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This is going to be a feisty episode. Is it?
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Two of us are on Greenwich Mean Time, two of us are on Pacific.
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J Cal still asleep in his head. I'm good, actually. You good? I'm good. All right. Well, great to be back.
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Welcome to the All-In Conspiracy podcast, where we repeat false statements and help spin them into tales of struggling against the establishment, the elite and the mainstream media.
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We will deliver to you, the people, the revolution against the powers that be, unless it offends You must be Beep.
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TRYING TO GET MY INVITE FOR NEXT WEEK. All right.
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We also enjoy Mums the word.
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We'll also enjoy sharing with you fantastic stories of opulence, Let's be neutral.
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opulence, leisure, and benevolent greed. Here we go.
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Joining me today are my co-hosts, General David Sacks, commander of the fourth battalion of the internet tweet brigade. General, welcome.
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Joining us from a remote location. In Moscow.
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Has there been like an establishment take over of the pod?
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I mean, what's up with this intro? Yeah.
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Every argument they make against us, you're basically just conceding it's true. Yeah, I know. Exactly.
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From his 12th century Mediterranean castle, Il Duce, Chamath Palihapitiya. Welcome, Chamath.
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How is the Mediterranean diet treating you? Um blue. Blue? Blue.
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And Emperor Nero Calacanis, ruler over podcasts, paid events, entrepreneurial universities, and dental SPVs.
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Emperor, thank you for letting me sit in your throne today. It's good to be here. Thank you. Dental SPVs. Shout out to my dentist.
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Wait, did you say king of STDs? That's what you said. SPVs. Oh, SPVs. Dental SPVs. Yeah.
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That's the thing with certain STDs, where once you are king, you're going to be KING FOR LIFE. THESYNDICATE. COM YEAH, THANK YOU.
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YOU'VE been doing You said five shows a week lately. Your voice is shot.
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I My voice is starting to go.
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So, I I asked you if you'd moderate and you you thankfully said yes. I've got the energy. I missed last week.
2:18
I enjoyed listening to you guys with BG. Great episode.
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Sorry I couldn't join, but let's kick it off. That's funny.
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I saw him watch the episode that I missed.
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He's not interested, He's like, "I'm not on the show. I'm not interested."
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don't have time to participate, I don't really have time to watch it.
2:34
The truth is, Sacks, why don't you admit to everyone that where you're in a show, you probably watch it four or five times. All right. So, let's kick this off.
2:45
Obviously, you guys recorded right before the Wagner Group attempted coup or potential coup or theorized coup began last week.
2:53
So, Sacks, you kind of sent out a text saying the show's already stale because, you know, you kind of missed that uh that news cycle by publishing right after it started, but you recorded right before.
3:04
So, let's do just a quick recap of what happened with Russia, Ukraine, and particularly its Wagner Wagner Group rebellion.
3:17
Last Friday, the Wagner Group, which is a Russian paramilitary organization led by Yevgeny Prigozhin, launched what seemed like an armed insurrection against Russia.
3:26
Wagner had occupied portions of Rostov-on-Don, a city of over a million people, a regional capital, and headquarters of Russia's southern military district before setting off towards Moscow and then abruptly stopping, I think about 200 km before reaching Moscow City.
3:41
At that point, there was supposedly a negotiation.
3:47
The president of Belarus got involved, and uh Prigozhin decided to step down.
3:53
Putin said, "I'm not going to persecute or I'm not going to prosecute you for these crimes."
3:56
He was given immunity, and it was uh announced that all the members of the Wagner Group were given the option of returning home or joining the Russian military, and the Wagner Group was going to be dis- uh dissolved.
4:09
Sacks, maybe you can kind of give us your summary of the events that took place.
4:15
And then we'll talk a little bit about the interpretation of what we think this means for the conflict in Ukraine.
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Well, you're right that this uh rebellion took place just after we dropped our last episode.
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And so, everybody, uh both on Twitter and in the comments, was dunking on me for my take on last week's episode that the much hyped Ukrainian counteroffensive was was not succeeding, that it was in fact failing.
4:38
I think there's abundant evidence for that, which hasn't changed.
4:41
Even CNN had written an article basically supporting the idea that the counteroffensive was not living up to what had been promised.
4:49
And so, everyone was in the comments saying that my take had basically aged like milk.
4:53
And this uh armed rebellion or mutiny by Prigozhin was evidence that the Russian regime was about to collapse, that Russia was in fact on the verge of civil war.
5:02
And you saw the exact same people who had oversold the counteroffensive now overselling this mutiny as something that would bring down the Russian regime and and the war.
5:15
And of course, that that did not happen.
5:19
It was certainly a highly unusual event, and I've read takes now from every different corner of the internet about what it was and what took place.
5:24
You have people speculating that this was all staged. I do not believe that.
5:27
I do believe that it was an insurrection or mutiny by Prigozhin.
5:32
I think the trigger for it was the fact that his Wagner organization was being merged in with the Ministry of Defense and the regular Russian army, and his men were all being made to sign contracts with the Ministry of Defense.
5:46
That would have resulted in a giant loss of income and status for Prigozhin.
5:51
Simultaneously, for months now, he's been criticizing the Ministry of Defense, specifically the the Minister of Defense, Shoigu, and the chief general of the general staff, Gerasimov.
6:03
So, he's been vocally critical of them.
6:05
And I think that this basically erupted into a a mutiny by him, where he basically tried to leverage his position.
6:14
Like you said, he marched what they now think are about 8,000 men, which is about a quarter of Wagner, into Rostov-on-Don.
6:22
He then took the Ministry headquarters and sent about 3,000 of his men on a convoy to Moscow.
6:30
I think that, although this is probably best described as a mutiny, I think that it did have coup optionality to it.
6:35
I think that Prigozhin was seeking to find out how much support Putin had and who might join him.
6:43
And he had put out a number of statements that I think, from the Russian regime's point of view, could be described as seditious that morning.
6:51
And there's a lot of evidence that he staged this attack on his base.
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He claimed that there was a missile attack by the Ministry of Defense, and that's what launched this march for justice.
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And in his comments, he was careful not to criticize Putin directly, but he had a lot to say about the Ministry of Defense and the overall conduct of the war.
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And it was, I think, harshly critical indirectly of of Putin.
7:13
And I think he was looking to see who might support him.
7:18
And what happened is that on the way to Moscow, during this convoy, nobody supported him.
7:23
In fact, all the statements came out from the other generals, including Surovikin, including all the regional governors, of uh members of the Duma, and other important figures in Russian society.
7:37
And there wasn't a single person willing to publicly support Prigozhin.
7:40
And that's when Putin went on TV, called this basically an act of treason and a stab in the back.
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And at that point, I think Prigozhin's options were pretty limited, and he basically took a deal that was brokered by Lukashenko, in which he would go into exile in Belarus, uh in exchange for basically being allowed to live.
7:59
Uh that was basically the deal that was ultimately cut.
8:02
And so, I think where things stand today is that, although I think this was an embarrassment and a black eye for the Russian regime, uh it never looks good for a regime to have any kind of mutiny or insurrection.
8:17
And I think that it does raise questions that Putin's now going to have to answer to his various allies and supporters about how stable his regime is.
8:24
I think ultimately, Putin has ended up in a place of consolidating Russian society behind him.
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Like I said, there were no power centers that supported this mutiny.
8:36
They all rallied to Putin's defense, and the people of Russia, even though Prigozhin is a popular figure, being kind of a war hero from the Battle of Bakhmut, the Russian society supported Putin.
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I think he's at something like 80% poll numbers.
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So, I think where things stand Well, like Levada Center, which is an independent polling agency, for example.
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These are not the Russian regime's own numbers, and when the poll numbers say in a poll that you don't support Putin?
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Well, I don't know how Levada Center, what their methodology is, but these numbers, when the numbers are bad, are cited by Western sources.
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But there are other forms of evidence, too.
9:12
You may have seen this video that went viral over the past few days of this song that's now the number one chart-buster in in Russia, where it's this very patriotic Russian song, where they're basically singing, "I am Russian."
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That's sort of the main chorus.
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Nick, can you pull up the song?
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I'd like to see this, please. Coming at you, 95. 5. I love Russia.
9:36
Oh my god, this is some serious propaganda. Wow, yeah.
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I mean, that looks like a pretty good party.
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If you look up the the lyrics to the song, the English translation of the lyrics, the gist of it is I I'm basically proud to be Russian and I don't care who doesn't like it.
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That's basically the the lyrics of it.
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you get invited to that party?
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I got so many jokes I'm not going to make them.
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I know you got to be careful. Be careful here, folks.
10:10
You got to be careful here.
10:12
It looks like a fun party. It's a catchy song.
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I mean, I love to dress up and show up.
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Tell me where to show up, Putin.
10:18
Tell me where to show up, Putin. I think the point here is that Russian society is united behind the state in wanting to fight this war and I think that part of the reason why Prigozhin's mutiny was so oversold as an imminent coup that would
10:33
bring about the collapse of the Putin regime and of the Russian war effort and of their front line is because that we since the beginning of those war we've had this narrative that if we applied enough pressure to Russia that there'd be a palace intrigue and a
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palace coup and that liberal forces inside of Russia would rise up and topple the dictator Putin and basically get them out of this war and I think what's happened is fairly predictable but it's the opposite of that which is the Russian people are rallying around the flag and rallying around Putin the
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war leader and they are a patriotic people just like the Ukrainians and I think both these countries that both the Russians and the Ukrainians are a proud people and I think they're in a fight to the death and I think that both countries Okay. regardless is existential
11:17
regardless is existential and we have basically stuck ourselves in the middle of this fight to the death between these two countries and I don't see this working out very well. Okay.
11:26
So, look, I I will make an admission.
11:26
I consider myself a modestly well-read person, modestly well-informed.
11:34
I had never heard of the Wagner Group or Prigozhin prior to this coup attempt last week.
11:39
Chamath, Jay Cal, had you guys heard of this person before and the Wagner Group? Yeah. Yeah.
11:48
Oh, well, maybe I'm an idiot or I'm just not interested.
11:49
I think what was so surprising was like how out of the blue the story seemed to be last week that there was this disagreement between this person that commanded this paramilitary organization who then turned around against Putin and stood up against him and marched back towards Moscow and it felt to me like it came a little bit out of the blue and was such like a a weird kind of shocking event.
12:11
Did it feel kind of like that to you guys that there was surprising instability and the surprising potential revolution happening locally?
12:20
I think stepping back here and just looking at the news cycle obviously I don't think many people expected this. This was a wild card.
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And so people could be humble in you know, their belief of like how much they actually understand about what's going on there.
12:35
The Russian soldiers are not in favor of this war.
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This is a war that's very unpopular in Russia actually.
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And for the Ukraine, having been invaded by Russia, they're fighting for their land and they're going to they are much more motivated.
12:46
I wouldn't believe any of this propaganda but this is a bit of a Rorschach test.
