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OpenAI Misses Targets, Codex vs Claude, Elon vs Sam Trial, Big Hyperscaler Beats, Peptide Craze

May 01, 2026 / 01:20:57

Video

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Jason, do you want to tell us about your

00:00:02

new favorite podcast? Oh, it's so good.

00:00:06

My feed is now because, you know, since

00:00:10

cancel culture ended, Sachs, everybody

00:00:12

uses the R word and the f word right

00:00:14

now. My entire feed on Instagram is

00:00:17

either gay or down syndrome or bulldogs.

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It's one of those three. And then I

00:00:22

stumbled upon the Miss Thing pod,

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Miss Thing. And they do a bit called gay

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name, straight name. Here's gay name or

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straight name for David. This good news

00:00:33

and bad news freeird. Here we go.

00:00:35

>> Gay name or straight name?

00:00:38

>> David.

00:00:40

>> David to me is straight.

00:00:42

>> Okay. But he has my perfect body. It can

00:00:46

be confusing because I'm kind of like,

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are you gay? And it's like, no, I just

00:00:50

want to be you, David.

00:00:51

>> Totally. Well, it's so like the

00:00:54

Michelangelo's David the male ideal.

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It's like incredible body kind of small.

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Sorry.

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>> Yeah.

00:00:59

>> Oh,

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>> it's a little rough.

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>> What?

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>> What are you watching there, Jal?

00:01:04

>> They basically nailed these two, but

00:01:06

okay, keep going.

00:01:07

>> I don't think Chimoth is on their short

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list, but I know Jason will come up at

00:01:10

some point.

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>> Gay name or straight.

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>> Maybe this is it.

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>> Chimoth

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on the count of three. Yeah.

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>> Three, two, one. gay. I'm seeing like

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Italian sweater, like really kind of

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like a loud vibrant sweater. He like

00:01:28

wears it to like poker night with his

00:01:30

like his boys and like not I'm not

00:01:33

talking like straight poker. I'm talking

00:01:35

like gay poker nights like at the bar.

00:01:38

>> Yeah. Always talking about wine.

00:01:40

>> Talks about wines.

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>> Always sort of like

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Yeah, exactly.

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>> Yep. Also, it's so like the guy at the

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gym taking off his shirt, taking

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selfies.

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>> Yeah. And everyone else is kind of like,

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"Excuse me, Chimoth. I'd like to use the

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mirror. I'd like to see myself.

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>> See you at the next day." Poker night.

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>> Totally.

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>> You bring the wine.

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>> We'll bring the sweater.

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>> Yeah,

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>> there it is. Wow. They did do.

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>> That is fantastic. That is fantastic. A

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shout out to my guys at the Miss Ding

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podcast.

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>> Wow, that was awesome. I think I'm gay.

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I never knew.

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>> Let your winners ride.

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>> And it said we open sourced it to the

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fans and they've just gone crazy with

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it.

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>> What did you do like cameo? Did you pay

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them to do that?

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>> Did it for me as a favor. So they did it

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for

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>> That's awesome. Well, thanks to those

00:02:41

guys to the miss. I've seen those guys

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before in clips. I find them very funny.

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>> It's so great. Shout out to my guys.

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>> That was awesome.

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>> All right, everybody. Seriously, welcome

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back to the number one podcast in the

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world. It's the All-In podcast with me

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again, David Freebergia, David Saxs, and

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of course, I'm Jason Calcanis. You can

00:03:01

call me Jay Cal if you're here for the

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first time. Topic one, open AI. They

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missed their targets for chat GPT

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Freedberg both on users and revenue.

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Let's talk about it. The Wall Street

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Journal says in a uh a breaking

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investigative report on Tuesday that

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OpenAI expected to hit 1 billion wows

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weekly active users before the end of

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2025. They missed that and they still

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haven't hit the milestone 4 months into

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2026. Also, Chamath, they missed their

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2025 revenue target for Chad GPT. Exact

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number wasn't specified, but as we've

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talked about here, they're at a 2030

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billion run rate. There's a little bit

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of accounting nuance that is yet to be

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worked out in the industry. Two reasons

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why this matters. Sachs, OpenAI has $600

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billion in spending commitments for

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compute. Just to put that in

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perspective, that's about what they're

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trading for on secondary markets. In

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other words, the entire value of the

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Open AI enterprise equals their spend

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commitments in the coming year. CFO

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Sarah Frier, who is coming to liquidity,

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is reportedly worried, hey, that revenue

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isn't growing fast enough to keep up

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with expense and OpenAI wants to IPO

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later this year. This has put Frier and

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Oughtman in conflict or uh maybe there's

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some natural tension there. Frier

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doesn't think OpenAI is ready for public

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reporting standards. According to the

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Wall Street Journal, Altman obviously

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wants to move faster, so they released a

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joint statement. this is ridiculous yada

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yada yada. Let's go to you Saxs. What do

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you think's going on here? Are these

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major headwinds or is this just managing

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expectations as the leader of the pack

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in the most important race of our

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lifetimes, the race towards super

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intelligence?

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>> Well, I actually have a little bit of a

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contrarian take on this. I know that

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OpenAI had a really bad week. Like you

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said, they had that Wall Street Journal

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article which said that they missed

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their numbers. They missed their 1

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billion user growth target. They missed

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their revenue numbers. That's called

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into question whether they can afford

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the data center commitments that they've

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made. And then in addition to that,

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they've also had the lawsuit with with

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Elon happening this week. So in the

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press, it ended up being I think a

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pretty bad week for them. But I have a

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contrarian take on this, which is I

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think that over the past week or two, if

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you look at kind of what's happening at

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the product level, it's been a pretty

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good couple of weeks for them. They

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released chat GBT 5.5 and the reviews

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from, you know, people I talked to in

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Silicon Valley have been really strong.

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You talk to developers, coders, they're

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very happy with it. At the same time,

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Opus 4.7, which is the latest anthropic

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release, appears to be a bust. People

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are complaining about it. They're in a

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lot of cases are rolling back to 4.6.

