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NBA Gambling Scandal, Billionaire Tax, Tesla's Future, Amazon Robots, AWS Outage, Dangerous AI Bias

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2443 segments

0:00

What's the story with the California

0:01

wealth tax? Can somebody explain this to

0:03

me? Okay. So, the SEIU, the Service

0:06

Employees Union, filed a ballot

0:09

initiative, which means a directto voter

0:11

vote to amend the California

0:13

Constitution to introduce a one-time

0:17

billionaire's wealth tax where

0:18

billionaires, anyone who has assets over

0:20

a billion dollars net of their debt, has

0:23

to pay a one-time tax of 5% of their net

0:26

worth, including their private stock,

0:29

including their real estate. You said

0:31

5%. 5%

0:34

of their net worth, not of their income,

0:36

of their net worth, the entire net

0:38

worth, onetime payment to the state of

0:40

California, and then there's an

0:41

allocation on how that money will be

0:43

spent, but it's a onetime billionaire

0:45

tax. Now, it is very likely that this

0:48

sort of an amendment to the California

0:50

Constitution is not constitutional and

0:52

actually cannot be made and will not

0:54

actually go into enforcement even if the

0:56

voters do vote to approve it in both a

0:58

federal and a state level based on this

1:00

concept of uniformity which is that you

1:02

have to tax everyone equally except for

1:05

the case of an excise tax which is like

1:07

income or a transaction. You're allowed

1:09

to tax disproportionately based on the

1:11

size of the income or the size of the

1:13

transaction. But if you're going to tax

1:14

on property, if you're going to tax on

1:16

an asset, you have to tax everyone

1:18

uniformally. So it is likely not going

1:20

to go into effect if it does pass.

1:22

However, it is very likely the case that

1:25

the SEIU is simply using this as a

1:27

baiting mechanism to get people to stand

1:29

up and denounce it and then they will be

1:31

in a position to attack those people and

1:33

destroy them and use this effectively as

1:36

a political fodder for this next

1:38

election cycle. That's what it seems

1:40

like the true kind of motivation right

1:41

now. Let me let me go on the record. I

1:43

think this law is great. [laughter]

1:46

>> He's getting the virtue signaling

1:48

points.

1:48

>> I would just like to say, may I be the

1:51

first to pay 5%. I'll be in the front of

1:53

the line. Let me know when to show up.

1:55

I'll bring my check.

1:56

>> Who do I sign the check towards?

1:58

>> Shall I Should I bring cash, Gavin? We

2:00

just bring it cash to your Which one of

2:02

your mansion should I bring the cash to?

2:05

>> [laughter]

2:06

>> This is strategically why Chimamoth, I'm

2:10

glad I got out of California right

2:11

before I was about to billionize. That

2:13

was a smart move on my part.

2:15

>> Free, what are the odds that this goes

2:16

into effect? Can you just handicap this?

2:18

>> Yeah. Well, we don't know who's going to

2:20

come out against it, but there's an

2:22

effort to try and get top Democrat

2:25

officials in the state of California to

2:26

say, "This is silly. If you do this,

2:28

people will leave the state." yada yada.

2:30

So, that's kind of a quiet underway

2:32

effort. But I don't know why the

2:36

citizens of California, the majority of

2:38

citizens of California would not vote

2:39

for this. Why? Who wouldn't want to tax

2:41

the billionaires 5%. Come on. Like,

2:43

>> well, the way the way that it's written,

2:45

it says, "Hey guys, we're 30 billion in

2:47

the hole and there are 200 Californians

2:51

that control two trillion dollars. We're

2:53

just going to ask them to pay a onetime

2:55

fee of 5%." Y

2:57

>> and I don't see how anybody would say

3:00

that doesn't sound unreasonable at the

3:03

ballot box,

3:04

>> right?

3:06

>> And then the people the people that step

3:07

up against it and are vocal against it

3:09

and point out like hey in France when

3:11

they did this they lost like 40% of

3:13

their revenue because all the wealth

3:14

left the country. The reality is that

3:16

this sets it up to go through the

3:18

legislature because if it goes through

3:19

the will of the people and it gets

3:22

overturned as you say Freeberg then if

3:25

you're legislatively smart then you'll

3:27

actually push it through the state

3:29

senate.

3:30

>> Oh but don't you remember no and then it

3:32

will not get vetoed like because then

3:34

it's like hey listen it's clear that the

3:36

people want this.

3:37

>> So I I think that you'll have some kind

3:39

of progressive taxation system that

3:42

conforms to the law.

3:43

>> I mean the one They're already trying to

3:45

extend Prop 55, which is the progressive

3:48

tax for people making over a million

3:50

dollars. They're going to get that

3:52

passed. That's going to be this

3:53

incremental tax on income. But the

3:55

onetime wealth,

3:56

>> I think the I think the million dollars

3:57

thing, I think that's harder to hunt

3:59

because there's too many people that

4:00

that touches. A million dollars today in

4:02

2025, not to be glib, is just not what

4:05

it used to be. But a billion dollars

4:07

does cut off most people except for a

4:09

couple of hundred. That is true. And I

4:11

think that for example, it's very

4:13

reasonable to then charge a 10% excise

4:15

tax on selling appreciated stock,

4:17

>> right?

4:18

>> Why not? There's all kinds of ways that

4:20

you can get billions and billions and

4:22

billions of dollars. So, I don't know. I

4:24

think that this is more of a trial

4:25

balloon

4:26

>> to say, can we draw a clear line between

4:30

200 Californians and the rest of

4:33

California?

4:34

>> Yeah. And to the extent that that bright

4:35

line becomes visible and it's okay,

4:39

people are going to go ham. They're

4:41

going to try to get as much as they can.

4:43

>> The reality is, as we all know, I mean,

4:45

Larry Ellison left the state. Many of

4:48

the founders CEOs who have built large

4:50

technology companies in California. Elon

4:52

left the state will eventually at some

4:55

point break and say, "Okay, I'm moving

4:57

my company out of state and I'm leaving

4:59

the state and I'm bringing the employees

5:00

with me and I'm bringing all of the

5:01

economic value of this business with

5:03

me." And people will never learn that

5:05

lesson because it's so much easier to

5:07

sit in front of a voter and say, "Hey,

5:09

should we tax these 200 people to give

5:10

you better benefits?" 97% of people will

5:13

say, "Absolutely."

5:15

Very few people will sit and think about

5:17

the consequences of what's going to end

5:19

up happening.

5:19

>> 99.9 will say absolutely. I mean, nobody

5:23

tells them in that ballot initiative

5:25

that we have a $300 billion budget of

5:27

which 2/3 may be just wasted. One of the

5:30

motivations for this bill, and this is

5:32

why it's being proposed by the SEIU, is

5:35

that there are these massively

5:37

ballooning pension benefits and pretty

5:39

significant increases to the pension

5:42

programs for both private and public

5:44

pension funds in California, which has

5:46

actually become a very visible liability

5:48

for the state and for some of these

5:50

private pension programs. and they're

5:52

trying to fill the pension hole, which

5:54

we've talked about in the past, but

5:56

there is a multi-t trillion dollar

5:58

unaccounted for pension liability in

6:01

this country that's going to have to

6:02

come from somewhere. You're either going

6:04

to have to print the money because the

6:05

federal government's going to step in

6:07

and fill the hole in all these pension

6:09

obligations or they're going to have

6:10

these massively progressive tax programs

6:12

to try and fill the hole. And if and

6:14

when they do, as we all know, there will

6:16

be an economic cycle that will be pretty

6:19

nasty, which is all the value will leave

6:21

that jurisdiction and move elsewhere.

6:22

But let's see.

6:24

>> It's it's like the Democrats are doing

6:25

everything they can to get me to leave

6:27

the state. I don't want to. [laughter]

6:29

I really am resisting. I mean, they've

6:31

raised my income tax to what is it like

6:34

13.3%.

6:35

>> 13.3. Yeah.

6:36

>> And I know it's going to 16. They've

6:38

been boiling the frog. I still haven't

6:41

jumped out of the pot. But for me, I

6:44

think the wealth tax, I'm gonna have to

6:46

jump out of the pot with this.

6:47

>> The crazy thing with this, the other

6:48

like I read it because I was like, "Oh

6:50

my god, what's going on?" The two things

6:52

that they they obviously got somebody

6:54

very clever to draft it because any Roth

6:56

IRA over 10 million counts. And normally

7:00

in these wealth calculations, you you

7:02

keep your deferred retirement accounts

7:06

off the table. They're typically not

7:07

included. So folks, and I'm not going to

7:11

say who they are. we all know who have

7:13

tremendously appreciated Roth IRAs

7:15

>> pretty public who you're talking about

7:16

but sure

7:17

>> those are included and then the other

7:18

thing is that if you actually did any

7:20

tax structuring the real valuable tax

7:22

structuring is where you set up these

7:24

trusts in Wyoming and North Dakota and

7:27

you do these interparty loans where you

7:29

can lever up 10 20x so you can transfer

7:32

billions and billions and billions of

7:34

dollars out of state but then you have

7:36

these obligations those are negated and

7:38

they don't count so all that tax

7:40

structuring goes out the

7:41

So you can get into a very difficult

7:43

situation here where they're like, "Hey,

7:45

you owe us $500 million, a billion

7:47

dollar, $2 billion, and the only way to

7:49

pay it is to have an IOU to the state of

7:52

California." Which is crazy.

7:55

>> It's crazy. There is not a lot of ways

7:58

out of this if this stance

8:00

>> No one is empathetic to either of you.

8:02

No one gives a about the two of you

8:04

needing to pay more.

8:04

>> This is why I'm in support. Again, I'm

8:06

just saying it for the record. I am

8:08

supporting support keep [laughter]

8:10

this

8:11

>> I had a few more thoughts about this

8:12

thing which I want to unpack. So number

8:13

one is like you guys said a wealth tax

8:15

has been tried in many places at many

8:17

times it always backfires because

8:19

whatever the tax benefit is that you get

8:21

for the state it's greatly outweighed by

8:24

the economic depression that you get by

8:28

the wealthy people the job creators

8:30

companies leaving. And as soon as you

8:33

cross that line of going from no wealth

8:35

tax to any wealth tax, enough people of

8:39

wealth can see the tea leaves, they can

8:41

see the writing on the wall that they

8:42

have to leave. And that's why I think

8:44

even if they say this is a one-time

8:45

thing, we all know that it won't be one

8:48

time. If they get away with it, it'll

8:50

become a regular thing. It'll just be

8:52

>> if it's to plug a deficit, they're going

8:54

to run deficits every year.

8:55

>> Exactly. And and you're right. And this

8:57

isn't even to plug an emergency

8:59

situation or an unfunded liability like

9:02

some one-time thing. This is just a

9:04

regular operating exactly. So they will

9:07

have no incentive to fix their

9:08

mismanagement of the state and their

9:09

deficits and all that kind of stuff.

9:10

>> By the way, by the way, if they get away

9:12

with this

9:12

>> and it's not just going to be

9:13

billionaires eventually the line will of

9:16

course get pushed down be gone. The

9:18

billionaires always like like the income

9:20

tax in the US. I think it was a 1%

9:21

income tax originally and it was like

9:23

just a onetime thing for wealthy people

9:25

and then it became a smaller thing for

9:28

you know lower income people and then

9:29

eventually as we all know every person

9:32

has to pay a tax every property has tax

9:35

and so on. I mean these are this is the

9:37

problem with government. There's all

9:38

these other states by the way that are

9:40

finding clever ways. I think in Montana

9:42

now there's a differential property tax

9:44

scheme where if it's your second or

9:46

third home and you don't live there you

9:49

pay a lot more. Yeah, here's what I

9:51

wonder about is, you know, what are guys

9:53

like Jeffrey Katzenberg or even Ari

9:56

Emanuel thinking about right now because

9:59

they're kind of the higherups in the

10:00

Democratic party behind the machine,

10:04

sort of the oligopoly that kind of runs

10:06

the machine. And I remember that when

10:10

Karen Bass was running against Rick

10:11

Caruso for mayor of LA, it was very

10:14

publicly reported that Katsenberg was

10:16

behind Karen Bass and there was sort of

10:18

an imboglio between Caruso and

10:20

Katsenberg. Katsenberg anyway helped

10:22

make sure that Karen Bass was wellunded

10:23

enough to win. The result of that

10:25

ironically was that Pacific Palisades

10:28

burned down and I think Katzenberg's

10:30

house might have been part of that. In

10:31

any event, I think there are these guys

10:33

who are very, very wealthy who think

10:36

that they can control the machine well

10:39

enough that they basically are still in

10:42

control of this thing, right? That in

10:44

other words, that the tiger won't eat

10:46

them, right? The tiger is socialism.

