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Trump AI Speech & Action Plan, DC Summit Recap, Hot GDP Print, Trade Deals, Altman Warns No Privacy

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Trump AI Speech & Action Plan, DC Summit Recap, Hot GDP Print, Trade Deals, Altman Warns No Privacy

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2565 segments

0:00

How much founder mode did you do?

0:01

>> Are you saying that I popped an ALP? I

0:03

need an ALP right now. Hold on. You

0:04

don't need anything right now. Are you

0:06

chewing it? What are you doing?

0:07

>> No. You put this nicotine pouch, you

0:09

upper deck it, releases it, and then you

0:11

become a god.

0:12

>> Is that the app that Tucker sent you?

0:14

>> Yeah. Tucker and I are going to do a

0:16

crossover.

0:16

>> Wait, did you work out a side hustle

0:18

here?

0:18

>> I haven't presented it to the group for

0:20

a vote yet. You're pre-

0:21

>> Wait a second. Are you being paid for

0:22

this plug right now?

0:24

>> Yes.

0:24

>> I'm just saying if you use the promo

0:26

code JCL.

0:27

>> Wait a second. Promo code J 15.

0:32

>> Okay, he broke up, which is good.

0:33

>> Is he on drugs? Is he taking drugs?

0:35

>> He's on drugs.

0:36

>> No, I'm not on drugs.

0:37

>> And he's doing a deal with

0:38

>> This is like a PSA for not taking this

0:41

stuff. You're so out of control.

0:42

>> Did you take two of them? What are you

0:44

doing?

0:44

>> I thought this stuff relaxes you. What

0:46

the hell is going on? Your internet's on

0:49

the fritz, too.

0:50

>> I fixed it. I fixed it. I fixed it. That

0:52

was Putin. Putin's got my internet.

0:55

>> Putin's got my

0:56

>> Oh my god. What flavor are you eating or

0:58

using?

0:59

>> Oh, today's chilled mint. Today's

1:00

chilled mint.

1:01

>> You don't seem very chill. You seem

1:04

>> This is the first one.

1:05

>> Agitated and angry.

1:07

>> No, I'm trying to get us back to that

1:08

original all-in energy where we laughed

1:11

and we had fun and we enjoyed each

1:12

other's company.

1:14

>> No, but Jakeal, seriously, do you have a

1:16

side deal going on with Alp right now?

1:18

>> No, I don't have a deal yet. I don't

1:21

know if I have a deal. There's no deal.

1:23

I'm texting Tuck right now just to cut

1:25

you.

1:27

[Music]

1:29

Let your winners ride.

1:32

[Music]

1:36

>> We open sourced it to the fans and

1:38

they've just gone crazy with it. Love

1:40

you guys. Queen of

1:44

>> All right, everybody. Welcome back to

1:46

what Jensen from Nvidia has confirmed is

1:50

the number one podcast in the world.

1:52

Yes, the All-In podcast is here. We had

1:55

an amazing time in uh DC last week and

1:59

we'll get into that. But uh hey

2:02

Freeberg, you crushed it on all those

2:05

incredible speakers last week. 10 days

2:08

you had to pull off that event Freedberg

2:11

and you did it. Chimath and I just

2:13

parachuted in to DC last week for the AI

2:16

summit. Sax was busy working with pus to

2:18

get all those executive orders done.

2:20

Take us behind the scenes, Freeberg. all

2:23

of these incredible speakers. You got

2:24

Lisa from AMD. You had Lutnik, I liked

2:28

him. Bessent, I liked him. We had to say

2:31

no to a lot of tech company CEOs that

2:33

found out about the event and wanted to

2:35

speak on stage. So, there was a big kind

2:37

of cut off that we had to make around

2:39

making sure that we got our message

2:41

across. I think if you watch the

2:43

content, we talked briefly about it at

2:44

the beginning, but the focus was really

2:46

on trying to dispel the negative AI

2:50

narrative and myth that AI is just here

2:52

to destroy jobs because there's this big

2:54

economic boom that's happening both with

2:56

respect to new industries that are

2:58

emerging, which is why we showcased

2:59

Hadrian and others, but then also the

3:02

infrastructure needed to support the AI

3:05

race with data centers, chips, mining,

3:09

and energy. And so we highlighted each

3:10

of those four industries. And then the

3:12

cabinet people found out about it and

3:14

wanted to get involved. So we were

3:17

unfortunately squeezing people on and

3:18

off stage. It's kind of crazy to tell

3:20

the secretary of treasury he has to get

3:22

off the stage because he's passed his

3:24

20-minute allocation. But uh we had to

3:26

line everything up so that the president

3:28

could get his Secret Service detail to

3:30

clear the stage and get set up in time.

3:31

That's why we were rushing everyone. But

3:33

man, what a week. What a rush. It was

3:35

awesome. Thanks to David Saxs for the

3:37

leadership and pulling it all together,

3:39

bringing those folks to the table. And

3:41

Sax, congrats on getting your EO signed

3:43

and your action plan published. That was

3:45

pretty cool. Pretty awesome to meet the

3:47

president and meet all those cabinet

3:49

members and have all of this day come

3:51

together because of the work you've been

3:52

doing. How does it feel? Like, Sax, how

3:55

are you doing in the afterlow there? I

3:57

can see that you're in the afterlow. You

3:59

sent me a picture of the four besties

4:02

with our incredible 47th president. How

4:05

you feeling right now?

4:06

>> Are you going to put that on the screen?

4:08

>> I may have it. I don't I don't know if

4:10

that's allowed. Are we allowed to put

4:12

that on the screen? I don't know what

4:13

the protocol is.

4:14

>> Yeah, I think we can.

4:15

>> Yeah. I mean, I haven't gotten my

4:17

picture. Um I did notice that I was

4:19

unfortunately when they took the picture

4:20

of the four of us with the president,

4:22

somehow I got cropped out by accident. I

4:24

think maybe they weren't using a wide

4:26

lens.

4:26

>> Wait, Jason, what was it like for you to

4:28

meet the president? Cuz just for the

4:29

audience, we all stood in line and then

4:31

we took a photo with the president

4:32

backstage and then we did a photo with

4:34

the four of us. But Jason, when you had

4:36

your moment with the president, what did

4:37

you say? Did you ask him about

4:38

immigration?

4:40

>> Did you ask about I have your photo with

4:42

the president?

4:42

>> Oh, it's on my phone.

4:44

>> Did you Did you bring up solar panels

4:45

with him? Like what was your big moment

4:47

all about?

4:48

>> I didn't know we were taking a picture.

4:49

That was like sprung on me. So I

4:54

was like, "Oh, we're taking a picture."

4:55

So my brother Josh who runs security for

4:57

us was like they need you in the back to

5:00

take a picture with the president and I

5:01

was like yeah I'm good I I got to I got

5:03

to prepare for you know some

5:05

>> Oh you were going to pass.

5:06

>> Well I thought he was joking with me.

5:08

>> So I was like yeah I'm good. I'm good.

5:10

So he's like no no I'm serious.

5:12

>> They're they're taking pictures with the

5:13

president. I was like we are okay. So, I

5:15

ran back and uh they put us in line and

5:19

then I was like, I think I'm getting

5:20

punked here because they kept repeating

5:22

to me, okay, Jason, you're last. You're

5:26

last. And they, you know, and I know you

5:28

guys like to put in a joke or two. So,

5:29

I, you know, I just got in line last.

5:31

And it's obviously, you know, it's it's

5:33

a big deal to take a picture with the

5:34

president. So, I didn't want to um, you

5:37

know, use that time inappropriately or

5:39

anything. So, I just said it's a

5:40

pleasure to meet you.

5:41

>> Just say it already. You like it. Just

5:43

say it. Just let's get it over with.

5:44

Just get it. Get to the end. You like

5:46

him. You tried not to. You know, you're

5:48

all Mr. Big Shot, Mr. Big Talk, and then

5:52

you got in front of him and you like

5:54

him. Just say it.

5:55

>> Uh, what I will say is,

5:58

>> Jesus Christ.

5:59

>> Like him or dislike him.

6:00

>> What a joke. You're such a goon.

6:01

>> I I had a great time. I had a great

6:03

time. Predictable. You're a predictable

6:06

goon. You know,

6:07

>> you don't even know what goon is. Okay,

6:09

stop riz. Stop oraura farming. You don't

6:12

know what gooning is. Okay. I had a

6:14

great time meeting him. It was a great

6:15

event or farming. Obviously, he's trying

6:18

to get his RZ up to impress his kids.

6:20

But, um,

6:21

>> it was great. And I didn't know what to

6:23

do in the picture. So, he did.

6:25

>> We can move on.

6:26

>> I

6:29

What do you think of his speech, Jason?

6:30

>> After he gave you a shout out, Jason

6:32

after the president gave you a shout

6:34

out.

6:34

>> I don't know about love. He said, "Even

6:36

Jason." How many times have you listened

6:38

to that clip over and over? How many

6:40

times?

6:41

>> How many times? How many people have you

6:43

shared that with? How many? Play the

6:44

clip. Play the clip.

6:45

>> I want to also uh

6:47

>> Oh, no.

6:48

>> Say hello and thank to Jamath and his

6:51

wonderful wife Nat. Thank you very much

6:53

for being here. Thank you very much. It

6:55

was great seeing you again.

6:58

Great couple. David Friedberg and uh

7:03

even as we know Jason Gall.

7:08

>> I say even. Thank you, Jason.

7:10

[Applause]

7:12

appreciation. I appreciate that.

7:14

>> Yeah, he's a good person.

7:16

>> I mean, he's a good person.

7:16

>> He called you a good person.

7:17

>> He called you a good person. So, here we

7:19

are.

7:20

>> What president What president's ever

7:21

called you a good person this? Come on.

7:22

>> I mean, it's it's obviously like surreal

7:25

>> for all of us, I think, to be this close

7:28

to the administration and then for Sachs

7:30

to be part of it. What I will say is you

7:32

have to give a lot of credit to this

7:34

administration for the velocity they're

7:37

going, what they're accomplishing. even

7:39

if you disagree with certain items on

7:40

the margins and their ability to engage

7:44

with leaders doing important work. And

7:47

if we compare that to Biden and Kamla,

7:50

like they weren't even letting people

7:52

come to the White House.

7:53

>> Is it Is this like

7:54

>> I love this administration. I love the

7:56

administration. I I like Trump. This is

7:58

a cabinet of CEOs.

8:00

>> Let me just say this. I'm not in love

8:01

with Trump. I'm in like with Trump.

8:04

That's where I'm at. I'm not in love

8:06

with Trump. I'm in like with Trump. But

8:08

what better team has ever been put

8:10

together? It is a cabinet of CEOs. It is

8:12

a cabinet of managers. It is a cabinet

8:14

of people who know how to get done. And

8:15

every time I go there, I'm impressed by

8:17

this cabinet. I pull my hair out when I

8:19

meet.

8:20

>> You admit that you're proTrump finally

8:22

Friedberg. You've been splitting it.

8:23

You've been dancing around the issue.

8:25

Are you full 100% in support of Trump?

8:28

You want to sit here and put me on the

8:29

spot? I put you on the spot.

8:30

>> I support my president. I support the

8:32

president.

8:32

>> Okay. So, you voted for him and you love

8:34

Trump. You voted for him and you love

8:36

Trump.

8:37

I love what he's doing

8:38

>> and you voted for him

8:40

>> and I have issues with the spending and

8:42

that's not been resolved. So like I said

8:43

before,

8:44

>> okay, great. Here we are folks.

8:45

>> My fullthroated endorsement will come

8:47

around when Doge actions are taken

8:49

seriously andor the White House puts

8:51

pressure on Congress to take action on

8:53

spending the budget.

8:54

>> What is everybody's favorite moment?

8:56

Favorite other than Trump, you know,

8:59

being absolutely amazing, great speech.

9:02

He's he's hilarious. Whatever. We'll put

9:04

pus outside that because it's hard to

9:05

compete with the president of the United

9:07

States. Sax, did you have a couple of

9:08

favorite moments? Give us a couple

9:09

favorite moments.

9:10

>> First of all, I think we should talk

9:11

about the substance of the speech

9:14

>> because I think this was the first

9:15

speech that President Trump has given on

9:17

AI since the AI boom began. He's he's

9:20

spoken about it before, but this was a

9:21

full-length policy speech and he

9:24

declared that the United States was in

9:25

an AI race. It's a global competition.

9:29

I think the the language that he used

9:31

was reminiscent of how President John F.

9:33

Kennedy declared that America was in a

9:36

space race. And in a similar way,

9:38

President Trump declared that we have to

9:39

win the AI race. I think you can argue

9:41

that the AI race is more important than

9:42

the space race. It's going to reshape

9:45

the global economy. It's going to

9:46

determine who the superpowers are of the

9:48

21st century. And President Trump was

9:51

really clear that we had to win it and

9:53

that he was going to support a strategy

9:56

for winning it. And then he laid out

9:57

what some of those key pillars are.