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They're saying that Opus 4.7 is

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rationing compute. It's reducing

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thinking time, not as good. there were

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some bugs and clawed. So if you just

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compare chat GPT 5.5 to Opus 4.7, it

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does appear that OpenAI has had a better

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couple of weeks on a product level. And

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I think there's reason to believe that

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the product improvements will continue.

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GPT 5.5 is based on a new base model

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called Spud, which is the first base

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model upgrade they've done in I don't

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know over a year. and having a new base

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model will pave the way for future

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improvements as well. So I think OpenAI

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is feeling pretty optimistic about their

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product right now and I think you're

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starting to see on X some of the

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developer mojo is shifting. I'm seeing a

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lot of people saying that they are

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shifting their their coding usage from

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Opus to GPT 5.5.

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So I think that SAM may end up being

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right but for the wrong reason. And what

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I mean by that is that when he made

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these big compute commitments, it was

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based on those estimates of hitting the

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billion users on the consumer side and

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hitting those revenue targets. The

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consumer business ended up being weak.

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So they missed those targets. But in the

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meantime, coding has become the

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allimportant sector of AI. And because

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they made all these compute commitments

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and they built out these data centers,

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they have more compute than anthropic

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right now. Anthropic is token

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constrained. It's reducing their ability

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to serve mythos, for example. It's

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causing them to engage in compute gating

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with Opus 4.7. And I understand why

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Daario made that decision. I'm not

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saying I mean it was a prudent business

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decision. I'm not criticizing him for

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it, but I think again I think Sam may

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end up being right here for the wrong

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reason, which is he missed on consumer,

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but enterprise is going gang busters and

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is giving him the ability now, I think,

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to catch up on code. your poly market

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>> which is the all important market right

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now

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>> of course and we talked about gro and

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cursor teaming up last week Elon and the

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team over there poly market showing now

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a 32% chance that openai goes public by

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the end of 2026 this is down from 60% in

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December and Shimath you gave a bit of a

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warning hey there's only so many dollars

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to go around SpaceX IPO is obviously

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getting out first and now if openai

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doesn't go out this year and anthropic

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does the sets up an interesting dynamic.

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What are your thoughts here generally

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speaking about the massive commitment

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that OpenAI has made? Are they going to

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run off the cliff or will it wind up

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being brilliant? Uh even if it wasn't

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strategically for the exact reasons,

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>> I think they're going to be fine. I

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think this is a multi-t trillion dollar

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company. I think Anthropic is a multi-

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trillion dollar company. I think the

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thing that's happening right now is uh a

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complete misunderstanding

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of what's actually happening

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inside of the world of AI. And there is

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one very specific choke point

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that is constraining everything which is

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access to the power that's necessary to

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drive these tokens. To the extent that

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open AI missed, I think what that is is

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an insight to not enough compute

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capacity today. And that problem is only

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getting worse. You've already seen that

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with Anthropic as well where they just

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found a way to economically induce

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Amazon to give them enough capacity so

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that you don't have to route through

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bedrock to get to the anthropic models.

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You're also seeing them do

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differentiated deals now with economic

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participation on top of what they

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already had from folks like Google to

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give them more capacity. What is my

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point? Everything in this market is

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power constrained. The reason that these

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folks may miss a number or a forecast

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have nothing to do with demand. It is

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entirely 100% due to the supply of the

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power necessary to generate the output

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token. There is a really interesting

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thing that was just announced today that

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will make this problem even worse, which

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is what you're starting to see now is

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backlogs build up of not just the access

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to the power, but then the componentry

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that's actually necessary. Not just

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resips and not just NAT gas turbines,

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but now you're talking about

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transformers and all the actual tactical

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grid infrastructure.

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Why is this important? If you look at

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the actual amount of gigawatts that are

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under construction, we have a huge

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mismatch now,

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people have announced all these

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projects, Jason,

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but less than half of it is actually

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being built. Less than half. Most of it

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is stuck in red tape.

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Most of that is because there are these

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supply chain delays. So there's no

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credible strategy to turn any of this

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stuff on. Who will this hurt? It will

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hurt Anthropic and OpenAI the most. Who

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will this benefit? It will benefit the

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hyperscalers, specifically Oracle,

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Amazon, Meta, Microsoft, and Google. And

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now what you're going to see is a

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negotiation and a trade back and forth.

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How much equity do I have to give up?

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How much control do I have to give up to

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get access to the compute versus how

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badly will I miss my growth forecasts if

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I don't? And now what that means is, and

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we spoke about this last week, that's a

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huge lane for Grock to just run through

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and SpaceX to run through cuz they have

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a ton of excess capacity. And so I think

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the cursor deal was the appetizer. But

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if I were Elon now, I'd be running all

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over this market because if the models

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catch up in quality, I think he could

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also do something really crazy with

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anthropic or open AI right now. Maybe

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not open AI because of the

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>> we'll get into the lawsuit in a bit

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>> the baggage.

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>> Yeah.

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>> But man, he and Dario should do a deal

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tomorrow.

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>> So you're framing, hey, the the limited

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resource here is compute. The demand is

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off the charts.

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>> No, the limiting resource is power.

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power which then powers compute which

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then provides tokens which then services

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the massive uh developer and co-work and

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all these other projects that consumers

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and enterprises can't get enough of. Got

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it.

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>> And Jason, the other factor that

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complicates that for anthropic and open

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AI is all the stuff that's sort of

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sitting around thumb twiddling. 40% of

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that is going to get cancelled because

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they've done such a poor job of creating

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a good positive halo around AI that 40%

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of all the announced projects get

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cancelled because 40% of all projects in

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the last four years have been cancelled.

