job at least outlying to to the basic reader, to the
12:22
regular relatively uninformed reader about how about different
12:28
concepts to generally be aware of.
12:31
So, for example, Open AI started, always started as a
12:37
safety company, but as a safety company has some kind of
12:43
paradoxical relationship with making money.
12:48
Because in order to be the lead safety company, the lead safety
12:53
company of the world, you need to be at the top, you need to be
13:00
at the head of the game, right? Open AI, which is a start, which
13:03
is a startup was competing with AI companies like Meta or like
13:14
Google or like Apple or Amazon. And these companies have been
13:20
developing AI for years as these enormous conglomerations that
13:25
have the GDP of countries at a time.
13:29
And not only and, and these corporations, these, these tech
13:33
companies are so powerful and so wealthy and so influential that
13:37
they really could basically take control over whole countries at
13:41
a time or mass parts of populations of countries.
13:44
So, for example, Karen Howe talks in the in this book about
13:49
there's parts, you know, an enormous and really crucial part
13:54
of safe AI is training the AI properly, right?
13:59
Meaning you have you're creating a personality, you're creating a
14:03
kid, you know, you're giving it access to more information than
14:08
we can even be aware of. Then we can even know what to do
14:11
with. You're giving AI all this
14:13
information and then you're asking it a question and asking
14:16
it to summarize all that information, all this compute
14:20
into a one word answer, into a one sentence answer, into one
14:24
paragraph answer. And what that ends up doing, we
14:28
can't predict what it's going to say or what information it's
14:32
going to draw from because we don't know all the information
14:35
it's drawing from. It's like take all of Twitter,
14:38
take all of Facebook, take all of Google and tell me how to
14:43
water my tree. And like imagine all the context
14:47
in which anyone could say water your tree appropriately,
14:50
inappropriately as far as gardening, as far as as far as
14:54
tree maybe be a reference to something else.
14:56
And all of Google, all of YouTube, all of X, all of
15:02
Twitter, whatever it is, all of Core and all of Reddit and give
15:05
me that information in the paragraph you can.
15:07
We can't predict what that's going to say.
15:09
So we have to train it. We have to train it what's
15:10
appropriate. We have to train it what's
15:11
acceptable. And there's the more advanced
15:15
training and then there's the more lower level but equally
15:19
important training, which is basically manually teaching it.
15:24
This is acceptable. This is not this considered
15:26
inappropriate? This considered OK for those
15:29
jobs for the lower the, the bottom tier of training AI and
15:34
this industry has been around for a long time.
15:36
Meta and Facebook famously, infamously have people.
15:42
It's, it's a, it's, it's a completely inhumane job because
15:45
what you're doing is you're, you're subjecting people to 10s
15:52
to, to to days, months, years of I mean these people, you know,
15:57
if you're in Venezuela or you're in Kenya and you're worried and
16:00
you're getting hired by open AI to, to, to to teach AI what's
16:04
considered a sexually explicit or gory or violent image, right?
16:11
You're looking at all this stuff, all these images or all
16:15
these. Text descriptions and sentences.
16:17
And, and, and quotes and paragraphs and essays even at a
16:20
time, and you're reading and seeing the most repulsive,
16:25
disgusting, terrible, terrible stuff, the darkest stuff on the
16:30
internet's there. And we're paying people a dollar
16:33
to $4.00 an hour to spend 20 hours a day trying to teach
16:39
training AI what's acceptable or not.
16:45
So that's just one component of the AI world and AI safety.
16:50
And in order to train the AI to do this, we need to make money.
16:56
In order to be able to make money, we have to sell our
16:59
products or at least have to commercialize our products
17:02
because that's the way that America works.
17:04
You could get people to invest in you, but then they expect
17:07
something out of that investment.
17:08
So for example, when Open AI made a partnership with
17:12
Microsoft and they, Microsoft initially I think gave them a
17:15
billion dollars, then 10, and I think I believe they're up to
17:19
$100 billion. But double check me on that.
17:25
Microsoft's not doing that for free.