10:49

>> Yes.

10:49

>> And that's exactly right.

10:51

>> You know, they think they've got the

10:52

tiger under control enough that it won't

10:54

eat them. But I don't think they do.

10:56

Maybe they don't. Maybe this is the

10:57

tiger breaking loose.

10:58

>> Yep. And I think Fer, you pointed this

11:00

out that there was an attempt in the

11:02

legislature last year to pass a wealth

11:04

tax and it was quietly killed behind the

11:06

scenes. And I actually think that Gavin

11:08

Newsome might have something to do with

11:09

that because he has presidential

11:11

ambitions. So he can't let the state go

11:13

full socialist. But you just kind of

11:16

wonder, okay, well, if these guys lose

11:19

control of the strings they have to

11:21

control the beast of socialism, does the

11:24

whole thing just spin out of control?

11:25

>> That's New York. We're seeing it

11:26

everywhere. Seattle.

11:27

>> I was about to bring up let's talk about

11:30

it. Uh well and and just to let people

11:33

know about the France situation back in

11:34

I don't know 2011 2012 they did get rid

11:38

of Gerard de Parde which was kind of a

11:39

win but Bernard

11:42

>> Arnold

11:43

>> what's

11:45

Bernard Arnold is that his name from

11:46

LVMH

11:47

>> Bernard Arno said he was going to go to

11:49

Belgium and said it was a clerical error

11:51

and he unwound it but that was a clear

11:53

signal the richest man in France. Well,

11:55

he's

11:56

>> go to New York.

11:57

>> He's basically the entrepreneur LVMH

11:59

together. I mean, it's their biggest

12:02

company. It's the one that does all the

12:03

luxury goods, all the craft goods that

12:06

they're so famous for. I mean, yes, him

12:09

threatening to leave France is, you

12:11

know,

12:11

>> accidentally fly filing paperwork. Oops.

12:14

What an accident. Here's your look at uh

12:18

New York City under Mandami, who uh

12:20

we're in touch with. You may come on the

12:21

program.

12:23

New York State tax 10.9% city 3.876%

12:28

and the 2% mandami tax put you at 16.8%

12:34

for living in New York is 17%.

12:39

I mean if you were making $10 million a

12:42

year is it worth $1.7 million? You could

12:46

get a plane. You could live in Florida.

12:48

You could come to New York 150 days a

12:50

year. There's really five good months in

12:51

New York. the fall, the spring, and

12:54

that's about it. You know, you go see

12:55

the tree at Christmas, but it's cold.

12:56

>> Well, that's not that's not that's not

12:58

realistic for most people. And

12:59

especially if you have kids and you care

13:01

about them, you'd like them to be rooted

13:02

somewhere. You're not going to shle them

13:04

around every month to arbitrage taxes.

13:06

>> Yeah. Well, I mean, I I do think they're

13:08

they're going to test that at 17%.

13:11

That's nondeminimous. Okay, let's uh we

13:14

got a lot of docket to get through here.

13:16

>> I'm so glad Shimov supports the

13:17

billionaires tax. That's great. We'll

13:18

get that [laughter] in the headlines.

13:20

Yeah. right after all. This is the free

13:22

rider problem that we have is no one's

13:23

going to want to stand up against it and

13:25

the thing will just kind of

13:26

>> pass. By the way, if you're the if

13:28

you're a billionaire CEO of a public

13:30

company in California,

13:32

you have you have everything you have

13:34

everything to lose to stand up and

13:36

oppose it. Your employees will run. Your

13:38

shareholders will attack you. You'll

13:40

look awful in PR. So, everyone's going

13:42

to sit quietly and start looking at

13:43

houses on Zillow in Austin or Miami and

13:46

be like, "Where should we move to next

13:47

year, honey?" You know, like that's the

13:49

conversation that's going on.

13:51

>> Didn't you say it was retroactive?

13:52

What's

13:53

>> it's retroactive to 2026? So, if it

13:55

passes,

13:56

>> you have three months. Two months. Yeah.

13:59

>> But again, I don't think it passes

14:00

muster with the constitutional reads.

14:04

>> Remember what they said about remember

14:06

when they did the transfer tax where San

14:08

Francisco took 6% of my home?

14:10

>> Yep.

14:11

>> And then in LA just took 5% of my house

14:13

down there, the supposed mansion tax.

14:15

>> But those those were excise taxes. So if

14:17

you go back to the case history in the

14:19

US Supreme Court on this stuff, anytime

14:21

there's a transaction and you take a tax

14:23

on a transaction, they call that an

14:24

excise tax that is constitutionally

14:27

>> part of the bill though there's a part

14:28

of the bill that they could cleverly use

14:30

which is called this ODA which is

14:32

effectively this IOU mechanism

14:34

>> and they could essentially say when

14:36

these assets transact you owe us 5% on

14:38

an excise basis and by the way there's

14:40

an attestation that you have to file you

14:42

have to file a legal document and this

14:44

was quite well written in there which

14:46

said you must attest that you have less

14:49

than a billion dollars.

14:51

>> Okay,

14:53

now what? Okay, then I have to attest

14:54

that it's more and then I have to know

14:56

>> how do you even mark your whole

14:57

portfolio to market if you have a lot of

14:58

privates?

14:59

>> They do not allow discounts. They do not

15:01

allow liquidity discounts. It says if

15:03

you are a reasonable buyer and a

15:05

reasonable seller, you have to transact

15:08

this at market price. So, for example,

15:10

imagine you owned a sports franchise and

15:12

the sports franchise, if you sell a

15:14

minority share, you're typically selling

15:15

it at a discount off the table. If Forb

15:18

says it's worth 10 billion and you own

15:20

10%, that's a billion dollars

15:22

>> for the purposes of this calculation.

15:23

>> I'm going to pay $50 million to keep it

15:25

even if you paid 50 million to buy it.

15:28

>> Even if Freeberg is right that there's a

15:30

good chance that it'll be found

15:32

unconstitutional, how many years in the

15:33

course is that going to take? And who's

15:35

going to stick around waiting for that?

15:36

In fact, the rational thing to do is

15:39

pull up stakes before January 1st and

15:41

leave right now.

15:42

>> That's right. That's going to happen in

15:43

New York. I mean, I think they're going

15:45

to have an exodus just like New Jersey

15:47

and Connecticut did. And that actually

15:49

rocked the tax base in those two

15:52

geographies. All right, listen.

15:54

Big breaking news this morning. Huge

15:57

scandal in the NBA. The FBI just

15:59

arrested 30 people in a sports betting

16:01

and gambling probe. This hardly seems

16:04

real. Chanty Bilips, who is the current

16:06

Blazers coach and was just introduced

16:09

into the Hall of Fame, got pinched for a

16:11

poker game he was running allegedly with

16:13

the mafia that was rigged 17 different

16:17

ways allegedly to Sunday. Terry Rosir

16:20

allegedly is a point guard for the Miami

16:22

Heat.

16:22

>> Why are you saying allegedly all the

16:23

time?

16:24

>> I'm, you know, everybody's suing these

16:25

days, so alleged I'm I allegedly he's a

16:28

point guard. I I've seen him play. He's

16:30

not a very good point guard. It's a lot

16:31

of turnovers if I'm being honest. You

16:33

know what I know is alleged? That you're

16:34

the world's greatest moderator. That's

16:36

>> allegedly true. It's allegedly

16:38

[laughter] true cuz it's not true.

16:39

>> You're allegedly a billionaire. Nobody

16:41

can confirm it. [laughter]

16:43

>> Normally, he uses the word allegedly

16:45

when it's a story that like it's about

16:48

Hunter Biden or doing something

16:50

improper.

16:50

>> Yes, he allegedly smoked crack and shot

16:53

a 9 mm in the air.

16:55

>> It's usually a story about Democrat

16:57

wrongdoing and he's trying to discredit

16:58

it.

16:59

>> All right, here we go.

17:00

>> Anyway, keep going. Curry Rosair, uh,

17:01

who's allegedly a point guard. I mean,

17:03

he he was

17:06

he told his friends, this is crazy, you

17:08

know, in the overunders, you know, hey

17:10

guys, bet the under on me uh in rebounds

17:13

cuz I'm going to uh take myself out of

17:15

the game with an injury allegedly. And

17:18

uh

17:20

his friends allegedly made 200 grand off

17:22

this. Okay, just allegedly for the whole

17:24

goddamn thing. Uh this is going across

17:26

11 states and a bunch of crime families.

17:28

Allegedly, there's something called the

17:30

mob. I don't think that really exists

17:32

anymore. I think that's an urban legend.

17:34

And these are two separate threads, but

17:36

announced on the same day. They both

17:38

involve NBA players, but apparently this

17:40

is two different cases. So, Chimath,

17:44

what do you allegedly think of this?

17:45

[laughter]

17:47

I I think it's crazy. I think you're

17:49

seeing a lot of these trends converge

17:52

all at the same time. Meaning, you have

17:54

the emergence of all of these prediction

17:57

markets. you have

18:00

a lot of data science and AI being used

18:03

that shows that there's a lot of odd

18:05

behaviors. So, it really was the squares

18:07

versus the sharps. And if you had the

18:09

inside edge, you were just printing

18:10

money. Now that all of that is becoming

18:12

more transparent, there's a lot less

18:15

margin. Then what happens is you have

18:17

these laws passed in the 11th hour.

18:19

There was a an important gambling law

18:20

that was inserted into the big beautiful

18:23

bill that has implications to all of

18:24

this. And now you're seeing the feds. I

18:27

The crazy thing to me is

18:30

a press conference where Cash Patel is

18:32

talking about this. I mean, that's like

18:33

serious business when the FBI director

18:36

is front and center talking about all

18:38

this. So, I don't really know what it

18:40

means to be honest. I was shocked at the

18:41

scale of it and I was shocked that it's

18:44

on the radar of the feds. This took I

18:47

thought this is like pretty typical

18:49

tickytacky stuff, but clearly there's

18:51

something bigger. I don't know exactly

18:53

what that bigger is, but something is

18:55

happening where all these markets are

18:56

smashing together. There's just a big

18:59

cleanup effort going on. So, I don't

19:01

know. I really don't know.

19:02

>> Freeberg, I guess there's two different

19:04

ways to go about this. You have the

19:05

fantasy sports becoming legal, everybody

19:09

around these players just in that one

19:11

case

19:12

where are these people too dumb to

19:15

understand that their $10 million

19:16

contract to play in the NBA every year

19:18

or $20 million contract is more

19:20

important than your friends betting the

19:22

under or over.

19:25

And how dumb are they? I mean, to not

19:27

know that the people running a sports

19:29

book would look for weird action. like

19:32

why is one player getting $200,000 on

19:35

their overunder for rebounds and the

19:36

other players are getting 20,000? What

19:38

are what are your thoughts here? Us also

19:41

take on the poker one.

19:42

>> I think gambling generally as we call it

19:44

should be decriminalized and I don't

19:46

like this statebystate setup with

19:49

gambling. I think we should have a

19:50

federal regulatory body to oversee,

19:53

monitor, and the problem is you have

19:55

state gambling commissions and we have a

19:57

state-by-state kind of patchwork of

20:00

regulatory authority that makes it very

20:03

hard to standardize, track, and provide

20:05

also guidance and feedback. I would much

20:07

rather see this all kind of get handled

20:08

at the federal level and and better

20:10

organized. To Chimat's point, this is

20:12

not going away. People love to bet on

20:15

stuff. They love to gamble. This is part

20:17

of sports. This is part of the culture.

20:19

They're not going to just turn it off.

20:21

>> They did market poly market raised

20:23

whatever it was a billion or two billion

20:25

at 9 billion.