00:12:28

Yeah. And there's there there are some

00:12:30

bad feelings about data centers, AI,

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jobs, etc. And that's causing some

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headwind. People are you literally doing

00:12:39

violent things in society and blaming

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data centers and AI for it. I don't want

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to give it too much air time. Freeberg,

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what's your take on the chessboard we're

00:12:47

looking at here? Either through compute,

00:12:50

energy or through going public on a

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business level, you know, the strategic

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nature of capital, compute and energy

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now playing a role in this massive

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amount of demand. still a ball in the

00:13:04

air kind of game. BCG had this theory, I

00:13:09

think I talked about this once before,

00:13:10

called the rule of three where they've

00:13:12

shown time and again that any stable,

00:13:14

mature, competitive market evolves to a

00:13:18

4:21

00:13:20

ratio of market share for basically 90%

00:13:22

of the market. So there's a market

00:13:23

leader that has four times the market

00:13:26

share of the second place, that's two

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times the market share of the third

00:13:29

place. This is the case in pretty much

00:13:30

every mature kind of competitive market.

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So you can kind of think about AI

00:13:34

probably evolving into a consumer market

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and an enterprise market. Open AAI, even

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if they're not at a billion, they're

00:13:40

still at 900 million weekly users, which

00:13:43

is well ahead of whatever Claude is at.

00:13:46

I think Claude is like probably subund

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million sacks, you may know. And then

00:13:49

Gemini is probably closer to them at 700

00:13:52

to a billion somewhere in that range.

00:13:54

Probably pretty neck and neck with open

00:13:56

AI. So, you know, the consumer market

00:13:59

looks like it's trending towards a chat

00:14:02

GPT/Google

00:14:04

fight for first place and second place

00:14:06

and then probably anthropic in third

00:14:08

place and maybe Elon emerges and takes

00:14:10

off enabled by his compute capacity and

00:14:13

then the enterprise market is a little

00:14:14

bit of a different story and that's its

00:14:16

own market which is kind of anthropic or

00:14:18

probably Google in the lead actually if

00:14:20

you look at all the vertex use. Google

00:14:22

claims that 75% of GCP customers are

00:14:26

active users of Vertex. So there's

00:14:29

probably a pretty sizable

00:14:32

market share that Google's captured on

00:14:33

the enterprise side as well. This is

00:14:34

also probably why Google stock has

00:14:36

absolutely ripped over the last couple

00:14:38

of months is they're literally in first

00:14:39

place or fighting for first place in

00:14:42

enterprise and consumer.

00:14:44

But I still think that there's a lot of

00:14:46

opportunity to Chimoff's point about the

00:14:48

compute and energy capacity constraints

00:14:50

in improving how we actually scale and

00:14:53

deploy models in both the enterprise and

00:14:56

the consumer setting. And it is such

00:14:57

early days and I just want to highlight

00:14:59

this paper that came out from MIT from

00:15:02

these two scientists and these guys

00:15:05

published a paper on pruning techniques

00:15:07

and neural networks. This paper showed

00:15:09

that you could actually reduce the size

00:15:10

of these networks by 90%.

00:15:13

And get the same accuracy out by pruning

00:15:17

very large models down to smaller

00:15:19

models. And then you can make a

00:15:20

selection on which model to run for

00:15:22

inference. And by doing this, you can

00:15:24

actually reduce inference costs by 10x.

00:15:27

You can get 10x the output per energy

00:15:29

unit that goes into the data center with

00:15:31

no loss of accuracy. And so it's a

00:15:34

really interesting call it algorithmic

00:15:35

technique that can be applied to the

00:15:38

existing large models to actually make

00:15:40

them much lower energy use. So if you

00:15:42

think about it, you're firing up a very

00:15:44

large model to answer a very simple

00:15:46

question. You can actually prune away

00:15:48

that model. Now this is probably going

00:15:51

to be the case in AI applications as it

00:15:54

is in traditional Google search. There's

00:15:56

a long tale of searches, but there's a

00:15:58

few searches that account for a large

00:16:00

percentage of search volume. It's like

00:16:02

what is the weather? What are the movies

00:16:04

times? You know, what's the stock price?

00:16:06

Like there's a certain set of things

00:16:08

that make up the bulk of consumer

00:16:10

energy. And there's probably a certain

00:16:11

set of things that probably make up the

00:16:12

bulk of coding output as well. And so if

00:16:15

you can get that 80% of searches or chat

00:16:18

interfaces or coding requests reduced

00:16:22

down through pruning techniques to

00:16:23

smaller models and then you have a whole

00:16:25

set of smaller models that can be called

00:16:26

dynamically and you reduce inference

00:16:28

cost by 90%. you can make much more use,

00:16:31

call it 10 times the use on data center

00:16:34

and energy capacity than we can today.

00:16:36

So I would argue that we're still in the

00:16:37

very early days of getting efficiency in

00:16:40

terms of output and tokens and we're

00:16:42

just in the very kind of early stage of

00:16:43

that which also unlocks the opportunity

00:16:45

for guys like Elon to reinvent how this

00:16:47

is done and potentially compete pretty

00:16:49

aggressively.

00:16:50

>> There are two ways to win. You could

00:16:51

throw compute at it or you can do SLM's

00:16:54

small language models and V SLM's

00:16:57

verticaliz small language model. So if

00:17:00

you had a verticalized small language

00:17:01

model for the weather, let's say that

00:17:03

doesn't exist, but uh you can you can

00:17:05

use it as an example. They will have one

00:17:07

for travel as an example. When you hit

00:17:09

Google for flight information, it's

00:17:11

obviously going to route you to

00:17:13

something lighter and faster that uses

00:17:15

Google flights. And Google flights has

00:17:16

been incor incorporated into Gemini.

00:17:19

Gemini now is right behind 700 750

00:17:23

million users

00:17:25

>> and it's exactly what we discussed I

00:17:27

don't know 18 months ago on this podcast

00:17:28

Freeberg that what if they put it at the

00:17:30

top

00:17:31

>> and what would that do to their search

00:17:33

revenue search revenue is surging and

00:17:37

they're also surging so they figured out

00:17:39

a way to balance those two competing

00:17:41

forces having search results that are AI

00:17:43

enabled and still getting people to

00:17:46

click on links they've done it

00:17:47

brilliantly apparently and the stock is

00:17:49

rewarding.