12:49
Everybody on the left got on Twitter and said this is the end of Putin.
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Everybody's going to rise up in the streets and they overplayed that you know, angle of the story and then of course the right or people who are pro-Russian or anti-the West backing this war are going to take the other side, Freeberg.
13:05
They're going to take the side of you know, oh, everybody loves Russia.
13:10
80% of people are voting for this.
13:10
It's ridiculous to think that anybody in Russia is going to answer "Do you like Putin? Do you support Putin?" on a survey. Can you imagine?
13:19
Putin's a murderous dictator who kills all of his enemies and he controls through violence.
13:23
Nobody's answering a survey correctly.
13:25
This you know, top song is complete propaganda.
13:29
Putin has control of the entire media apparatus there.
13:34
What this showed actually, if you step back and you look at to the party though if you were invited?
13:38
Well, I mean, are there going to be potential LPs there?
13:42
Last week I It's just a joke, folks.
13:46
But stepping back, if you look at modern-day dictators they tend to stay in power for about three decades. Putin's in his third.
13:53
And uh I think we're going to see in uh the next 10 years Putin lose power and he's going to be out of power.
14:03
And when we look back on it it's going to be one of two causes.
14:05
It's going to be either cancer which you know, the speculation is he's he's had cancer and that's why he disappears from view because he might be getting treatment.
14:14
Uh and we'll look back on us that the end of his power will be and his control of Russia which he controlling these controlling through violence and fear of violence and threat of violence is exhausting.
14:27
You have to be paranoid and that's why it generally doesn't last that long especially compared to the West where we have a democracy and people last about a half decade.
14:37
He will we'll look back on his end which will be in the next 10 years either through cancer or through his invasion of Ukraine.
14:43
This is the biggest blunder he's ever made and and this is a really crazy sign that somebody would actually attempt or even float a coup is insane.
14:56
He's murdered every single person who has ever even either challenged his authority in a minor way.
15:02
The fact that his one of his right-hand men, this is one of his tight inner circle.
15:08
The fact that one of the people in his tight inner circle would actually start heading towards Moscow is insane.
15:14
So, to say this wasn't a big deal and Putin's you know, now consolidated power and everybody's in the street dancing, that's just not true. It's not true.
15:24
This is just simply not true.
15:26
I never said it wasn't a big deal.
15:26
I wasn't talking about you.
15:28
I was talking about the mids on Twitter.
15:29
I never mentioned your name.
15:30
I think that um your point Jay Cal at the beginning that this doesn't really seem to change anyone's point of view on the outlook, your point of view sounds like it's the same as it was a week ago.
15:40
Sach, your point of view is probably the same as it was a week ago.
15:44
I think there are a couple of takeaways here.
15:46
Fir- first of all they've had polling of opinion in Russia for a long time and like I said, when the polls go the way that the Western sources want, no one questions their accuracy.
15:57
Again, I don't know exactly the methodology but Levada Center is an independent pollster that Western publications do trust.
16:04
I hear them repeat it over and over again.
16:06
And you know, by their methodology which I assume hasn't changed, I think Putin's popularity before the war is around 65%.
16:15
Now they're showing it at about 83%.
16:17
Jason, you may not like the war and you know, I certainly don't like the war the war, yeah.
16:22
Nobody likes the war but I I think it is simply a fact that the Russian people have rallied around the flag and they do support this war and and Putin as the leader.
16:33
Now, I do think he has egg on his face here from this Prigozhin uprising.
16:36
In terms of did did I see this coming?
16:37
No, I didn't have this on my bingo card.
16:39
I don't think anybody else did either.
16:42
However, did I know who Prigozhin is? Certainly.
16:44
I mean, I've been tracking Prigozhin's statements since around February.
16:47
He's been vocally criticizing the Ministry of Defense specifically Shoigu and Gerasimov in increasingly insubordinate and you could argue even seditious ways.
16:56
I'm really kind of surprised in a way that he wasn't dealt with before this and I'm sure that the Kremlin is kicking itself for probably not dealing with it sooner.
17:07
But in terms of why he's still alive, I think that Putin had a really tough decision to make about you quash this rebellion completely which would have led to horrific images of you know, violence potentially in Moscow or Russians hurting Russians and Russians killing Russians that might have actually led the the Russian front to question itself or collapse.
17:30
So, I think he did the expedient thing which is he cut a deal.
17:31
He got Lukashenko to help broker it and he cut a deal.
17:34
And I think at the end of the day, I think that he made the cool-headed decision that was in his and in Russian interest which was to avoid this to getting to the point of a bloody violent insurrection.
17:47
Okay, Chamath, any um any point of view shift for you coming out of the Prigozhin event of the last week on Russia-Ukraine?
17:57
I mean, I want to know how much he got paid to stop marching towards Moscow. Yeah.
18:00
I mean, it is like a mob boss, right? It must have been a lot.
18:08
Not bad for a guy that was what Putin Putin's caterer a few years ago, right?
18:12
He started a catering business.
18:12
Guy spent nine years in jail.
18:14
This guy's like nine years in jail.
18:16
It's it's like the Sopranos.
18:19
He went to jail for nine years for selling illegal hot dogs or something and all of a sudden 30 years later, the guy got just paid billions of dollars to basically stop his paramilitary group from taking over one of the largest countries in the world.
18:30
It's the largest nuclear arsenal in the world, yeah. It's so crazy.
18:34
so just so you know who this guy is, I mean, he he really is the street thug that Putin is always accused of being. He was a street thug. He did go to jail.
18:44
He was one of these guys who came up in Russia as a businessman when to be a businessman you you had to be so tough.
18:51
Businessmen were getting murdered left and right by gangsters.
18:52
You almost had to be a gangster yourself.
18:54
Apparently, he made some money in the supermarket chain business and that led him to create a catering business which brought him to Putin's attention and he started catering for the Kremlin.
19:04
He's sometimes called Putin's chef.
19:07
I don't think he was a chef himself.
19:08
He was the guy who owned He owned the business and then from there he was given the license to create this PMC, this private uh military corporation. Wagner Group.
19:19
He wasn't the only founder of it.
19:21
He had a co-founder who was actually the military man behind it but Wagner became this this group of mercenaries who do all sorts of business in Africa mainly where they are working on behalf of governments there to protect mineral resources or oil wells, all sorts of things.
19:40
a Sopranos captain, who would he be like? Phil Leotardo?
19:41
Does like 20 years in jail, comes out.
19:44
I think it's sort of like John Gotti going against Michael Corleone. Yeah.
19:48
that Putin is sort of the very cold, rational guy with everything in his head who's very calculated and doesn't reveal much.
19:56
More like a Michael Corleone.
19:58
Whereas I think that He's emotional. He's emotional. Yeah.
20:03
He's been saying these statements for months here, which I don't see how they could possibly Loose cannon.
20:05
And the crazy thing though is is that what you saw on Twitter and social media was unrestrained glee, really delirium Sure.
20:15
over the idea that Prigozhin might topple Putin and become the custodian of Russia's thousands of nuclear weapons. Yeah.
20:22
And you know, so my comment on this whole thing is be careful what you wish for.
20:26
Why in the world would Americans want that?
20:28
We'd be jumping out of the frying pan into the fire.
20:31
You know, I've been saying since the beginning of the war that this fantasy that Putin's going to be toppled by a palace coup and you're going to replace him with Navalny or something like that or we're going to get Gorbachev 2. 0.
20:40
I said that was always unrealistic and what you're much more likely to end up with is an even worse dictator or Possible, yeah. or a hardliner.
20:49
And I think that is what would happen if Prigozhin had taken over.
20:52
I think it would have been much worse for the West.
20:55
The final point is what's the takeaway from here?
20:57
Is I think this is going to put more pressure on Putin to conduct the war in a more violent way.
21:01
I I know that people already think that the war is horrible and violent, but Putin has been criticized by hardliners on his right for basically making the war a special military operation instead of an all-out war.
21:15
And Prigozhin I think expected to find more support among the sort of ultra-nationalists in Russia and among the military who have been critical of Putin for waging the war in what they consider to be too half-hearted or an incomplete way.
21:29
They would like to see this declared to be a war.
21:32
They would like to see the full mobilization of Russian society.
21:34
And this is the problem that I see now is that I think Putin already knew, but this has to underscore for him that this war is existential for him personally.
21:45
If he loses, it's the end of not only his regime, but probably his life in Russia.
21:49
And I think he's going to do whatever it takes to win this war.
21:51
And I think you could see now over the next few months a full mobilization in Russia.
21:56
And I think that this could lead us to the next point of escalation in this war.
22:00
That is if this Ukrainian counteroffensive actually successful on some level.
22:04
Right now it is it is not succeeding.
22:06
So there's no reason there's no reason for Putin to do that, but I get if this counteroffensive succeeds, you will see the next level of escalation.
22:13
So Sachs, you did a great job stringing six points together.
22:14
I think my key takeaway is which is now 18 points you've made.
22:20
So you can retire for the rest of the show.
22:21
My key takeaway from your series of statements, however, is an important one, which is to watch the potential escalation driven by Putin here. Any wrap-up?
22:32
Otherwise, I'm going to move forward with the affirmative action.
22:34
you know, thinking Thinking about this like there's a famous Sun Tzu quote, "The supreme art of war is to subdue the enemy without fighting."
22:43
This is a a big mistake and we need to make sure that we don't get into an a war with Taiwan and China and China over Taiwan. So Okay.
22:49
We have to avoid these things and then that's where Sachs and I are in alignment.
22:54
Sun Tzu Calacanis, we heard it here first.
22:57
Let's uh move forward with peace.
22:59
I can only hope that the conflict ends soon as I've always said. Mhm.
23:03
I realized over the last week how little I know about the Russian military conflict with Ukraine.
23:10
And I appreciate Sachs's contributions. Super helpful.
23:12
I went to Cal, UC Berkeley, 1997, fall of '97.
23:18
And it was the last year that Cal had affirmative action admissions.
23:25
And I remember at that time there was a big case a guy named Bakke was rejected by the University of California Davis Medical School.
23:32
And he alleged reverse discrimination in 1974 and sued the University of California.
23:39
And eventually it became a landmark US Supreme Court case, Regents of University of California versus Bakke.
23:44
And in 1995, the UC Regents voted to eliminate affirmative action.
23:50
So the year that I was at Cal, I think it was the last year of affirmative action admissions.
23:54
And it's obviously been a pretty hot topic here in California for the past, you know, 25 30 years.
24:06
This morning the Supreme Court ruled on two separate cases regarding using race as an admissions criteria in college admissions.
24:15
And the votes were six to three against affirmative action in the University of North Carolina case and six to two against affirmative action in the Harvard case.
24:24
Ketanji Brown Jackson recused herself because she previously served on Harvard's board of overseers.
24:30
All the conservative as they're, you know, kind of characterized judges voted to strike down affirmative action and all the as they're characterized liberal judges voted to keep it.