10:00

Number one was was innovation. We have

10:02

to get the red tape out of the way and

10:03

let our geniuses cook and clearly was

10:05

very supportive to a lot of the CEOs and

10:08

entrepreneurs in the crowd. Number two

10:11

is infrastructure. He touted the

10:13

hundreds of billions of dollars of

10:14

investments in energy and power

10:17

generation and grid upgrades and data

10:19

centers that he's supporting. And then

10:21

he also supported AI exports. He said

10:24

that we have to make America's tech

10:25

stack the global standard. So I think

10:27

those were really important messages.

10:29

And then on top of that, I think there

10:31

was also some parts of the speech that

10:34

maybe have gotten less attention but are

10:36

also important where he said that it's

10:39

not only important that we win. He said

10:42

it's important how we win. And he sort

10:45

of mentioned three non-negotiables here.

10:47

Number one was that American workers

10:49

have to be at the center of the

10:50

prosperity that we create.

10:53

Number two is that the AI models that

10:57

the government procures and buys must be

11:00

free of ideological bias. So no woke AI.

11:03

And he also signed an executive order to

11:05

prohibit woke AI in the federal

11:07

government. We could talk about that in

11:08

a second. That probably was my favorite

11:10

moment.

11:10

>> That was your favorite moment.

11:11

>> That was my favorite moment.

11:13

>> The red meat moment. I thought that was

11:14

>> that was the red meat. Yeah.

11:15

>> That was the red meat for the base.

11:16

Yeah.

11:16

>> Yeah. The third thing is he he did say

11:18

that we do want to prevent our

11:19

technologies from being misused or

11:21

stolen by malicious actors. And look, we

11:23

we are going to monitor for emerging and

11:25

unforeseen risk. So, you know, we're not

11:27

going to disregard the risk. But he had

11:30

this really good line in the speech

11:31

about how even though AI, look, it's

11:33

it's a daunting technology because it's

11:35

so powerful and like any revolutionary

11:38

technology like that, it can be used for

11:41

bad as well as good. But the the

11:43

daunting nature of it is all the more

11:45

reason why we have to do it in the

11:47

United States. Why would the United

11:48

States has to be the pioneer and the

11:50

leader is cuz we don't want the power of

11:52

that technology being developed in other

11:54

parts of the world at least other parts

11:57

of the world are going to have it but we

11:58

want to be the ones on the cutting edge

11:59

who are defining it and leading it.

12:01

>> Fantastic. Okay.

12:02

>> So I think it was a it was a really

12:03

important speech. I think this idea of

12:05

an AI race that is similar to the space

12:08

race, I think is going to be the

12:10

dominant frame on AI policy for years to

12:14

come.

12:14

>> Well, it's pretty clear, you know, this

12:16

presidency, this term is going to be

12:18

earmarked, I think, by four key

12:21

initiatives. AI, crypto, immigration,

12:25

and tariffs. I think that feels like

12:27

what they're locking into as what's

12:29

important for the next three and a half

12:32

years. I think you would agree with

12:33

that. And it's just great that you're

12:35

spearheading and helping the president

12:37

with two of those four. And just I the

12:39

velocity to me is what's super

12:41

impressive. Any way you could take us

12:43

behind the the scenes of how this stuff

12:45

is getting done so quickly. It feels

12:48

like there's some operational

12:53

cadence here that we didn't see in his

12:55

first term. Certainly didn't see in the

12:56

Biden term, but there's a there's a

12:59

cadence here that's different. Yeah.

13:00

Startup speed. H how is that?

13:02

>> Well, yeah, we call it he's working at

13:04

tech speed. I just think that the

13:05

president's constantly working. I mean,

13:07

he's just so energetic. I mean, he

13:09

basically works like two full work days.

13:11

I think it's well known that he doesn't

13:13

need a lot of sleep and he's continues

13:16

to work late into the night. And I just

13:18

think his energy propels everything

13:20

forward. I also think that there's a

13:23

very cohesive team at the White House

13:27

>> under the chief of staff, Susie Wilds. I

13:29

think it's very important. I think she

13:31

runs a tight ship and then you've got

13:32

the deputy chief of staffs under her and

13:35

I think most of these people have been

13:36

working together for a long time and

13:38

it's a team that works well together and

13:42

I just feels very coherent and cohesive

13:45

to me.

13:46

>> So I think it's a very effective team.

13:48

>> It does feel like that. The pace is

13:50

great. It means you're going to get more

13:52

shots on goal and you'll be able to try

13:53

more things and and get more

13:54

accomplished just like we see in

13:55

startups. Chimamoth, outside of the

13:58

president's talk, we'll go around the

13:59

horn here. Top two or three moments from

14:01

the discussions, just lightning round

14:03

here, rapid fire. What do you got? Top

14:05

two or three moments for you, Chamath,

14:07

just in the discussions that were

14:08

enlightening to you, inspiring to you,

14:10

notable to you.

14:11

>> I came out of it very motivated. I think

14:14

that the combination of the speech, the

14:16

executive orders, and the clarity of the

14:19

big beautiful bill

14:22

now give those of us that are in these

14:24

markets a ton of runway to go and

14:27

execute. And so those things reinforced

14:32

by the various members of the cabinet I

14:34

think were very important. That was one.

14:37

And then the second thing were the

14:43

market commentary from both Lisa Sue and

14:45

Jensen I thought was really valuable.

14:48

>> And then the third was Chris Wright and

14:53

Doug Bergam talking about energy. And I

14:56

tweeted this yesterday, but we are sort

14:59

of back to basics almost in a sense

15:01

where in the absence of power, I think

15:04

AI is is not going to be the thing that

15:06

we think it can be. So that's going to

15:08

create an enormous amount of appetite by

15:10

the federal government to do deals and

15:12

get players on the field. That's to me

15:15

very exciting. So

15:17

>> yeah, I came away really

15:20

riskon, I guess, is best way to say it.

15:22

>> I love it. Freebridge, you have two or

15:24

three moments outside of the president's

15:26

speech. Obviously, that's the pinnacle

15:28

there. So, let's just go below the

15:30

pinnacle. What were the other two or

15:31

three moments for you that were salient,

15:33

inspiring, notable?

15:35

>> I thought Jensen did a great job. I

15:37

don't know what you guys thought, but he

15:39

is very compelling and has a incredible

15:42

uh vision and view on where AI is taking

15:45

us, where it's headed, and what the

15:46

challenges are. So, I really appreciated

15:49

him taking the time to come and join us.

15:51

last minute he rearranged his schedule

15:52

to come out for it and it was great. By

15:55

the way, on the point on energy, which I

15:57

still think is the biggest unsolved

16:00

issue right now in America besides the

16:02

uh the federal deficit and the debt

16:04

problem,

16:06

Chris Wright agreed to rearrange his

16:08

schedule to come and join us at the

16:09

all-in summit in September. Oh, great.

16:11

To continue the conversation. We didn't

16:12

get enough time to talk about it. So, we

16:14

are going to hear more from Chris

16:15

particularly with a particular focus,

16:17

which is what I wanted to spend time on.

16:18

didn't get a chance last week on nuclear

16:20

and where are we cuz he actually is very

16:22

passionate like he said at the thing

16:23

it's where he's spending most of his

16:25

time right now and I think it's very

16:26

good to hear the deep dive on where we

16:29

are in the cycle on trying to accelerate

16:32

nuclear energy deployment in the United

16:34

States same question to you after pus

16:37

you got two or three moments that stood

16:39

out

16:39

>> let's just talk about the executive

16:40

orders for a second because I think it's

16:42

pretty cool that the president of the

16:44

United States signed three executive

16:45

orders at the all-in summit that we just

16:47

hosted I And that was pretty amazing.

16:49

One of them was to promote AI exports

16:53

because we want the American tech stack

16:55

to become the global standard. The

16:56

second was around AI infrastructure to

16:58

make permitting easier so that we can

17:01

help solve those energy problems you're

17:03

talking about Freeberg. And then the

17:05

third one was on preventing woke AI in

17:07

the federal government. And that to me

17:09

is probably my personal favorite because

17:12

we spent a couple years on the show

17:14

talking about how when we're talking

17:16

about woke, you're really talking about

17:17

censorship, right? We were talking about

17:19

censoring people's views based on

17:22

ideological bias, ideological dogmas. We

17:24

saw what was happening

17:26

>> in social media before Elon bought X

17:28

that helped

17:30

>> bring things back. But we were on a

17:33

track, I think, before President Trump's

17:34

election to repeat that whole social

17:37

media censorship apparatus in the form

17:39

of AI bias or AI censorship. And we saw

17:43

this with the whole black George

17:45

Washington and where some AI models were

17:48

saying it was worse to misgender someone

17:50

than to have a global thermonuclear war.

17:53

>> Yeah. And this wasn't an accident

17:55

because if you go back to the Biden

17:56

executive order on AI, there was

17:58

something like 20 pages of language on

18:00

there encouraging DEI values to be

18:03

infused into AI models.

18:06

>> So again, we were on track to repeat all

18:09

the social media censorship, all the

18:11

trust and safety stuff in this new world

18:14

of AI, but it would have been even more

18:15

insidious because at least when someone

18:18

gets censored, you kind of find out

18:19

about it.

18:20

>> It's explicit. It's not.

18:21

>> It's explicit. But with AI, it would

18:23

have been worse because you wouldn't

18:25

have even known. It would just be there

18:27

rewriting history in real time to serve

18:29

a current political agenda. It would

18:31

have been brainwashing our kids.

18:32

>> Oh, and people trust these AIs more than

18:34

they should. I mean, these things are

18:36

making a prediction of the next word

18:38

coming. This is not like God-given truth

18:41

here. And so, Freeberg, you wanted to

18:44

interject about this one because this is

18:46

actually I'll be honest, Saxs, I'm

18:47

surprised you're saying this was the

18:48

most important one to you. I like that

18:50

you clarified it because it was the one

18:51

that was mocked or kind of like people

18:54

were like what why is this important? I

18:56

think you made a good case for why it's

18:57

important. Freeberg your response. Yeah,

18:59

but sex this is not about broadly making

19:03

quote AI non ideological. Private

19:06

companies should still have the right

19:08

through freedom of speech or freedom of

19:10

expression or freedom to operate to make

19:13

AI that does whatever they want it to

19:14

do. What the EO was was that the federal

19:16

government would not procure

19:17

ideologically biased AI. Is that

19:19

correct?

19:19

>> Yes. Exactly. No, we're we're aware

19:21

>> just to make sure that the the federal

19:23

government is not trying to instruct

19:24

private companies how to operate. It's

19:26

simply saying if you want to sell to us,

19:28

this these are the rules of the road.

19:30

>> Yes, that's true. So, we were very

19:32

careful about the First Amendment

19:34

issues. And you're right that if a

19:36

private company wants to put out a

19:37

biased AI product, we're not going to

19:40

tell people they can't use it.

19:41

>> And it could work. It could be

19:42

successful. People might like it. Ya.

19:44

>> Yeah. We're just saying that the federal

19:46

government is not going to spend

19:47

taxpayer money

19:49

>> buying AI models that have compromised

19:52

their accuracy and quality because

19:54

they're beholden to some, you know,

19:56

ideological agenda,

19:58

>> which is similar to the approach with

20:00

the universities, right? Hey, listen,

20:01

you could have a biased university.

20:03

We're just not going to fund it. We're

20:04

not participating. I think it's it's

20:06

quite reasonable in that way. And

20:08

>> yeah, and I would just say that, you

20:09

know, we were a lot more careful about

20:11

this than the Biden administration was

20:12

when they required that DEI be inserted

20:15

into all these models. They didn't

20:16

distinguish between public and private

20:19

money or government procurement versus

20:21

private models. So they just they were

20:23

trying to suffuse DEI into everything.

20:25

And what we're looking for here is just

20:28

neutrality, right? We're looking for a

20:30

lack of ideological bias. The first step

20:32

was to get rid of that Biden EO, which

20:34

the president did his first week in

20:35

office. This goes a little bit further

20:37

and it's a little bit of a shot across

20:38

the bow of these Silicon Valley

20:41

companies saying, "Look, you need to

20:42

play it straight. You need to be

20:44

ideologically unbiased."

20:45

>> As the default,

20:46

>> as the default, when you sell to the

20:48

government, you can't insert your values

20:50

at the expense of accuracy. Look, at the

20:52

end of the day, accuracy and truth

20:54

seeeking is the standard, right? You can

20:57

measure. That's the goal.