00:17:50

>> I'll just add one statement to what you

00:17:51

said, which is like you're using what I

00:17:53

would call a humanistic on

00:17:58

humans don't intuitively know what this

00:18:01

model is. It's not just a verticalized

00:18:02

model, but there are going to be models

00:18:05

that will be discovered through

00:18:07

automated pruning techniques that will

00:18:09

then be working in concert. So, lots of

00:18:12

small models that link together. And we

00:18:13

don't define each model by some human

00:18:15

heristic like this is a search travel

00:18:17

model.

00:18:18

>> This is a maps model. We don't we don't

00:18:20

know why these models work the way they

00:18:22

do when they get broken down. But I do

00:18:24

think that that's really where the

00:18:25

evolution is happening. So effectively a

00:18:27

model becomes a macro model. It's got

00:18:29

lots of smaller models underneath it

00:18:31

that can be dynamically called and that

00:18:33

allows you to have 10x the inference for

00:18:35

the same unit of energy.

00:18:36

>> Sax,

00:18:37

>> let me just build on your point about

00:18:38

Google. Jcal, I would say that if

00:18:40

there's a single reason why OpenAI did

00:18:44

not hit its user targets and its revenue

00:18:48

targets, certainly around consumer,

00:18:50

you'd have to say it's because Google

00:18:52

managed to take meaningful share, you

00:18:55

know, they were basically nowhere a year

00:18:58

or so ago. Sergey came out of

00:19:00

retirement, helped focus the company,

00:19:03

and like you said, they did a brilliant

00:19:05

job improving Gemini and putting it at

00:19:07

the top of search, incorporating it.

00:19:09

Now, that being said, again, I don't

00:19:11

think the news is all bad for OpenAI

00:19:13

because I do think that the 5.5 release

00:19:15

was great. We're hearing really good

00:19:17

things about Codeex. I do think that

00:19:19

Codeex is taking share in coding tokens

00:19:23

right now. And I just think we're in a

00:19:25

really interesting place where these

00:19:27

companies are constantly oneuping each

00:19:29

other. I mean, two weeks ago it looked

00:19:31

like Anthropic was going to be

00:19:32

completely dominant, right? I mean,

00:19:34

Anthropic was growing at 10x. Open AAI

00:19:36

was growing at 3x and it looked like

00:19:38

>> and then the servers started going down.

00:19:39

Did you see that this week? The server

00:19:41

going down. People were in my office

00:19:43

were complaining we can't get on claud.

00:19:45

>> Listen, competition brings out the best

00:19:47

in everyone. Anthropic forced open AI to

00:19:50

compete. Google's forced open AI to

00:19:52

compete in consumer. I just hope the

00:19:54

market stays competitive for as long as

00:19:55

possible. I do think that's what's best

00:19:57

for consumers, our economy, and for our

00:20:00

country overall. Let me just say one

00:20:03

other area where I think OpenAI had a

00:20:06

good week is in this red-hot area of

00:20:10

cyber. Obviously, Anthropic made a huge

00:20:13

splash with Mythos. It hasn't been

00:20:14

commercially released. Their compute

00:20:16

constraint, but as a proof of concept or

00:20:18

training model, it hit a new level of

00:20:20

capabilities with cyber. But now OpenAI

00:20:22

has released a new model called GPT 5.5

00:20:25

cyber which has just been through a

00:20:26

bunch of tests and they've shown this

00:20:29

was testing done by the AI security

00:20:31

institute that GPT 5.5 is the second

00:20:34

model to complete one of their

00:20:36

multi-step cyber attack simulations end

00:20:38

to end. So it has the same level of

00:20:40

capability as Mythos and it does appear

00:20:43

to be commercially

00:20:46

ready. You know, they've got the compute

00:20:47

to serve it. So I do think that that's a

00:20:51

big accomplishment. I mean, look, we

00:20:53

knew that other cyber models were

00:20:55

coming. It wasn't just going to be

00:20:56

Mythos. In fact, within 6 months or so,

00:20:59

all the Frontier models are going to

00:21:00

have Mythos level cyber capability. But

00:21:03

it's impressive that OpenAI got this GPT

00:21:07

5.5 cyber out. so quickly and I think

00:21:11

5.5 might be the first cyber model that

00:21:14

cyber defenders actually get to use

00:21:17

because again I don't think they're as

00:21:18

compute constrained as anthropic is

00:21:20

>> and this is an incredible opportunity

00:21:22

you know for the crowd strikes and

00:21:24

PaloAlto networks of the world both of

00:21:26

which have been on the program they come

00:21:29

out and they start attacking this space

00:21:31

man you could really

00:21:33

see everything get tightened up and this

00:21:37

could be an incredible revenue stream

00:21:39

for everybody who's got whether it's

00:21:41

cursor claude or open eye or Gemini.

00:21:44

This is an amazing opportunity to

00:21:45

tighten up as much as it is to get

00:21:48

attacked.

00:21:48

>> Can I make a point about that? Cuz look,

00:21:50

there is so much fear right now almost

00:21:52

the level of panic about mythos. People

00:21:54

are treating it like a doomsday weapon

00:21:56

or something like that. It's not. is

00:21:58

simply that the frontier models have

00:22:00

reached the point where they're capable

00:22:02

of automating cyber activities just like

00:22:05

they're capable of automating coding.

00:22:08

But that means that a model could power

00:22:11

up a cyber attacker or cyber defender

00:22:13

the same way they can power up a coder

00:22:16

and allow them to discover a lot more

00:22:18

vulnerabilities. So there is obviously a

00:22:20

risk there. But I think it's important

00:22:22

to understand that Mythos or GPT 5.5, it

00:22:26

doesn't create the vulnerabilities. It

00:22:28

just discovers them. The bugs were

00:22:30

already in the code. They were sitting

00:22:31

there waiting for some hacker to

00:22:33

discover. If we can now use AI to find

00:22:37

these bugs in advance, these

00:22:39

vulnerabilities and patch them, then you

00:22:41

actually harden our infrastructure and

00:22:44

and you harden our security. I also

00:22:46

believe that this leap from let's call

00:22:49

it preAI cyber to post AAI cyber it's

00:22:52

going to be I think a big one-time

00:22:53

upgrade cycle because again you're going

00:22:55

to find all these dormant bugs and

00:22:57

vulnerabilities but I think that once we

00:23:00

get past that upgrade cycle you're going

00:23:02

to reach a new equilibrium between AI

00:23:04

powered cyber offense and AI powered

00:23:06

cyber defense it's going to become a lot

00:23:08

more normal it's not going to feel like

00:23:10

this huge disruption which is to say I

00:23:12

think you know people are treating this

00:23:14

as like some existential threat. I don't

00:23:17

think it is as long as everyone does

00:23:18

what they're supposed to do, which is

00:23:19

use the new capabilities to harden their

00:23:22

code bases and infrastructure and

00:23:24

security before the hackers get a hold

00:23:25

of these capabilities.