24:37
Both of these cases were filed in 2014 by a group called Students for Fair Admissions.
24:44
And effectively the court said that at Harvard, at UNC, the schools were systematically discriminating against Asian Americans in violation of civil rights laws by using their race as a as a system for for profiling, excluding, and trying to be more inclusive of a more diverse and racially diverse set of applicants.
25:04
So Chamath, I'd love your read, I guess, on the surprise or this was an accept expected case.
25:11
I think Sachs and I mentioned this before, but I think we both expected this to happen.
25:19
I think it's probably important to maybe set up a more practical explainer.
25:26
Friedberg, so Nick, if you want to just throw up that image that I just sent you, we can sort of explain the genesis of the lawsuit.
25:35
So what you can see here is admit rates into Harvard by race, ethnicity, but also by academic decile. Yeah.
25:47
And so what it basically shows in a nutshell is an African-American student in the 40th percentile of the academic index is actually more likely to get in than an Asian student at the 100th percentile.
26:02
And so that at the core is sort of what was being you That means that means that the Asian-American student had better scores than 99% of other applicants. Right. And still didn't get in. Right. Right.
26:18
So you have to go back, I think, to 2003 when essentially what the Supreme Court said is like, "Look, we're going to allow this affirmative action stuff to last roughly for another 25 years, but by that point we expect that the work that needed to be done will have been done."
26:36
Again, this is them saying this, not me.
26:41
And so I think what today does is actually quite important not just for what it means for universities, but also what it means for private enterprises.
26:51
So just to take a second on this.
26:54
I think what happens today is the pretty obvious stuff, which is that you have to change university applications, you have to change all of the admissions profiling, all of the stuff that you would normally do.
27:08
You probably, I'm not even sure if you can even have a box where you can declare race. Maybe you can or cannot. I don't even know.
27:14
But all of that changes today.
27:16
So then the question is, well, what's the first order derivative? What changes next?
27:21
And I called someone who's a pretty well-known constitutional Supreme Court lawyer on this.
27:26
And the next step is probably going to be around athletics-based and legacy-based admissions.
27:35
So athletics-based admissions are pretty obvious, which is you don't really have great grades, but you're really stupendous at a sport that's important to that school.
27:46
So then they let you in because they want to compete in said sport for whatever reason.
27:51
The legacy one is even more prickly, which is nah, you're kind of a dummy, but your parents are rich and or went to the school before.
27:58
And so then they let you in as well.
28:01
And his thought on this is that those things will go away.
28:09
Because if you can't use race-based admissions to kind of balance the scales, then it'll become pretty quick where somebody launches a legacy-based lawsuit or an athletic-based bias lawsuit and wins that as well.
28:24
So that's the first order derivative.
28:25
So, you know, the thought Are those cuz those aren't constitutionally protected, whereas equality based on race No, but it becomes a huge headache for these schools. Right?
28:38
And so you're going to be fighting these admission standards constantly changing.
28:41
And so if you're not going to let, you know, a bunch of poor minority black and brown kids in, but you're letting in the sons and daughters of rich important people, I think that that's going to paint that school in a very bad light.
28:56
So I think that's important, Chamath.
28:58
white, typically white, typically white legacy Although one would say the great thing over the last couple of decades is there have been a lot of minorities that have gotten into these very elite schools, which means this their kids would be the first generation that's eligible for legacy, but you're going to wipe that away.
29:16
So I think from a just a social stigma perspective, and I have a solution for this, which I'll get to at the end for those people.
29:22
But So I think that's the first order derivative.
29:24
The second order derivative is now what lawsuits get launched and what are the implications for private companies, right?
29:31
So right now this affects any institution that receives federal funding.
29:35
And that includes all the universities.
29:37
So there's no private or public university really except for a handful that don't take this money.
29:40
So they'll all have to do this.
29:44
But the really important question after that will be what happens to companies like Apple or Facebook or Exxon who have race-based programs to try to attract African-American engineers or Hispanic chemists, whatever the program is that you want to come up with.
30:05
Will those get challenged and will those companies have to change?
30:07
And my friend's thoughts on that were that yes, that those would also change.
30:13
And that's going to have a really important impact on private enterprise and how they approach this stuff and how DEI stuff works.
30:18
And frankly downstream, how ESG works because all these ESG checkboxes now, some of them will actually become illegal, right?
30:25
So I think the importance of this decision can't be really understated.
30:30
It's going to the changes will be slow and then they'll be fast.
30:37
They'll first touch higher ed, but then I think they'll touch private enterprise.
30:39
And so I think it was a it was a very important decision in America that just happened.
30:46
Chamath, what is what is the right ethics and and values?
30:51
I mean, what are you guys I guess we could just do this around the table.
30:53
J Cal, maybe you kick it off.
30:56
Should we I mean, from your point of view, do you think that values should include racial diversity in admissions in universities?
31:05
Yeah, this is like the ultimate Or is the values about equality of opportunity for everyone regardless of race, right?
31:13
You're asking the exact right question, I think.
31:15
That's cuz I'm the world's greatest moderator, but yeah, go ahead.
31:19
Doing a solid job so far.
31:19
And this creates a lot of cognitive dissonance for people, right?
31:21
Because you you really want to believe that the world is a meritocracy and uh, you know, if you were to take other pursuits in the world, you'd never say like we should let race, gender age affect people's performance in the 100-yard dash or their their compensation at a company, right?
31:41
All of that should be based on achievement.
31:46
And so there is a question on what achievements should be taken into account when you apply to a school.
31:52
And it's pretty obvious the legacy thing, you know, is you know, a back door into these schools.
31:59
But we want to feel like we're also making progress because listen, the world has been unfair.
32:06
The world was built on slavery and our country has you know, is only 150 years past that and so rights act was what, 1964 or 65?
32:14
Like we've we've we really want to see everybody achieve here.
32:19
So I think you have to pause for a second and say, well, if the goal is you want to see you know, black Americans perform better and I think that's the the underlying concern here.
32:33
And it is based on the legacy of America.
32:36
Well, how do you do that?
32:36
And I think we're looking way too far down in the educational pipeline.
32:43
The solution here is really child care.
32:45
The solution here is nursery schools, pre-K, elementary school education.
32:47
And those things need competition and that's where people fall behind.
32:51
To be looking at this at the end of the academic journey is I think crazy.
32:55
So you know, when I'm president, I'm going to have 365 day a year you know, uh child care and pre-K and that's where we should if we really want to try to make up for some wrongs in the history of this country and try to have better outcomes, we need competition in schools which means probably breaking some of these unions and giving people vouchers and choice.
33:19
And then we have to invest more in the early stages of education.
33:23
And I think everybody wants to see a better system here.
33:27
DEI to Chamath's point is it is illegal to hire people based on race, gender, any of those criteria, obviously.
33:35
And the DEI programs are trying to fill more applicants.
33:38
So their goal typically, in the way they don't break the law is to just try to in their best cases find more applicants.
33:46
Um but even that does feel like there's many times in life when um people will say things in corporate America like we have too many white guys in this these positions.
34:00
We need we cannot hire another white guy.
34:02
So the reality of DEI that I've seen up close and personal when I was at AOL, I've told the story before.
34:09
Somebody said to me, there's no way for us to make you an EVP. You have to stay at SVP. And I said, why is that?
34:13
Like I'm doing all this EVP level work.
34:15
And they said, cuz you're a white guy.
34:19
And the entire company is white guys at EVP and we cannot add another white guy there, but we'll just give you the same bonus compensation, so don't worry about it.
34:28
And so there's all kinds of games being played here, but I think it's great that we're having this conversation, right?
34:32
It's a hard conversation for America to for me, the I've talked about this in the past.
34:36
I've always had concern when we make the shift away from equality of opportunity to equality of outcome.
34:47
Because we all have this objective that we want to see everyone have equal rights to success in some way in the United States.
34:54
The question is at what point do you move beyond opportunity where everyone is given an equal opportunity in this country to invest themselves in transforming their own lives versus a equality of outcome where regardless of how much you do, how much effort or your trials you are given the same as everyone else.
35:20
And that ends up looking a lot like socialism and it's very concerning because I think it limits progress and opportunity for everyone.
35:26
The real challenge with this particular topic is college admissions about outcome or is it about opportunity?
35:32
It's outcome in the sense that you spend 12 years going to elementary school and high school and working hard to get yourself into college.
35:43
So it's the outcome of all of that effort and some people aren't given the opportunity to have success during those 12 years.
35:50
And you know, and it is an outcome What do you think we should do?
35:54
And it's an opportunity because it's about going to college because without having a great college cycle, you may have a more tougher time getting into a into the workforce.
36:00
So it that is why it's a hard value question for me.
36:04
I I I don't have a great answer on this.
36:07
But I'm just pointing out it's it's a lot like the abortion argument where both sides have some value-oriented point of view that feels like it's negating the other person's point of view.
36:19
But at the end of the day, they're they're both coming from either this is an opportunity or it's an outcome decision and that's what makes it so challenging.
36:25
The National Bureau of Economic Research did a study in 2019 that they published.
36:31
And what they found was that 43%, so 4 3, 43% of white students admitted to Harvard were athletes or legacy students or children of faculty and staff or had a relative that were donors to the school. 43%. Wait, it's rigged?
36:51
And then they found on top of that that 75% of those white students admitted from those four categories would have been rejected if they had been treated as a normal applicant.
37:01
So I think for all the people that are looking at all the black and brown kids that may not get into a place like Harvard if you don't look at these other categories it is a it's a bit of a gross injustice, quite honestly.
37:16
So I think that these institutions have to evolve and if if you're going to be forced to be meritocratic, then actually be meritocratic.
37:23
And by the way, I actually am fine with legacies and donors, but I think what should happen is you should just publish a rate card and you should make it hyper transparent. And so I love it.
37:34
For the rich guy who's got an idiot son or daughter, let's just be upfront and honest with everybody.
37:38
It costs $50 million to get into Stanford.
37:40
It costs $80 million to get into Harvard.
37:43
We all know these numbers, so we should just publish them.
37:46
You should pay the price and be done with it.
37:48
And for Harvard and Stanford and Yale and all these schools having an extra 10 or 20 dummies but an extra two or three billion may be a reasonable trade-off, but at least it would be transparent and fair.
38:00
Right, this is an important free market question as well because these are private institutions.
38:03
They're privately funded.
38:05
Not if they take federal dollars, they're not. Agreed, yes.
38:08
But if they take federal dollars, they're not.
38:09
And then it becomes a government processing.
38:11
It's government influence. It's a state school.
38:14
All those Is there a separate category here?
38:15
Just like country clubs or any private membership club where the members of the club get to decide who they want to admit to the club?
38:25
And is that un-American and should the Supreme Court and should our Constitution have a role in defining how private institutions make decisions about who gets in?
38:33
No, Harvard could absolutely return all the federal funding, the billions of dollars a year they get.