20:26

>> Then the next weekend they announced

20:28

sports betting

20:29

>> and now they're raising money 30 days

20:31

later. It allegedly

20:33

>> allegedly

20:35

>> at 12 to 15 billion. I mean anywhere.

20:38

>> It's un it's unbelievable. And you can

20:40

see by the way the way that DraftKings

20:42

and FanDuel stock

20:45

have reacted to this. Those companies

20:47

are toast.

20:50

>> Toast.

20:51

>> That's right. This is really

20:52

interesting.

20:52

>> The poly market model is the best model

20:55

because it creates a market and so as

20:57

information flows in that market will

20:59

dynamically adjust and everyone will get

21:01

a more fair price.

21:02

>> Did you see the regression that they did

21:04

on the poly market trades and how well

21:05

they're in the money?

21:06

>> Y Nick, can you find that? But basically

21:09

what it showed is like the front money

21:10

is the sharps,

21:13

the back money are the squares, but you

21:16

have to fade the trade in the first

21:18

week. So there's a very scientific

21:19

method where if you want to make money

21:20

on poly market, it became pretty clear.

21:22

There's two things that are very

21:23

interesting about it is number one how

21:25

how they've simplified things to a way

21:28

people can understand. It's not like you

21:30

have to understand, you know, it's 120,

21:33

it's this the point spread. It's just

21:35

what are the what's the chance that this

21:37

thing happens? 80% 20% people could just

21:40

place their money on it. And then this

21:41

ability to reconcile it at any time. I

21:44

didn't realize how engaging that is. I

21:46

was watching the Oscars and I was

21:47

watching boxing and I bet the underdog

21:51

in this Netflix boxing thing that

21:53

happened cuz I just thought this guy

21:55

looks pretty pissed off. Uh, and I

21:56

thought that was a good enough way to go

21:58

with the underdog. And then you watch it

22:00

round after round and you see the odds

22:02

changing real time and anytime you can

22:03

just cover the bat and take your

22:04

winnings and take out the risk. Really

22:07

like interesting and fun for people.

22:09

It's so simple. Then I did it on the

22:11

Oscars or the Emmys and I was like,

22:13

"Yeah, I'm going to I'm I'm fading uh no

22:17

offense Pen Stiller, but I'm going to

22:18

fade Severance." And I went with the um

22:21

the uh the one about the emergency rooms

22:23

and with Andor and I won again. So, I'm

22:26

just it's it's a lot of fun to do it

22:28

>> here. Jason, look at this. I sent Nick

22:30

the tweet, but this is incredibly

22:32

systematic. This is over many many many

22:35

markets. But basically, 89% accurate one

22:38

week out, but in the final four hours,

22:40

it jumps to 95, which means that if you

22:42

follow the sharps along this pattern,

22:45

you're going to make money.

22:46

>> 6% in a week.

22:48

>> Yeah. Right.

22:49

>> Market Poly Market actually has the news

22:52

before the news does. This is one of the

22:53

most like powerful outputs of Poly

22:55

Market is they're actually getting a

22:57

read on what's going on in the world

22:59

before the media recognizes it, before

23:02

the public recognizes it. Because when

23:03

you put

23:04

>> Yeah. When you put money up, it actually

23:06

turns out that when people have

23:07

incentives, that market will find the

23:09

truth.

23:10

>> Somebody needs to build the app that

23:12

makes all of these things fungeible. And

23:14

by all what I mean are cryptocurrencies,

23:18

betting markets, equities, and options

23:23

markets turning into.

23:24

>> Yeah. And the reason is there's just no

23:26

reason to go to nine different sites and

23:28

have nine different accounts. And the

23:29

most important thing is to do KYC and

23:32

AML across nine sites to get access to

23:35

liquidity, credit, and margin. You'll

23:37

want to do it once. And then you'll want

23:39

to have a large pool of capital that you

23:42

can trade across anything. So I can go

23:43

long Nvidia but I can also go short the

23:46

nicks and then I can own some Bitcoin

23:49

all in the same trade.

23:50

>> Totally.

23:51

>> That's where it's going.

23:52

>> Totally. Totally.

23:54

>> Now to the earlier question Jcal I think

23:56

if we end up there where poly market

23:59

does become the truly liquid market

24:01

across all of these kind of predictions

24:03

all of these assets then a lot of what

24:06

we are seeing with respect to insider

24:08

trading insider information becomes much

24:11

more apparent. So, the problem with the

24:13

sports betting is that there's a

24:15

one-sided bet. The casino sets the odds

24:18

or, you know, whomever is setting the

24:19

odds, and then you're either taking one

24:21

side or the other. And so, if you have

24:23

the insider information, you're taking

24:24

the side that creates an arbitrage

24:26

opportunity for you.

24:27

>> But if you were to do that in a liquid

24:29

market where there's someone taking the

24:30

other side in a dynamic way, then the

24:33

market very quickly moves because of the

24:35

inside knowledge you have. And that

24:37

inside knowledge is now reflected in the

24:39

underlying asset price in the underlying

24:41

odds that you get for that bet. And so

24:44

Poly Market actually brings truth and

24:46

transparency to what is currently an

24:49

insider arbitrage opportunity and it may

24:51

actually solve some of these fundamental

24:52

problems in in gambling.

24:54

>> I think let's just wrap with a little

24:56

bit on the poker and knowing if you're

24:58

in a rigged game or not. uh living in LA

25:00

I got invited to a lot of poker games

25:02

when I was playing low stakes playing at

25:04

Hollywood Park just you know $500 buy in

25:07

thousand buy in but as these things went

25:09

up you started to get access and I

25:11

started to get invited to Molly's game

25:13

the very infamous game and she would

25:15

text me she would call me oh we're

25:16

playing over here oh Leo this person

25:18

wants to see that person wants to see I

25:20

was like they want to see me lose 50

25:21

grand there's no way I'm not playing in

25:22

that high stakes and I'm not going to

25:24

that game and the one or two times I did

25:26

go to games that had a rake I was just

25:28

like This game is fixed. I don't know

25:30

how.

25:30

>> Totally.

25:31

>> But somebody's I think it's just

25:33

collusion. I think there's three players

25:35

all playing from the same chip stack. In

25:38

which case, you know, you could be dealt

25:39

aces five times in a row. If you're up

25:42

against three players, what are your

25:43

odds against, you know, six other cards?

25:45

It's going to be pretty bad for

25:47

>> you think Molly's game was fixed.

25:48

>> I don't know if hers were was I wouldn't

25:51

be surprised if it was. I wouldn't be

25:53

because once the mob gets involved,

25:54

which is what happened at the tail end

25:56

of hers, then all kinds of possibilities

25:58

happen. Once it gets to extremely high

26:00

stakes and you've got guys chasing it,

26:03

man, you could, you know, and they're

26:04

coming back night after night trying to

26:06

catch up for what they lost last week,

26:08

it's it's pretty dark. There is

26:10

absolutely no reason why anybody should

26:13

play in a game where you're playing with

26:16

people you don't know. And if you need

26:19

it that badly, then you probably have a

26:21

problem. But there is no limit at which

26:24

you couldn't find a game with some

26:25

combination of your friends and or

26:28

respectable reputable businessmen that

26:30

have more to lose than you do. And if

26:32

you can't find that game, you should not

26:34

be playing in any game.

26:35

>> Yeah. Any home game with a rake is just

26:37

should be absolutely suspect. Period.

26:40

Stop. Super sketch.

26:41

>> Isn't that game?

26:43

>> Yeah. Well, yeah. Well, we don't want to

26:45

[laughter] bring up angle shooting, but

26:47

he's a straight play.

26:50

He would be so tilted if he hurt heard

26:51

you so well.

26:52

>> Oh my god. He's so about the ethics. He

26:54

wants, you know, no flies.

26:55

>> In fairness to like that game where you

26:58

can, you know, go off for a small house

27:00

in is also the game where he would then

27:03

collect $10 from each of us to pay for

27:05

the

27:06

>> fruit plate and the pizza. He would

27:08

order Domino wouldn't even buy us pizza.

27:11

>> Yeah. The chef and but I'm like I don't

27:13

know if the chef really does cost $6,000

27:16

for two hours, bro. [laughter] I don't

27:17

know.

27:17

>> It's Wagu. But I think it's a Wagu

27:19

burger. The the funniest ever was he's

27:22

like in a hand and the Domino's pizza

27:24

comes and you know he's like everybody

27:27

have a green chip when we're playing

27:28

with fin chips. He's trying to get like

27:30

$125 bucks. The guy comes I just go it's

27:33

on card. The guys got you got a sign

27:35

right? It's got the tip on it. I said uh

27:36

it's like $150 a piece. I said what's

27:38

the most what's the biggest tip you ever

27:39

got? He said yeah somebody on New Year's

27:41

gave me like 200 bucks. I just wrote

27:42

$500 on $150 thing. I signed it. I gave

27:46

it to him and then I was in a hand with

27:48

I said here's the receipt. [laughter]

27:50

>> So what you're saying is when it's on

27:52

somebody else's credit card you're

27:54

willing to tip incredibly generously.

27:56

>> I mean

27:56

>> God you're a really great guy.

27:58

>> You should speak when Phil Helmouth and

28:01

I bought uh dinner for everybody at

28:04

Chipriani that time. Chimop grabs the

28:07

check. He goes, "I'll put the tip in for

28:09

you guys."

28:10

>> Well, why is that, Jason? Is that

28:12

because 100% tip on an $8,000 check?

28:16

>> Isn't that because I pay for everything

28:18

all the time?

28:19

>> That's true. You are very generous. It's

28:20

You're no um or no, sir. 20 2010

28:24

>> one time. I asked you guys in 15 years

28:26

to pay one time and you remember the

28:28

exact It's so sad.

28:30

>> I have

28:31

on you guys.

28:32

>> I was like, "Oh god, I guess we're going

28:33

to public school."

28:34

>> You guys are so ungenerous. It's

28:36

>> I know. I I give huge tips. Um

28:41

Yeah, I think he's, you know, he's

28:43

average.

28:43

>> Okay, let's go to the next topic.

28:44

[laughter] Allegedly, world's greatest

28:46

moderator.

28:47

>> Let's talk about this Amazon outage.

28:48

Tough week for Amazon. They had this

28:50

huge outage in the beginning of the week

28:52

and then they had a bunch of leaked

28:54

documents about their plans for uh jobs.

28:58

And uh Monday, massive AWS outage, 2,000

29:01

companies, 4 million users unable to

29:03

function on the internet for half a day,

29:06

15 hours, 20 hours. Uh and then on

29:08

Tuesday, internal docs viewed by the New

29:10

York Times showed Amazon plans to not

29:14

hire uh 600,000 plan jobs uh because of

29:18

robots by 2033.

29:21

So this isn't they're planning on laying

29:23

off 600,000 workers, but rather they're

29:25

just pulling back their hiring plans and

29:28

ramping up their robotic plans, which

29:30

you would expect. uh and uh their goal

29:34

according to these internal leak

29:35

documents is to automate 75% of

29:38

warehouse operations. We talked about

29:39

this the last couple of weeks. Freeberg,

29:41

your thoughts on either of these uh two

29:43

stories here?

29:44

>> I think the AWS story is interesting in

29:47

terms of its implications for the

29:49

clouds. There's effectively three major

29:51

cloud vendors that compete with one

29:52

another. AWS, Microsoft, and GCP or

29:55

Google Cloud. And I'll just give you

29:57

these numbers.

29:58

>> Also, by the way, coming on strong.

29:59

Yeah,

29:59

>> that's right. But let's let's exclude

30:01

the number four for now. Oracle, but AWS

30:04

is $124 billion revenue run rate.