17:26
They're expecting returns. They're expecting, hey, I gave
17:29
you a billion dollars. What do you have to show me for
17:31
that? And Open AI has an enormous
17:35
amount of pressure to show them, hey, we created this new
17:38
product, We created this great product.
17:39
But if they're so focused on safety and they're so focused on
17:42
wait, we can't advance until we make sure that this machine,
17:45
that this software, that this code, that this bot, whatever
17:48
this is, this AI is operating in a way that is safe and
17:53
predictable and within the confines of the restrictions
17:56
that we set for it. If they don't have time to do
17:59
that, then Open AI is essentially it is it at a
18:04
constant state of civil war over but whether to be safe or not,
18:10
and this is supposed to be the safety company too.
18:16
It's all too crazy. It's all too crazy then, you
18:20
know, there's obviously the economic potential issues of AI
18:23
and there's something else that that Karen Howe talks about
18:27
where for example, there I actually don't remember if she
18:33
talked about this in the book yet.
18:35
She talks about the environment. I'll get to that in a minute,
18:39
but I think I read online maybe then about an AI tax.
18:45
And so this would be that we're going to switch.
18:48
The government would switch taxing labour from people to
18:53
taxing labour of AI. If AI is going to take jobs away
18:58
from people and going to generate so much productivity,
19:01
it doesn't make sense to tax the citizens that are working on a
19:06
much smaller scale at this point in time and humanity for
19:11
America. And instead we should be taxing
19:15
the companies and the corporations whose AI are
19:20
creating those values and taking those jobs and generating that
19:24
value. And then you take a common pool
19:26
and you just when you redistribute it to people who
19:29
don't have jobs anymore because they lost all those jobs to AI.
19:32
And then you wonder, what, what are you going to do when we're
19:35
on, when we have no jobs? And what are we going to do when
19:39
our jobs are meaningless or useless and everyone's on social
19:43
media all day or on drugs all day or constantly consuming
19:48
something or buying something. And then the humanity ends up
19:51
like in Wall-e, Yeah, you don't want that either, really, You
20:02
know, So you got to think about those repercussions.
20:04
And you got to think about what to do financially.
20:07
You got to think about the fact that AI in order to work on the
20:14
scale that it is working, in order to grow on the scale that
20:17
it's growing, it needs data centers.
20:19
And for data set and data centers take reason require,
20:23
excuse me, resources. And resources include all the
20:30
resources that humans need like real estate and land.
20:35
For example, Chile is example of a company that sorry, a country
20:40
that is basically being used to mine AI components, minerals.
20:48
And the real estate and land is being used as as as as Centers
20:54
for data. And they it has to take clean
20:57
water. The data centers they have to
20:59
take clean water because water from pipes and water from in the
21:03
minerals in waters that are used.
21:05
So sorry context you need water for cooling.
21:09
The reason why you need to cool these certain these sensors is
21:12
imagine if you have a computer and you're overworking the
21:14
computer gets warm gets hot. Imagine you have 100 computers
21:17
or 1000 computers. Imagine that with all these data
21:21
centers that are required to compute and store and power all
21:26
the and generate all everything that all the AI companies, Meta,
21:31
Apple, Instagram, sorry Instagram, whatever Google, Open
21:35
AI, Enthropic, Clod, the whole everything.
21:42
Those all need servers which all need to be cooled with water by
21:50
using water that needs to be clean water because the bacteria
21:54
in the mineral and the minerals in tap water or from the pipes
21:58
or from sewage, much like humans where it's not great for us to
22:02
drink that and we generally need a filter or some kind of form of
22:06
filter to clean our water. It actually would impact the
22:10
hardware and the data centers and caused decay and actually
22:14
caused them to break. So the cooling centers need to
22:17
use clean water. They need real estate, they need
22:19
electricity, they need power. And like all these things that
22:22
like we need that, like these things that would bring people
22:25
out of poverty. Remember, the question isn't
22:28
whether or not this technology exists.
22:30
The technology certainly exists. And the reason why we know that
22:33
is because China, who America hopes is still ahead of I, you
22:38
know, we'll see. I hope so.