38:37
That's totally reasonable then they can decide to just focus on legacy admits.
38:43
That's totally reasonable.
38:43
It's within their rights.
38:45
Sacks, I we got to hear Sacks, I I know that I know that you used up your quote your speaking quota already.
38:49
Well, yeah, I didn't want to I didn't want to butt in so already.
38:53
my Give him four of my points. I want to hear it.
38:55
Yeah, I talked about it in the last second.
38:55
You get four of J Cal's minutes. Go ahead.
38:57
I give you four of them minutes.
38:58
So yeah, two two points, I guess.
39:00
So on the legacy thing, I agree with Chamath that we should get rid of it. It's not meritocratic.
39:03
I think that if they did publish a rate card, that would be more honest, but they would be too embarrassed and ashamed to do that.
39:11
But I think making that argument exposes the hypocrisy of it.
39:15
I've already told my kids I'm not helping them get into college, so they're going to do it on their own.
39:18
And so look, I think the legacy thing the way.
39:21
That's the best gift you can give kids. Yeah. That that perspective. Sorry, go ahead, Sacks.
39:25
I didn't mean to interrupt.
39:26
So that's that's point number one.
39:26
Fully agreed on on the legacy thing.
39:27
With respect to the decision itself, the I'm sorry, Sacks.
39:31
Can can I just clarify that?
39:33
Do you believe that the legacy thing should be like in federal law?
39:36
I mean, is that a government thing?
39:38
Or do Do that that's how those institutions should behave? Cuz those are different.
39:42
I mean, I'm asking are you suggesting that the law should be involved?
39:45
That the government should be involved?
39:47
I don't know if it's a legal thing cuz I don't know how to implement that law, but I think it's something they should stop doing one way or another.
39:51
Maybe it should be a law, but I think it should stop.
39:54
So, I think that's point number one. thing.
39:56
For private For pri- private membership So, just let me just double click on that.
40:00
Do you think that should extend to private membership clubs like country clubs as well that they shouldn't be allowed to decide who they let in and don't let in?
40:06
What makes it different that it's Harvard?
40:08
Is it because it's education versus any other private membership club?
40:12
No, because it takes federal funding. It takes taxpayer money.
40:14
You and I should not pay for some person to be able to get into a school they don't deserve to get into just because their parent went there or just because their parent wrote a check. That's unreasonable.
40:25
And if they don't take federal funding?
40:28
These schools take so much federal funding that they're quasi-public institutions, even the private ones.
40:33
So, that's the distinction That's the distinction for you just to be clear.
40:37
Yeah, and also there is a strong meritocracy opportunity argument on this.
40:43
And I think it's why that whole parents college admission scandal was was such a big deal is that for a lot of people in this country the ability to have your kids advance themselves by being the first to get into college or going to college or going to a better college.
40:58
That is a big part of creating opportunity in this country.
41:01
So, for people to try and defraud that, I think created a huge backlash.
41:04
So, look, I think that the legacy thing needs to end some way or another.
41:10
I don't know exactly what the right legal implementation is.
41:16
I have two questions for the panel.
41:17
Number one, should you be able to say by geography, "Hey, listen, we're Harvard or we're Stanford.
41:22
We we want to have a representation of people from around the world, so we're going to you know, have the top three students from each country or you know, or by population however you do it, you know, mathematically, come in.
41:35
So, a little bit of geography because I did hear from one of these coaches that cost like six figures to get your kids into the college.
41:41
They said the best thing you can do is like move to Kentucky.
41:46
You know, and then Harvard and Stanford are looking to get a certain number of students from each state.
41:51
I don't know how true that is, but they said that's like one of the the top ways to do it and then Well, do you remember Jason?
41:55
Just to build on your point.
41:56
I don't know if you guys remember, but a few years ago the the in-fashion thing to do was to learn to play squash.
42:02
And I remember all these parents telling me that and they had kids that were older than my kids and they were they were hiring full-time squash coaches because apparently squash was like something angle. angle shots. Yeah.
42:15
I think like stop with the angle shooting, guys. Yes.
42:18
The gun should go off, you should run the race, and your time is your time, and you should go to whatever the best school is that you deserve to get into based on your academic ability.
42:28
Now, going back, the big problem, and I think Jason, you really nailed it on the head, trying to fix it with affirmative action at the university is still quite unfair in the sense that there are so many black and brown kids, I think, with tons of potential that don't even get there.
42:47
And so, the real question is what are you doing at the grade school and at the high school and at the preschool so that you actually get more of these kids to the starting line?
42:54
Because fixing it when they're 18, I think, is a little too late. Yeah. Right?
42:59
Fixing it when your kids are three, four, and five years old, that's when they deserve and need all the help in the world. Two years old.
43:08
That's why we need school choice. We need charter schools.
43:10
We need to break the monopoly that the unions have over the schools, running it running it for their own benefit and not for the kids. enemy.
43:16
If you define institutional racism as conditions that trap people in conditions of poverty across generations, I'd say the abysmal quality of our public schools are number one.
43:28
Number one, two, and three.
43:28
And the reason is cuz there's no competition and the unions run it for their own benefit.
43:33
They How long did they shut down these schools for in California cuz they didn't want to work cuz they're afraid of No, no, don't say the C-word. We just got a label. God. We'll beep it out.
43:41
We're going to beep it out.
43:41
We're going to beep We got labeled.
43:44
That was not for the benefit of kids and it wasn't even medically necessary.
43:46
That was a benefit they saw for themselves. Yeah.
43:49
Chamath, you come you come from a family Yep.
43:52
that were members of unions because they worked for fire, for police. Um, is that right? Yeah.
44:00
We speak negatively about the effects of the teachers unions on our public education system and it I I I I think it's absolutely correct.
44:08
But how do you share the point of view from the other side?
44:11
If you're a teacher and you're a member of the union and the union takes care of you, what's the argument Yeah, sure.
44:18
to say this union is damaging public education and the teacher that's working in the union and a member of the union says this is necessary for my livelihood to protect me, for my benefit.
44:29
Help us hear the point of view because we all have the strongly held point of view that the unions are destroying and eroding public education.
44:34
But what's the other side?
44:37
People have the right to form unions.
44:41
But what we all do is we are forced to be consumers of one educational product because of how we pay taxes.
44:46
We pay taxes in I think in my in California we each pay $16,000 into the educational system.
44:52
And so, if you're a parent, you should get that 16K back and be able to choose what you do with it, so there's competition.
44:58
So, the unions can have protection, but there still should be competition for these services.
45:05
And I I I think they're they're two separate issues. Yeah.
45:06
I There was one other thing, which is I just want to give a shout-out to a nonprofit that I support called SMASH Academy, smash. org.
45:15
It's done by Mitch and Freada Kapor.
45:18
The uh Mitch Kapor founded Lotus 1-2-3.
45:22
If you're under the age of 40, you might not know him.
45:27
And what they do is they realized that a lot of the students who do get into good colleges, it turns out a lot of the black and brown students, they get accepted and they're behind in math.
45:35
And so, what SMASH has done is they have a three-year program.
45:40
And I go speak at it sometimes and I donate money to it and I encourage you to do the same.
45:43
They have a this intensive summer program.
45:45
So, before you go to college, Chamath, if you were one of those students, you know, you might get into college and then they drop out or even worse, they switch from a STEM to liberal arts.
45:57
degree to a non-STEM degree because they're two years behind on STEM or a year behind on STEM.
46:01
And so, the Kapors found this like little opportunity to to kind of catch people up and I think that's what we have to do.
46:08
We have to address this much earlier and not put a band-aid on it.
46:12
Yeah, and in the system the the Ivy League system um, you know, needs to Well, it's not just Ivy's, right?
46:19
I want Let's not just pick on Harvard, but it's like it's like all the state schools. No, all institutions. Okay.
46:26
All institutions that receive federal funding.
46:28
They need to take a deep look in the mirror and say, "Are we doing the best thing for society?"
46:30
The second question I had for the panel was Well, I'm not getting the union point of view, by the way, but yeah. Yeah.
46:35
But are pure academics the best way to accept people into a college or should there be some blend of it?
46:41
Like putting sports aside cuz that's an obvious one.
46:45
But, you know, is there's academics, but then there's also creativity.
46:46
You know, if you you might be terrible on your SATs or standardized tests and you might be an incredible virtuoso pianist.
46:51
So, I think what is the criteria and making that criteria fair is what we all want and it feels tremendously unfair.
46:59
My point of view is if the government is funding these schools, then the government certainly has to have a point of view on what's the reasonable model for admissions.
47:11
If the government's not funding the schools, I love a diversity in a marketplace.
47:16
I love having different schools having different admissions criteria that allow different people to find their path through different institutions.
47:25
To your point, Juilliard does not care perhaps as much what you did on, you know, your SAT in chemistry.
47:36
And art schools do not care as much how well you did in math.
47:41
And STEM schools don't care whether or not you won an art competition.
47:44
And I think that that's the important thing that we need to preserve.
47:48
We need to preserve optionality for institutions to define what sorts of individuals they want to try and recruit and progress and train and get ready for the workforce and the path in life that they then choose versus trying to create a cookie-cutter model for what the government says it's fair for everyone.
48:07
And as much as we can take government funding out of these institutions and out of these systems and give them the freedom to set their own admissions criteria and create differential educational systems, I think that's going to create the best diversity of a workforce.
48:22
And I'm I would kind of be more excited about that sort of an institutional system than one that is standardized by the government.
48:29
You know why that'll never happen?
48:33
Because the profit motive of these universities is really to be shadow organizations for their endowments.
48:40
And the thing with endowments is that the people that work there very much want to get paid and behave like profit-generating organizations.
48:48
And I think the issue is that if their sole job was to really fund the operational expenses of the university, then the endowments would be run very differently, right?
49:04
Like take Again, I just looked up on the internet, but Harvard has about the operating expenses are roughly five and a half billion dollars a year, but the revenues are about five and a half billion dollars a year, right?
49:15
So, if instead you had to basically fund, you know, there was essentially no revenue per se, right?
49:21
There was there was very little tuition and you didn't take any federal funding, you'd have to come up with five billion dollars a year, so you'd just basically take that as a draw from your endowment.
49:32
The endowment would be run very differently.
49:34
It would be a don't lose money endowment.
49:38
That would generate very low ball returns.
49:40
I think the problem with that is that that's not how the endowment at Harvard works.
49:47
They wouldn't necessarily make risk-seeking investments in things like private equity and hedge funds and venture capital and to the extent they did, they would just make much, much fewer, much, much smaller or both.
49:58
So, I think what you're saying could be possible, but the problem are probably the endowments at these universities.
50:03
Okay, well if 53 billion dollars by the way Harvard's endowment now, so Yeah, it would be 10%.
50:08
Can anyone tell me who the largest real estate owner is in San Francisco?
50:14
Without looking it on the internet. Oh, no, I know, I know. It's that Art Institute.
50:19
The Academy of Art University.