20:59

>> So, we don't want the quality, accuracy,

21:02

and truth seeeking to be sacrificed

21:04

because of these any are you still are

21:07

you still seeing that are like when you

21:08

say these Silicon Valley companies I

21:10

mean is this still kind of a widespread

21:13

concern or widespread deployment from

21:16

your point of view where you're sitting

21:17

like are you still seeing a lot of the

21:18

models being trained on ideological

21:20

systems that you know are preferential

21:23

to one group and not to another

21:24

>> I think it was a much bigger concern 6

21:26

months ago and I think there's been such

21:27

a huge vibe shift since President

21:29

Trump's election and taking office that

21:31

like the woke stuff is sort of going

21:33

away on its own but

21:34

>> I and I I think that's the trajectory

21:36

we're headed. But it was

21:37

>> But you still think it's important

21:38

enough to make sure that there's any

21:39

error?

21:40

>> Yeah. It's like, look, this is make sure

21:41

this thing doesn't come back from the

21:43

dead. I think that there's been a huge

21:44

vibe shift since President Trump's

21:46

election and woke has definitely fallen

21:49

out of favor and it seems to be going

21:51

away on its own. But we could still get,

21:54

you know, Orwellian outcomes with AI.

21:57

And I do think it's very important to

21:58

just keep underscoring that what AI

22:01

models should be focused on is the truth

22:04

is on accuracy. And we don't want

22:06

ideological agendas to sacrifice that.

22:09

And um and I think I think that even

22:11

though this is a less salient issue now

22:14

than 6 months ago, precisely because of

22:16

the vibe shift, I still think it's

22:17

important to underscore this point that

22:19

we don't want

22:20

>> would you go so far

22:21

>> we don't want AI taking an Orwellian

22:23

direction.

22:24

>> Yeah. Would you go so far as to limit

22:26

free speech and and make it

22:29

non ideologically biased? Like would you

22:31

make that law if you could

22:33

>> because again the the decision about the

22:35

federal government procuring versus what

22:37

these private companies can choose to

22:39

reflect as their quote values in their

22:41

systems.

22:42

>> No, he just you already answered that he

22:43

would not.

22:44

>> Yeah. No, look, I we understand the

22:45

difference between public procurement

22:47

and private speech and again in a way

22:49

that the Biden administration did not

22:51

because they were saying that all AI

22:52

models

22:53

>> Yes. had to be adhere to a specific

22:55

ideology

22:56

>> to the CI stuff. So

22:57

>> yes, it was an ideology they wanted

22:59

embedded in it. You're saying don't put

23:00

an ideology in. But just to be clear

23:02

here, I want to make one point. This is

23:04

the defaults. Anybody who wants to could

23:07

when they start their prompt or they set

23:08

up their preferred language model could

23:10

say, "I'm an atheist. Here's what I

23:12

believe. Please speak to me with this in

23:14

mind." Or, "I'm a Catholic. Uh, you

23:17

know, I'm a Protestant." Whatever you

23:18

want. Here's my belief system. Please

23:22

never reference, you know, these three

23:24

subject matters in this way. So this is

23:26

the default. I think it's a great thing

23:28

to

23:29

>> I think that's a great example, JCAL. I

23:30

do think we'll end up seeing religious

23:32

AI. I think we'll see AI that's tuned to

23:34

people's religious

23:36

ideological, but I think yeah,

23:37

>> I have one of the startups we did was

23:39

doing a learning app and they were

23:41

struggling and they just made a prayer

23:42

app and their prayer app went parabolic

23:46

and now they're just like printing

23:47

money. So there is definitely a a huge

23:50

market here.

23:51

>> Check out what what were your

23:52

highlights?

23:53

>> It was great to be, you know, included

23:56

in everything. So I appreciate that we

23:57

had uh No, I'm being dead serious.

23:59

>> Your invitation finally didn't get lost

24:01

in the mail.

24:02

>> No, but here's the thing. It I think

24:04

this could have been a nonall-in thing.

24:05

It could have just been, you know, you

24:08

could have done it and just invited who

24:09

you wanted to. So I like that it was

24:10

under the all-in umbrella and that we

24:12

didn't censor anything and we went right

24:13

at hard topics. I'm a moderate. I know

24:15

people want to make me into like a

24:17

stupid lib, but I am an independent

24:18

moderate. And there were moments in time

24:20

when we had great debate, too. This

24:22

wasn't just a love letter to the

24:24

administration. One of the great moments

24:26

was J. D. Vance. It was just great that

24:28

he wanted to come chop it up and just

24:30

hang with the besties. And he came out

24:33

and he went right at me. He was like,

24:34

"Hey, you treated me like a beep at the

24:37

thing. We had a big debate and you know,

24:39

he went right at me." And then I was

24:41

like, "Okay, it's on. Want to talk about

24:43

stuff?" And he said, "Yeah, let's get

24:44

into it." And that's what I love about

24:46

JD. JD to me seems like the politician

24:49

of the future. I know this is like the

24:51

Trump's administration, but

24:52

>> So, you like him?

24:53

>> No. No. I I'm in like with Trump. I'm in

24:56

love with JD because he's young. He's

24:58

opinionated and he likes to mix it up.

25:00

He's on Twitter all day long. He engages

25:03

people on Twitter. He engages people in

25:05

other groups. I'll leave it at that. And

25:07

uh we had a really, I think, honest

25:10

discussion about immigration. And we got

25:12

back to the highskilled immigration

25:14

question. That's the third rail for MAGA

25:16

and and for the country right now.

25:18

Immigration recruiting.

25:19

>> You mean you brought it up right off the

25:20

bat?

25:21

>> No. No. He said he wanted your hobby.

25:24

You brought it up. Your hobby horse very

25:27

I want to continue the debate and I

25:28

said, "Okay, let's continue the debate."

25:30

So, here we go. He was super spicy and

25:32

he made a great super spicy point that I

25:34

want to point out here on Amplify. if

25:36

companies are going to be laying people

25:38

off. And there was an incredible uh

25:40

chart that came out. It was in the

25:41

Financial Times and they showed male

25:43

college graduates versus

25:47

non-olgraduate males. And there was

25:49

usually a huge gap in unemployment

25:50

between those two. In other words, if

25:52

you had the college degree, you you had

25:54

a much better chance than the non-ol

25:56

male. And now those two things have

25:59

flipped or they're like neck and neck.

26:01

If you have a college degree, you have

26:02

no advantage as a man coming out in

26:05

this, you know, 20 to 27 year old range.

26:07

This is men. Women are actually doing

26:09

better. More women in college than men,

26:12

yada yada. But he's very attuned to

26:15

this. And he said he's got big concerns

26:17

right now. So this is again why I love

26:19

JD because JD is very tuned into the

26:22

fact that people are asking for more

26:24

H-1B visas and that typically is to save

26:27

money and supposed to be very skilled

26:28

people. But why is Microsoft laying off

26:30

9,000 people then asking for more, you

26:32

know, H-1B visas? This is a really

26:34

honest, truth-seeking question. And I

26:37

it's hard for this administration to

26:39

talk about this issue because I know you

26:40

got Steve Miller, Bannon, whatever

26:42

people all the way on one side who want

26:44

to deport 20, 30 million people, Tucker,

26:46

and you know, and then you have other

26:48

people who are more moderate. And I

26:49

thought that was like a really great

26:50

moment in time for America and for us as

26:53

a podcast to challenge and have a really

26:55

important discussion. And he made some

26:56

great points there. Number two, we had a

26:58

great debate, I think, about energy. Uh,

27:02

disagree.

27:03

>> You disagree. Okay.

27:05

>> I disagree with the because I think you

27:06

challenged him with I I think you

27:08

challenged him with things that were not

27:09

facts and not true. And I'm happy to

27:11

debate that with you offline. I think he

27:13

was caught off guard, but I think it was

27:14

pretty like

27:16

>> rough and inappropriate.

27:17

>> 100 If you think it's inappropriate,

27:18

that's fine. I

27:19

>> Jake's favorite moments were all the

27:21

ones where he got the ones where we had

27:22

debates.

27:23

>> That's what you're describing.

27:24

>> No, no. Where there were debates. got

27:27

with the vice president. You got into it

27:29

with the secretary of energy. Those your

27:31

favorite moments when you got to

27:33

>> Okay, great. So, okay, fine. I like when

27:35

there's a little conflict, a little

27:37

debate about an important issue. And

27:38

when I walk the audience, which was, you

27:41

know, 90%

27:43

Republican, GOP, MAGA, etc. People said

27:46

that was a great moment. I really like

27:48

that debate because he kept saying like

27:50

nonreliable energy and whatever. And I

27:51

said, are you talking about solar? And I

27:53

think there was a little misinformation.

27:54

>> Reliable. No, it's not.

27:56

>> You put it with a battery. Right now,

27:58

Texas is 30% some days wind and energy.

28:01

You know, like I can tell you I live in

28:02

the great state of Texas.

28:03

>> Texas is Texas roughly 5% solar. Just so

28:06

you know.

28:06

>> What's that?

28:08

>> Texas is roughly 5% solar,

28:10

>> right? And wind puts it up to 25 to 30%

28:12

on the top days is coming from that. My

28:14

point about that is and it's cheaper to

28:16

put in a solar uh and battery farm than

28:18

a new coal plant. It is 100%. We can

28:21

pull up the stats.

28:22

>> It is twice the cost to do solar than it

28:24

is to do nat gas. It takes 4,000 acres

28:26

whereas gas takes 20 acres.

28:28

>> I said coal.

28:30

>> Yeah, but these the big advocacy with

28:32

these guys is to use nat gas to use

28:34

methane. He was saying coal clean coal

28:36

clean coal. He said it 50 times.

28:38

>> These methane plants are half the cost

28:39

of solar. They can get stood up in less

28:41

than two years to generate a gigawatt.

28:44

And instead of being 4,000 acres of

28:46

solar, you can get it done for, you

28:48

know, call it 20 acres. Now talk a

28:50

little bit about pollution. And that's a

28:52

big part of why they're doing this.

28:53

Well, a big part of methane is that it's

28:55

actually cleaner than coal, which is why

28:57

they're using it. Cleaner than oilar.

28:59

>> Cleaner than oil and the two ways of

29:02

getting energy. Now, science guy, now do

29:07

>> I'm trying to give you the fact about

29:08

why about why it is cheaper and faster,

29:10

which is what he was making an advocacy

29:12

for, right? It's not about like solar.

29:14

Yes, you're right. It has a lower carbon

29:15

footprint when you're running it. But at

29:17

the end of the day, what these guys are

29:19

focused on and a big challenge for

29:20

America is how do we scale energy

29:22

production in the states and scaling

29:24

energy production, I personally think we

29:26

need to fix the regulatory roadblocks in

29:28

nuclear. And Chris Wright's been very

29:29

vocal on this.

29:29

>> We all agree on that.

29:31

>> But the fact is this NA gas supply that

29:33

we have in the United States and the

29:36

fact that we can deploy nat gas energy

29:38

production very quickly is what makes it

29:40

such a reliable source right now. if the

29:41

US wants to have a chance at scaling

29:43

from 1 terowatt to two faster than

29:46

projected today and that's the reason

29:48

you know it's not it's not about like

29:49

solar is being bad solar is bad like

29:51

that's not the the argument it's just

29:52

like dude we we got to get moving fast

29:54

and we got to have reliable energy

29:57

in our debates I just want to point in

29:59

our debates when there's bad faith

30:00

moments I think it's a bad faith moment

30:02

for when I say coal versus solar and

30:04

then you say no you're wrong it's solar

30:07

versus n gas and that's what he was

30:09

doing this is what politicians do here

30:11

all in. We like to do, you know, uh,

30:14

fact-based, truth first stuff, not

30:16

biased stuff. And so solar, you're

30:18

comparing. So, you know, solar and how

30:22

fast it is versus how fast it is to go

30:23

to net gas. Of course, it's faster to go

30:25

to net gas if we have those available.

30:27

Let's put that aside. It's an important

30:28

debate. The fact that you and I are

30:29

debating it is important. And I also

30:32

thought Lisa from AMD was fantastic. I

30:34

haven't heard from her. By the way, I

30:36

just want to point out that when I got

30:38

back to the conference, so I I left for

30:40

a time to go back to the White House and

30:42

then I came back.

30:43

>> The first thing everyone said to me

30:45

>> when I got back was,

30:47

>> "Did you see Jal being a jerk to Chris

30:50

Wright?" They were everyone was like,

30:52

"Oh, about the Yeah, a jerk.

30:54

>> He's a civil servant. He has to answer

30:57

hard questions. You didn't talk to him

30:58

in a in a in a in the way that you

31:00

would." Basically, everyone thought you

31:01

were a jerk to Chris, right? And you

31:03

were kind of a jerk to JD. And what are

31:05

your favorite moments?

31:06

>> Call me an

31:07

>> What are your favorite moments from the

31:09

conference? You're reminiscing about

31:10

>> that. You were an to me.