00:23:27

>> Yeah. And if Chimath, if you were to

00:23:29

look at this to build on Sax's point,

00:23:32

there are about 5 million or so security

00:23:34

experts in the world. We talked about

00:23:36

token cost. 40 hours of tokens just

00:23:39

pounding it, you know, a week. You could

00:23:42

create another five million for a

00:23:44

hundred dollars per chief security

00:23:47

officer per security expert. So it's the

00:23:50

volume of security expert agent saxs to

00:23:52

your point. Yeah. You could have 50 50

00:23:55

million of them 100 million of them.

00:23:57

They're not finding something unique.

00:23:59

They're just they never sleep. They're

00:24:01

relentless in their pursuit of these

00:24:03

problems. It's a really great point.

00:24:05

>> Just kind of just refine that. So yeah,

00:24:06

there's probably 5 million people in the

00:24:07

cyber industry, but there's probably

00:24:09

only a few thousand really elite

00:24:10

hackers.

00:24:11

>> Sure,

00:24:12

>> those hackers didn't have the time to go

00:24:14

after the entire surface area of every

00:24:17

possible attack vector out there. And so

00:24:19

if you train a model to do what they do,

00:24:22

obviously, like you said, it can operate

00:24:24

with a scale and speed that a human

00:24:26

hacker can't. So obviously, you know,

00:24:28

what you need to do is get these tools

00:24:30

in the hands of the white hats, let them

00:24:33

do the cyber attacks themselves to then

00:24:35

find the vulnerabilities and patch them

00:24:37

before the black hats get a hold of

00:24:39

these capabilities. But I think it's

00:24:41

just just one last point on this, I'll

00:24:42

stop. It's just it's really important to

00:24:44

understand that the Chinese models are

00:24:46

going to have these capabilities within

00:24:47

approximately 6 months.

00:24:49

>> Oh, they have them now in Deep Seek 4

00:24:50

for sure. They've got some level. Well,

00:24:52

no. Deepc4, I mean, Dec 4 is impressive

00:24:55

in a lot of ways, but its capability is

00:24:57

not at the frontier. It's maybe 80 80

00:25:00

85%. Let's call it the American

00:25:02

frontier.

00:25:02

>> Chimoff, you wanted to get in on this.

00:25:03

Let's get Chim in.

00:25:04

>> Two things. The reason that this is even

00:25:08

possible is because humans are

00:25:10

errorprone and when humans code, they

00:25:12

create holes. And so, humans exploiting

00:25:15

humans is where we've been for a long

00:25:18

time. Now we have computers exploiting

00:25:20

humans because the computers go and seek

00:25:21

out all these bugs that humans wrote.

00:25:25

In the next phase it'll be machines

00:25:27

versus machines.

00:25:29

And so I think the nature of cyber is

00:25:31

going to completely change. Probably in

00:25:32

the next five or six years there'll be

00:25:34

so much reason to rewrite all of the

00:25:38

software that runs the world.

00:25:41

In one part because you're going to be

00:25:42

asked to show more operating leverage

00:25:44

and revenue growth, but in another part

00:25:47

because everything else that was

00:25:48

handmade in the past is just

00:25:50

fundamentally insecure. Either way, all

00:25:52

roads will lead to all the operational

00:25:54

software that runs the world will get

00:25:56

rewritten. More and more of it will be

00:25:58

written by machines. More and more of it

00:26:00

will be impregnable as a result. But

00:26:02

then the cyber threat actually will only

00:26:04

increase because then you're going to

00:26:06

try to figure out how to use a machine

00:26:07

to inject something into another machine

00:26:09

so that some agentic loop inject some

00:26:11

malware or injects a bad token. And I

00:26:14

think that's a very complicated thing.

00:26:16

What I will tell you is

00:26:18

I'm not even sure if I'm allowed to say

00:26:19

this, but

00:26:22

a very good probably the best cyber

00:26:24

security company in the world run by one

00:26:26

of the very best CEOs in the world who

00:26:29

may or may not be speaking at liquidity

00:26:32

would tell you that they have penetrated

00:26:36

and can essentially

00:26:39

manipulate every model. Let me just let

00:26:42

me just say it roughly that way.

00:26:43

>> Okay, perfect. Yeah. And I uh at the

00:26:46

breakthrough prize uh which three of the

00:26:47

four of us were at I talked to George

00:26:49

Kurtz the other person you were kind of

00:26:51

describing was not that

00:26:52

>> sitting beside Nash. Yeah I'm talking

00:26:54

about

00:26:54

>> Nash and George are the two guys leading

00:26:56

this Palo Alto Networks Crowd Strike and

00:26:59

they understand the what George told me

00:27:01

was there is just a line out the door of

00:27:03

people who want this product or service.

00:27:06

And if you look at it, Freeberg, like

00:27:09

the murder rate, like we're sitting here

00:27:11

with the lowest murder rate in the

00:27:12

history of humanity. It has gone down

00:27:15

massively in our lifetimes, but

00:27:17

massively over the arc of history. I

00:27:18

think that's what's going to happen with

00:27:19

cyber. There is only so many attack

00:27:21

vectors, and the remaining attack

00:27:23

vectors are just going to be human

00:27:24

factors, right, Freeberg? That's always

00:27:26

been the case. And as we make the

00:27:28

software more resilient, then the the

00:27:31

weak link is, you know, the secretary

00:27:33

who puts her post-it note, you know,

00:27:36

with the password there or the

00:27:38

accountant who, you know, uses their

00:27:40

dog's name plus one, two, three for

00:27:42

their password, right? That's the the

00:27:44

historical one. Okay, let's any anything

00:27:46

you want to add, Free Bird, as we wrap

00:27:48

there? Oh, that's

00:27:49

>> Why is your bed so messy, by the way?