50:19
I knew this because they kept buying things and using them, I think illegally.
50:25
used all the profit over the years to buy more real estate and she accumulated the largest real estate portfolio. Yeah, yeah, yeah. In San Francisco. Who is she? Sorry, who is she?
50:32
The The founder, I forgot her name.
50:35
This is a for-profit university or private or I mean a a non-profit university?
50:39
Yeah, there's a lot of artists that come out of Academy of Art and they work in a lot of different industries including industrial design, including animation.
50:45
That's actually what I'm saying.
50:48
Is it like RISD or is it like actually an art school?
50:50
Oh, no, it's a great art school. Yeah, Academy of Art.
50:55
Anyway, let's keep going.
50:55
So, look, speaking of STEM, making a big pivot away from art to AI.
51:01
Couple big news items, you know, the AI frenzy continues here in Silicon Valley all the way from early to growth stage funding through to M&A events.
51:12
We saw this week Databricks, which is a privately held data infrastructure company announced that they were acquiring MosaicML for 1. 3 billion dollars.
51:24
That headline number is based on a cash and stock purchase price where the value of the stock that was being used to acquire MosaicML was based off of the last round's valuation for Databricks, which was 38 billion dollars from a fundraising that they did in 2021.
51:40
So, arguably the valuation should be lower and the overall purchase price could be considered lower, but that's besides the point.
51:47
MosaicML, as you guys may remember, is a company I mentioned a number of episodes ago led by the founder of Nirvana, which was an early AI business that was acquired by Intel and then he started MosaicML and he offers open-source models and I shared the performance data of their most recent announcement on the show a few weeks ago.
52:12
You know, there's rumors.
52:12
I don't have any confirmed reports, but there's rumors that MosaicML saw their ARR grow from 1 million to 20 million dollars since January.
52:21
There was other rumors that said they were only at 6 million of revenue.
52:24
Regardless, Databricks is paying a pretty hefty premium and I think it begs the question, what do data infrastructure, database companies end up looking like in the future if AI has to become part of the core infrastructure of every enterprise and this is creating a big shift.
52:40
So, Sachs, as our enterprise software investor expert, maybe you can share with us what this means for the sector.
52:50
Does this buoy excitement for AI infrastructure startups?
52:54
Does this change the investing landscape?
52:56
Is it just reinforcing what folks are already doing?
53:02
I think it's a a reinforcement.
53:02
I mean, this space is probably the hottest space where you're talking about like AI infrastructure for enterprises.
53:06
I think it's probably the hottest space right now in in venture land.
53:09
We actually looked at this deal.
53:12
We had a small allocation in their next round.
53:13
They had a term sheet for a series B.
53:19
Emergence was actually going to lead it and This is MosaicML? Yeah. Yeah.
53:24
I don't know if I'm supposed to be telling you all this, but No, it's done now.
53:28
Yeah, go ahead yeah, it's time to This is a great This is why people tune in. Breaking news. Breaking news.
53:31
They had a term sheet from Emergence to raise 50 million at 400 post. Wow.
53:39
And yeah, and we were going to have a small allocation in that and as I recall, the valuation was somewhere around 30 to 35 times ARR, which actually is not that insane for a very fast-growing company in a hot space.
53:52
So, that implies about 10 million of ARR.
53:55
I don't remember the exact figure, but I think it that's sort of the ballpark, but growing very, very quickly.
54:00
I mean, up from like one or two at the beginning of the year. Right.
54:05
So, I actually understand why someone would want to acquire or invest in this company.
54:11
Like I said, I think we wanted to invest and while we were sort of, you know, trying our best to get say anything when I talked about them on the show a few weeks ago.
54:18
You were just sitting there mum's the word or Actually, I knew that this deal was was basically in the works because the founder called us up and he had already promised us a small allocation in the round.
54:29
Naveen did and he called up and said, "Actually, I've got this deal, so we're putting the round on hold."
54:33
And so, I didn't think I should say anything cuz obviously it was still ongoing.
54:40
But yeah, we we knew about this deal that was kind of coming down the pipe.
54:42
I we didn't know for sure that it would happen, but but yeah, we we heard it was in the ballpark of this like 1. 2, 1.
54:47
3 billion dollar number, which like you said, because Databricks is a private stock, maybe it's only half of that or 750 or something like that, who knows.
54:57
It's still a great deal, but you know, a lot of people are saying it's a crazy deal.
54:59
I don't think it's a crazy deal because before this happened, after Naveen signed the term sheet for the series B, an investor came over the top to invest at a 700 million dollar valuation.
55:12
So, people were kind of going crazy.
55:14
Now, I don't think that's necessarily irrational behavior.
55:18
I think that's more of evidence of a mania going on, but I think that what he got offered is obviously a fantastic deal and I think what it's evidence of is that these big enterprise infra companies are going to try and build an end-to-end tool chain here.
55:31
And I think MosaicML had a very, very important part of the tool set, which is training up these models, basically maximizing GPU efficiency because GPUs are basically the scarce item right now.
55:45
We have a GPU shortage and it's probably not going to get better for a year or two if that.
55:51
So, this is a very important part of the of the stack and I think it's probably a smart acquisition for both Databricks and I mean, remember Snow Snowflake, which competes with Databricks, also acquired Neva, which was founded by one of my colleagues, a guy I work with and and new really great guy, Sridhar, for 150 million dollars last month that deal was announced.
56:12
And the pattern recognition that seems to emerge here is that if you're in the data infrastructure business, it seems like it's becoming critical to level up, that it's not just about storing and moving and manipulating data, but the interpretation of data through models and the tooling to build those models becomes a critical component of all of
56:35
these tool kits that these software companies have to provide to their enterprise software companies and it's a big leveling up that's necessary, which seems to me there's other companies out there like them that are also going to need to strap on tools like this to make themselves competitive in this marketscape, which means that there are more acquisitions still to come. Yeah. Yeah.
56:54
Chamath, J Cal, you guys agree or have a different point of view?
56:58
Looking at it, it's a it's a big number, the headline number, but I agree with Sachs that the actual numbers half the number.
57:03
So, if it was, you know, if you look at the number of engineers they had based on LinkedIn data and PitchBook data, probably 60, 70 employees, 80 employees and then 40, 50 of them are engineers.
57:15
So, that puts it at 30 million dollars per engineer and that's one way to look at these acquisitions.
57:21
And I think, you know, probably 3 to 10 million dollars per engineer for like really high-end engineers is more of the going price, but if this is half that amount because they bought it with Monopoly money, in other words, their 2021 price for their company, it's great.
57:37
And then you get nailed it.
57:38
Freeberg, what's happening is this layer of natural language on top of any service, whether it's something as simple as Yelp or something as complicated as a giant financial company with tons of transaction data, being able to talk to it and understand it and then have your machine learning team build tools so business owners don't have to hire data scientists.
58:05
The actual business leaders can talk to the data and get back answers or just say, "Hey, tell me about our customers.
58:12
How have they changed over the year?"
58:13
And then, "Hey, that's pretty interesting.
58:15
Tell me more about our customers and, you know, how are they reacting to these three new products?"
58:23
And you will get back in intelligence that previously was unable to be accessed.
58:31
And so, I was I was just at Sequoia yesterday with or two days ago with the latest seven graduates from our accelerator.
58:37
We bring them to meet with Sachs and his team.
58:41
We bring them to meet with Sequoia.
58:42
And when we were at Sequoia, I realized that of the seven companies, four of them would not have been possible before these machine learning APIs were available. And OpenAI is but one.
58:53
There are now in the companies I'm talking to, they're they're trialing Freeberg on average six, seven, eight language models before they pick one and they're not picking OpenAI every time.
59:05
Putting that aside, these businesses were not possible before this technology was introduced and available via API in the last six to 12 months.
59:14
And I think there's a bunch of businesses that economically would not work that now work. I can give one example.
59:22
There are countless meetings that are recorded over Zoom, right?
59:28
Think like a local school board meeting.
59:30
Well, nobody could ever make a database of all the discussions going on at local school boards and then analyze all that.
59:37
But now, because all of those are saved on Zoom and they occur on Zoom and they're available for public record, you could ingest every single one of those and then build a Bloomberg terminal of every discussion happening at every school board everywhere in the United States.
59:52
And do that with chat GPT or any of the language models and then get really great insights from it.
59:57
That would be too costly to transcribe at, you know, $100 every hour or two and normalize, let alone to analyze.
1:00:07
And so, I'm looking at businesses as an investor, what I'm looking at right now is businesses that were previously not economically viable before this technology and then that are now economically viable, if that makes sense.
1:00:21
And I'm just looking at each company under that lens right now and I'm finding a lot of interesting startups.
1:00:26
They seem to have that in common.
1:00:28
Chamath, similar news supporting this very quick evolution further up the value stack.
1:00:34
So, we were just talking about these companies that are providing effectively tooling as infrastructure.
1:00:42
Um a little bit more up the value stack is inflection AI, which was started by Mustafa Suleyman and Reid Hoffman, uh who was a co-founder while Mustafa was working with him as a venture partner at Greylock.
1:00:55
But Mustafa, as you guys know, was the a co-founder of DeepMind, which Google bought for $400 million really created the core of Google's AI capability and is considered one of the kind of preeminent thought leaders and entrepreneurs built that has built in this space.
1:01:10
He started inflection and the business just announced today that they've just closed a $1.
1:01:16
3 billion funding round led by Microsoft, Reid Hoffman, Bill Gates, Eric Schmidt, Nvidia uh with an intention of building the largest AI cluster in the world, 22,000 Nvidia H100s as part of the build-out, but I think you've shared, Chamath, historically that these big funding rounds for these AI businesses that haven't necessarily even launched product yet don't make sense.
1:01:40
Is this still, you know, kind of reinforce your point and you know, what's your read on on the inflection funding?
1:01:48
Well, the list price of an H100 is about 30-odd thousand, but the street price, so it's very hard to get it.
1:01:53
So, if you go to the if you go to like eBay and try to buy an H100, it's like 40 or 45,000.
1:02:01
So, if you have a 22,000 cluster of H100s, that's about 900 million dollars of capex, just that.
1:02:10
And then, you know, the all the sundry stuff around it, call it roughly plus or minus a billion dollars.
1:02:17
And so, of the one and a half billion they've raised, let's say a billion goes into building this 22,000 node cluster.
1:02:24
You have 500 million for SG&A.
1:02:24
And so, what that leaves behind is basically two and a half billion of enterprise value for their chatbot. So, I don't know.
1:02:33
I mean, I've never used Pi.
1:02:35
Has any any of you guys used it?
1:02:37
Do you guys know if it's good?
1:02:39
Jason, I'm sure you've experimented with it.
1:02:40
Have you experimented with it or not really? Which one? Pi.
1:02:45
That's what their That's what their chatbot is called, Pi. I think it's like hey. pi. com or something.