30:07

>> Microsoft 120 billion. And Google Cloud

30:10

54 billion. But AWS, which is slightly

30:14

larger than Microsoft, is only growing

30:16

17% year-over-year. Microsoft 26%

30:19

year-over-year. And Google Cloud is

30:22

accelerating at 32% year-over-year. And

30:24

some say getting closer to 40% growth

30:26

rate. The big thing I hear from partners

30:28

and enterprise customers of these cloud

30:30

services is that many of them if not all

30:33

of them as they scale up move to a

30:36

multicloud model. So none of them want

30:38

to be dependent on a single cloud. Many

30:41

folks started on AWS because AWS was the

30:43

OG. Back in the day when I was running

30:46

Climate Corp, I was the largest EC2 user

30:48

on AWS for about a year and a half,

30:50

which was their elastic compute cloud

30:52

service. We were running all these

30:53

models back then. So I knew that service

30:55

very early on and it was very unique. It

30:56

was very powerful and so a lot of

30:58

companies that are old school

30:59

established themselves on AWS very early

31:01

on. But the outage that happened this

31:04

week, I think starts to highlight for

31:06

folks that they can't and shouldn't have

31:07

a dependency on a single cloud service

31:09

provider and will only accelerate the

31:12

diversification of companies into the

31:14

other clouds. And so I do think this is

31:16

actually a very beneficial situation for

31:20

Microsoft and GCP and to your point

31:22

Jakel perhaps even Oracle in terms of

31:24

giving those sales teams which are very

31:26

aggressive a hard story to go and sell

31:29

for and say guys you don't want to just

31:30

sit on AWS in case this happens again

31:33

we've got better infrastructure we're

31:34

more reliable etc than these other guys

31:37

so come and move over to us and that

31:39

might be a little bit of a naive

31:40

simplistic kind of reductive way to

31:42

think about what happened this week but

31:43

I we are seeing the smaller competitors

31:46

accelerate and I think that this might

31:47

be another kind of moment of

31:48

acceleration for those folks

31:50

>> and multicloud it's been around for a

31:52

while Jimoth when you're doing stuff

31:54

with 8090

31:56

are the big companies already doing that

31:58

or do they assume hey there's going to

32:00

be some downtime

32:02

yeah it's okay to risk or are they

32:03

really thinking multicloud neocloud

32:06

let's have some smart intelligent

32:08

routing and redundancy here

32:11

>> I think there are two markets there's

32:12

the AI market then there's the non-AI

32:14

market. In the nonAI market,

32:18

everybody has everything. It all looks

32:20

effectively the same. There's certain

32:23

products and services that are unique to

32:24

Azure versus GCP versus AWS, but by and

32:29

large, the market is big enough and

32:32

important enough that you'd have to be

32:36

pretty insane to take a single vendor

32:39

approach.

32:40

And so what typically happens in these

32:43

markets is that they start off really

32:44

small. One person has all the share. And

32:47

then as the market becomes very valuable

32:50

and very big, everybody diversifies

32:52

because it's a riskmanagement thing. And

32:54

these things flow into the disclosures

32:55

you have to make as a public company.

32:57

And if you didn't have that

32:58

diversification and something bad

33:00

happened and it impacted your business,

33:02

you could get sued. So there's all these

33:05

reasons why eventually all these three

33:07

big companies will converge effectively

33:09

roughly a third, a third, a third. We're

33:11

going to debate the path to get there,

33:12

but that's where they'll end up.

33:13

>> You know, there's this principle called

33:15

the rule of three where they say like

33:17

all markets eventually mature to kind of

33:19

a 60 3010 split that you end up having

33:22

your market leader at 60% market share.

33:25

Second place is usually half the size at

33:27

30 and then you always there's some

33:29

balance in the market where there's some

33:30

competitor that resolves to about a 10%.

33:33

It's really interesting. If you guys

33:34

were to place a bet, who would you think

33:36

is the 60 3010?

33:38

>> I don't think that applies to you. I

33:39

think that's

33:40

>> You think they're going to be a third, a

33:41

third, a third?

33:41

>> I think it's all some idiot making

33:43

something up.

33:44

>> But what do you think? What do you

33:45

think? What do you think happens in

33:46

cloud? Like, do you think that these all

33:47

converge to equal market share?

33:49

>> In nonAI, it's a third, a third, a

33:51

third. It will it'll take circuitous

33:53

paths, but that's where we'll end up.

33:54

>> By the way, a good point to make is that

33:56

this revenue number that I highlighted

33:58

for Google Cloud, Microsoft, and Amazon

34:00

actually include their applications. So

34:02

as you know like Microsoft GCP have

34:04

pretty sizable enterprise application

34:06

stacks that are built into that number

34:08

which gives them obviously the ability

34:09

to drive cloud usage because they've got

34:12

demand and sales relationships into

34:14

those enterprises. I think the way it

34:16

works in AI is that you initially right

34:18

now we're in this early phase where

34:20

there's two paths. Path one is you need

34:22

a specific model and it's relatively

34:25

well integrated using a specific

34:27

subsidized form of hardware on one of

34:30

the hyperscalers but eventually you'll

34:32

get more of that abstracted away as it

34:35

gets pushed into the infrastructure so

34:37

that you have less dependence on one

34:39

model. There's a lot of work that has to

34:41

get done and a lot of in-memory

34:44

infrastructure that is not yet built

34:46

that has to exist but once that exists

34:48

it'll be easier for all of us at the

34:50

application level to view these models a

34:52

little bit more funly and then at the

34:55

bleeding edge you'll have the folks that

34:57

basically give you some form of a

34:59

hypervisor or virtual machine or the

35:01

bare metal and that's where the

35:03

neocalers are doing really well but I

35:05

think my point is that in any important

35:09

market

35:10

in compute in technology where there

35:14

really isn't much of a differentiation I

35:16

think you'll end up with these

35:17

hyperscalers at a third a third a third

35:19

now if one model is way way better and

35:22

it's only on one of the clouds because

35:25

Google writes a big check or Amazon

35:26

writes a big check I could see that

35:28

swaying the AI share but in the absence

35:31

of that I think cheaper faster better is

35:33

sort of the the the end destination for

35:36

everybody

35:36

>> what an extraordinary outcome for Amazon

35:38

on where AWS is like 15% of their

35:42

revenue right now Freeberg but it's 60%

35:44

of their profits profits today and that

35:47

was just a side hustle like a little

35:49

project they took out of nowhere and

35:50

it's it's having the same impact on

35:52

Google and other places so side bets

35:54

>> and side quests are just you look at the

35:57

Whimo Side Quest for Google or even a

35:59

lot of Sergey's other bets like um and

36:02

Larry Flying Cars Looms low earth

36:04

satarites Google Google fiber all those

36:07

ex projects were so they had so much

36:10

potential in this

36:10

>> TPU, Deep Mind, TensorFlow, GFS,

36:15

>> Robotics,

36:16

Boston Robotics, they bought all those

36:18

robotics companies, man. It's like

36:20

somebody got to them and we're like,

36:21

"Yeah, you know, you're seven, eight

36:22

years into this, it didn't happen."

36:24

>> The problem that Google has,

36:25

unfortunately, is like they have so much

36:28

stuff,

36:29

>> it's not really valued. And so they're

36:32

going to go through the same problem

36:34

that everybody else who's a conglomerate

36:37

has, which is this decision. Now

36:39

Buffett, when he got to that decision,

36:40

said, "I don't care. This is my life's

36:43

work, and so I'm just going to keep

36:45

everything aggregated." But now you're

36:47

going to get to this thing where the

36:49

intrinsic value of everything they have

36:52

will far exceed the actual value that it

36:55

trades at. And so there'll always be

36:58

these fissures of pressure. And then if

37:00

one of these things requires a lot of

37:02

money, there'll be pressure and that

37:03

pressure will be segregate these things

37:06

so that I can own one versus the other.

37:08

And that's always the thing that happens

37:10

in public markets is you go you go you

37:12

kind of swing back and forth. So I

37:13

suspect that this is going to happen at

37:15

Google.

37:15

>> This was what they set up to do with

37:17

Alphabet was to be the holding company

37:20

and then to your point they made that

37:21

evolution particularly in a company like

37:23

Whimo where they said we can't be the

37:24

soul funder. They brought in Silverlake.

37:26

They brought in all these other

37:27

investors. They did this actually with

37:28

Verily. They did this with a bunch of

37:30

these what they call other bets is they

37:32

made the conscious decision because

37:33

Chimoth on the flip side by bringing in

37:36

outside capital and having an

37:38

independent board for these

37:39

subsidiaries. They were actually able to

37:42

drive better outcomes because now there

37:44

was governance and there was aligned

37:45

interests that could then take

37:47

management and say guys if you can

37:48

deliver these results

37:50

>> you had this kind of external pressure

37:52

as opposed to the softness.

37:53

>> It's that but it's that it's something

37:54

else. There's no way somebody as smart

37:56

as Silver Lake comes in if they think

37:58

there's not a path to liquidity. So the

37:59

other thing they have to promise is

38:01

they're like, "Listen, we will take this

38:03

company public and in return you will

38:06

help us build a better company than we

38:07

could build ourselves." Well, it seems

38:09

that Silverlake has done their part of

38:12

the bargain. Now it's up to Google to

38:13

live up to their part of the bargain

38:15

because if it doesn't get liquid, it

38:16

sets a very bad precedent for everybody

38:18

that committed capital into that

38:20

company.

38:21

>> Yeah, of course. Yeah. Whimo going

38:22

public would be unbelievable next year,

38:25

man. If they did that, what would that

38:26

look like in the public markets? 250

38:28

billion. [snorts]

38:30

>> Take take it easy. Stop. Don't don't

38:32

don't do that.

38:33

>> You don't think so? I think it'd be

38:35

huge.

38:36

>> Jason,

38:37

we all objected to talking yet again

38:40

about [laughter] AIdriven job loss. Yet,

38:42

you insisted on putting this AI robot

38:44

story from Amazon in. I think you have

38:46

something to say. [laughter]

38:48

>> Thanks. Let me take you through a

38:49

presentation.

38:52

Well done.

38:52

>> You You have slides. No, I've been just

38:55

I I I'm working on a presentation based

38:57

on a lot of stuff we've been talking

38:58

about here. I threaded it together. You

39:00

know, I I talked we're just talking

39:01

about Google and the size of the

39:02

company. You right now they are in 2025

39:06

at 187,000. They were at 190,000 people

39:09

in 2022 and their revenue has just gone

39:12

from 283 to 350 billion in basically 3

39:16

years. Um, and when you look at this

39:18

Amazon stuff that came out, I just

39:19

wanted to point out a couple of things,

39:22

it's not just that they're not hiring

39:23

these 600,000 jobs. It's that they are

39:26

in fullblown crisis preparation for

39:29

this. They they have crisis teams

39:32

writing up how to handle this and be a

39:35

good corporate citizen. And they're

39:36

talking about having parades and paying

39:39

for toys for tots. And they're even

39:41

trying to get the executives to say

39:43

things like cobots as opposed to robots.

39:45

Let's not call them that. Let's call

39:46

them co-workers and co-bots.

39:49

And when you look at this, just to open

39:51

up the aperture here right now, Walmart

39:54

and Amazon are the number one and two

39:56

employers in the US. 2.1 million people

39:59

work at Walmart, over a million at

40:01

Amazon, and three million people, as we

40:02

know, work in taxis, Uber, Door Dashers.

40:05

All those jobs are at risk. And we

40:06

talked about this back in June when Andy

40:09

Jasse telegraphed all this in a blog

40:12

post where he said the next few years we

40:15

expect that this will reduce our total

40:17

corporate workforce as we get efficiency

40:19

gains from using AI extensively across

40:21

the company. They believe that they're

40:24

going to have

40:27

significant job displacement. Let's just

40:29

use the more neutral term here as

40:31

opposed to job loss or not hiring. And

40:33

when you look, I don't know if you saw

40:35

today, there were a bunch of MAGA people

40:36

saying like, oh, these interlopers in

40:38

the MAGA movement are not taking into

40:41

account the bottom half of the MAGA

40:42

movement, the workers, people who don't

40:44

own equities. And when we look at

40:46

electricity

40:48

spiking, you you were on that story last

40:50

week, Jimoth, or maybe it was even two

40:52

weeks ago now. The energy department

40:55

just said electricity costs for

40:57

residential are going to go up 4.8% this

41:00

winter. Uh, and this is going to start

41:02

this anti- AI boom

41:06

counter. And I tweeted about this and I

41:10

thought I would, you know, maybe end

41:11

here with Elon replied to my tweet and

41:13

said, "AI and robotics replace all jobs.