31:15

>> Anyway, the point is one thing you're

31:17

going to get here at the Allin.

31:20

This is where everyone%

31:22

two out of three were

31:23

>> everyone was saying this. You almost

31:24

derailed the whole thing.

31:26

>> Nobody derailed. You're a civil servant,

31:29

Mr. Sachs. You're a civil servant.

31:31

You're all civil servants.

31:32

>> I've been putting up with you for 5

31:33

years on this podcast.

31:34

>> The hard questions.

31:35

>> It was perfect training for government

31:37

services beyond the podcast being

31:39

interrupted by you for 5 years.

31:41

>> Yes.

31:42

>> That's why I'm so ready to dwell.

31:44

>> You learn about you work for us, all of

31:46

you. And you're all going to take hard

31:48

questions. And you're all going to take

31:49

hard questions on September 7th, 8th,

31:51

and 9th when we have the allin summit in

31:55

>> Los Angeles. By the way, by the way, one

31:57

thing I'll say is Chris Wright's chief

31:59

of staff came out to me afterwards and I

32:01

said, "Oh, I'm sorry. I heard Jake was a

32:02

jerk to to Secretary Wright and he's

32:05

like, "Oh, no. Chris loved it. He loves

32:07

mixing it up." Okay, of course.

32:08

>> And he's coming to he's coming to Olan

32:11

Summit in on September 8th. So,

32:12

>> can't wait to debate him more. Can't

32:14

wait to mix it up more.

32:15

>> So, he he likes mixing it up. So, kudos

32:17

to him.

32:18

>> Okay.

32:18

>> And so did so did JD Vance, the vice

32:22

president to you. Stop calling him JD,

32:24

by the way. Well, I mean, listen, I just

32:26

want to say Vice President J. D. Vance

32:29

and I have been directly communicating.

32:31

We had a We Yes.

32:33

>> No, you haven't.

32:34

>> David Sachs, your worst nightmare.

32:36

>> Oh my god. Your worst nightmare.

32:38

>> The nation is ruined. What the

32:40

>> We let Jake Allen to Washington and now

32:42

look what's happening.

32:43

>> Yeah.

32:44

>> And listen, I want to level set with

32:46

everybody.

32:47

>> We I am going to ask whatever

32:50

question I want to whatever guest we

32:51

have and nobody's stopping me. The only

32:54

way you're going to stop me is by

32:55

writing me a huge check to buy

32:57

me out of this podcast and replacing me

32:59

with some mid until

33:00

>> or if the Secret Service keeps you off

33:02

stage, which might be an option.

33:03

>> Or Secret Service keeps up stage. But

33:04

the truth is, this is one of the great

33:06

things about this administration sex is

33:08

that they love to mix it up. They like

33:10

great debate. You know who didn't like

33:13

great debate and ran from it? Kalama

33:15

Ding-Dong. She wouldn't even come on

33:17

this podcast. You know who doesn't like

33:19

debate? Tik Tok.

33:20

>> We get that at Bernie's Biden who didn't

33:23

even know what a podcast is.

33:25

>> Tim Waltz who doesn't own

33:27

>> you. You definitely you definitely have

33:29

your moments, bro. You definitely have.

33:30

>> But Tim Waltz doesn't own an equity. He

33:33

literally doesn't own one share of any

33:34

company, doesn't his home

33:36

>> and Tim Waltz is on there giving a hard

33:38

time about the uh Trump savings

33:40

accounts.

33:42

>> I mean, I don't even know if that's a

33:44

hat though, which you loved. You thought

33:46

that was going to win the election. I

33:47

thought he might be able to speak to

33:49

like the middle of America and then I

33:51

find out like

33:52

>> when they do the the Deep Oppo research

33:54

that the guy doesn't own one stock.

33:57

>> The guy doesn't own his home. He's

33:59

financially illiterate and we're making

34:01

him

34:01

>> employed by the government. He's been

34:03

employed by the government his whole

34:04

life.

34:05

>> I mean, have you

34:07

There it is.

34:08

>> That's what Jake thought would win the

34:10

election.

34:11

>> You're never going to live that down. I

34:12

remember when you tweeted you thought

34:13

that was it. You thought that was the

34:15

master stroke. I thought it might

34:17

>> master stroke that was going to win them

34:19

the election.

34:19

>> Hey, listen. No straanis does not bat a

34:21

thousand. No, no, even no straanis

34:25

cannot bat a thousand. But it did come

34:26

out, by the way, that Nancy Pelosi

34:29

wanted to do the speedrun primary. I

34:30

don't know if you saw that, just not to

34:31

rehash too much stuff. Sax, I want to um

34:34

say there was one point of difference if

34:35

you want to get into it around the the

34:37

the content part of part of it where and

34:40

this is something that

34:42

>> the press was having a field day with

34:44

and they really keyed on which was hey

34:47

respecting IP, respecting copyright.

34:50

What's the feedback been so far on that

34:52

which was a pretty spicy part of

34:54

President Trump's speech?

34:57

>> Well, I think what the president said

34:59

was just very pragmatic. He said we had

35:01

to have a common sense approach towards

35:03

intellectual property. And he said if

35:05

you have to make a deal with every

35:07

single article on the internet, every

35:10

single website, every single book, every

35:12

piece of IP in order to train an AI

35:15

model, it wasn't feasible. He said,

35:17

"Look, I appreciate the work that went

35:20

into people creating these works, but

35:22

you're not going to be able to negotiate

35:24

a deal for every single one of them. And

35:26

if we require our AI models to do that

35:29

and China doesn't and they won't.

35:31

They're just training on everything

35:32

whether it's you know pirated or not

35:34

then we're going to lose AI race. So I

35:36

think he took the side of a fair use

35:38

definition. I don't know if he used the

35:39

term fair use but effectively he was

35:41

taking the side of a reasonable fair

35:44

use.

35:46

>> What did you think of that part Dave

35:47

Freeberg? You have any thoughts for

35:48

Jimoth on that part?

35:49

>> I think he's absolutely right. I've said

35:50

this before. If something's in the

35:52

internet, if something's in the open

35:53

domain, and I strongly disagree with the

35:57

idea that AI getting trained is the same

36:00

as AI replicating copyright material. If

36:03

AI outputs text or outputs audio or

36:07

outputs video that contains copyright

36:10

material, it is 100% in violation of

36:12

copyright.

36:13

>> And he said that, by the way,

36:14

>> yes. And if the AI is learning, it is

36:16

understanding patterns, it is

36:18

understanding reasoning, it is

36:19

understanding concepts by reading

36:21

copyright material just like humans do.

36:24

A writer, an author reads a bunch of

36:26

fiction, learns good techniques, learns

36:29

good concepts, learns good theory from

36:32

reading all those books and then goes

36:33

and writes his or her own book. They are

36:36

not violating copyright material. In the

36:37

same way,

36:39

Freeberg, what if it's all the New York

36:40

Times on the open internet?

36:43

>> 100%. You're you're 100% correct that

36:45

should be paid for or licensed. I'm

36:47

talking about the open internet. I'm

36:49

talking about open material. I'm talking

36:51

about stuff that's in the open domain

36:52

which

36:52

>> common crawl.

36:53

>> There's a thing called common crawl.

36:55

>> If there was if somebody stole a hundred

36:59

books, let's say, and put them on their

37:01

website and it was a pirated Russian

37:03

website with a thousand books on it and

37:04

you accidentally crawled it, you would

37:06

be obligated to take that out then. I

37:08

think we all agree.

37:09

>> Correct.

37:09

>> Okay. Correct.

37:10

>> Cuz that's what a lot of the lawsuits

37:11

around. So, I think we're reaching

37:12

something. I just want to say, you know,

37:13

this is such an important point,

37:15

especially to me as a content creator

37:16

and somebody who spent his career in

37:17

this. I've been thinking about the

37:19

endgame and um I was I'm here in Park

37:22

City. I was just giving a a keynote and

37:24

I wanted to show you something I made

37:27

saxs because I think we have to get to

37:28

the the endgame here. So, in my talk, I

37:33

talked a little bit about how can we get

37:35

through this fight and then maybe

37:37

getting to a solution. So, I had my team

37:39

mock up

37:41

the New York Times website here and chat

37:44

GPT doing a deal with them. So, here you

37:46

see you're on the New York Times website

37:48

and you ask it a question powered by

37:49

GPT. You ask it, hey, you might ask this

37:53

question. In fact, you log in with your

37:54

chat GPT credentials. You're and it

37:56

could be Gro, it could be Gemini. Give

37:58

me the earliest mentions of Putin, you

37:59

know, if you were a fan of Putin or

38:01

something. And it would then go through

38:02

that and give you your your Putin

38:04

references. And then I made another one.

38:06

And then obviously this would be an

38:07

exclusive to Chat GPT. It would be one

38:09

of those things where you know they get

38:11

an exclusive. And then here on the uh

38:13

Disney Plus channel, imagine you could

38:15

make yourself into a Jedi Knight and you

38:17

could then upload your photo. You know,

38:19

kids might really get into this. You

38:21

upload your photo, you can make You

38:22

talked about this free a couple of times

38:24

of the future of narrative storytelling.

38:25

You up your photo and then it makes you

38:27

into a Jedi Knight. There's there's

38:29

Darth Calacanis. So

38:32

>> that looks to me like you're infringing

38:33

on their trademark. What's that?

38:36

>> Are you infringing on their their

38:37

copyright?

38:38

>> This is fair use. This is fair use. This

38:40

is a perfect example of fair use for

38:41

editorial.

38:42

>> You're also infringing on some Osmpic.

38:43

That's absolutely infringing.

38:46

>> Trust me, I am definitely infringing on

38:48

some OMIC here, guys. I'm I'm past

38:50

those. I'm on to peptides now, man. I'm

38:52

on the Wolverine protocol. So, look at

38:54

>> Are you

38:54

>> Yeah, I started doing the I mean I I

38:57

don't What could go wrong?

38:59

>> Don't take a podcaster's advice. Please

39:03

don't take a podcaster's advice on your

39:06

healthcare rule number one. Take

39:08

Chimat's advice because he's got 6% body

39:10

fat, which I think attributes to much of

39:13

your pomp and circumstance around your

39:15

privates. I think it has to do with the

39:17

lack of fat. But I'm going to leave it

39:18

at that.

39:19

>> First of all, it's 11 and a half, but

39:21

you know, it that's that's like right

39:23

that's like right before I go on summer

39:25

vacation. Then it then it ends up at 12

39:27

or 13.

39:27

>> Did you go get that? Did you go get that

39:29

gelato? What was that place we went that

39:30

we love? Lulu me. I've gone there every

39:33

day. Every day so far.

39:34

>> Did you do two or one? Be honest. Two or

39:36

one?

39:36

>> Bro, I've had I've had I've been doing

39:38

>> No, no. Per session. Do you do two or

39:40

one? Be honest.

39:41

>> Per session, too. I start with the

39:42

medium and then and I finish with a

39:43

small.

39:44

>> Yeah, exactly. You This stuff is so

39:46

good.

39:47

>> I've never tasted any gelato like this.

39:49

It's incredible.

39:49

>> I mean, it's unbelievable. We have to

39:50

license it for the United States and the

39:52

all-in brand. We have to license it from

39:53

them.

39:54

>> It's really incredible. But Chamath just

39:55

generally speaking or anybody who wants

39:56

to have at it. Friedberg Sachs, what do

39:59

we think about the endgame here? Because

40:01

there's some major lawsuits here.

40:02

They're going to get settled in the next

40:04

year or two. What What do we think about

40:06

sort of the future I've shown here

40:08

today?

40:09

>> I think what Sax just highlighted is

40:11

exactly right.

40:12

>> Look, we got to have a common sense

40:13

approach here or we're going to lose the

40:15

AI race. I mean, one of the out one of

40:18

the key determinants

40:20

>> of AI quality is the amount of data that

40:22

you have. It's very simple, right? It's

40:24

there's a few building blocks. There's

40:25

energy, there's chips, and there's data,

40:28

and there's algorithms. And if you lose

40:30

on any one of those dimensions, then

40:32

you're in trouble, right?

40:33

>> So, look, you just can't have a

40:35

situation where China can train on the

40:37

entire internet. And RAI models are

40:40

hamstrung by needing to contract,

40:43

>> negotiate contracts with every single

40:45

website.

40:45

>> But right now, Europe, Elon owns X,

40:47

right? He owns Twitter for now X. Does

40:50

Sam Alman have the right to use X in his

40:53

corpus?

40:54

>> It's public.

40:56

>> No, it's not. No, it is not public

40:58

endpoint.

40:58

>> It's not a public.

40:59

>> I just honestly I don't

41:01

>> there's I don't know the answer to that.