22:40
I don't know if I believe that, but China who is our famous
22:45
infamous competitor, they they're doing pretty good.
22:56
They're doing pretty good and they are working on alternative
23:01
fuels that we're sources that we're not using.
23:03
And they are they're just, they're stepping up in ways.
23:12
They lifted 650 million people out of poverty.
23:16
That's what I was going at. They lifted 6.
23:19
They lift, they lifted almost double the population of the
23:23
United States out of complete poverty.
23:27
So we have the resources and the technology to do it.
23:31
And the question is what we're going to focus our efforts on
23:33
the AI companies and the AI world and the leadership this
23:37
these tech Bros in Silicon Valley, their excuse for using
23:45
all these resources for AI and not for people at the moment is
23:48
because down the line, AI is going to be such a great tool
23:52
that no one's going to need anything.
23:54
And so we're just making it short term pain for a long term
23:57
gain. And I don't know why we can't
24:03
have some short term gain and long term gain sometimes,
24:08
especially if we worked hard enough to create that technology
24:13
that we know that has been put in practice within the last 20
24:18
years on planet Earth, should be able to lift millions of people
24:24
out of poverty, should be able to create a higher scale, higher
24:32
quality of life than ever before.
24:34
And even if you want to say we do, which I do think we do,
24:38
obviously I think most of the world, even in the worst parts
24:42
of it, was probably better off than they were 50 years ago or
24:45
100 years ago. I, I got to believe I, I, I
24:48
think so. We seem to be spending an awful
24:57
lot of resources on AI and we only think that it's worth the
25:02
trade off because Sam Altman thinks so.
25:08
Because Dario, whatever his name is over at Anthropic thinks so.
25:14
I even know if you think so. Bra or Brockman, Greg Brockman.
25:19
It's a very small AI world and most of these guys keep on
25:25
branching off and starting their own companies, not because it's
25:29
such an amazing environment and everyone's thriving.
25:32
It's because no one trusts each other and because the
25:34
competition is so intense and the and they feel, everyone
25:36
feels that the threat that's so existential to life is so
25:44
prevalent that they need to take matters into their own hands
25:49
instead of collaborating, instead of working together.
25:55
And it seems that unfortunately, that's it, that Sam Altman is at
25:58
the root of all this because most of these people have come
26:02
and gone through him and come and gone as a consequence of him
26:07
or because of him or stated that he was the reason why.
26:10
They feel that there is no transparency or minimal trust or
26:16
murkiness in the vision of what AI is going to be.
26:22
And that's crazy, and that's crazy.
26:25
That's crazy. So I don't think that, you know,
26:28
and I think there's a lot of amazing avenues of science for
26:31
us to be able to go down. I think there's a lot of avenues
26:34
of life, of technology that we can go down to improve
26:40
everything without having to necessarily make these enormous
26:45
sacrifices on such a grand scale.
26:47
Or at least have a little bit more of a diverse perspective as
26:50
to who, you know, what the actual end goal is and who's
26:53
going to accomplish it. And 25% chance that it's
26:59
existential to humanity. One out of four.
27:06
I think that like we don't need to continue down.
27:09
Like we could hit the brakes with that and we could focus on
27:14
other sciences, we can focus on implementing nuclear, we could
27:17
focus on and that, you know, I mean, we could catch up.
27:19
We can catch up on what it actually means.
27:22
And this is actually an important part of AI too, What
27:24
it means to be a human, what it means to be a person.
27:27
What does it mean to be creative?
27:28
What does it mean to work? What's the purpose of working?
27:30
And when our jobs are gone, when we don't need to work, when
27:34
there is universal basic income, when we are all living on that
27:36
Wally ship, what are we going to do?
27:42
Are we going to be distracted? How do you find meaning?
27:45
Every Elon Musk is so concerned about preserving consciousness,
27:51
but we're not focusing on exercising consciousness.
27:55
We're not focusing on building on exercising its muscles.
27:58
In fact, everything around us has been put here to decay it,
28:05
including the things that I'm habitually doing on a regular
28:08
basis. I'm on social media a lot.