1:02:50
I think I did try it once and it was not memorable. Oh, Poe? You mean Poe? No, not Poe. No, no, no. That's Poe. That's Poe.
1:03:00
Pi is like a personal one where you talk to it and it asks, "Hey, how are you doing?"
1:03:04
And their concept is like you have this one relationship.
1:03:06
So, it's like one chat thread.
1:03:08
It's not kind of how I like to work with the I use threads and I share threads with my team.
1:03:14
So, I'm not a fan of this like you have one relationship with one assistant.
1:03:18
the thing is it's interesting to note that very rarely when you invest money in the billions of dollars does the capex or purchase of one specific form of equipment take up literally 25% of the enterprise value. That's atypical. At least for a startup.
1:03:40
If you're if you're buying a fixed plant of a slow cash flow generating business, then maybe you know, a bunch of that has some value.
1:03:46
So, that that's what stood out to me in all of these things.
1:03:49
Freeberg is again increasingly this is all just a pass-through to Nvidia.
1:03:55
It's probably in some ways a pass-through to the big cloud providers.
1:03:58
So, whenever I see a chip maker and a cloud provider come together to put in a lot of money, it's essentially round-tripping cash.
1:04:03
They're giving the money, which then they use to buy their services and then, you know, you just you're just pumping revenue. So, I hope it works.
1:04:10
Chamath, I wish them the best, but you know, that's the You know, we just talked about where the infrastructure companies that are increasingly looking like more commodity service providers if they don't up-level with AI tooling acquiring MosaicML and acquiring Neeva.
1:04:32
Do you think that that's an indication of more M&A to come?
1:04:36
And if so, doesn't that justify the increased funding, the increased valuation, and the activity that we're seeing in the early stage with some of these businesses?
1:04:44
I think for sure there's going to be more M&A and I think the valuations will be high, not because these companies have a lot of revenue yet, but because it's very strategic for these big infra companies to assemble the end-to-end tool chain.
1:04:56
I think we should explain to folks what that means.
1:04:58
Enterprise software companies provide software to businesses that are not traditionally technology companies.
1:05:04
They also provide software to other businesses to help them build new tools to help them build out their business.
1:05:10
So, an enterprise software company can sell to United Airlines or can sell to Visa or can sell to Ford and that software can then be used by that company to build tools that are powered by the database or powered by the data analytics or increasingly powered by AI tools.
1:05:25
And so, they can build AI applications and AI capabilities into their business, whether it's United Airlines or Expedia or Visa or whomever.
1:05:34
And that's why this these companies are so critical in terms of enabling the transformation of industries with AI tooling and and why, you know, getting AI tooling into their capability set is so critical right now.
1:05:47
It's important to note though, guys, that whenever you have the emergence of a new sector Sacks, I think you were right that M&A goes up, but it tends to be that the valuations go down.
1:05:57
Peak M&A froth happens at the beginning of the cycle when hype is at maximum and facts are at the minimum.
1:06:06
And that's okay, you know, that's good for the startup.
1:06:08
It's marginally negative for the existing shareholder of a large company.
1:06:12
And then over time, it gets itself sorted out when the facts are more obvious.
1:06:16
So, you know, it's kind of like you guys remember when the optical networking craze Oh my god.
1:06:20
had these multi-billion dollar acquisitions and where did they go?
1:06:26
They went they went nowhere. They just disappeared.
1:06:29
We actually have like a market map that we did that I think can explain this concept of a end-to-end tool chain.
1:06:35
So, this is a slide that our growth team shout out to Mike Robinson and Kemmy Gabor, they put this together in preparation and part of the investment memo for Mosaic.
1:06:44
And I think to explain the point you were kind of making, Freeberg, like why do enterprises need these services?
1:06:53
One really simple way of thinking about it right now is that every enterprise would like to roll out its own chat GPT.
1:06:59
They would all like to have their own internal version of chat GPT where their employees, for example, could ask questions and get answers.
1:07:08
That's where all the action is right now.
1:07:09
Every enterprise would buy that tomorrow if it existed in the way that they want. of what that is, Sacks. Yeah, give an example.
1:07:17
would be that, you know, any employee in the company could ask questions to the AI model, the way you can ask chat GPT questions, and it would have all the enterprise's data and it would also understand their permissions and have all the security settings so that only the right people could get the right information.
1:07:30
That's the kind of intelligence they want to unlock.
1:07:32
I mean, there are lots of other use cases as well. a corporate oracle. A corporate oracle.
1:07:38
So, I can if I'm in HR, I can ask, "Hey, tell me about our, you know, compensation." Yeah.
1:07:42
Totally, co-pilot for the CEO.
1:07:44
I think there's going to be lots of these.
1:07:46
I think the sales team's going to have their own co-pilot.
1:07:47
I think the marketing team's going to have their own co-pilot and Customer support has it already, yeah.
1:07:52
Customer support will have it.
1:07:55
Engineers will have their own co-pilot.
1:07:56
So, there's going to be a lot of these, but I think enterprises want one at the level of the call it the company intranet where employees could just ask it questions.
1:08:03
And but they do not want to share their data with OpenAI. That's like very clear.
1:08:08
They want to roll out their own models.
1:08:11
So, the question is, well, how do you roll out your own model?
1:08:12
And what this shows here is the different pieces of the stack that you have to have.
1:08:14
So, first, you capture all of your data.
1:08:16
You got to label it to be classified right for the model.
1:08:20
You got to store it somewhere.
1:08:21
Then, you need to get one of these open-source AI models off the shelf and there's a probably the most prominent site for this called Hugging Face, which already has something like I think a $2 billion valuation.
1:08:31
That's another like really crazy valuation to ARR multiple, but Hugging Face has kind of all the open-source models. It's very active.
1:08:42
And so, people grab the latest open-source model that's the best fit for them.
1:08:46
And then, they need to train that model.
1:08:48
And that's really where Mosaic played.
1:08:50
And there's a ton of activity right now in this last mile problem of how do you customize a model to make it suitable for your use, whether you're an enterprise, whether you're a customer service team, whether you're a SaaS app that wants to incorporate AI capabilities into your app.
1:09:06
That's where the all the action is right now is customizing these open-source models.
1:09:10
That then leads to basically be able to get the right inferences.
1:09:15
And there's a sort of a separate category around hardware that is, you know, we don't play there.
1:09:19
But this is kind of the end-to-end tool chain.
1:09:21
I think these big tech companies are going to be racing to put this whole thing together. it out, yeah. Yeah.
1:09:26
And that's there'll be more M&A as your prediction, which means more startup valuation booming, more capital deploying.
1:09:31
There was a uh couple of articles this week.
1:09:35
And Chamath, this is your red meat as much as Ukraine is Sachs is cuz you've talked about this at length.
1:09:43
Social messaging startup IRL is shutting down after board investigation found 95% of its claimed 20 million users were actually fake.
1:09:52
This is a company that in June of 2021 raised a $170 million series C at a valuation of over a billion dollars, making it one of the many proclaimed unicorns of Silicon Valley led by SoftBank's Vision Fund.
1:10:02
The investor who was sitting on the board said uh that they didn't know if uh we've ever given an investment term sheet to a startup faster than SoftBank gave to IRL at the time.
1:10:12
At the same time, different story, but in the same week, a company called uh Byju, which Chamath you have talked about in the past, was once valued at $22 billion and claimed to be and claimed to be India's most valuable startup is in turmoil as shareholders and creditors are seeking to dilute the founder and he's rushing to find capital and raise a billion dollars to try and buoy the company.
1:10:33
Process, one of the investors, marked the company's valuation down to 5.
1:10:36
1 billion, so down 75%, I guess the question is overall are we still seeing this kind of turmoil in Silicon Valley from the ZIRP era funding of startups in stark juxtaposition to the excitement and the frenzy around AI?
1:10:52
It's a characteristic of the exact same thing.
1:10:54
Meaning if you replaced AI with crypto it's the exact same thing.
1:11:00
If you replaced AI with co-working if you replaced AI with I don't know, synthetic biology, if you replaced AI with SaaS this has all happened before.
1:11:16
I think it's important to identify what this is.
1:11:21
What this is is that there aren't enough checks and balances and there are fundamentally people who are deeply inexperienced, who are in the wrong job.
1:11:32
And in the few key moments where the venture capitalist is supposed to add value that person is ill-equipped and unprepared. Why?
1:11:40
Because they were the VP of X, Y, and Z at some startup.
1:11:45
And they got hired through no fault of their own into a dynamic because these venture funds wanted to raise larger and larger amounts of money. So, what happens?
1:11:54
You don't even know how to ask the basic questions or even more insidiously, you don't have the courage to say the hard thing.
1:12:05
And so, these things happen that are frankly inexcusable. Right?
1:12:10
So, in the case of one of these companies, and I've mentioned this before they approached us for financing and when we asked for a data room we got a Google Doc link to a spreadsheet.
1:12:24
Now, there's no reasonable world in which a company is that unsophisticated when it comes to understanding their business. Right?
1:12:32
A data room should include an enormous amount of operational and financial metrics that you can use to come to your own conclusion so that you can present it transparently to the investor.
1:12:43
The idea that boards wouldn't even hold these companies accountable is just a sign that the board members themselves are pretty fundamentally inexperienced people.
1:12:53
And I think the thing that we do, which is a mistake, is we say, "Oh, well, X, Y, and Z firm led this deal."
1:12:57
Yeah, that may be true, but really what it means is that firm in a grab to get the money hired some person that checked some boxes, put them in the job, that person led around and there just wasn't any infrastructure to either teach that person or then that person to have the courage to hold the founder responsible.
1:13:22
That will play out in AI as well.
1:13:22
It's just that we're at the beginning of the hype cycle. Right?
1:13:27
Because we replace AI again, as I said, with any of these other things, we sat here a little bit hand-wringing when we saw these crazy valuations for these NFT projects. Where are those now? Right? So, you name it.
1:13:39
This is about fundamentally inexperienced people doing a job that seems pretty easy from the outside but in practical reality, there are only a few legends in our business.
1:13:51
Most people, and I think it was Shy Goldman that did the math on this, most people do not know how to run these businesses well.
1:13:56
Nick will find that tweet you can show.
1:14:00
I think it's like 2 and 1/2% of all of the funds that are in PitchBook, so over 800 of them, have ever generated more than 3x in two funds.
1:14:10
So, this is a hard business, it turns out.
1:14:12
You can't just wake up and be an investor, it turns out.
1:14:13
And that's what we're finding. So, I don't know.
1:14:18
It's not very surprising in the end.
1:14:19
None of this is surprising. Good summary.
1:14:21
Chamath had a really good point in the middle there is that there is a generation of venture capitalists who were added during the boom, who were operators, but they've never been taught to have the discipline of capital allocators.
1:14:31
And one of those key pieces of discipline is asking uncomfortable questions and doing uncomfortable diligence.
1:14:39
And you can trust people, but you need to verify.
1:14:42
That is a key part of the job.