41:02

There's some edge cases here. We're

41:03

going to have to come up with

41:04

>> It's not about whether it's behind a

41:06

payw wall or not. It's whether these

41:07

APIs exist and whether you're you're

41:09

actually contractually allowed to use

41:11

them or not.

41:12

>> The terms of service. Correct.

41:13

>> The terms of service. It's published on

41:15

every website what the terms of service

41:16

are with respect to the content. I think

41:17

it would be okay to let people opt out,

41:21

you know. So, we already have this with

41:22

Common Crawl. You can put in the footer

41:24

of the website, you put in robots.txt

41:27

and you opt out of Common Crawl.

41:29

>> Common Crawl is like this nonprofit

41:31

organization that basically archives the

41:33

entire web every few months.

41:35

>> Funded by Gil Elbaz,

41:37

>> former Yeah.

41:39

>> formerly of Google. Great fan of the

41:40

pod. Shows up to our summits. Great guy.

41:43

>> And all of Open AI was built off of

41:45

Common Crawl originally.

41:47

And he but they're very clear by the

41:48

way. They say you have to clear

41:50

copyrights. You don't get to just use

41:51

open Chrome.

41:52

>> Can I go out on a limb? I don't know if

41:54

you guys saw this Amazon deal with the

41:57

New York Times for $25 million. Did you

41:59

see that today?

42:00

>> No,

42:00

>> I didn't see today. Explain it, please.

42:02

>> I think that the New York Times licensed

42:05

Amazon all of their content, including

42:07

The Athletic and a bunch of other things

42:09

for training. 20 million. Sorry, 20

42:12

million a year.

42:13

>> Okay, here we I read that and I thought

42:16

this is the peak of these deals. These

42:18

deals will only go down in terms of

42:22

dollar value from here.

42:24

And it it actually brought me to this

42:27

point where I was thinking to myself, is

42:29

it even realistic

42:32

to believe that patents and copyrights

42:36

actually exist in 5 years? And I went

42:39

through this exercise of like if a

42:41

computer studies the

42:45

periodic table and also understands the

42:48

laws of physics, the laws of biology,

42:49

the laws of chemistry and then

42:50

independently deres

42:53

some material that is otherwise

42:54

patented,

42:56

what will happen?

42:59

And then separately, if two competing

43:01

AIs invent a new material from scratch,

43:05

how will the international courts deal

43:08

with this? And if you take all of these

43:10

examples to the limit, at the limit, the

43:13

idea that there are copyrights,

43:16

enforcable copyrights,

43:18

I think is a very fragile assumption. So

43:22

I'm actually thinking more that we have

43:24

to spend some time understanding the

43:27

landscape of a world that doesn't have

43:30

copyrights and patent protections and

43:32

instead what is the surface area in

43:35

which you compete what is trade secret

43:37

what does that mean in a world of AI and

43:39

I think it's quite an interesting thing

43:41

to think about

43:43

patents are a totally different piece I

43:45

think that's a fascinating string to

43:46

pull on I will tell you I will take the

43:49

other side of the bet if we want to make

43:50

a poly market on this. I will guarantee

43:52

that this will be the beginning of the

43:54

deals and the deals will go up from

43:55

here. I'll tell you why. The reason the

43:57

New York Times made that deal is to make

44:00

it apparent that what OpenAI has done

44:02

has damaged their business because now

44:04

they have a customer and their customer

44:06

is Jeff Bezos at Amazon and Jasse and

44:09

now they can show damages because and

44:11

now those damages could give them an

44:13

injunction against OpenAI and OpenAI's

44:16

got to take it out of their crawl of

44:18

their you know construct and that's

44:20

going to be really expensive for them.

44:21

It's not not doable, but it's going to

44:24

be expensive. And let's think on a

44:27

societal basis of what we want as a

44:29

society. Do we want a society in which

44:31

journalists, writers, artists,

44:33

musicians, filmmakers, actors cannot

44:35

make a living, podcasters, or do we want

44:37

a world in which they can?

44:38

>> And I think technologists,

44:40

>> hold on, let me hold on. As a

44:43

technologist, as a technologist, we

44:45

typically think if we can crawl it, it's

44:47

ours.

44:47

>> What I can tell you as an artist is if I

44:49

make it, it's mine. and you need my

44:51

permission because it's my art and I

44:53

think it the industry will do better if

44:55

they respect them because now the New

44:57

York Times can hire more fact checkers.

44:59

>> But can I just ask you a question?

45:00

>> Yeah, go ahead. Sure.

45:01

>> But why do you have to connect the two

45:04

as immutable things? meaning why can't

45:06

somebody make something still you know

45:10

let's just say it's a song but that song

45:12

can now be made by multiple AI models

45:16

but if they make the song

45:19

there's a reasonable claim that even if

45:21

they don't have the copyright more

45:23

people will want them to perform the

45:25

song than some random AI

45:27

so can't you make a living without

45:29

having the copyright

45:31

>> which is the choice of the artist some

45:32

artists are were very well known for not

45:35

wanting their art to exist in some

45:36

mediums. As a perfect example, the

45:38

Rolling Stones for a long time thought

45:40

they would be sellouts if they had their

45:41

music used in commercials. And when they

45:43

did Start Me Up with Windows, that was a

45:45

really big concession from them. And

45:47

that's up to the artist to make that

45:48

decision. You make a a valid claim. Hey,

45:50

yeah, you go on tour and make more

45:51

money. But that's the artist decision,

45:52

not the technologists or the people

45:54

stealing their content. And by the way,

45:55

$20 million a year is a hundred $200,000

45:59

highly paid journalists, fact checkers

46:01

at the New York Times. They're going to

46:03

get 10 of those deals. And it's going to

46:06

create a golden era age of journalism

46:09

and content. And we should be happy.

46:11

>> I told you this example, Jason, but at

46:13

at Beast, we did a a licensing deal of

46:16

our content to allow OpenAI to learn

46:19

>> Yeah.

46:20

>> to run training runs on our videos. And

46:23

at the board, the thing that we kept

46:25

talking about was I was I was really

46:27

concerned like, let's just do a a couple

46:28

year deal max.

46:30

>> And the reason is we have no idea what

46:32

this looks like. in

46:34

>> five or 10 years. And there's just as

46:37

much chance to your point that we get it

46:39

wrong as right. Now that was about 6

46:40

months ago. And so the intuition that I

46:42

had back then was maybe we should keep

46:44

the deal term as short as possible. But

46:47

now when I see how important AI is in

46:50

the global landscape and what China is

46:51

doing, I think on the margins that this

46:54

idea that these copyrights will mean

46:56

something

46:58

>> in my mind, I am underwriting the value

47:03

of these things going to zero and I'm

47:04

asking myself instead for my businesses,

47:07

how are we actually building a real

47:09

defensible moat and not a piece of paper

47:12

that we can use to sue somebody?

47:14

>> Okay, Freeberg, you want the last word

47:15

here? We got to move on to some other

47:17

topics. I

47:17

>> I just want to be the last word.

47:19

>> I just want to be clear that nobody is

47:22

losing their copyright.

47:24

>> Copyright is the right not to have your

47:26

work copied. And if an AI model produces

47:29

outputs that copy or plagiarize your

47:32

work, then that's a violation of the

47:34

law.

47:35

>> And I think the president specifically

47:37

said that we're not allowing copying or

47:39

plagiarizing. The question is whether AI

47:42

models are allowed to do math on the

47:45

internet. You know,

47:46

>> pattern recognition pattern recognition.

47:47

>> Basically, that's what it is. And it's

47:49

and Jal, I think you're conflating the

47:51

two. And I I don't want to be

47:52

interrupted. I just want to say this.

47:54

>> I understand the distinction.

47:55

>> And and I think that this idea that like

47:57

I can't, for example, go to the library,

47:59

rent a book, read it, and then learn

48:01

some of the good techniques on how to

48:03

write a good book should be restricted

48:05

to humans in this AI context. Like this

48:07

is exactly what they're doing. They're

48:09

identifying patterns and then they're

48:11

building predictive algorithms that

48:12

allow them to output stuff that starts

48:14

to fit within different kind of, you

48:16

know, variable settings. Do you guys

48:18

think it's possible that if you

48:20

allocated enough compute

48:22

at the problem, you could write Michael

48:26

Kryton's Jurassic Park Denovo without

48:29

ever having read it?

48:31

>> Yeah, me too. Me too. I I think

48:33

>> I don't know what that would mean. Like,

48:35

>> well, this is my point. I know who

48:37

Michael is and I know what Jurassic Park

48:39

is. I don't know what it means

48:40

>> this issue.

48:41

>> I don't know what it means to say can AI

48:42

write that like

48:43

>> but you guys remember the Ed Sheeran

48:45

lawsuit. Do you remember the lawsuit?

48:47

>> I I did. But let me just make one point

48:48

here on this cuz you're saying I don't

48:50

understand it. I spent my career in it.

48:51

I understand it much better than you do

48:53

>> and I understand it from lawsuits and

48:54

being in the weeds on it. Like I

48:56

understand it from first principles

48:57

which you do not. And I will say this is

49:00

what we're talking about here is the

49:02

definition. It's the definition of a

49:04

derivative work. and the output matters.

49:07

So if you were to take my knowledge and

49:09

then create a derivative work from it

49:11

and you used a percentage of my work and

49:13

that's where this will get into the

49:15

nuance is what percentage of the

49:17

original work is used in the derivative

49:19

work and under what context a commercial

49:21

context or a non-commercial this is

49:23

clearly a commercial one if it's a if

49:25

openai was a nonprofit right now we'd be

49:27

having a distinctly different discussion

49:29

because it would there would be you

49:30

wouldn't be competing with me as the

49:32

copyright holder to use this new medium

49:34

and create the derivative works and it

49:36

has to change substantially. So if it's

49:38

a if it's a cliffnotes

49:40

>> when China has the only models that are

49:42

able to meet your stringent definitions

49:44

of copyright.

49:44

>> Well, no. Here's the thing. I think the

49:46

China fear the China fear is

49:48

I'll be totally honest here.

49:49

Just because China steals IP does not

49:52

mean you get to steal from Americans. In

49:55

America, we have rules. And when you go

49:57

to China, and by the way, we spent the

49:58

last 30 years. The major issue with

50:00

China is not Taiwan. It has been

50:03

the technology industry itself. Let me

50:05

finish. The technology industry itself

50:07

has leaned on our government for 30, 40

50:10

years, including Microsoft, including

50:11

Google, to make sure our trade secrets

50:13

are not stolen, our IP is not stolen,

50:15

our movies are not stolen. That is the

50:16

key issue with China. So just because

50:18

China's a thief does not mean American

50:21

companies get to

50:21

>> have you seen Have you seen the latest

50:23

batch of Chinese open source models or

50:26

open models?

50:27

>> They they steal everything. Does that

50:28

mean you should be able to steal

50:29

Windows? Should you be able to steal

50:32

Jason? We don't think it's stealing.

50:35

Elon has said this pretty clearly, but

50:37

Grock 5 and for sure Grock 6 will not

50:40

use Common Crawl. It will not use the

50:42

internet. Okay? It'll just be an

50:44

enormous amount of synthetic data. And

50:46

back to what Freeberg and I just agreed

50:49

upon, if you synthetically go and try to

50:51

generate all this content to learn

50:53

across, you're invariably going to

50:54

produce something that's already been

50:56

created.

50:58

>> That's like some sci-fi level.

51:00

>> I understand. That's what's happening

51:02

now. It's happening now.

51:04

>> If somebody

51:05

>> What do you think happens to Grock 5 or

51:07

Grock 6? Is that violating copyright? It

51:09

didn't even know that it existed

51:11

>> on the output. Yeah, that's fine. If it

51:13

on the output created a similar work,

51:17

they would need to then take it down.

51:19

And so that that would be a really

51:22

interesting new that's a new space we're

51:24

going to have to contend with. So you

51:25

can if it does happen is a new concept

51:29

that we would have to address in a new

51:30

way. I'll give you I'll give you a

51:32

science corner example. There's this

51:33

EVO2 model that they published at the

51:35

Arc Institute which Patrick Collison you

51:37

know is the name Sherman.

51:39

>> So that EVO2 model they just ingested

51:41

all the DNA data they could find in the

51:43

world. Trillions and trillions of base

51:45

pair of data that they ingested

51:47

>> and then they looked at patterns in DNA

51:50

and that's it. They had no context for

51:53

what the DNA represented. They had no

51:54

context for the concept of genes. none

51:56

of the structured understanding of what

51:58

that DNA does, what it is. And you know

52:00

what it did? It fed in the BA gene

52:03

variant and the thing output a warning

52:06

saying I think that this is a pathogenic

52:08

variant to DNA without having any

52:10

context. This is the the breast cancer

52:12

alil and it didn't have any knowledge

52:14

and it did it wasn't trained on that at

52:16

all. It had no knowledge that there are

52:18

pathogenic variants for cancer and it

52:20

identified that this was a genetic

52:21

variant that can cause some sort of

52:23

pathogenic outcome in the organism. So

52:25

that was that's a great example where

52:27

there's a lack of understanding at the

52:29

human level on what really drives some

52:32

of the patterns in nature, the patterns

52:33

in society, the patterns in behavior

52:35

that are kind of emergent phenomena

52:36

perhaps that these AI models are

52:38

starting to identify. And I think to

52:40

Jama's point, we may end up seeing this

52:41

in things like entertainment as well.