00:27:50

Why can't you just ask the room service

00:27:52

to come in?

00:27:52

>> Listen, I'll tell I can tell you what

00:27:54

happened. Listen, I'm here in Atlanta.

00:27:55

And also, why don't you have a suite

00:27:57

like where there's two rooms? Like, is

00:27:58

it just one room? This hotel only has

00:27:59

one.

00:28:00

>> It's just one room. Yes.

00:28:01

>> You know, either you're cheap or poor.

00:28:03

Which one is it? I'm cheap. Here's I'll

00:28:06

tell you what. Here's a situation. I'm

00:28:08

in Atlanta for the Knicks game tonight.

00:28:09

>> You're in one room.

00:28:10

>> Here's what I do. I just want to explain

00:28:12

to you value for value. Some people

00:28:13

spend their money on private jets and

00:28:15

they spend $30,000 flying to Atlanta. I

00:28:18

spend 30,000 on courtside seats. I don't

00:28:20

want the suite. I want to put it into

00:28:21

the seat side.

00:28:23

>> You can do both. I guess I could do

00:28:24

both, too. I don't I'm I'm in the

00:28:26

process of becoming

00:28:28

>> I don't understand

00:28:29

>> of embracing my richness. Okay.

00:28:31

>> If you've already convinced yourself

00:28:32

that you should spend $30,000 for

00:28:35

courtside tickets, which I think is

00:28:37

outrageous, but okay. You've already

00:28:38

convinced yourself like 10k each, but

00:28:40

yeah. Yeah.

00:28:40

>> A hotel room that has two rooms. Okay.

00:28:44

>> Probably cost 15% more than what you're

00:28:46

paying.

00:28:46

>> It's 2x, but yes, you're right.

00:28:48

>> I'll get the I'll get the hotel room. 20

00:28:50

or 20% more, but you room like 200 bucks

00:28:53

a night. So you pay 400 a night. You get

00:28:54

another hotel.

00:28:55

>> I mean it's it's Atlanta. The most I'm

00:28:57

in the best hotel the most expensive

00:28:58

hotel is 500 a night in Atlanta. It's no

00:29:00

big deal. But everything's sold out

00:29:02

because all the Knicks people are coming

00:29:03

here.

00:29:03

>> So you're selling me double that would

00:29:04

have been a thousand and you couldn't

00:29:05

spend,000.

00:29:06

>> Everything is sold out because the

00:29:08

Knicks are here.

00:29:08

>> So we have to look at your dirty beds.

00:29:10

>> It's gross.

00:29:11

>> The bed's not that dirty. Come on. Just

00:29:13

deal with it. Okay. Take it out and

00:29:14

post.

00:29:15

>> I have a private jet story about flying

00:29:17

to Atlanta.

00:29:20

>> You reminded me. Okay. So yeah, there

00:29:22

was some event there. So I I flew my

00:29:23

team there, you know, there's a few

00:29:26

people on my plane and it's kind of a

00:29:28

long flight. Was it like 4 hours or

00:29:29

something

00:29:30

>> from the back? Yeah.

00:29:31

>> Yeah. So I went in the back to to sleep.

00:29:34

Well, first, you know, we we started the

00:29:35

flight and I had a few bottles of Papy

00:29:37

Van Winkle on on the plane. And so we

00:29:40

started off with like a drink and then I

00:29:42

went in the back and and fell asleep and

00:29:43

I woke up basically when we landed.

00:29:45

>> So I come out and like all three bottles

00:29:47

are basically cashed of like Happy Van

00:29:50

Wink.

00:29:50

>> Oops. Those were like two grand a

00:29:52

bottle.

00:29:53

>> No, no, they're more. These were like

00:29:54

antique bottles. Like one of them was

00:29:56

>> I have one of those from your plane. I

00:29:57

have one of those from the old Falcon.

00:29:58

Yeah.

00:29:59

>> Yeah. They were like these vintage

00:30:01

>> $4,000. I remember. Yeah.

00:30:03

>> Anyway, you can't even find this [ __ ]

00:30:04

anymore. So these guys, they asked me

00:30:07

like when we land like, "Hey, Sax, how

00:30:09

much did it cost for you to fly us to

00:30:12

this event?" And I said, "Well, about

00:30:14

$8,000 in jet fuel and about $12,000 of

00:30:17

Happy Van Winkle."

00:30:20

Well, you gota you got to fuel the the

00:30:22

vibes as well as the plane. It's uh

00:30:25

>> Is Atlanta nice? I've never really

00:30:27

>> Do those people still work for you or

00:30:28

are they are they uh

00:30:31

>> they called in Atlanta? Um is Atlanta

00:30:33

nice? Listen, last year I went to the

00:30:34

Detroit games and that city was on the

00:30:36

rebound. Atlanta has an incredible

00:30:37

opportunity to rebound. I'll say it that

00:30:40

way. There's a great opportunity for

00:30:42

them to upgrade the city. I I went to

00:30:44

Waffle House at midnight last night.

00:30:46

There was no shootings. Okay, let's keep

00:30:47

moving. By the way, do you get royalty

00:30:49

points at the Best Western Atlanta or

00:30:51

No,

00:30:52

>> I get double points because I use my

00:30:54

Best Western uh Visa card. Yeah, it's

00:30:56

everywhere you want it to be. All right.

00:30:59

Use the promo code Jcal and get a

00:31:01

thousand extra points. In other Open AI

00:31:04

news, Musk versus Alman, the trial of

00:31:08

the century or maybe the decade has

00:31:11

started. Elon is of course accusing Open

00:31:13

AI of breach of charitable trust, unjust

00:31:15

enrichment. He's accusing Open AAI of

00:31:18

essentially flipping a nonprofit into a

00:31:21

for-profit. He's seeking 150 billion in

00:31:23

damages that they revert back to a

00:31:25

nonprofit that Alman and Brockman be

00:31:28

removed. And there were some fireworks

00:31:30

between Elon and the Open AI lawyers.