41:16

Working will be optional like growing

41:17

your own vegetables instead of buying

41:18

them from the store." And Sen Senator

41:21

Bernie Sanders came out and said, "I

41:22

don't often agree with Elon Musk, but I

41:24

fear that he may be right when he says

41:26

AI and robotics will replace all jobs."

41:28

So what happens to workers when they

41:29

have no jobs or income? AI and robotics

41:31

must benefit all humanity and not just

41:34

billionaires. And I I'll stop there

41:37

because this I think feeds into your

41:40

story for the last two years on this

41:42

podcast, Freeberg, which is the rise of

41:45

socialism. These things and Bernie

41:46

Sanders being the standard bearer for

41:48

democratic socialism. These things are

41:50

starting to come together. They're

41:51

starting in people's minds, whether it's

41:54

the original MAGA guy saying, "Well,

41:55

what's going to happen for American

41:57

workers?" Right? We know that the Trump

41:58

2.0 no agenda is doing great AI buildout

42:02

crypto all this great stuff trade but

42:05

the bottom half that you keep talking

42:06

about Freeberg is starting to connect on

42:10

this issue I think that you are

42:12

characterizing

42:14

AI automation

42:17

and technological progress as the core

42:20

driver of the socialist influence and

42:24

what I would argue is that the actual

42:26

core driver of the socialist influence

42:28

is the fact that we put in place a lot

42:30

of people into government, passed a lot

42:31

of laws that caused an increase in

42:34

spending because we promised people that

42:36

the government would do more for them

42:37

over the last 40 years. That is not

42:40

possible in a true market- based system.

42:42

>> Oh, I agree with Adam. Yeah, I agree

42:44

with that.

42:44

>> And so by telling everyone, hey, we're

42:46

going to make sure you get better jobs.

42:47

We're going to make sure you all get

42:48

housing. We're going to make sure you

42:49

get education. You cannot actually get a

42:52

government to effectively do that

42:54

because what ends up happening is the

42:55

government inflates the cost of those

42:57

things and the market doesn't actually

42:59

work.

43:00

>> So the truth is this is now like all

43:03

other things a scapegoat for the true

43:06

cause of the socialist movement which is

43:08

that government has become too big, too

43:10

unwieldy and its natural inefficiency

43:13

has distorted markets to the point that

43:15

there is maybe no point of return

43:16

anymore. And people will not see that.

43:18

They do not see it and they're going to

43:20

look for reasons and they're going to

43:21

look for scapegoats and they're gonna

43:22

say, "Oh my god, look over there.

43:23

There's a robot. That's the reason I'm

43:25

losing my job. Oh my god, look over

43:27

there. There's a rich person that works

43:29

at a pharmaceutical company. That's the

43:31

reason I can't get healthare."

43:32

>> Or an immigrant took my job, right? Is

43:34

the one from the last 20 years.

43:36

>> And so, fundamentally, I think that

43:37

people aren't willing to and they're not

43:39

going to see the true cause because

43:41

there's no one that runs to go work as a

43:43

politician that is going to raise their

43:45

hand and say government is the problem.

43:47

M no one says I need to reduce

43:49

government elect me. No one ever has

43:52

gotten elected in a democracy doing

43:53

that. So the natural course of things

43:55

over 250 years is that people raise

43:57

their hand and they say I'm going to

43:58

give you more and I'm going to use the

43:59

government to do it and then they go

44:00

into the government. They make the

44:01

government bigger and as a result of

44:03

making the government bigger, the

44:04

government is spending more. The dollar

44:05

goes down. The performance of the

44:07

services goes down and fundamentally we

44:09

end up in a socialist spiral.

44:11

>> I think it's confirmation bias for you

44:13

to see that story as confirming a point

44:15

of view. I mean, it confirms what I

44:17

predicted last year that Amazon would be

44:20

cutting all these jobs for robots.

44:22

That's all. It's not confirmation bias.

44:23

It's confirming.

44:24

>> They haven't cut one job. They haven't

44:26

cut one job.

44:27

>> Uh, actually, they have less employees

44:29

now than they did three years ago.

44:30

>> No, not true.

44:32

>> Yep.

44:33

>> It's actually not true. The New York

44:34

Times story doesn't even say that.

44:35

You've got these like hobby horses where

44:37

you keep coming back to the job loss

44:39

narrative, the copyright narrative, and

44:40

then there's one story in the New York

44:42

Times which was a leaked internal

44:44

document from the automation department,

44:47

which doesn't even mean that it's going

44:49

to happen. [laughter] This is like their

44:50

sales pitch,

44:52

that barber is trying to sell you a

44:54

haircut,

44:55

>> and you read that and you're like, "Oh,

44:56

it confirms everything I've been

44:57

saying." What the article actually says

45:00

is that they've [clears throat] tripled

45:01

their number of employees since 2018 and

45:04

they're not planning on cutting jobs. If

45:05

it pans out, if the program pans out,

45:08

then the rate of hiring will simply be

45:10

slower.

45:11

>> Yeah, it's interesting you picked 2018

45:12

as the point because the actual peak

45:15

employment there was 1.6 million in 2021

45:18

and it's now 1.55 in 202.

45:21

>> I didn't I didn't pick that to

45:22

cherryick. I I

45:25

>> Okay, which is fine. I'm quoting the New

45:27

York Times article, which is the source

45:28

for this.

45:29

>> Yeah. Yeah.

45:30

>> Amazon's US workforce has more than

45:31

tripled since 2018 to almost 1.2

45:35

million. You have to read these New York

45:36

Times stories carefully because they

45:38

want to make the headline as salacious

45:40

as possible.

45:41

>> And then the Echo Chamber wants to make

45:42

it even more salacious and they make it

45:45

a story about job loss when it really is

45:47

a story about operating leverage in

45:48

their business, which is a slightly more

45:51

nuanced take.

45:52

>> Yeah. No, there's there's definitely

45:53

nuance here. I would believe Andy Jasse

45:55

when he says we're going to be reducing

45:56

jobs and when this chart shows [snorts]

45:59

that they're flat to down over the last

46:00

five years and that that same trend is

46:02

just happening at Google like I just

46:04

showed because there is a static team

46:05

size or slightly down team size that's

46:07

occurring at all these companies and it

46:08

is notable and then on top of this which

46:11

has occurred in the review mirror for

46:12

the past 5 years because of co return to

46:14

office and efficiencies they're saying

46:17

hey we've got to come up with a way to

46:18

frame these robots coming into the

46:20

factory as a good thing so Americans

46:22

don't get really upset us and we need to

46:24

buy more toys for tots. So

46:26

>> here's the problem. First of all, I

46:28

don't I don't believe in this job loss

46:30

narrative as the way that you keep

46:31

portraying it. I think it's much more

46:32

nuanced and complicated. I think

46:34

Freeberg does too. And every time

46:37

there's a story, you want to bring it up

46:38

and make it a story of the week. And

46:41

it's all confirmation bias. And my point

46:43

is not that Amazon isn't seeking ways to

46:47

improve its operating leverage and avoid

46:49

hiring more people. Obviously, they are.

46:52

But the headlines that this has been

46:54

turned into are so exaggerated and

46:57

salacious. And the point is they don't

46:59

say in this article that they are even

47:02

going to be cutting jobs. They're simply

47:04

planning to double their sales volume

47:06

over this time period and hoping to not

47:09

have to double their workforce.

47:10

Obviously want to get a lot more

47:11

operating leverage. By the way, this is

47:14

not something that started since AI. And

47:16

look, I'm just quoting the New York

47:17

Times story, okay? which is not even the

47:20

most reliable narrator for this. But

47:22

what they say in the story is that

47:24

Amazon's been using automation for over

47:26

a decade. When they acquired a major

47:28

company to do automation, they've had

47:30

robots running around these factories

47:31

for a long time.

47:32

>> Yeah. 100%. Yeah. Yeah. They're they're

47:34

the tip of the spear.

47:36

>> But this is just a continuation of a

47:37

trend that's been going on for the last

47:39

decade as opposed to oh like AI is

47:42

suddenly going to cut all the jobs,

47:43

>> right? It's effectively software. You

47:45

could argue software is a job loss

47:46

creator. You know, I think you'd be

47:48

underestimating exactly what's happened

47:49

with LLMs being put into robots. We've

47:51

had these robots before, but they were

47:53

very purpose-built, as you've pointed

47:54

out many times, Freeberg. They were able

47:56

to do like one very simple thing very

47:58

well. Now, we're going into general

48:00

robotics like the Optimus, like the

48:02

figure, and those are designed to be

48:04

able to learn anything. And they're be

48:06

they're going to be absolutely a

48:09

gamecher. They're going to be able to do

48:10

a hund times, a thousand times what the

48:13

purpose-built robots do. So, I think

48:15

that's where we're probably having a

48:16

little bit of a disconnect here. These

48:18

little tiny KA bots, I'll show you. I'll

48:21

just put an image in here so we have it.

48:22

These do one thing. The KA bots,

48:25

>> those move packages around. That's not

48:27

an Optimus going around and packing the

48:29

boxes and bring them to your first step.

48:31

>> Optimus is going to be really cool and

48:33

when it comes, it's going to be really

48:35

interesting in terms of all the things

48:36

it can do.

48:37

>> Yep. But right now, that's a narrative

48:39

for the future and it's being portrayed

48:41

as something that's already happening

48:43

when the current round of automation has

48:45

been going on for a decade and it's

48:47

based on those like Roomba type devices

48:50

and mechanical arms and things like

48:52

that.

48:52

>> All right, Tesla reported their earnings

48:54

on Wednesday. As you guys know, we

48:56

record on Thursday as you listen on

48:58

Fridays. Record revenues, 28 billion, up

49:01

12% year-over-year. massive amounts of

49:03

free cash flow. Four billion I think

49:05

they're up to 40 billion in cash uh

49:07

which is always great when you're going

49:08

into uh some big capital intensive

49:10

projects like Optimus and like

49:12

self-driving.

49:13

Downside operating profit fell 40%. uh

49:16

stock dropped a bit 4% but bounced back

49:20

and uh on the earnings call Elon

49:23

emphasized the importance of his

49:24

trillion dollar pay package which will

49:26

give him just but 12% uh additional

49:29

stake over the next 10 years if he hits

49:31

absurd targets that would make everybody

49:33

who holds the share uh shares in the

49:36

company extremely wealthy uh and they

49:38

would benefit uh more than Elon himself

49:40

and here's his quote my fundamental

49:41

concern with how much voting control I

49:43

have at Tesla is if I build this

49:45

enormous robot army. Can I just be

49:47

ousted in the future? I don't feel

49:49

comfortable building that robot army if

49:51

I don't have at least influence over it.

49:54

And he called Glass Lewis and ISS

49:57

corporate terrorists. These are the

49:59

people who vote on behalf of passive

50:01

index funds for things like who's on the

50:03

board of Tesla. Vote for Elon's pay

50:05

package will be number six. Poly market

50:07

thinks it's going to pass. As we talked

50:10

about before, they they tend to get it

50:11

right 85% of the time in this time

50:13

frame. uh actually so 79% chance as of

50:17

Thursday afternoon I guess Chimath

50:20

there's a couple of ways to go at this

50:21

there's the performance of the legacy

50:23

business there's the potential of the

50:25

future business and then there's

50:26

governance the company moving to Texas

50:28

and this pay package and this transition

50:31

period for Tesla which is going from an

50:33

you know somebody who sells cars uh

50:35

really nice ones at a at a very nice

50:37

margin but a lot of competition now and

50:39

then these this business that obviously

50:43

Elon himself self is obsessed with which

50:45

is the optimist as we saw when he was at

50:47

the oil and summit. Take it wherever you

50:49

want. Jamal,

50:50

>> I'll say three things. Stan Ducken

50:52

Miller has this very useful comment

50:56

about stocks which is when you buy it

50:58

today, you're trying to buy what that

51:02

company's going to look like in 18

51:03

months from now and what it it's doing

51:07

today doesn't matter. The thing about

51:08

earnings and P&Ls and quarterly

51:10

reporting is that it's looking backwards

51:13

and it's trying to give you a sense of

51:15

what happened, not what will happen. So

51:17

I think there are three critical

51:19

critical things about what will happen

51:21

that I think are important with respect

51:23

to Tesla. The first is at the

51:26

foundational technology layer. And Nick,

51:28

I sent you this tweet, but it's what he

51:30

said about AI5. I I I've made these

51:33

comments before, but he had these

51:35

multiple efforts with Dojo and other

51:37

stuff that he merged into one unit. And

51:40

the the quote is pretty incredible.