1:14:44
You can trust the founders, but you have to verify that the data you have is correct.
1:14:50
The fact that SoftBank did this at incredible valuation and the person who did this deal never checked that the customers were real is makes you unfit to serve in the job.
1:15:01
And I will do diligence and during that time period, Freeberg, I had many founders say to me "You're asking for more diligence than the lead.
1:15:12
And this deal is closing and we are oversubscribed." And I said, "Okay."
1:15:17
And they said, "Okay, so you're not going to you're not going to require this diligence."
1:15:20
I said, "Oh, no, we require this diligence.
1:15:20
We want to see your, you know, very basic stuff.
1:15:22
Your bank statements, your P&L.
1:15:24
We want to talk to We want you to give us a list of your first thousand Give us a list of 500 customers from last month.
1:15:30
We'll give you five numbers.
1:15:32
We're going to talk to five random customers."
1:15:33
Like, people did not want to do this stuff.
1:15:35
We do that this work at our firm when we start to own 5, 10% of this and we train our founders to do to be ready for proper diligence.
1:15:42
All that diligence is happening now.
1:15:44
Now, in the early stages, there's not much to go on, but you can check stuff.
1:15:49
During this period, people founders used the hot market to not participate in the due diligence process.
1:15:57
And when you look at companies a lot of times people will sus- suspend disbelief.
1:16:01
You know, this company uh Byju, I don't know a ton about it, but it seems to have you know, like an educational app, like a company brilliant.
1:16:09
org that Chamath and I are um inv- early investors in and Chamath incubated great, great business.
1:16:15
Um and but then their business and their revenue seems to be based on a series of like Kumon-like in-person instruction.
1:16:21
Oh, that's not a high gross margin business. Sorry.
1:16:25
If you have to have a storefront you're not a software business anymore.
1:16:30
And so, people started giving valuations, and this is the second part and I'll just wrap on this.
1:16:34
People started giving valuations to these companies that were real-world businesses, that were low-margin businesses, direct-to-consumer, whatever it was.
1:16:41
They suspended disbelief and they gave them valuations for high growth high gross margin businesses.
1:16:47
And that was another mistake.
1:16:49
And you put those two things together not doing diligence and then just misvaluing of actual assets that's the cleanup work that's been that's going on right now. And it takes years.
1:16:59
I mean, it took decades for them to pinch Bernie Madoff.
1:17:04
It can take 10 years for these frauds to come out.
1:17:06
There was a guy who kept telling the SEC about Bernie Madoff.
1:17:09
I think he was like nine years since the first time he he let them know that the, you know, perfect returns were just not possible statistically.
1:17:19
So, it it takes time, but they're they're picking these uh folks up everywhere.
1:17:23
Do Kwon got picked up in Montenegro, you know, the guy from Luna.
1:17:27
And it's going to take a decade to clean up all of the fraud in our space.
1:17:29
I think this was sort of mentioned by Chamath, but I think it needs to be a bigger point, which is the influence of fund size on these decisions.
1:17:39
I mean, Craft Ventures are in the 6 to 700 million range.
1:17:42
So, when we write a check, it's usually 10, 15, 20 million dollar check in a series A company.
1:17:50
That's like a big check for us.
1:17:50
We're really going to sweat that decision.
1:17:52
For SoftBank, a 10 to 20 million dollar check in a hundred billion dollar fund, which is what they had it doesn't even make sense.
1:18:00
It's a waste of their time.
1:18:01
It's not even a rounding error.
1:18:03
For them to basically make a decision check for you. Yeah, exactly.
1:18:07
So, for them, they had to write $200 million checks to justify their time managing a hundred billion dollars.
1:18:14
And so, the mistake when they make a mistake is 20 times bigger than it should be.
1:18:19
That should have been maybe a $10 million mistake, not a $200 million dollar mistake, but their fund size forced them to basically write these gigantic checks.
1:18:27
And they were writing them into companies that were effectively seed stage or series A companies.
1:18:32
If it was into a growth stage company, I think that's fine.
1:18:35
There's a lot more data and there's a lot more customer references that you can check at a later stage company.
1:18:40
By the way the number one part of diligence, I'd say for us, other than looking at metrics, which is anyone can do, is the off-sheet references.
1:18:48
Talking to customers from a list that you figured out yourself, not from the company itself, is probably the single most important qualitative part of of diligence.
1:19:00
So, I don't know what happened here, but It's not stated explicitly, but I think it's important.
1:19:04
David, you have credibility.
1:19:05
So, when you say something, Sachs, people listen because you have bonafides that are undeniable.
1:19:12
Same thing with Jay Cal, same thing with you, Freeberg.
1:19:14
I think, you know, and this may sound mean, but it's like most of these people are just X, Y, and Z mid-level VPs from a startup, and that's a great thing.
1:19:24
But, it's not necessarily going to give you the gravitas, especially if that's not what you were forced to do to help build that company.
1:19:32
And when push comes to shove inside of a boardroom or in the middle of diligence, there has to be conflict.
1:19:38
I think it's a necessary feature of good decisions.
1:19:40
And that conflict arises internally within your investment team, but it also has to come externally with the executives of the startup and with the CEO themselves, because when you're prosecuting a good decision, it's unbelievable that you agree on 100% of things, and there has to be certain things that are controversial.
1:19:57
Otherwise, by definition, that company isn't really even pushing the boundary.
1:20:02
So, I just think that these are all skills that are poorly taught while you are building a business.
1:20:07
It is not the reason why you should have been in charge of allocating 50 and 100 million dollar checks into companies. That is just crazy town.
1:20:16
I love your point, Sachs, though, about fund size dynamics.
1:20:18
Fund size dynamics are destiny. All right, it really is.
1:20:23
And and the optimal fund size for venture is somewhere between 250 and 600 million, according to everybody who's been doing this for, you know, more than a decade or two and who's successful, whether it's the costs are coming down.
1:20:36
So, as the input costs come down, whether it's for engineers and co-pilots and and hardware and abstraction layers, then theoretically greater outcomes should be generated with fewer dollars in, which would again tell you that fund size is should actually go down, not up.
1:20:50
But, the reason they go up is because you get paid an annual management fee, and so obviously the way to wait the way to make more money is to get 2% on a larger fixed number every year versus 2% on a smaller number.
1:21:02
Or, you know, for example, what we did was we were like, we're going to go and hit grand slams.
1:21:08
And so, I traded off management fee in return for 30% carry. Mhm.
1:21:11
And that turned out to be literally a multi-billion dollar smart decision, because I gave up tens of millions of dollars up front for back end.
1:21:20
Now, the back end could have gone to zero.
1:21:22
Now, maybe it still can, so who knows.
1:21:24
But, you know, most folks wouldn't do that.
1:21:28
Most folks take the sort of risk-adjusted bet and say, "You know what?
1:21:32
I'll just take the 2% and I'll raise a 200 million, then a 500 million, then a billion, then a 2 billion dollar fund." And they overlap.
1:21:39
Yeah, and they stack them all, and they get the 2% and all of a sudden the profits don't matter, which means the outcomes don't matter, which means the diligence is perfunctory, and it becomes a theatrical exposé that you can use, you know, this sort of thin fig leaf you can point to LPs and say, "We did our work here.
1:21:55
Give us more money for this next fund."
1:21:57
That's the rat race that the venture community is in, and it's going to get played out in companies like IRL and Byju's and a lot of these AI companies, quite honestly.
1:22:06
Well, and it the chickens have come home to roost for all the crypto investors.
1:22:10
different is is I think what I'm trying to say.
1:22:11
This time is not different.
1:22:13
Did you guys see there was some article that reported that fundraising for late stage funds is just like cratered? Dead.
1:22:20
So, Insight was trying to raise a 10 billion dollar fund, and they've only been able to raise two, according to this article.
1:22:26
It was a it was 22 down to 10, and of which they've raised two.
1:22:28
Okay, so 10% and then Tiger was trying to raise 12, they cut it to six, and then they can only raise two. Makes sense. Yeah.
1:22:35
So, basically, that's like a whatever uh 80 to 90% reduction in the size of these funds.
1:22:44
Yeah, meanwhile the sovereigns, where they were going for this money, are buying sports teams.
1:22:48
They're like, "You know what?
1:22:48
Instead of tech, let's just buy sports teams." series A.
1:22:52
And they're buying Manchester United, and they're buying distressed portfolios. Yeah.
1:22:55
And the and the sovereigns crunch.
1:22:58
There's a huge We've talked about it before, but there's a huge crunch in late stage financing.
1:23:00
It's only going to get worse over the next 18 months.
1:23:04
I asked Brad last week, like, how many of these zombie corns you think there are out of the 1,400? He said 30 to 40%. Yeah.
1:23:12
I think he might be, you know, could be Look, out of 1,400, I think it could be 700 are zombie corns. it's at least 700.
1:23:17
I think it's I think it's probably 60%.
1:23:19
Yeah, and so then the other 40%, let's say, how many of them have a down round coming? I think 60% go to zero.
1:23:29
Of the remaining 40%, half of them probably return money.
1:23:35
And then of the remaining half, half of those maybe get 1 and 1/2 X.
1:23:40
And then you get a geometric distribution from there, which means the blended return of that entire stream of unicorns will be about 1.
1:23:45
1 X, but it'll be very massively distributed.
1:23:49
that's exactly right, Chamath. I I would Yeah.
1:23:52
And and everybody's getting their money back, except if you don't have diversification.
1:23:55
Yeah, it's it's the I think the market is sending a very clear message, which is these funds getting No, no, most people won't get their money back.
1:24:04
Most people won't get their money back, but on average, it's going to be one extra turn.
1:24:07
Yeah, so it's not going to be evenly distributed, correct.
1:24:10
Well, I'm glad that the term zombie corn has held.
1:24:12
Guys, um we are coming up on our time.
1:24:15
Do you guys want to do science corner, or do you want to um Yeah, that's the thing.
1:24:19
must need to use the bathroom break.
1:24:20
So, go ahead and just If you could just go do it, we're going to go and take a leak, and we'll come back and make you a urinal joke. You know, I'm okay. I'm going to wrap.
1:24:31
So, look, it's been great.
1:24:31
It's been great being your host.
1:24:35
Give us the science corner.
1:24:35
Give us some Give us some hug me. You don't embrace me.
1:24:36
You don't You don't love my contributions.
1:24:40
Freeberg, Freeberg, I actually I posted a clip of RFK talking about vaccines.
1:24:45
I'd love for you to listen to it and actually give us the critique. Yes. I will. We'll do it next week. viral right now.
1:24:51
He did such a good job explaining his position on that. He did such a good job.
1:24:54
Yeah, look, did you guys read the Offit piece?
1:24:56
I forwarded it to you, and I said, "Please read this."
1:25:01
If you guys read that piece, I'll watch his clip and let's talk about it next week. Is that cool?
1:25:06
So, Offit is a Yeah, he is a vaccine scientist who RFK Jr.