00:31:32

Elon kind of leveled up the discussion.

00:31:34

He said, quote, "If we make it okay to

00:31:37

loot a charity, the entire foundation of

00:31:39

charitable giving in America will be

00:31:42

destroyed. That's my concern."

00:31:44

Obviously, there's a ton of interesting

00:31:47

nuances here. Specifically, Greg

00:31:49

Brockman keeping a diary where he was

00:31:52

journal maxing his plans uh like a Bond

00:31:55

villain here. And uh the excerpts from

00:31:59

his diary include conclusion, we truly

00:32:02

want the BC Corp. The true answer is

00:32:04

that we want Elon out. If 3 months later

00:32:07

we're doing BCorp, then it was a lie.

00:32:09

Can't see us turning this into a

00:32:11

forprofit without a nasty fight. I'm

00:32:13

just thinking about the office and we're

00:32:15

in the office and this story will

00:32:16

correctly be that we weren't honest with

00:32:19

him. In the end, it's still about

00:32:20

wanting a for-profit just without him.

00:32:22

yada yada yada. Freeberg, your thoughts

00:32:24

on this case? Is Elon going to win? I

00:32:27

just don't know why Greg Brockman's got

00:32:29

a freaking diary where he's like

00:32:31

literally documenting. I mean, I love

00:32:33

the guy, but what the [ __ ] is he

00:32:34

thinking? Like, you're just sitting here

00:32:36

at home and like, let me write about the

00:32:38

the crime I'm committing or let me write

00:32:40

like and let me record it. And by the

00:32:42

way, let me never delete it. I don't

00:32:44

understand this.

00:32:45

>> It's not just journal maxing. It's

00:32:47

discovery maxing.

00:32:49

>> It's smoking gun maxing.

00:32:51

>> I don't get it. I don't get it, man.

00:32:54

>> I mean, do you guys remember from the

00:32:57

wire in that scene where the guy's like,

00:33:00

"Is you taking notes on a criminal

00:33:02

conspiracy?"

00:33:04

He's got everybody in the room. Can we

00:33:06

play that clip? It's like,

00:33:08

>> "What are you doing, Greg? [ __ ] is you

00:33:10

taking notes on a criminal conspiracy?

00:33:14

What the [ __ ] is you thinking, man?

00:33:16

>> If you're going to commit a crime, you

00:33:18

do not write down the date and time of

00:33:21

the crime in your journal.

00:33:23

>> Well, look, we don't know it's a crime.

00:33:24

Let's not.

00:33:25

>> Okay, sure.

00:33:27

>> A crime, but yes, you keeping

00:33:30

shenanigans. Jamat, do you keep a diary?

00:33:32

>> What do you think, Juel? Do you keep a

00:33:34

diary?

00:33:35

>> I I believe ruminate. No, I'll tell you

00:33:38

right now, rumination is the path to

00:33:41

unhappiness. Nobody gives a [ __ ] about

00:33:43

your feelings. Writing your feelings

00:33:45

down is only going to make you

00:33:46

miserable. Talking to your spouse about

00:33:48

your feelings.

00:33:50

>> Just go to a beautiful dinner, sit

00:33:52

courtside at the next, and do what I've

00:33:54

been doing for 30 years.

00:33:56

>> [ __ ] maxing.

00:33:57

>> [ __ ] maxing. And the register goes up.

00:34:00

All you have to do is work. Start new

00:34:02

projects. Nine out of 10 foul. Place

00:34:04

nine out of 10 bets. One wins and you're

00:34:06

golden. Go sit courtside at the Knicks

00:34:08

game.

00:34:09

>> Keep going. Life's too short.

00:34:10

>> And just keep moving forward. Don't

00:34:12

write anything down. Period. Full stop.

00:34:15

>> It's good advice. Yeah, I just The

00:34:17

biggest surprise to me was this guy's

00:34:18

got a diary. I just I don't know anyone

00:34:20

that has a diary. I've never heard of

00:34:21

this. So anyway, that was shocking.

00:34:24

Besides that, I have no view on what's

00:34:26

going to happen with the case or what

00:34:27

the judge will do.

00:34:28

>> I have no comment on the case either. I

00:34:30

think it's weird that Poly Market hasn't

00:34:33

budged even as all of this discovery has

00:34:35

been published. It's effectively at 42

00:34:37

or 43% that Elon wins. So, one of the

00:34:41

friends in our group chat said what may

00:34:44

just happen is that Elon technically

00:34:45

wins and he's just credited back the $40

00:34:48

million. And so, maybe that's what this

00:34:51

poll is front running.

00:34:54

But on a totally separate note, I think

00:34:56

Jason, I know you say it as a joke, but

00:34:59

this idea of just keep moving forward,

00:35:02

don't ruminate, I think is very good

00:35:03

general life advice for everybody to

00:35:06

follow.

00:35:06

>> The modern-day therapy industrial

00:35:09

complex and the medication industrial

00:35:11

complex, I believe, is

00:35:14

>> around rumination. Well, it does pivot

00:35:15

around rumination.

00:35:16

>> Yes.

00:35:17

>> That is the gateway drug to all these

00:35:18

things.

00:35:19

>> Yep. Talk about your problems.

00:35:21

You know, when these people go to

00:35:22

therapy, you ever hear these people?

00:35:23

Howard Stern's like, "I've been in

00:35:24

therapy with the same person 2 or three

00:35:25

days a week for 40 years." I'm like,

00:35:27

"Okay, what's the incentive for the

00:35:28

therapist to stop charging you $1,200 an

00:35:31

hour? There is none." Then they lose a

00:35:33

revenue stream. They lose a customer.

00:35:34

It's all a giant [ __ ] fraud. Facts.