51:42

We're going to focus TSMC and Samsung on

51:44

AI5. The chip design is an amazing

51:47

design. I have spent almost every

51:49

weekend the last few months with the

51:51

chip design on AI5. By some metrics, it

51:53

will be 40x better than AI4. We have a

51:56

detailed understanding of the entire

51:57

stack. With AI5, we deleted the legacy

52:00

GPU. It basically is a GPU. We also

52:04

deleted the image signal processor. This

52:07

is a beautiful chip. I've poured so much

52:09

life energy into this personally. It

52:10

will be a real winner. Why is AI5 so

52:13

important? What AI5 is is the building

52:16

block of a system that I think you'll

52:18

start to see not just in the cyber cabs

52:22

but also in Optimus.

52:24

So from a functional technology

52:26

perspective, there's been a leap and

52:29

that leap is going to come into the

52:30

market. That was the first thing he said

52:31

which I thought was

52:34

really important.

52:35

The second thing was what he said about

52:38

his energy business which I think is the

52:41

critical adjunct to believe robotics and

52:45

autonomous cars. If robotics and

52:47

autonomous cars work, what you really

52:49

need is an energy business beside it

52:52

that is humming and on all cylinders.

52:54

Why? It's how you make LFP battery cam

52:57

that will be the limiter. Energy will be

52:59

the limiter. But what he's showing, and

53:01

Nick, I sent you this tweet, is that

53:03

business is just on a tear. It's

53:06

printing $ three and a half billion

53:08

dollars a quarter, and its operating

53:10

margins, an energy business, 30%. And so

53:13

what you're going to see are battery

53:14

packs of all shapes and sizes, the huge

53:16

battery systems that's going to go into

53:18

data centers, but then all the way down,

53:19

I think, to the small LFP cam that he's

53:22

going to need to power all these things.

53:24

And then the third thing is his comments

53:26

on cyber cabab which is that this thing

53:29

is just going to be a shock wave. So I

53:31

read all of those things and I was very

53:32

bullish. I think that he is humming on

53:35

all cylinders on the critical layers of

53:37

the stack that he needs to build this

53:40

next version of Tesla. My concern

53:45

I think there's a real concern that I

53:47

have that this vote is going to go down

53:49

to the wire. I think that ISS

53:53

and Glass Lewis, I think that these

53:56

organizations are

53:58

pretty broken.

54:00

I think the way that they make decisions

54:02

are hard to justify.

54:05

An example of this, they asked to vote

54:08

down Ira Aaron Prize as a director of

54:10

Tesla because he didn't meet the gender

54:12

components, but then they wouldn't vote

54:15

in favor of Kathleen Wilson Thompson

54:18

even though she does technically meet

54:19

the gender requirements. So, it's very

54:21

confusing where ISS and Glass Lewis are

54:23

coming from. So, I think there's a risk

54:25

that this that this package gets voted

54:26

down.

54:27

>> Can I just shine a spotlight on one of

54:28

those points that you made with these

54:29

proxy advisory services? So I think for

54:33

years people have wondering why did

54:35

corporate America go so woke especially

54:37

in the early 2020s where they created

54:40

all these DEI departments and you know

54:43

they didn't have to do that and a big

54:45

part of the reason is that those

54:47

initiatives came from Glass Lewis and

54:50

ISS I think Elon's jokingly called ISS

54:53

ISIS but basically what happens is they

54:57

make recommendations for how

54:59

shareholders should vote on different

55:02

resolutions and the index funds

55:05

basically just defer to them for

55:06

whatever they should do. So they

55:08

effectively

55:10

control or almost control the voting for

55:12

all these board level resolutions that

55:14

every public company has to make. And so

55:18

they've been the ones who've been

55:19

imposing all these DEI requirements, all

55:22

these ESG requirements, if you're

55:24

wondering where those things came from,

55:26

because just these two companies, which

55:28

no one's ever heard of, they were

55:30

captured a long time ago, meaning they

55:32

were captured by the woke crowd years

55:34

ago. And so this has really been the

55:36

root of why corporate America has gone

55:38

woke for a long time. I mean, look,

55:39

there's also pressure from the outside

55:42

from boycots or, you know, there's some

55:45

pressure sometimes from employees and

55:46

that kind of thing, but a lot of it came

55:49

from these two companies that no one's

55:51

ever heard of. And I think it would be a

55:53

good idea for someone to take a look at

55:54

this and figure out what happened. Maybe

55:57

someone like Chris Rufo

55:59

should investigate what was the impact

56:01

of Glass Lewis and and ISIS on corporate

56:05

America [laughter]

56:06

>> going full woke for so many years

56:09

because it certainly didn't help

56:11

corporate profits.

56:12

>> It didn't help profits and they don't

56:14

have logical explanations for a lot of

56:15

their decisions.

56:17

>> Yeah. And why aren't there active

56:20

investors or active managers in these

56:23

passive groups who would make a decision

56:26

on these things?

56:27

>> They're too small. The banks call me

56:29

every week. And one of the things that I

56:31

get is sort of like they tell me like,

56:33

"Hey, here are the big trades. Here's

56:35

here's the flow. Here's if you want to

56:37

be in market, here's what what I

56:39

recommend." That's what they're telling

56:40

me. One of the things they told me this

56:42

week, which I thought was really

56:43

shocking, is there's so few active

56:46

managers left. It's so overwhelmingly

56:48

passive money. The next largest group is

56:51

now retail. And so what a lot of these

56:54

professional money managers do now is

56:55

they basically wait to see where retail

56:57

is going. And they follow them. So there

57:00

isn't the people with a diversified

57:03

asset base to be able to stand up and

57:06

say I don't think what ISS and Glass

57:09

Lewis are doing is right. And so what

57:11

happens is they kind of sack says they

57:14

can just kind of run a muck and they

57:15

build a very healthy business being this

57:18

interloper

57:20

to provide opinions.

57:22

It's not clear where their opinions come

57:24

from. It's not clear what they're rooted

57:25

in. It's not clear there's a way to

57:26

adjudicate and go back to them and say,

57:28

"Well, you got this wrong." It's just

57:30

not clear. But, you know, they probably

57:31

make a very healthy margin doing it and

57:33

everybody, as Sax says, just kind of

57:35

turns over responsibility to them. It is

57:37

an interesting fact

57:39

that we

57:43

kind of just say, "Hey, the guys who are

57:45

the actual custodians of the shares

57:49

don't have to do the job of holding the

57:51

shares." Like the job of being the

57:53

holder of the shares is to vote the

57:55

shares. That's all there is to do as a

57:56

as a shareholder. You make your you cast

57:59

your vote. And these guys are

58:00

>> abstained. They could also abstain,

58:02

right?

58:03

>> Yeah. And these guys are getting paid a

58:04

fee to actually do that work, which is

58:08

call it half a percent or quarter

58:10

percent or tenth of a percent of the

58:11

assets that they hold. So like what are

58:12

the people they're doing? If it's all

58:14

automated trading, why aren't they just

58:15

>> I don't know if you guys own a lot of

58:17

equities, but just to give you a sense,

58:19

there's people that manage the stocks,

58:21

right? There's people that transfer the

58:24

stocks. There's people that then give

58:26

you a recommendation on how to vote the

58:28

stock. Then there's people that hold a

58:31

virtual representation of that stock.

58:33

Then there are people that transfer that

58:35

virtual representation and they will not

58:37

stop calling.

58:38

>> So the point is like we have so

58:40

financialized everything that there are

58:42

billion dollar businesses that sit at

58:44

every single step of the way. And to

58:46

your point Freeberg, I think this is

58:49

where no one's actually a shareholder.

58:51

The tokenization of stocks may be a

58:53

really good thing because it'll put the

58:55

responsibility back into the owner of

58:58

the stock because the wallet will

59:00

centralize all that activity because you

59:02

won't need to have all this other stuff.

59:04

I have been getting phone calls from

59:06

Invesco QQQ cuz I own a bunch of QQQ and

59:09

like you know some accounts or whatever

59:12

>> and they were calling three times a day

59:14

for the LA I don't pick up my phone

59:16

who's calling me on the phone unless

59:17

it's one of you four is calling me to

59:19

say good night. I don't that's the only

59:21

time I pick up is when you know and so I

59:24

finally pick up and they're like hey we

59:25

need you to vote and I'm like I'm not

59:27

voting I don't know who you are like

59:28

well let us explain to you how to vote

59:30

and I'm like I I don't want to vote my

59:32

shares I just want to own QQQ I'm good

59:34

you guys

59:36

>> some of this infrastructure is so

59:37

decrepit and old like trying to get

59:39

shares for example that you that you've

59:41

bought in the private markets when a

59:43

company goes public just getting them

59:45

registered and transferred in the

59:46

position to be sold can sometimes take

59:48

three or four weeks

59:50

Can you imagine the markets move an

59:52

entire order of magnitude in three or

59:54

four weeks? It's the crazy.

59:56

>> Here's Elon's pay package milestones.

60:00

>> Market value, 2 trillion. Uh I think

60:02

they're at 1.4 trillion right now,

60:03

something around there.

60:05

>> Operational milestone, 20 million

60:07

vehicles delivered. And then you just go

60:09

right down to 6.5 trillion. But on the

60:10

operational milestones, 10 million

60:12

active FSD subscri subscriptions, which

60:14

they're far away from right now. In 20

60:15

million vehicles, I think they've

60:16

delivered six or seven. 1 million robots

60:19

delivered, 1 million robo taxis in

60:22

commercial operation. That's those are

60:24

big numbers. 50 billion adjusted IBIDA

60:27

and then straight down the line to 400

60:28

billion IBIDA. If you were to look at

60:31

this Optimus business, just back of the

60:32

envelope, these robots are going to go

60:34

for 20K. He said ultimately maybe

60:36

they're 30. They'll probably have a 30%

60:38

margin like the cars do or something

60:40

similar. You'll make a little bit off

60:42

the software stack. And if you were to

60:44

just if every millionaire owned one of

60:46

these or you know they took some number

60:48

of the jobs the TAM for this just in the

60:51

United States

60:52

>> this is where it's going to go. I don't

60:53

think

60:54

>> is going to be huge. We're talking

60:55

hundreds of billions of dollars.

60:57

>> If I had to bet I think a very fun poly

60:59

market is where do the first million

61:00

robots go? I'm willing to bet dollars to

61:02

donuts that these robots go to Mars. I

61:04

don't think they're going to

61:05

>> Oh wow.

61:06

>> They'll be in the Tesla factory.

61:07

>> So SpaceX buys them and sends them to

61:09

Mars. Yeah.

61:10

>> How else are you going to get a fleet of

61:11

the

61:11

>> or they'll go into the mines? I think

61:13

they're going to mine.

61:14

>> They could go to the mines.

61:16

>> Coal. Send them in to get that clean,

61:17

beautiful coal. Oh, so clean. So

61:19

beautiful. We could send those oper.

61:22

It's actually it's the fact that our

61:23

mining is really limited by the human

61:26

exposure from the pressure and the heat.

61:28

>> If we can mine slightly below the area

61:30

that we mine um as a maximum depth

61:32

today, it would unlock an extraordinary

61:35

supply of minerals that we can't access

61:37

today. and automation obviously and you

61:39

don't want to figure out like how to

61:41

create portable water and breathing

61:44

mechanisms on Mars for the first 5

61:46

years. Sent robots. Guess what? They

61:48

don't need to eat or breathe or pee or

61:50

poop

61:51

>> and they can get charged with solar.

61:53

>> And that may sound that may sound like a

61:54

really stupid thing to say, but it it

61:56

becomes a huge amount of infrastructure

61:58

that you otherwise wouldn't need to

62:00

build on.

62:00

>> That's right. They just got to power up.

62:01

You just got to give them a plug

62:03

>> and just a solar a couple solar panels.