28:10
I'm on my screens a lot. I am not present a ton.
28:14
I am not looking around my backyard and thinking I should
28:18
play, you know, I should play with my kid there often enough.
28:21
I'm not looking around at my neighbors, like someone to talk
28:23
to and a relationship to have and a band to start and, you
28:28
know, and a bonfire to have and concert to go to often enough.
28:32
Because I'm in my own head listening to the podcast about
28:34
about how the world's ending. So is humanity going to be
28:39
preserved? Probably.
28:41
But what does it mean to be a person?
28:43
What does it mean to have value? What does it mean to have
28:45
meaning? I'm happy we have religion.
28:52
I'm really, really happy in times like this.
28:54
We have religion. And I'm really, really happy
28:56
times like this that I have Judaism and that the Western
29:04
world has done so much to divorce itself from religion
29:09
because, and I actually do understand this, there was,
29:13
there is for a lot of people and historically was an enormous
29:19
amount of dogma that goes with religion.
29:21
That is to say that a lot of times if someone says why, you
29:26
say shut up because I told you so.
29:29
And a lot of times they really, and every time, every time there
29:32
is a why and every time there is a how and every time there is a
29:36
So what. And the question just is, are
29:39
you willing to ask those questions?
29:41
And what does that mean? And the people that are dogmatic
29:48
are the people that don't want to answer those questions or
29:50
don't want to look into those questions, or the different
29:52
dogmatic people are the people that don't that, that that tell
29:54
you to be quiet. And to no, it can't be right.
29:59
What you're saying isn't right. If it conflicts with my
30:01
perception, with my perception of reality, it cannot be the
30:04
case. And Judaism, from my
30:09
understanding and from my school of thought is the shattering of
30:12
that. That's what Abraham represents,
30:14
Avraham, the forefather, and it's the end.
30:18
Shimsunafal Hirsch, Samsonafal Hirsch, who is I've spoken about
30:21
before, but is lived in the 1800s in Germany.
30:24
Incredible Rabbi reading his stuff has reading a lot of his
30:30
stuff has changed my life as far as his views on education, on
30:33
his views on family, on his views on just just really,
30:38
really extremely thoughtful and reason God views on Torah and
30:45
views on personal responsibility.
30:47
And one thing that he is constantly, constantly
30:50
emphasizing, and I think that this is something that we
30:53
sorely, sorely need in our society, is the idea that there
31:00
is a greater moral objective good and humanity is objectively
31:10
flawed. And we are constantly on the
31:14
search to get closer to that objective good.
31:21
Not easier, not comfort, not comfort.
31:26
We're trying to get better, we're trying to get good, we're
31:30
trying to grow. We're trying to get closer to
31:33
the divine truth of the capital T in God that is God and not
31:37
gods, and the oneness that is reality.
31:44
And when we just reject information because of dogma, we
31:50
can't get closer to there. Abraham started as an
31:53
iconoclast. That was the way that he found
31:56
God was by breaking down perceptions.
31:58
The way he found God was breaking down dogma and saying
32:02
that doesn't make sense, that doesn't make sense, something
32:04
must make sense and then communicates with the universe
32:12
in some kind of manner. And again, there is so many
32:19
layers to reality. There's so many layers to
32:24
consciousness. There's so many layers to the
32:27
world around us. And we've been talking about
32:30
this forever, forever. All religions, ancient
32:34
religions, modern technology. The story of the matrix is just
32:39
another story of the story of God, you know, and this world is
32:42
is is is something that you know, is some kind of
32:46
preparation for the world to come.
32:48
And reality is layered and God created the world and with
32:51
different, different stages of development and evolution and,
32:56
and, and I mean, just let layers of reality and layers of
33:02
meaning. And we have to try to get
33:06
better, not to confuse ourselves for the end all be all.
33:13
And what it seems to me be and what Sam Altman and what these
33:20
tech billionaires, Peter Thiel, who's his mentor, by the way,
33:26
original backer introduced him to his boyfriend or husband in
33:30
the hot tub, 3:00 in the morning, ketamine parties and
33:34
stuff like that. These are people that are more
33:38
interested in preserving themselves forever than
33:42
elevating themselves to be a part of a greater truth of
33:44
reality. And Sam Altman.