52:43

All right, this has been an amazing

52:44

debate. We got to move on. And you know

52:45

what? We're going to have more amazing

52:47

debates September 7th through 9th in Los

52:48

Angeles at the All-In Summit. The lineup

52:51

is stacked. Alibaba's co-founder Josai

52:54

Tomma Bravo co-founder Arc Invest Kathy

52:56

Wood Uber CEO Dra Sequoa's Rolaf Botha

53:00

YouTuber Cleo Abram and many many more

53:02

coming you get the last word here go

53:06

>> I was just highlighting this tweet that

53:08

I saw

53:10

>> where talking about Chinese openweight

53:12

models are basically open source models

53:14

so

53:15

>> basically all the leading American

53:17

models are closed source and all the

53:18

leading Chinese models are open source

53:19

this is kind of the way things played

53:21

out.

53:22

>> It's a pretty good technique for

53:24

catching up because then you got the

53:26

larger open source developer community

53:28

helping you out.

53:29

>> But the point is just that these open

53:31

source models are catching up pretty

53:33

fast. We're ahead in many other aspects.

53:35

Our chips are a lot better. Our data

53:37

centers are better and so on. And I'd

53:38

say our closed source models are better.

53:40

But they have this one area of open

53:41

source models. So again, if you

53:43

hamstring our AI models access to data

53:46

by creating a whole bunch of new

53:48

requirements for contract negotiations,

53:50

like we could really lose the AI race.

53:52

This is a really big deal. It's not a

53:54

madeup concern. I don't know why you

53:55

think it's made up.

53:56

>> I never said that it's made up. I think

53:59

it's an opportunity for America to

54:00

actually have a distinct advantage,

54:01

which is that $20 million from Amazon

54:04

alone is 1% of the New York Times

54:07

revenue. And that's going to go directly

54:08

to the bottom line. It's going to allow

54:09

them to hire more journalists. Then that

54:11

protected site will have be giving in

54:14

real time something. These language

54:15

models are going to have to go hack and

54:17

steal that real-time data is going to be

54:19

a distinct advantage for Gemini, OpenAI,

54:21

Amazon, whoever chooses to do it. And we

54:23

can create

54:24

>> you have this like nostalgic sort of

54:26

quasi romantic notions about like

54:29

journalism and the need to save the New

54:31

York Times.

54:32

>> It's also art. It's I mean you can say

54:34

all the derogatory things you want about

54:36

me personally, Saxs. That argument

54:38

doesn't work. No, no. You just said I

54:39

have this whole nostalgia whatever when

54:41

you

54:41

>> Yeah, you do. You're nostalgic for

54:42

journalism as it used to exist.

54:44

>> When I know I've beat you in the debate

54:45

is when you make it personal like that.

54:47

It's not personal. I'm not being

54:48

nostalgic. I'm trying to create a

54:50

sustainable a sustainable advantage for

54:52

America. And you are our public servant

54:55

and you're learning AI. You will take my

54:57

feedback.

54:59

>> You will take my feedback.

55:00

>> We're going to ignore your feedback.

55:01

Take your feedback. Public service.

55:03

>> Throwing in the trash. No, you take it

55:06

and I will be showing up at the White

55:08

House for my tour.

55:10

>> You have this crazy idea that we're

55:11

going to win the AI race by tying one

55:13

hand behind our back so that you can

55:14

subsidize journalists so you can

55:17

subsidize movies. You'll get more

55:20

content. You said before you want more

55:21

training data, pay for it. Pay for more

55:24

training data. You're the zar. Take it

55:26

back to pus. All right, let's keep

55:28

moving here.

55:29

>> We have to keep moving. We have a great

55:31

This is great debate. Great debate here

55:33

on the All-In podcast. It's not going to

55:35

stop, folks.

55:35

>> It's just you yelling. It's just you

55:37

yelling saying things that don't make

55:38

sense.

55:39

>> Okay, you can say that.

55:40

>> You only have like three topics going

55:43

on. You can you can personally attack.

55:45

>> You know what it is? It's like we got to

55:46

let in more immigrants. Number one.

55:48

Number two, high skilled immigrants.

55:50

>> AI is going to put everyone out of work.

55:52

By the way, no sense of perceived

55:53

contradiction between those two things.

55:55

Number three, we need to like subsize

55:57

here. You know, the audience says the

56:00

same. When the three of you guys attack

56:02

me, Jason,

56:05

when the audience

56:06

gang up on me like this, the three of

56:08

you gang up on this and you personally

56:09

attack me, the audience comes up to me

56:11

and they say, "Wow, you really nailed

56:13

and beat."

56:13

>> Have you done that today?

56:14

>> No, not yet. Not yet. But a little bit

56:16

of the buting.

56:19

>> Yeah, that's true. Let him eat the

56:22

He's emaciated. He's 11% body fat. Let

56:25

him eat. Let him cook. All right.

56:27

Listen, you and I, Saxs, will do more

56:29

debate and it's going to be amazing.

56:30

allin.com/ yada yada yada for tickets.

56:33

Get in there, folks. Uh, we have to get

56:35

to the docket. We're an hour in and we

56:37

still have all the news.

56:38

>> We should talk about this this um AI

56:40

privacy issue that Sam Alman mentioned.

56:41

>> All right, that's a great segue cuz I

56:43

saw that as well, David Saxs, and as our

56:46

civil servant working on AI, this is

56:48

something where you can have an

56:49

additional contribution. There's more

56:51

work we can give you. All right, listen.

56:53

Here it is. AI user privacy is becoming

56:54

an issue because friend of the pod Sam

56:58

Alman says there is no legal

57:00

confidentiality when using his product

57:03

chat GPT. Here's a 30 secondond clip

57:06

again. Friend of the pod fop Sam Alman

57:10

on the vaugh people talk about the most

57:13

personal in their lives to chatt

57:15

young people especially like use it as a

57:16

therapist a life coach uh having these

57:18

relationship problems. What should I do?

57:20

And right now, if you talk to a

57:23

therapist or a lawyer or a doctor about

57:25

those problems, there's like legal

57:27

privilege for it. We haven't figured

57:28

that out yet for when you talk to

57:29

ChachiBT. So, if you go talk to CHP

57:31

about your most sensitive stuff and then

57:33

there's like a lawsuit or whatever, like

57:35

we could be required to produce that.

57:36

And I think that's very screwed up. I

57:38

think we should have like the same

57:39

concept of privacy for your

57:41

conversations with AI that we do with a

57:44

therapist or whatever.

57:45

>> Okay, Saxs, this is bringing up

57:47

something super important.

57:49

What's your take on it?

57:50

>> Okay. Well, I I think this is an

57:52

interesting topic because like

57:53

copyright, this is an area where we have

57:55

existing law, but it does make you

57:59

rethink whether those laws are truly

58:02

applicable or make as much sense in this

58:04

new world. So, the existing law, the

58:08

existing example is search history. You

58:10

know, the government can get a copy of

58:12

your search history. They can subpoena

58:14

it.

58:14

>> Yeah. Every true crime story starts with

58:17

the person's search for how do I kill my

58:19

husband slowly with you poison and then

58:21

they Yeah, that's

58:22

>> right. Exactly. The point is though that

58:26

I think Sam is right about the legal

58:28

treatment right now, which is that your

58:31

chat history isn't any different than

58:33

the search history in the eyes of the

58:34

law. But it is much more personal. It's

58:37

much more interactive than your search

58:38

history. You are using it like you said,

58:41

you could use it as a as your doctor.

58:43

You could use it as your therapist. You

58:45

could use as your lawyer. And so the

58:48

ability for the federal government to be

58:50

intrusive is so much greater than with

58:53

your search history. So I don't know

58:56

what like the right policy should be

58:59

yet, but I I will say it does make me

59:01

uncomfortable.

59:02

>> Yeah, there's a market.

59:04

>> Can I make a recommendation to my AIR?

59:06

>> Yes, please. He's our

59:07

>> Why don't we Why don't we let AI models

59:11

get bar certified and get medically

59:15

certified? So, if the AI models, it

59:18

turns out, are actually proving to be

59:19

more accurate, more thoughtful,

59:23

more responsive, more reasonable,

59:25

whatever it is, whatever metric we're

59:26

using, and they pass the same criteria

59:29

as one would need to pass to qualify for

59:31

the bar or to qualify for a doctor

59:34

certificate. Why don't we do that for

59:35

the AI? If that then happens, then the

59:37

the same privilege occurs to the AI as

59:40

it does to the individual human that

59:42

does it. And now if you extrapolate from

59:43

where that takes us, if we're suddenly

59:45

giving AI the same sort of privileged

59:47

rights that we give to privileged

59:48

humans, where's that going to take us

59:50

ultimately with respect to the overall

59:52

rights for AI?

59:52

>> Well, and they have responsibility. Hold

59:54

on a second. I just want to point out

59:56

here once again, you have a mind-blowing

59:58

concept here. I've never heard anybody

60:00

vocalize that. Could they actually be

60:01

certified in that knowledge? And if they

60:04

pass the test, makes sense they would.

60:05

But then you also get responsibility.

60:07

>> So with great power comes great

60:08

responsibility. I will tell you this.

60:10

>> You can turn this stuff off. But this is

60:12

an opportunity. I'm going to send a note

60:13

to you.

60:14

>> And it sounds crazy today, but I

60:15

guarantee if you put it on Poly Market,

60:16

there will be a date when this happens.

60:18

>> Poly market. Shout out to Shane. Let's

60:19

get that up there. I just want to point

60:21

out I'm going to email Elon about this

60:22

when I get off the pod.

60:24

>> This is an opportunity to create the

60:25

signal of the signal equivalent of an

60:28

LLM. The all of your chat should be

60:30

encrypted. All of it should be by by

60:33

default. Encrypt it by default on Grock.

60:35

Make it so that Grock can't even see it.

60:38

They don't have it. So when you try to

60:39

subpoena it, you can do what Tim Cook

60:41

does, which he says like, I don't have

60:42

it. You, if you want to try to back door

60:45

it, you can. That's a market

60:46

opportunity. I can tell you I only use

60:48

the Brave browser and Brave search for

60:50

this reason. I don't want my search

60:52

history like saved somewhere or

60:54

whatever. that. You can take

60:56

control of this as an individual, but

60:57

the defaults matter and you have to then

60:59

do the work. It's a great market

61:00

opportunity. Chimoth, I don't even want

61:02

to know what you're talking to chat GPT

61:04

about. What are you What's in your chat

61:05

GBT logs?

61:07

What's in there, Chimoth? How to extend?

61:09

How to get the extra centimeter? What's

61:10

in there? You trying to

61:13

What's in there?

61:14

>> I keep asking it to find me a moderator.

61:16

>> Oh, great. I keep asking it to find me a

61:19

participant who's not a douche. Um,

61:25

>> my god, you are so deep in your villain

61:27

era and you're leaning into it and I'm

61:29

so here for it, Chimat. I love your

61:30

villain.

61:31

>> You know why? I am so

61:33

>> Why are you going into your villain?

61:34

>> I am so riskon right now. It's like

61:37

>> it's liberating actually. It's amazing.

61:41

>> It's really amazing.

61:42

>> Is there any blowback to how outlandish

61:45

you've become this year? Any blowback at

61:47

all? Has it had any negative consequence

61:49

on business or hiring or anything?

61:51

>> No. But but outlandish? How how have I

61:53

been outlandish?

61:54

>> You're you're you're just filter off.

61:56

You're filter off. And I think it's

61:58

great. I think you're over two windows

61:59

back. It's absolutely fantastic we're

62:00

seeing here. I asked chat GPT about my

62:03

future and uh my IQ. It's very

62:05

interesting when you ask chat GPT to

62:06

analyze you.

62:07

>> I suggest everyone do it.

62:08

>> Well, actually, yeah, when you just ask

62:10

chat GPT or whatever, what do you know

62:12

about me?

62:14

>> And it's scary how much it already does.

62:16

>> It's scary. There's this great

62:17

personality test. You can put this

62:18

personality test into Grock and this guy

62:20

like made this prompt and it goes and it

62:23

tells you all your personality based on

62:25

your Twitter ex history. It is wild how

62:28

accurate it is. What does it say about

62:29

you, J? I'm actually curious.