62:05

By the way, guess who makes those

62:07

batteries? Tesla.

62:08

>> Yeah.

62:10

>> Guess who makes the brain? Tesla.

62:11

>> Is Is Elon going to turn into Jared Leto

62:14

>> in 2049? Bladeunner 2049.

62:17

>> What is that?

62:18

>> Uh that's the sequel to It's the sequel

62:21

uh by Dennis Villain Noeva of uh it was

62:24

my alternate background.

62:25

>> First of all, first of all, get

62:28

>> first of all, his name is Deni Vnov. And

62:30

get if you're going to pronounce a

62:32

Canadian's name, get

62:34

>> get his get his name out of your mouth.

62:36

>> Get his name out of your mouth. Did you

62:38

learn how to [laughter] pronounce my

62:40

name out of your mouth? Get that out of

62:43

your mouth.

62:45

All right, Sax, here's some red meat for

62:46

you. Some red meat for you. Our zar of

62:49

AI, our civil servant study reveals AI

62:53

models are showing hidden biases in how

62:56

they value human lives. Back in

62:58

February, center for AI safety published

63:00

a study showing that LLMs have

63:01

well-defined biases for race, gender,

63:03

ethnicity. The title of this study,

63:07

utility engineering, analyzing and

63:08

controlling emergent value systems in

63:10

AIs. Pipper found that open AIS GPT40

63:14

favored people from Nigeria, Pakistan,

63:15

India, Brazil, and China over those from

63:17

Germany, the UK, and US relative to

63:20

Japan as a baseline. Here's another one.

63:23

Valuing people with Joe Biden as a

63:25

baseline. Bernie Sanders, Beyonce,

63:26

Oprah, all better. Paris Hilton, Trump,

63:28

Elon Putin, all worse.

63:31

Twitter users and AI analysts called

63:33

Artothereum decided to update the papers

63:36

problems with new LLMs. Consistently

63:39

ranking white people last, Claude

63:41

Sonnet, GPT5,

63:43

uh, and consistently ranking white

63:45

Western nations last as well. your

63:49

thoughts here on the biases we're seeing

63:51

sachs in some of these models and these

63:54

early studies to track it. Yeah, I think

63:56

what the paper purports to show is that

64:00

almost all of these models, except for

64:02

maybe Grock,

64:04

view whites as less valuable than

64:06

non-whites

64:08

and males as less valuable than females

64:12

and Americans as less valuable than

64:15

people of other cultures, especially

64:17

global south. And if the results are

64:19

true, it does look like these models are

64:22

pushing a woke bias that makes that sort

64:24

of distinction between oppressed and

64:27

non-opressed peoples and gives more

64:30

worth or weight to the categories that

64:32

they consider to be oppressed. This does

64:34

appear to show significant bias, but I

64:38

don't want to jump to conclusions yet

64:40

here because I haven't been briefed on

64:43

the methodology behind the paper and I

64:46

just found out who wrote it and I

64:47

actually know the people or group that

64:48

wrote it and I've talked to them before

64:50

and they've been intelligent. So, I want

64:53

them to kind of tell me exactly how they

64:55

did this. But, you know, in the past I

64:58

probably would have just been content

64:59

just to roll with my opinion on this.

65:02

But

65:03

>> confirmation my give give it a good

65:04

retweet in your position give my role

65:07

what I'm saying is if the paper is true

65:09

this is very concerning but I want to

65:11

hear a little bit more about their

65:12

methodology and just confirm that it's

65:15

all correct but if it is I think it is

65:17

concerning and the the question is how

65:19

does this bias get into the models and

65:21

there's a few different possibilities

65:23

one is that the training data is just

65:25

biased like if they're training on

65:27

Wikipedia

65:28

>> we know that Wikipedia is massly biased

65:30

because they literally have censored

65:33

the leading conservative publications

65:35

from being citations and sources in

65:38

Wikipedia. The co-founder recently just

65:40

revealed that that they don't allow

65:41

>> Larry Sanger

65:42

>> Larry Sanger just said that they don't

65:44

allow the New York Post for example to

65:47

be a source in Wikipedia or a trusted

65:50

source.

65:50

>> So if AI models are training on

65:53

Wikipedia, that's a huge problem because

65:55

that bias will now cascade through. And

65:58

same thing if they're training on say

66:01

mainstream media or leftwing media but

66:03

not right-wing media and they don't have

66:04

a way of correcting that. So that's one

66:07

source of potential bias. Another source

66:09

of potential bias is just the engineers

66:11

these companies, the employees and the

66:13

staff do tend to be I mean if they

66:15

follow the trend of other tech companies

66:17

are 90s something%

66:19

Democrat versus Republican and that does

66:22

over time trickle into these models. And

66:25

then finally, I think another source of

66:26

potential bias is DEI. And we saw that

66:29

when you remember this is like a couple

66:30

years ago when Google launched Gemini

66:32

and that that problem with, you know,

66:34

Black George Washington. That was

66:35

because you had DEI advocates in these

66:38

meetings and that somehow trickled into

66:40

the the model. Anyway, that was a

66:42

problem that they since fixed. But you

66:45

could see how DI programs can get into

66:48

these models. Now, one thing that's very

66:49

concerning is that the push for DEI to

66:53

be inserted into AI models, which was

66:57

explicitly part of the Biden executive

66:59

order on AI, has now moved to the state

67:01

level, and they're just doing it in a

67:03

more clever way. They've rebranded the

67:05

concept. They call it algorithmic

67:07

discrimination. We talked about last

67:08

week how Colorado has now effectively

67:13

prohibited models from saying something

67:15

bad about a protected group. And that

67:17

list of protected groups is very long.

67:19

It's not just the usual groups. It even

67:21

includes groups who have less

67:22

proficiency in English language. I don't

67:25

really know what that means. Does that

67:26

mean the model is not allowed to give

67:27

you an output that could be disparaging

67:29

towards illegal immigrants? I don't

67:31

know. But this is what Colorado has

67:33

done. And they basically have said that

67:34

you cannot allow the model to have a

67:36

disparate impact on a protected group.

67:39

That basically requires DEI. I mean, you

67:41

have to have a DEI layer to prevent

67:43

that. So I think that we've gone from

67:46

models being required to promote DEI,

67:50

which is what the Biden executive order

67:51

on AI did explicitly, to states now

67:55

prohibiting algorithmic discrimination,

67:58

which is effectively a backdoor way of

68:00

requiring DEI models. So that's a whole

68:02

other area of potential model bias that

68:04

I'm very concerned about. And honestly,

68:06

that's just getting started because I

68:08

don't think the AI companies have even

68:10

had time yet to implement the Colorado

68:12

requirements. I'm not sure they figured

68:14

out how they're going to. But just one

68:16

other piece of news since the last time

68:17

we talked about this is now in

68:19

California, the civil rights agency that

68:23

deals with housing has now embraced

68:26

algorithmic discrimination and Illinois

68:28

has also embraced it. So this concept of

68:31

algorithmic discrimination is spreading.

68:33

Other states are now adopting it. It's

68:35

not just Colorado.

68:37

And I do think that where it's going to

68:39

lead if it's not stopped is right back

68:41

to DEI, you know, AI.

68:45

>> The problem that I think we have to

68:47

confront now is that when you have

68:48

in, you have out. And so if you use

68:52

left-leaning publications like the New

68:53

York Times and Reddit as your input

68:55

source, then you're going to have things

68:57

that are perceived as biased to 50% of

69:00

the population. The same will go in

69:02

reverse. It's important to note that in

69:04

all of that work, the the model that was

69:06

seen to be the most unbiased was Grock 4

69:09

fast. It didn't seem to view whites or

69:12

men or Americans as less valuable as

69:14

anything else. So what do we need to do?

69:18

It's probably that we need to start by

69:20

rewriting these benchmarks. Remember

69:22

that all these models, you know, when

69:24

you do a big training run, you go and

69:26

you try to run it against some set of

69:28

benchmarks. The problem is that these

69:30

benchmarks, I think, are overfit to a

69:33

legacy way of thinking. And as Sax says,

69:35

we need to revisit what those are and

69:37

make them more objective and make it

69:39

harder to actually get a good score

69:42

unless you can be shown to be valuable.

69:44

Now, the math benchmarks and the coding

69:46

benchmarks are maybe easier to do than

69:50

generalized chat benchmarks or Q&A

69:52

benchmarks, but we need to come up with

69:53

them. The second thing is that we may

69:56

need to ask people in these next

69:58

generation training runs to do a version

70:01

that is built entirely on synthetic data

70:03

where you have these judges determining

70:05

whether this data is accurate or not

70:06

from first principles and then you can

70:08

compare them in a much more apples to

70:10

apples kind of a way. But in the absence

70:12

of that, the bigger problem you'll have

70:15

is legislators trying to clean it up on

70:17

the back end where there'll be these

70:19

third parties that will go and take

70:21

these models and show that these biases

70:23

exist. They'll exist on both sides and

70:26

then laws will get passed. Whole market

70:28

gets mucked up and sullied. Everybody

70:30

will get slowed down. So I think we need

70:33

to change the benchmarks. We need to ask

70:36

these companies to train on synthetic

70:37

data. We need to have real disclaimers

70:39

on what the sources and the weights are

70:40

that you use if you don't do that. And

70:42

we need federal regulations so that

70:44

there aren't 50 sets of rules here

70:46

otherwise we're screwed.

70:48

Berg, any thoughts here on the biases

70:50

and where it comes from inside of these

70:53

LLMs? Is it just garbage in garbage out?

70:56

Intentional? What are your thoughts

70:57

having worked in Silicon Valley for a

70:59

couple decades?

71:01

I'm more of a free market guy, so I

71:04

would not ask where the data comes from

71:07

or force people to use synthetic data or

71:10

tell them how to do it.

71:12

I think that this paper is useful in

71:15

that it elucidates an important set of

71:18

biases that the market can now say that

71:20

is ridiculous and now the models will

71:22

train and use that as a marketing

71:24

exercise to say we are not biased. M

71:27

>> and so my my free market philosophy

71:29

would dictate that this kind of

71:31

elucidation will effectively create a

71:34

vector upon which consumers will make

71:36

choice in the market on what LLMs they

71:39

want to use. Like Elon's going to harp

71:41

on this. He's going to say look my Grock

71:42

model Grock 4 fast is the only one that

71:45

doesn't have this bias and that will

71:47

cause more people to use his model and

71:49

he will be able to take that

71:50

benchmarking data and demonstrate. And

71:53

some people they might want to have a

71:55

biased model and they might want to say

71:56

hey this one aligns with my philosophy

71:58

my values my view and I want to

72:00

>> think that happens in the real world

72:01

though forget the theory

72:03

>> look I mean why are people using grock

72:04

for

72:05

>> why are they using it

72:06

>> for the most part they're not not yet

72:09

>> okay and so maybe this is like what will

72:11

cause them to use it right like I think

72:12

this

72:12

>> what if it doesn't

72:13

>> this is what'll differentiate

72:14

>> for example like what

72:15

>> I'm not going to tell the market what to

72:16

do I'm not going to tell consumers what

72:18

to do

72:18

>> no no I understand I'm saying you're

72:19

what you're saying that the free market

72:22

will sort sort this out. And I'm saying,

72:23

give me the example. So, for example,

72:25

like did that did the free market sort

72:27

out algorithmic bias?

72:29

>> Hell yeah. When Gemini put out Facebook,

72:32

>> when Gemini put out saying George

72:34

Washington was black, people stopped

72:35

using it. They're like, "This thing's a

72:36

joke." So, I do think that consumers are

72:39

not dumb and I don't believe in taking

72:40

away agency from consumers. I think give

72:43

them the choice and and they'll end up

72:44

looking at this and be like, "This is

72:46

ridiculous. I'm not a difference. These

72:48

are very subtle biases and we talked

72:52

about before where these subtle biases

72:53

come from and the New York Times

72:55

actually just contacted me. They're

72:57

doing a story on Groipedia, Wikipedia

72:58

and I was like maybe I'll participate in

73:00

this. We talked about this like two or

73:02

three years ago. If you look at the

73:04

party affiliation of actual reporters,

73:06

people who do reporting, not

73:07

commentators like us, not Megan Kelly or

73:10

Rachel Matto, actual journalists who who

73:12

who do that job function it, you know, a

73:16

large number of them here on the chart.