33:50
Oh crap, I forgot. The company signed up to be part
33:57
of this, to be part of this company.
33:59
Hang on. I think he was fun helping fund
34:01
it and brain upload that there was going to upload his digital
34:07
consciousness and his brain. Ah. 02018 but Sam Altman just
34:20
dropped $10,000 deposit on a brain upload paying a start load
34:24
a start up to you to euthanize you so for so that it can one
34:27
day maybe bring back a digital copy of your mind.
34:31
According to Here's the MIT Tech Review in 2018, Sam Altman tells
34:36
MIT Technology. Review.
34:37
He's pretty. Sure, mines will be digitized in
34:39
his lifetime. And then on Instagram over here.
34:44
Who's this account? Artificial intelligence In 2018,
34:48
Sam Waltman paid a $10,000 deposit to join a wait.
34:51
List for a Nectome. That's the company Nectome, a
34:54
startup offering 100% Fatal Brain 100.
34:57
Percent fatal brain preservation procedure.
35:05
And he thinks it's worth it to die today, to have his
35:09
consciousness or his brain live forever.
35:11
I don't know that we're supposed to be doing that with our
35:14
bodies. I don't know human life.
35:18
There seems to be something particularly unique about our
35:23
consciousness with our flesh that is even biblical.
35:31
I mean, that's not even biblical.
35:32
It's specifically biblical that God created, that we took, God
35:37
took. I was just reading this today
35:39
actually. If anyone wants the sources hit
35:43
me up because these are Jewish sources, Midrash Tantuma and one
35:51
of the things it talks about is layered reality where God
35:54
created our spirits, our souls before he created our bodies,
35:59
which is why our consciousness seems to be something that we
36:01
can't like locate in our bodies. And actually, one thing I hope
36:06
that we do discover from AI is we're going to understand a
36:12
remarkable amount about how our our brains work, because our
36:15
brains mostly work like LLMS most of the time, large language
36:22
models, most of the time our brains work.
36:26
We talk to people, we're in different contexts, we're in
36:31
social situations, we're in work situations.
36:34
We scroll through our library of associations and compute in
36:39
order to best guess and approximate what the most
36:43
valuable response is. That's exactly how AI works.
36:48
And when we're talking to people, we even like to even
36:50
guess what they're starting to say.
36:53
Like when you're using that e-mail where it's using the
36:55
e-mail where it starts typing, you start typing words and it
36:57
guesses the rest of your sentence for you.
36:59
And sometimes it's awesome and sometimes it's terrible.
37:02
We're like that in written in person too.
37:04
But if we can find the ways that our brains are similar, but the
37:11
ways that humans are different, and you say, you know what?
37:15
We see how memory works, but how does creativity work?
37:20
How does the process of generating new information and
37:26
not regurgitating old information work?
37:29
We don't really understand that. And I think that's actually
37:32
what's that's, I think what is I, I believe what is puzzling
37:38
people the most is when you give AIA document and say A50 page
37:44
document and say, summarize it for me in the paragraph.
37:48
It can do that. If you say, what do you think is
37:54
now going to be a consequence of this 50 page document?
37:59
We have no idea where it comes up with that, with that, with
38:01
those kind of answers. And we have no idea how people
38:03
come up with those kind of answers.
38:08
All this, I think, is to say that we have a lot to look
38:12
forward to, I believe. But I think we have to tread
38:15
very carefully because we are hurtling towards an AI Cliff
38:29
that could affect all of us, our perceptions of reality, what
38:35
reality is, what news is, what work is, what work means, what
38:39
life means without necessarily having those answers.
38:43
And we're going to be forced to confront it a lot sooner than I
38:47
think. I think it's happening now.
38:50
It has to be happening now. Most people's day.
38:53
Tim Dylan said this the other day and it was another week,
38:55
another month. And it was so true.