62:31

>> It says the same thing about all of us.

62:33

We're all likeworked

62:35

narcissist, ENTJ. You can literally run

62:38

the MyersBriggs against your

62:40

>> Yeah, your chat history. It's actually

62:43

But I I like your mind-blowing concept

62:44

there, by the way, of like them becoming

62:46

certified in some way. Okay, fresh

62:49

economic news. It's time for the

62:51

administration to take their victory

62:53

lap. GDP growth was 50% higher than

62:56

expectations in Q2 as the Fed held rates

62:59

at 4.25%. In Q1, GDP declined 50 basis

63:03

points. That's probably due to the

63:04

imports. People were stockpiling goods.

63:06

>> That's the most pointless chart ever.

63:09

>> Okay. And then Yeah, it is. I agree.

63:10

It's a little bit Yeah,

63:11

>> it's distorted by I wanted to have both.

63:14

I wanted to have both as bar charts.

63:15

This one

63:16

>> totally on drugs. Just say it. It's

63:18

okay.

63:18

>> What drugs are you on? I'm not I had

63:21

coffee and now I'm out. I'm out.

63:23

>> We're all friends. You can tell us. Is

63:24

it really just out?

63:25

>> All right, that's it. I'm taking it out.

63:27

>> Oh my god.

63:28

>> I took it out. And now let's get back to

63:30

the here. Okay. The Fed kept rates

63:32

unchanged for the fifth straight

63:34

meeting. This time, two out of 11 Fed

63:36

governors desented from Pal's decision.

63:38

Two of the dissenters were both

63:39

Republicans nominated by Trump. So, it

63:41

seems like the Fed is becoming a little

63:42

polarized now, too. First time in 32

63:44

years that more than one governor

63:47

dissented. And um yeah, even one person

63:50

dissenting is rare. Here's a 25-second

63:53

clip of Pal explaining how GDP factored

63:57

into the cut decision. Nick, please play

63:59

the clip. Recent indicators suggest that

64:02

growth of economic activity has

64:04

moderated. GDP rose at a 1.2% pace in

64:08

the first half of this year, down from

64:10

2.5% last year. Although the increase in

64:14

the second quarter was stronger at 3%,

64:16

focusing on the first half of the year

64:18

helps smooth through the volatility in

64:21

the quarterly figures related to the

64:23

unusual swings in net exports. The PCE

64:26

index and then I'll throw this over to

64:27

you Sax for for the official position

64:29

here for June dropped on Thursday. PC is

64:32

the Fed's preferred gauge of inflation

64:33

over CPI. PCE rose 30 bips in June in

64:37

line with estimates and um if you

64:40

remember we talked about in a previous

64:41

episode CPI rose a bit 13% or 30 bips

64:45

from May to June. So, we're not any

64:47

we're not close to the 2% uh target and

64:50

that's what the Fed keeps saying. We're

64:53

not there yet. And the economy is al

64:55

fuego saxs. You note I don't know if you

64:58

noticed this, but people are talking

64:59

about the QDP the second quarter print

65:02

which was amazing for GDP. You were

65:04

talking about it a bunch on the socials.

65:06

He keeps referencing the first half. So,

65:08

he's trying to blend those two together,

65:10

I think, because of the the tariff

65:11

differences or, you know, maybe to to

65:13

smooth it out as he said. What's your

65:15

take on this? The GDP boomed in, you

65:17

know, 3% which is pretty great.

65:20

>> The problem No, the problem that Jerome

65:22

Powell has is that he's trying to smooth

65:24

it because it allows him to justify his

65:29

political decision.

65:30

>> Okay.

65:31

>> But the reason why you have to segregate

65:33

Q1 and Q2, Q1 was before tariffs and Q2

65:37

was after tariffs. So I think you have

65:38

to segregate these two things. And if

65:40

you look at the run rate from Q2, what

65:42

you're probably going to see in Q3 and

65:44

beyond is more similar to Q2, which is

65:48

to say a large surplus, good GDP

65:52

expansion,

65:53

and moderating inflation. So why does

65:57

the Fed not cut? Because at this point,

66:00

not cutting is the only thing that you

66:02

can do to slow the Trump administration

66:04

down going into the midterms if you

66:06

wanted to politicize the job.

66:11

If, however, on the other hand, you just

66:12

take the data as is and you ignore Q1

66:15

because it was pre-tariff and you start

66:17

to look at Q2 and you project forward,

66:20

if you inject a 100 basis point cut into

66:22

the economy, this thing is going to go

66:23

gang busters and Trump is going to look

66:25

like an economic genius going into 2026.

66:28

So I think that again in the absence of

66:30

politics you cut

66:32

>> Okay. Sachs, what's the take from inside

66:34

the administration and around it? I know

66:36

you're you're not speaking for the

66:37

president on this issue, but you're in

66:39

the administration, so I'm assuming

66:40

you're

66:40

>> Look, I'm not speaking for anyone, but

66:42

obviously the 3% number is way ahead of

66:44

expectations. It's a fantastic number.

66:47

It just feels like, you know,

66:48

everything's humming on all cylinders

66:50

here. One thing you didn't mention, but

66:52

I think is relevant, is the new trade

66:54

deal with the EU.

66:55

>> We're about to get to that, by the way.

66:57

That's the next story.

66:58

>> Oh, okay. Well, I mean, I would include

67:00

that because

67:00

>> Okay, include it. Yeah.

67:02

>> I mean, I think it was a deal that just

67:04

got announced where the EU is going to

67:06

open its markets to US products. No

67:08

tariff on US products, but they will pay

67:10

a 15% tariff coming into the US. They're

67:13

going to be investing 600 billion in the

67:16

US. They're going to be buying 750

67:18

billion of US energy. and then some very

67:22

large number I guess they didn't specify

67:24

number on defense products basically

67:26

American military products hundreds of

67:28

billions which is the followup to their

67:31

commitment to raise their contribution

67:33

to NATO to 5% of GDP up from I guess it

67:36

was sort of like 2% before

67:38

>> so I mean this is a huge deal for the

67:42

United States I think it's a huge win

67:44

for the Trump administration and the

67:46

deal is so good that what I'm seeing

67:48

from European sources on X European

67:51

publications just commenters is that

67:55

they they were like outraged. They felt

67:56

like they got taken to the cleaners

67:58

here.

67:59

>> Good.

67:59

>> And

68:00

>> okay,

68:01

>> you see you see a lot of that on X by

68:03

European side. A lot of the European

68:05

leaders are saying that Ursula chickened

68:07

out. So, you know, all those stupid taco

68:10

memes are going away now because people

68:11

are realizing that

68:14

Trump's willingness to raise tariffs on

68:18

these countries as a threat to

68:21

renegotiate better trade deals is

68:23

working. It's working extraordinarily

68:25

well. Just this EU deal, one way to

68:27

think about it is you add it all up,

68:28

it's about $2 trillion. It's effectively

68:31

$2 trillion of stimulus into the US, but

68:34

without money printing.

68:36

>> Yeah. Over the next three years. So it's

68:37

not inflationary.

68:38

>> It's not insignificant. Freedberg, your

68:40

thoughts on the Fed, the GDP print, and

68:44

then maybe you could get into the

68:45

granular

68:47

details of that print. If you pull up

68:51

the schedule of data, so this is the

68:53

national income and product accounts

68:55

data from the Bureau of Economic

68:57

Analysis. So this is where the inflation

69:01

print comes from. I think there are two

69:03

lines worth taking significant note of.

69:06

The first is the furnishings and durable

69:08

household equipment line. So in June,

69:11

the cost for furnishings and household

69:13

stuff jumped 1.3% month over month on an

69:17

annualized basis, right? That's almost

69:19

15% year-over-year if it were to

69:22

continue at that level. And then the

69:24

second one is this recreational goods

69:27

and vehicles that jumped 9% month over

69:30

month. Neither of those categories have

69:31

jumped that much in in kind of recent

69:33

history. So part of the argument that's

69:36

being made is that what we are seeing in

69:39

these jumps is actually some of the

69:41

first effects of the tariffs and the

69:44

cost of goods that are being imported

69:45

because these are largely imports having

69:48

an adverse effect on the consumer. And

69:51

so I think this is kind of a wait andsee

69:52

moment on some of these categories that

69:55

are predicted to have a tariff price

69:57

effect starting to show through. So I

69:59

think this is where a lot of folks are

70:00

keeping a close eye on and it kind of

70:02

provides a little bit of the support for

70:04

the economists that are saying we should

70:05

keep rates steady because if we are

70:07

seeing a significant inflationary effect

70:09

here it's worth noting that there's

70:10

something that we need to be thoughtful

70:11

about rate policy.

70:13

>> I think this is um a really good point.

70:15

If you look in this debate, which is

70:17

obviously highly political,

70:20

we're at inflation 2.567%.

70:24

Spending is increasing. Obviously, stock

70:27

market at an all-time high. Unemployment

70:29

trending down again. So, we're at like

70:31

4.1%.

70:33

And people are just yoloing into crypto

70:35

and they're doing sports betting.

70:36

Bitcoin at an all-time high. I think the

70:39

Fed now is in a position where cutting

70:41

rates seems like putting kerosene on the

70:43

fire. If Trump

70:45

tanked the economy in Q2, he probably

70:47

would have gotten the rates. But now I

70:49

don't think it's reasonable, as you're

70:51

saying, Dave, the the reasons to not cut

70:54

are building because the economy is on

70:56

fire. So maybe the shock and bore

70:58

approach to tariffs, which is now

71:02

becoming a playbook. I had a nice talk

71:03

with Lutnik about this, who I love, by

71:05

the way. He really described to me how

71:08

they're doing these. And the shock and

71:09

bore playbook is basically Trump says

71:12

something completely outrageous,

71:14

shocking, everybody goes crazy, the

71:15

media loses their mind, business leaders

71:17

lose their mind. Lutick told me that

71:19

what he does is he sets the table and

71:21

proposes something reasonable because,

71:23

you know, now I'm a big, you know,

71:25

direct contact with all the

71:26

administration. Sax, thank you for that.

71:28

Um,

71:30

and he described it. Trump comes in,

71:31

sees all the stuff, and then he starts

71:33

making these micro tweaks. So it's on

71:36

the finish line. It's in the red zone, 5

71:38

yard line. Trump comes in and then he

71:40

sticks it to them again with three or

71:41

four extra asks and then they wrap it up

71:44

and that this is becoming really

71:46

effective. So it was chaotic at first.

71:48

It seemed nonsensical, but they've put

71:50

the Fed in a really bad position because

71:53

they never seen this before. They've

71:56

never seen this before. So now they're

71:57

going to be in this defensive position

71:59

of what if we cut it and the market

72:02

rips. To your point, Chimoff, you just

72:04

said the market will rip the second they

72:05

cut that. And the cynical view of this

72:08

is the market rips as we go into the

72:10

midterms, which is the same claim the

72:12

Republicans made about the cuts that

72:14

Biden did in September right before the

72:17

election. So, there is some level of

72:18

politics and gamesmanship going on here.

72:20

But you have to hand it to the Trump

72:22

administration for what they're doing

72:25

with this sort of 2.0 playbook. If this

72:28

was Sachs premeditated and we all just

72:30

didn't understand it, fine.

72:32

The outcome here is

72:35

this administration has to live or die

72:37

by the results of these 600 billion from

72:40

the EU, 550 billion in investment from

72:45

Japan. You put those two together, I

72:46

asked Lutnik, is that at the event, is

72:49

that going into the sovereign wealth

72:50

fund? And how does that get, you know,

72:53

spent? And he said at the discretion of

72:55

the president and he's advising him to

72:57

spend it on putting more nukes in. So

72:59

that's fascinating. We have a trillion

73:01

dollars now that we can put into nuclear

73:05

power plants and these small module

73:08

reactors. And that's what Lutnik said he

73:10

wanted to spend it on. He's going to

73:11

advise the president to spend it on. But

73:12

now we've got them investing in our

73:14

country. It's absolutely brilliant. If

73:16

it works out, we'll see if it works out.

73:18

>> April 2nd was liberation day and the

73:22

media went crazy. They were predicting a

73:24

black Monday. The market crash. They

73:26

basically tried to spook the markets and

73:28

create fear. They said that we're going

73:30

to go into a recession or depression.

73:32

And now look at where we are. It's just

73:33

a few months later. All the markets are

73:35

at all-time highs. Trump has extracted

73:38

trillions of dollars in these trade

73:40

deals that people know.

73:41

>> Premeditated. Tell us the truth.

73:43

>> Premeditated.

73:44

>> Hold on. President Trump has extracted

73:47

trillions of dollars from other

73:49

countries using powers that other

73:51

presidents didn't even know they had.