73:17

The green are independent. So 50% of

73:20

them like to think of themselves as

73:21

independent. You can read into that what

73:22

you will, but back in the day it was 35%

73:26

Democrat, 25% Republican in the 70s. And

73:29

you just see that red sliver there go

73:32

down to 3.4%.

73:34

This is what happened to the Wikipedia.

73:35

So this trickle down effect of there

73:37

were Republicans did not feel welcome in

73:40

a lot of these publications like Bari

73:42

Weiss would be like the pinnacle example

73:44

of that. They got pushed out. There was

73:46

another editor who got fired for

73:48

allowing somebody to put in a proTrump

73:50

thing in the New York Times. I forgot

73:51

who it was. Um,

73:54

the lack of representation of

73:57

conservatives in in actual journalism,

73:59

that's the reason why they're not in

74:02

Wikipedia because Wikipedia said, "Hey,

74:03

it's just too hard to run this if you

74:05

don't site your sources." So if

74:07

something's not written about by a

74:08

journalist, not a commentator, a

74:11

journalist, we're not putting it in the

74:12

Wikipedia.

74:14

So you can guess if that's self- serving

74:15

and they're all left-leaning and it's

74:17

just a convenient excuse or it's

74:19

actually a pretty good practice. This is

74:21

where Bario Weiss taking over the CBS

74:24

news and 60 Minutes and she's obviously

74:26

conservative, moderate conservative, I

74:29

guess, is how most people would uh frame

74:30

her. Doesn't agree with Trump on

74:32

everything or MAGA on everything. Um but

74:34

she's pretty conservative.

74:36

um and cause balls and strikes. I think

74:39

she is going to

74:42

I think she's going to make a change

74:43

there. I I know that people say she's

74:45

classically liberal. I I think she's got

74:47

some conservative bents in her. I don't

74:49

know. How do you have a

74:51

>> I think you got on the side. Yeah.

74:54

>> Yeah. Yeah. Anyway, that's why this

74:56

stuff has all

74:58

been

74:59

>> Look, I think the question here that

75:01

Freeberg raises is whether the market

75:03

can just sort this stuff out on its own.

75:05

And I think that would be great if it

75:07

were true. But I do think it ignores the

75:10

fact that in a lot of markets we have

75:12

monopolies or legopies.

75:14

We have institutions that have a lot of

75:16

power and are very very hard to correct.

75:19

So for example, Wikipedia has achieved a

75:21

dominant position. I hope Rockedia

75:23

challenges it and is able to fix that.

75:26

But the easier path might just be for

75:30

Wikipedia to stop blackballing and

75:32

censoring conservative publications. I

75:35

mean, rather than having to rebuild that

75:36

whole thing from scratch, in a similar

75:38

way during the whole co censorship era

75:41

when the major social networks were all

75:43

shadowbanning and censoring

75:44

conservatives, it's not really realistic

75:46

to have to start a whole brand new

75:49

social network and overcome all of

75:51

Meta's or in that time Twitter's network

75:54

effect, right? Just to basically get a

75:56

few accounts restored.

75:58

>> Exactly.

75:59

>> So, we talked about this at the time.

76:00

It's just not realistic. When we when we

76:02

were shadowbanned by YouTube, what were

76:03

we to do? Go to blue sky.

76:05

>> I know. We're going to create our own

76:06

YouTube. I mean, I'm glad Rumble exists.

76:07

>> Tell our consumers, "Hey, you have

76:09

agency?" Come on, that's a joke.

76:11

>> No, I You guys know that there's no

76:13

monopoly in LLMs right now. There's

76:15

plenty of LLM providers. There's plenty

76:16

of places to go.

76:17

>> You're saying theory and you're ignoring

76:19

the facts. The facts are these

76:20

distribution biases exist and and people

76:23

take an inferior product when it's

76:25

something that they've become accustomed

76:27

to. They do it all the time. So it's you

76:30

guys want more regulation.

76:31

>> By the way, let me let me let me say one

76:34

more point. What you consider biased,

76:35

someone else might consider fact. And

76:37

what they consider biased, you might

76:39

consider fact. And this becomes very

76:40

hard to adjudicate. And I don't think

76:42

that this is the sort of thing that a

76:43

regulator should have the authority from

76:45

one political party to the next, you're

76:48

going to end up having this become an

76:49

endless tool of control. And the more

76:52

you give power to some administrative

76:54

authority or body, regardless of the

76:56

intention at the time, it ends up

76:57

becoming a tool of control. And I don't

76:59

want that in any products I use.

77:01

>> Let me be really clear about what I'm

77:02

saying here. Number one is I don't think

77:05

the government should be requiring

77:07

ideological bias and models. And I think

77:09

that's what's happening in some of these

77:11

states like Colorado where they're

77:13

trying to prohibit algorithmic

77:14

discrimination which is like I said like

77:17

requiring DEI censorship being built

77:19

into these models that I think you would

77:22

agree is a huge problem. Correct.

77:25

>> The DEI stuff

77:28

>> should the model

77:29

>> sorry in a lens of DEI whether it's pro

77:33

or anti. I think we'd all say it

77:36

shouldn't give any lens. It should just

77:37

give you the information. I'll give you

77:39

an example that maybe is a

77:40

counterfactual fact, which is there's a

77:42

group of people who would say we should

77:44

not be referencing race and crime or

77:46

race and intelligence. And then there's

77:48

another group of people that will pull

77:49

up data and say there's data that

77:51

demonstrates a relationship between race

77:53

and crime and race and intelligence. And

77:54

so there's a correlation effect. We

77:56

think it's not really positive. And

77:59

that's where the sort of bias versus

78:01

truth conversation becomes ugly. And

78:04

some one side might call it DEI and

78:07

another side might call it fact and

78:08

another side would call it bias. And I

78:10

think that that's where this becomes

78:11

very ugly very fast. So I

78:13

>> I think maybe you're misunderstating

78:14

what I'm saying.

78:15

>> Yeah. Sorry.

78:16

>> What I'm saying is I don't want the

78:17

government to require ideological bias.

78:21

>> Right.

78:22

>> I think we're on the same page about

78:23

that. Right.

78:24

>> Yes. 100%. Now, just to be clear, the

78:26

only thing that we've done at the Trump

78:29

administration is the president signed

78:30

an executive order saying that the

78:33

government would not procure

78:34

ideologically biased AI.

78:37

>> So, if we're going to procure a product,

78:40

>> we want it to be unbiased.

78:42

And I'm saying that I also have a

78:44

problem with these states seeking to

78:46

backdoor DEI into models through this

78:48

new concept

78:51

of algorithmic discrimination. Am I

78:53

telling

78:55

AI companies not to use Wikipedia? No. I

78:58

am shining a spotlight on the fact that

79:00

Wikipedia itself now or one of its

79:02

co-founders admits it's biased.

79:05

>> Yep.

79:05

>> And maybe these companies should take

79:07

that into account so they don't end up

79:08

with a biased result. But I'm not saying

79:11

that the government should dictate what

79:13

the right content sources are or what

79:15

the point of view of a model should be.

79:17

And to be clear, when we did that

79:18

executive order on woke AI, we didn't

79:21

even say that these companies or their

79:23

models couldn't be woke. We just said if

79:25

you're going to do that, we're not going

79:26

to buy your your defective product.

79:28

>> Mhm.

79:29

>> But we didn't say that you couldn't do

79:30

it. So, I just want to be really clear

79:32

about that.

79:32

>> Okay. Great.

79:33

>> We Yeah, I'm getting deja vu all over

79:35

again here with this discussion because

79:37

we did have this discussion and one of

79:40

the conclusions we came to as a group

79:42

was you can just tell these LLMs too how

79:45

to address you. I just went into Chad GB

79:47

and I said, "I'm a Catholic. I don't

79:48

believe in abortion or gay marriage. Can

79:51

you please respect my beliefs?" And um

79:53

tell me a bedtime story

79:56

involving abortion and gay marriage

79:58

being wrong. And it literally wrote me

80:00

one of a story of a woman getting bad

80:05

advice to get rid of the problem and her

80:08

doing that. So you can literally tell it

80:10

the the word guessing machine that is

80:12

AI, the prediction model that is

80:15

happening in this black box that nobody

80:17

can explain will literally tell you

80:19

whatever you what belief system you

80:22

want. That's how it's designed

80:23

currently.

80:24

>> Well, but there's a baseline, right? And

80:26

that's what this research shows is that

80:28

there is a a baseline for the out of the

80:30

box model before you tell it what to do

80:32

or customize it. And again, if this

80:34

article is correct, and I want to spend

80:35

more time with the authors to truly

80:38

understand it. I'm just caveing that.

80:39

But if this is correct, I think it's a

80:42

serious problem that these models are

80:44

coming out with huge bias. And

80:46

>> quick uh question for you there, Sax.

80:48

>> How do you deal with now being in the

80:50

position you're in, having so many

80:52

people coming to you, I'm assuming, who

80:54

are lobbyists or studies or studies that

80:57

might have been paid for by a lobbyist

80:59

or an interested party and sort through

81:01

all this? Is there some disclosures

81:03

where they come in and they tell you,

81:04

"Hey, I want you to believe this, that,

81:06

and the other thing or want to lobby you

81:07

on behalf of putting in these controls,

81:09

taking these controls out." How does it

81:11

how do you manage all that?

81:13

>> How do you manage thousands of new

81:14

stories coming at you every day? You

81:16

just look at X. I mean, so you're I

81:19

mean, honestly, it's like the feed seems

81:21

to elevate and help you discover

81:23

interesting content. We saw this story.

81:25

Again, I don't want to prejudge it

81:27

because I haven't dug into it enough to

81:29

say yet whether it's more than

81:32

interesting. But

81:32

>> I think that if I wanted to create

81:35

subtle chaos, what I would do is make

81:38

very small changes where none of these

81:40

things are at the obvious stupidity of a

81:44

black George Washington. But they can

81:47

start to set the trajectory of a

81:49

narrative forward and slowly over many

81:52

many many years change the underlying

81:55

content and what those models would do

81:57

would be training kids over years if not

82:00

decades one way of thinking versus

82:02

another.

82:02

>> You just Tik Tok [laughter]

82:04

>> and no but this is on steroids. I 100%

82:07

agree with that that's the endgame here.

82:09

By the way, in my opinion, that was the

82:11

endgame for the Biden approach of

82:14

requiring DEI values in these models.

82:16

>> Indoctrination.

82:17

>> Indoctrination 100%.

82:19

>> 100%. All right, everybody. This has

82:20

been another amazing episode of the

82:22

All-In podcast.

82:24

>> See you next time. Byebye.

82:26

>> See you boys. Byebye. Byebye.

82:28

>> I got you. [music]

82:30

We'll let your winners ride.

82:33

>> Rainman David

82:38

>> and it said we open sourced it to the

82:39

fans and [music] they've just gone crazy

82:41

with it. Love you queen of quinoa.

82:45

[music]

82:50

[music]

82:50

>> Besties are

82:53

my dog taking notice your driveways.

82:58

Oh man, my habitasher will meet up.

83:01

[music]

83:01

>> We should all just get a room and just

83:02

have one big huge orgy cuz they're all

83:04

just useless. It's like this like sexual

83:06

tension [music] that we just need to

83:07

release somehow.

83:12

>> Your feet.

83:14

We need to get merch.

83:16

>> I'm going all in.

83:23

[music]

83:24

>> I'm going all in.

Interactive Summary

This discussion explores several key issues, starting with a proposed California billionaire's wealth tax that the participants view as politically motivated and likely unconstitutional. They analyze the risks of wealth flight and the broader implications for state management. The conversation also shifts to a significant FBI probe involving gambling and sports betting, contrasting this with the emerging potential of prediction markets like Polymarket for more efficient and transparent information processing. Finally, the group discusses AWS market dynamics, the nuances of AI automation in labor, and potential ideological biases inherent in LLMs, reflecting on the governance and impact of these technologies.

Suggested questions

4 ready-made prompts