38:57
Like most jobs are BS. Most jobs are not real.
39:00
Most jobs you don't need to be doing, and the reason why you're
39:03
doing is to make you feel good. Now, that's it.
39:08
That's it. But then we got to identify
39:12
what's worth quitting your job for, what's worth building on
39:17
the side that you love, that you want to create, that you need to
39:23
create. So interesting.
39:25
I've been playing guitar for five years and I think it was
39:31
really valuable because I had to.
39:32
I never was crazy about the guitar, but I taught myself the
39:35
discipline. The discipline of practicing
39:36
something and playing and getting better at it, even if it
39:39
wasn't natural or even something that didn't necessarily always
39:42
speak to me because guitar was not the instrument that spoke to
39:44
me. It was always piano.
39:46
And then this couple of days ago, I sat down, I was ChatGPT
39:49
and I gave me a couple of finger exercises and a couple of scales
39:53
and chords to practice and learn and start to coordinate a new
39:56
skill and learn piano in my head.
39:58
And just the I, I, I got this incredible feeling of passion
40:06
and appreciation and awe and depth that a guitar never gave
40:14
me from playing the piano, even though is rudimentary, even the
40:19
beginning, I had the, the, the basics understanding of music
40:22
and the basic understanding of theory that I can understand
40:25
what I'm doing on the piano and I'm playing just a little bit.
40:27
I'm just. I'm just twinkling away, but
40:30
there's something inside me that that that shares with the piano,
40:34
that speaks piano. What is that?
40:39
What is that that speaks piano over guitar or over saxophone?
40:43
What is that that does that that that makes writing work for me
40:47
instead of math and losing myself in writing and losing
40:52
myself in a podcast and losing myself in a conversation with
40:56
someone and just seeing where things go or just just in a flow
40:59
in a basketball game or, or in jiu jitsu and you and you're
41:02
just gone and you're in the moment and you're just, and you
41:04
have no idea where this creative explosion comes from.
41:10
We're going to, we have the potential to start to figure out
41:14
how to identify that. Now that's what we should be
41:18
focusing on. That's what AI could help us do.
41:20
It's not going to help us listen.
41:22
It could help preserve you in the way that you are in your
41:25
ridiculously limited form forever if you want.
41:30
But you can use it to discover so much more.
41:32
You can use it to do. We, we, we could focus on so
41:35
many different things. We could use it to focus on
41:37
different sciences. There's a, you know, I, I think
41:45
there's a lot of potential for good.
41:46
I don't like to be doomsday, even though I am scared.
41:50
I think that being scared does not mean you have to be glass
41:52
half empty, just means you have to be vigilant, just means you
41:55
have to be thoughtful. And I think I think that we can
42:01
do great things. I have a lot of, I've been
42:04
reaching out to a lot of people about the economics of AI and
42:06
the downstream potential implications of what it would
42:08
mean for a society and money. And we know that economics tends
42:13
to drive everything, war, civil war, you know it even, I mean,
42:20
countries that are rich have a lot or tend to be a lot more
42:24
morally or socially, quote UN quote developed.
42:27
I don't know if I agree necessarily, but I think that
42:31
people would say that, you know, if it comes to, if you go to the
42:36
supermarket and there's only it's, and it's get food or your
42:42
kid dies, their supermarket, your supermarket experience is
42:46
going to be very different about letting the person go ahead of
42:48
you in line or take that last piece of chicken in the in the
42:50
supermarket. So, you know, abundance leads to
42:54
a potential of flexibility for morality and abundance leads to
43:00
potential for creativity and meaning.
43:03
But that means that we have to really study that and we have to
43:06
really understand it. And then we have to implement it
43:08
on a mass scale and fix a lot of the damage that we've done by
43:12
keeping people isolated and keeping people glued to social
43:14
media and keeping people addicted to smartphones and
43:17
addicted to chemicals and addicted to food and addicted to
43:20
drugs and addicted to alcohol. And be instead driven by the
43:26
spirit of adventure and love and enthusiasm that that is what
43:34
makes humanity so special. More episodes coming this week.