73:53

>> 100% 100%. Was it premeditated? Cuz it

73:56

was chaotic. the market did the market%

73:59

moves because of the media by the way

74:01

those moves because they were scared

74:02

>> and we just had a 3% GDP growth

74:05

>> print

74:07

how things could be

74:08

>> what I think happened is that President

74:11

Trump saw an opportunity here that other

74:13

people ignored it's like when a CEO

74:15

comes in to a company a new CEO comes in

74:18

and that company's been mismanaged for a

74:20

decade but it's got wonderful assets on

74:22

its balance sheet it's got a market

74:24

position that's still very strong has

74:26

been underutilized. And he came in and

74:29

understood that the United States had

74:30

tremendous leverage in all these trade

74:32

negotiations. Actually, they weren't

74:34

even trade negotiations then, in all

74:35

these trade relationships. And he was

74:38

able to essentially renegotiate all of

74:40

them. And look at the results. I mean,

74:42

they're just staggering. And you know,

74:44

everyone said that, "Oh, Trump's going

74:46

to chicken out. He's not going to hang

74:47

tough." It's all these other countries

74:49

that have folded like, I don't know,

74:51

lawn chairs. I mean, they have all

74:54

capitulated.

74:55

>> Yeah. Yeah, they follow.

74:56

>> It's really remarkable.

74:58

>> But you're not answering my question.

74:59

Was this premeditated? Give us some

75:00

insight here.

75:01

>> I don't know what this is. What are you

75:02

talking about?

75:03

>> When they came out and they was like,

75:04

"Oh, 100% tariffs, 200% tariff." The

75:07

market was not making that reaction

75:09

based upon the media. They were making

75:11

it based on Trump was saying. So, was it

75:14

premeditated this shock and bore shock

75:16

and reasonable negotiating strategy or

75:19

do you not know? Well, you're not privy

75:20

to Look, I'm not speaking as an insider

75:22

here, but we said at the time that all

75:25

of that was happening and Larry Summers

75:26

was on the pod preaching doom is that

75:29

all of that was an opening bid. It was

75:31

all a start to a negotiation and we had

75:33

to see where it ended up and that the

75:36

administration still had to stick the

75:38

landing.

75:38

>> Okay,

75:39

>> but I got to say based on

75:41

>> EU, Japan, and South Korea, I mean, this

75:43

is looking really good right now.

75:45

>> Well, listen, it's the top five that are

75:47

like 90% of the negotiation. As Trump

75:49

said, there was another little note he

75:50

did in the keynote when he kind of

75:52

drifted into his, you know, different

75:53

things he wanted to talk about where he

75:54

said, "I don't even need to know about

75:56

the bottom countries. I've never even

75:57

heard that names of some of these

75:59

countries." He's just got to nail the

76:00

what, the top five, the top 10, and

76:02

we're done. And this administration has

76:04

to stick the landing as well because

76:07

these are handshake deals right now.

76:08

They have to be inked. They have to be

76:10

approved. So, there's there's a lot more

76:12

work left to be done. But I said as

76:14

well, there's one other piece of it. We

76:16

talked about the the um

76:18

>> you know the fact that Europe has 0%

76:22

tariffs on American products but but

76:23

even after this deal

76:26

>> that the European products into coming

76:28

into the US will have a 15% tariff and

76:30

we're not including the $600 billion of

76:32

European investment in the US. We're not

76:33

including the 750 billion of sales of

76:36

American energy to Europe. Okay, just

76:39

talk about the tariff that 15% and what

76:41

we're seeing now across the board is

76:42

generating about 300 billion a year of

76:45

additional tariff revenue that goes to

76:47

help balancing the budget.

76:48

>> Yeah.

76:49

>> So 300 billion a year over 10 years is 3

76:51

trillion. That is a big number.

76:52

>> It's incredible. Yeah. It's got to

76:54

>> I don't know if that that completely

76:55

satisfies Freeberg, but that's a big

76:58

help.

76:58

>> Freeberg, do you think that there is a

77:01

chance that inflation is going to tick

77:04

up because of all this? like this is a

77:06

lot of money being pushed into the

77:07

system again. So, could we see a

77:09

three-handle on inflation in the next 6

77:11

months or what's the probability of that

77:12

in your mind?

77:13

>> That's the big concern everybody has.

77:15

>> I don't I I don't know. I I don't know.

77:16

I think the the big question if you look

77:18

at each of these categories, one way to

77:20

think about it is how much margin is the

77:23

seller making?

77:24

>> If they're making 30% margin and we

77:27

charge a 15% tariff, does their margin

77:30

go down to 15%. or do they take their

77:33

margin down to 20% and raise the price

77:35

by 5%. What's the right balance? And

77:38

what will happen is that now with this

77:41

effective you know tariff which is a

77:43

sort of tax on the system a tax on the

77:45

market will find its kind of new

77:48

equilibrium where the buyers are willing

77:50

to pay X and the sellers are willing to

77:52

sell it Y and I think every market's

77:54

going to be a bit different. So I think

77:55

in some of these categories we will see

77:57

significant inflation where there is a

77:59

very thin margin that the seller has in

78:01

selling and in some of the categories

78:03

where there's a monopoly and they have a

78:04

big margin they're going to eat it

78:06

because they don't want to have

78:07

competition and they don't want to see

78:09

pricing competition emerge. So I think

78:10

we'll see it vary by category and you

78:12

know we'll see how it goes. All right

78:14

listen this has been another amazing

78:16

amazing episode of the number one

78:17

podcast in the world according to Jensen

78:19

Wong from Nvidia and me and uh great job

78:23

everybody. Great job to everybody. It's

78:25

a class.

78:25

>> Great job everyone. Even JCAL. Even J.

78:28

Even Jason. Great job.

78:31

>> And actually, I want to thank Freeberg

78:33

cuz Freeberg did most of the work to

78:34

organize the AI.

78:36

>> Let's give him a big shout out. There's

78:37

me.

78:38

>> Great job.

78:39

>> I mean, guys, can we just make a note

78:41

here?

78:42

>> One of us can run for Manurian candidate

78:45

president in eight years. And look at me

78:47

and the president. I put on the red tie

78:49

out of respect. I put my blue suit on

78:51

out of respect for the president. Does

78:53

it not look like I'm running president

78:56

Jason.com?

78:59

All right, listen.

79:00

>> That photo could be like, you know, that

79:02

famous photo of uh Bill Clinton meeting

79:04

JFK. You know, that could be the thing

79:06

that that could be the thing that

79:08

>> I'm in like that famous image

79:10

>> that propels you to the presidency.

79:12

>> I'm in like Thank you for giving me that

79:14

and and for putting me in touch with

79:15

each member of the administration

79:17

directly. Thank you for that. And we had

79:19

a wonderful tour of the White House the

79:21

next day. What a wonderful tour. Some of

79:24

us had at the White House the next day.

79:25

But in all honesty, no. I was

79:27

>> Did you?

79:27

>> No. I was taking the pictures. That was

79:29

my joke cuz it was all of you guys were

79:31

giving you a tour. We could have gotten

79:33

you a tour.

79:33

>> I mean, listen, I love J.

79:34

>> Did you ask for a tour?

79:36

>> I'm I'm not the kind of guy to ask. I'm

79:38

the guy.

79:38

>> Some of us have actual meetings to do,

79:40

bro. I mean,

79:40

>> it's all good. It's all good. I got a

79:41

lot going on. I got a lot to announce

79:42

and happen in the coming weeks. But Sax,

79:44

do do take us behind the scene here.

79:46

>> And I think it was hilarious. So, I

79:48

don't mind getting trolled by the

79:49

president. It was great. But how did you

79:51

how did that go about behind the scenes

79:53

that he nailed that joke?

79:54

>> Don't tell him. Leave it. Leave it.

79:56

>> What did you do? I mean, cuz that looked

79:57

like it was workshopped or is he just

79:59

naturally I mean, he's obviously

80:00

naturally comedic, but did you put that

80:02

in with him? Did you have to clear that

80:03

with him? Hey, Dunan, Jal, whatever.

80:06

>> Well, they asked me for the names of,

80:09

you know, my co-hosts and so they could

80:11

do shout outs. So, I gave him the list.

80:14

>> Oh, no. And I just I said and I put even

80:16

Jake House,

80:20

>> but I mean he went for it.

80:23

>> No, he he he got we went through it. So

80:25

>> he got the joke. Okay.

80:26

>> He got the joke. We went through it.

80:27

>> He got the laugh. He got it. He heard

80:28

the laugh and he heard the laugh and he

80:30

doubled down.

80:31

>> I thought it'd be funny. But no, we went

80:33

through everyone's names beforehand

80:35

>> and uh

80:36

>> I mean, talk about EQ. The guy's EQ is

80:39

off the charts, man. He just he's timing

80:42

is great. I suggested I suggested the

80:44

name JCAL and he's like, "No, no, give

80:45

me his full name." He thought it was

80:47

more courteous.

80:48

>> He's actually a very

80:50

>> courteous man. He wanted to use your

80:54

full name, not just your nickname.

80:55

>> I think what he probably realized was

80:56

for my parents who were

80:58

>> just over the moon. So, thank you for

81:00

that. It meant a lot to my dad who's

81:02

>> That's lovely.

81:02

>> Yeah. He's been struggling a bit and it

81:04

it really Let me get a little choked up

81:06

here, but my dad's been struggling a

81:07

bit. And um I got to see him in Brooklyn

81:09

after that and we were on a tech stream

81:11

and and it meant a lot you know cuz for

81:14

a kid from Brooklyn to get a shout out

81:15

from the president of the United States

81:16

is

81:16

>> you made it.

81:17

>> I mean it's just

81:18

>> your father your father should be really

81:20

proud of you.

81:21

>> Thanks man. Appreciate it. I appreciate

81:22

it boys. All right listen for your

81:24

Sultan of science the amazing Dave

81:26

Freeberger who put that event together

81:27

in 10 days and then jumped right in.

81:29

He's got to run a hollow at the same

81:30

time. So I just want to give our MVP of

81:33

the week.

81:33

>> We should give a shout out to the Hill

81:34

and Valley guys for partnering with us.

81:36

Jacob, Jacob Hellberg did a great job.

81:38

>> Love Jacob. I love Jacob.

81:39

>> And Delian and Chris.

81:42

>> Thank you guys. They were our partners

81:43

on the event.

81:44

>> Hillen Valley did a great job. Yeah, I

81:45

love those guys.

81:47

>> But yeah, just I'm giving the MVP of the

81:49

week for of the besties to you, David

81:51

Freeberg. You put a lot of work into

81:52

this. So, and we appreciate it. You're

81:54

running a hollow and then you went right

81:55

into working on the all-in summit which

81:57

we'll be at in a couple weeks. Chimat,

81:58

thank you for buttoning up. We're

82:00

getting a little complaints from the HR

82:01

department about the uh the buttons and

82:03

so we we've now renegotiated that. I'm

82:05

going to I'm going to unbutton three

82:07

buttons now and walk around Forte.

82:09

>> Perfect. And Saxs, I will see you at the

82:11

White House. JD and I will be in the

82:12

commissary. So, we'll invite you to

82:14

lunch with us in JD.

82:16

>> It's called the Navy actually

82:18

>> in the mess. Yeah. And and you know

82:19

what? Lutnick's joining us as well. And

82:21

um who's our energy guy? Chris. Chris

82:23

said he wanted to jump in on that. So

82:25

maybe you can join us. I'll invite you

82:27

now that I am deep into the

82:28

administration.

82:30

>> Thank you for tuning in everybody.

82:31

Allin.com events. The scholarship

82:33

tickets are up. So, if you want to try

82:35

to get one of the very few scholarship

82:36

tickets, we always like our upandcomers.

82:38

Please, if you're if you're of means,

82:40

don't apply for the scholarship. You

82:41

won't get it in. But if you're up and

82:42

coming and you're part of the audience

82:43

and you want to get one of those

82:44

discounted tickets, we have a limited

82:45

number of those available.

82:46

All.com/events.

82:48

Love you besties. Byebye. Love you.

82:50

Byebye.

82:52

>> Let your winners ride.

82:55

>> Rainman David.

82:59

>> And it said we open sourced it to the

83:01

fans and they've just gone crazy with

83:03

it. Love you.

83:04

>> Queen of kinshine.

83:07

[Music]

83:12

>> Besties are gone.

83:15

>> That is my dog taking a notice in your

83:17

driveway.

83:20

>> Oh man, my dasher will meet me up. We

83:23

should all just get a room and just have

83:24

one big huge orgy cuz they're all just

83:26

useless. It's like this like sexual

83:28

tension that we just need to release

83:29

somehow.

83:31

Wet your feet. Wet your feet.

83:34

>> Your feet.

83:36

>> We need to get mer.

83:41

[Music]

83:45

I'm going all in.

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