1:25:08
references often as someone that he met with and spoke with and says, "I caught him in a lie."
1:25:15
And Offit basically said, "Here's exactly what happened. Here's the conversation. Here's the data. Here's the facts. Here's the science."
1:25:22
And I would really, really, really encourage you guys to read that. Please.
1:25:27
And then I'll watch his clip, and like let's have a real kind of analytical conversation about statements that are good questions to ask and good things to interrogate, and things that are being said that maybe aren't factually correct.
1:25:40
And I think that we need to kind of really as a service to ourselves and to people that listen to us, really do that work.
1:25:46
So, let's do that and come back and talk about it next week, if that's cool.
1:25:49
But, I encourage everyone to read Offit. He put it on Substack.
1:25:51
Nick will put the the link in the the notes here.
1:25:53
Let the dialogue continue.
1:25:55
Yeah, let the dialogue continue, exactly.
1:25:56
I think that's the most important to talk about that certain senator that all of a sudden just basically gave us the Heisman?
1:26:02
No, we've had a lot of those, by the way.
1:26:04
So, let me just be clear, that's not the only Heisman we've received on the All-In Summit.
1:26:07
I will say that the speaker list for the All-In Summit is looking fan- tastic.
1:26:16
Uh we're going to have a We're going to have a great time.
1:26:19
And I'm really excited for the conversation.
1:26:21
some folks Heisman does because of our support of RFK?
1:26:26
That did happen, and specifically the fact that you That's really open-minded. Yeah.
1:26:29
And then there were other folks who were insulted by things that were said about them by people on the show.
1:26:37
Do you guys want to hear about the the Nanograv Yes.
1:26:40
release that came out yesterday?
1:26:42
Okay, I'll cover this one real quick.
1:26:45
hummer that we're all getting? What is that all about? That's it.
1:26:46
It's a slow hummer, exactly. So, Tell us.
1:26:49
Are you Are you talking about like the new H3 EV, but it only goes up to 50 mph? What is that?
1:26:56
The new hummer, the new HV, you know, the an EV?
1:26:58
They're coming out with an EV of that thing. It's hilarious. Yeah. It's like a great troll.
1:27:02
I remember when Schwarzenegger got the hummer back in the '90s, and Congratulations, that's amazing.
1:27:07
I can drive all your cars.
1:27:07
And then the hummer was the cool car to drive.
1:27:11
Yeah, and then it became like Freeberg in his mini Cooper. Isn't that a manly car? Okay.
1:27:16
So, yesterday a paper was published by an international um scientific consortium.
1:27:22
This group is called Nanograv.
1:27:26
And they've been using a series of instruments to measure pulsars, and including a 500 meter radio telescope array, um which uh allows them to see What's so funny?
1:27:37
No, I just I had like three urinal jokes in one sentence, and I had to stop myself. get them out now. Go ahead. I'm muting. I'm muting.
1:27:44
The Nanograv data that was released is 15 years of data from pulsars.
1:27:49
And pulsars are neutron stars, which are stars that have collapsed on themselves and are basically super dense and start spinning.
1:27:55
And then these pulsars, you know, you basically like a lighthouse, you can see the light.
1:27:59
So, it looks like a almost like a strobe light.
1:28:02
And we can see thousands of these across the universe, and we can observe them.
1:28:06
And the rate at which the pulsing is coming out of these pulsars tells us a lot about what is happening in the space between Earth and those pulsars.
1:28:17
And when you collect enough data over a long enough period of time, which is what these folks have just released is 15 years worth of this data, you can start to see really interesting patterns in the data that support the the theory that space-time itself is slowly vibrating, being stretched, being compressed, being pulled apart, being pushed back together because of very large gravitational events happening around the universe.
1:28:46
And what that means is you guys have all seen, you know, that kind of two-dimensional image of a black hole.
1:28:50
And Nick, if you could find one online and pull it up, where it looks like, "Hey, at the middle of a black hole, space itself collapses in and it collapses down."
1:28:57
And what happens is space and time get significantly elongated when they're really close to gravity.
1:29:03
Gravity actually pulls space, sucks it in, sucks in time, and it becomes distorted.
1:29:10
And so, when you have large black holes around the universe spinning and running past each other, they're actually pulling and stretching space time itself, and that sends out ripples throughout the universe.
1:29:20
Ripples that are slowly undulating space and time itself.
1:29:27
So, by observing all of these pulsars around the universe and the rate at which these pulsars are pulsing and seeing slight variations, we can start to measure and actually see those waves.
1:29:40
Those very slow waves of space time itself undulating and being pushed and compressed.
1:29:45
And so, it supports Einstein's general theory of relativity, which indicated that space time itself can be warped by gravity.
1:29:51
And it provides a really interesting picture on the universe itself.
1:29:55
That all around us we have large masses that are many, many millions or billions of light years away that are creating waves in space and time itself that we as humans will never kind of observe, realize, or feel ourselves, but it's part of the fabric and the underlying nature of our universe.
1:30:15
With space and time being slowly warped and slowly elongated, slowly compressed.
1:30:20
Um and it's a really fascinating picture of the universe.
1:30:22
Over time, as scientists gather more and more of this data, it will provide insights into where in the universe these massive black hole events may be occurring and also provide insights into the early picture and the large scale structure of the universe, which helps us better understand how everything started and where we're all coming from.
1:30:40
So, it was a really fascinating data release.
1:30:42
I think it's a really kind of profound thing if you take a little time and think about it. It's super exciting.
1:30:48
Uh it's getting a lot of press coverage today and encourage us all to pull our heads out of the Ukraine war and Silicon Valley and money and all this stuff and realize that there there things of extraordinary scale and structure that are that are happening around us.
1:31:00
Let me ask you two questions.
1:31:03
Number one, why does it matter?
1:31:06
And number two, any theories here of what we might discover, you know, if this, you know, goes 10x or 100x in terms of the the information we're getting.
1:31:16
Many years ago, it was theorized that there's what's called a cosmic microwave background radiation, the CMB.
1:31:23
And what that is, it's the leftover heat from the formation of the universe.
1:31:26
When the universe when the Big Bang happened Yep.
1:31:30
and these scientists figured out how to create really sensitive radio telescopes and um put them in the the the uh in orbit and they started to observe the background radiation.
1:31:39
And what that showed us was the fingerprint of the universe, the original structure of the universe.
1:31:44
That created ultimately all the galaxies, super galaxies, and then ultimately all the stars, and then the planets, and everything that that came from that.
1:31:53
This could be the beginning of seeing a gravitational background of the universe, where we could actually start to see perhaps the fingerprint of the space time of the whole universe, of what the actual structure of space itself and time itself looks like throughout the universe with the perturbations being driven by some very large, massive, super massive black holes.
1:32:13
There was a black hole discovered this week that's 30 billion times the mass of our sun.
1:32:21
There are these massive objects out there that are actively distorting space time, and we're going to start to get a fingerprint of that with this sort of data.
1:32:29
And over time, that just gives us a better sense of what the overall structure of the universe looks like, not just from the heat energy that we're collecting, but also the gravitational waves that we're now able to observe through the inference of this data collection.
1:32:41
just make deepens our understanding of the universe, but there's not like the universe.
1:32:44
Yeah, which is amazing and interesting, but And and and it validates and proves the general theory of relativity, which if you think about the application of that down the road, that may lead to things like close to or as fast as light travel or things related to time travel or you know, there's a lot of things that people have theorized for decades about, you know, black holes and the warping of space time itself.
1:33:07
I'm not saying that any of this stuff is Did you see the Three-Body Problem trailer?
1:33:13
Uh yeah, it looks amazing. It looks amazing. Looks amazing.
1:33:16
What a great What a great show. I have to wait so long.
1:33:18
I hate it when they put out trailers so early. When is it coming out? Three-Body Problem? Next year. Oh, wow. Yeah.
1:33:24
Oh, I still haven't seen your movie, the guys your movie that you wanted me to see. Which movie is that?
1:33:31
Oh, Everything Everywhere All at Once?
1:33:31
I got a better movie for you.
1:33:33
I got a great pull for you.
1:33:36
Uh it's on pay-per-view right now.
1:33:36
The a movie called about BlackBerry.
1:33:40
It tells the story of BlackBerry.
1:33:40
It's like an independent film. It is awesome.
1:33:46
I just reviewed it on This Week in Startups.
1:33:47
It's called called BlackBerry. Yeah.
1:33:50
I think it's called BlackBerry.
1:33:52
this has been episode 135 of the All-In Pod.
1:33:56
I really appreciate our time together.
1:34:00
I think we finished time to get you back to your Nirvana concert. Hey-o.
1:34:06
What's the background on this one? Is that a rival? What is that? What's that background? What movie? That's a black hole. That's a black hole. Just a black hole. Okay.
1:34:15
I think that that's from Might be a vent Might be a vent line. Sachs's hair?
1:34:20
Cuz he looks like Did you get it cut, Sachs? He got a cut. Did Did you cut it? No.
1:34:24
You broke our hearts, Sachs. a mild fluffing. Show us. Show us the fluff. Let's go. Let's see. Aw, boo.
1:34:33
I mean, it's still crazy that or what? Looks good.
1:34:36
You got to just keep growing it out, man.
1:34:37
J Cal, you want to take us out? You do a better outro. All right, everybody.
1:34:40
For David Sachs, the architect, coming at you.
1:34:45
Z100 Morning Zoo, Chamath Palihapitiya, Two for Tuesdays, Tears for Fears coming up, and Friedberg with the science project.
1:34:52
All right, traveling back in time with David Friedberg, Two for Tuesday, Jackson Browne, the load out. Here we go. Got you.
1:35:04
That's why I'm the world's greatest moderator.
1:35:05
I'm the world's greatest moderator.
1:35:08
I can do my NPR voice if you like. Do it.
1:35:11
All right, closing us out here, episode 135, K C R W, 92.
1:35:15
3, the sound of Santa Monica.
1:35:19
This Sunday at the Venice Farmers Market, two for one on the organic milk. Go check it out.
1:35:24
And we'll see you all later on the politics of culture, David Sachs uh chiming in on the Republican GOP position, which we did consider.
1:35:35
Friedberg deeply going into science, and Chamath Palihapitiya on wealth disparity.
1:35:42
For everybody, I am your host here at K C R W.
1:35:46
Jason Calacanis is the world's most moderate moderator.
1:35:48
We'll see you next time, K C R W. Bye-bye.
1:35:52
I can do any of these radio bits. Bye-bye. Bye-bye. Love you guys.
1:35:59
We'll let your winners ride. Rain Man, David Sachs.
1:36:06
And I said, we open sourced it to the fans and they've just gone crazy with it. Love you guys.
1:36:09
The queen of Kim Kardashian.
1:36:29
We should all just get a room and just have a one big huge orgy cuz they're all just It's like this like sexual tension that they just need to release somehow. We need to get merch.