00:35:37

Uh, in terms of this case,

00:35:38

>> I wouldn't go that far. I do think that

00:35:40

there's a lot of value in kind of

00:35:42

untying some of these Gordian knots that

00:35:44

people have because of how they grew up.

00:35:47

But there's a difference between that

00:35:49

and being specific and just randomly

00:35:51

ruminating cuz I don't think there's a

00:35:53

lot of productive.

00:35:53

>> You've got an acute issue like in trauma

00:35:57

in your life. Yeah, sure. Unpack it,

00:35:59

figure it out. I'm just talking about

00:36:00

this neverending self-improvement,

00:36:03

you know, ruminating thing. Uh but

00:36:05

getting back on topic here, Saxs,

00:36:09

what's the And we're we're talking about

00:36:11

a jury, I believe, in Oakland.

00:36:13

>> No, but it's a bench trial. This is

00:36:14

important. It's a bench trial where the

00:36:16

jury is advisory in capacity,

00:36:19

>> but ultimately that judge, she will make

00:36:21

the final call

00:36:22

>> and she'll do the damages. And so, is

00:36:25

this a case sacks of like we've got a

00:36:28

Bay Area jury judge and we've got Elon

00:36:33

who's considered, you know, a bit

00:36:35

right-wing and people don't all agree in

00:36:37

that area in terms of his politics. And

00:36:39

then you have this Sam Alman New Yorker

00:36:42

story and people finding out that so

00:36:45

many different people feel they got

00:36:47

screwed by him. You put these two things

00:36:48

together, it's impossible to handicap

00:36:50

where this turns out. Sachs, your

00:36:52

thoughts?

00:36:53

>> Well, yeah, I don't think this is about

00:36:55

politics. I mean, I guess you could

00:36:58

argue that what Elon is seeking, which

00:37:01

is to protect the charity, is if

00:37:03

anything a left-coded sort of principle,

00:37:06

although I don't really think it's left

00:37:07

versus right. Look, I don't want to take

00:37:09

sides on this trial. I'm just watching

00:37:11

like everyone else. The last time I

00:37:12

weighed in on some Elon litigation, I

00:37:16

got deposed for six hours. Remember

00:37:18

that? Cuz they just assume that somehow

00:37:20

I know something,

00:37:21

>> right?

00:37:21

>> I've never talked to Elon about the

00:37:22

case. I don't know anything about it.

00:37:24

>> Yeah.

00:37:25

>> I'm going to see what happens like

00:37:26

everyone else. Now, one thing I I will

00:37:29

say having just read some of the

00:37:31

coverage is that apparently the company

00:37:35

at some point did offer Elon shares in

00:37:38

the company, but he thought that there

00:37:41

was something kind of icky about it. Do

00:37:43

you remember this that

00:37:44

>> Yes. Because at at one point I said on

00:37:46

our show when this dispute started

00:37:49

happening but before it became a court

00:37:50

case I said look if Open AAI at a

00:37:53

certain point decided they had the wrong

00:37:54

structure they should just gone and done

00:37:56

a make right with Elon and he should

00:37:59

have been a shareholder on the cap

00:38:00

table. What I didn't know is that

00:38:02

apparently they did try to do something

00:38:04

like that but Elon turned it down

00:38:06

because he did want the entity to remain

00:38:10

a charitable entity. In other

00:38:13

>> had a principled view of it according to

00:38:15

the reports and was like no we're trying

00:38:17

to save humanity and then you're giving

00:38:20

this keys to the kingdom to Microsoft

00:38:21

that's all come out

00:38:24

>> and I I also have not talked to Elon

00:38:26

about any of this but my guess is like

00:38:30

most of these things there'll be some

00:38:32

sort of settlement or something here but

00:38:34

maybe he takes it to the mat who knows

00:38:36

Judge Rogers who's doing this

00:38:38

61-year-old Obama appointee politics has

00:38:42

played a role. Saxs, they have had to

00:38:44

tell the jury like however you feel

00:38:45

about these individuals politically,

00:38:47

whatever, please put that aside. But of

00:38:49

note is that she oversaw the Epic Games

00:38:51

versus Apple trial over App Store

00:38:54

exclusively ruled in favor of Apple with

00:38:56

some caveats um that they don't have a

00:38:59

monopoly, etc., etc. So, this is going

00:39:02

to be a really interesting one. And I

00:39:04

think the worst case scenario is open AI

00:39:07

for for OpenAI is they have to unravel

00:39:09

this somehow and that would delay the

00:39:12

IPO. That would cause chaos in

00:39:14

shareholders and I guess the best case

00:39:16

is some sort of settlement. And if Elon

00:39:19

put the first 40 or $50 million in, he's

00:39:21

he's due 10 20 30% of the company after

00:39:24

dilution.

00:39:26

All right, let's keep moving through the

00:39:27

docket. Lots more to discuss and uh good

00:39:30

luck to everybody in their lawsuit and

00:39:31

those of you betting on market all-in

00:39:34

summit selling up fast. Our fifth

00:39:37

edition Los Angeles September 13th to

00:39:39

15th. Go to allin.com/events

00:39:41

and uh speakers are going to be top

00:39:43

tier. Apparently Freeberg is having this

00:39:47

as his major creative outlet. I heard

00:39:49

some back channel chimoff today that

00:39:51

he's going to be doing Broadway musical

00:39:55

uh illusionist. tap. I got a tap dancing

00:39:58

situation.

00:39:59

>> He's literally going fullon entertainer.

00:40:02

This is going to be vaudeville sachs

00:40:05

wrapped up. He's just going to take it

00:40:07

to a whole new level. Musical numbers

00:40:10

>> like Nathan Lane.

00:40:12

>> I think if you're coding that it's going

00:40:15

to be his big gay summit. Yes, it could

00:40:17

be a big gay summit.

00:40:19

>> Might be our last year in LA, guys.

00:40:22

>> Why?

00:40:23

>> Not might be.

00:40:24

>> Might be. Oh, everybody wants to go to

00:40:25

Vegas apparently.

00:40:28

Those bones, baby. Can you imagine

00:40:31

leaving the summit for lunch and going

00:40:33

and playing crabs? Jimoth, we get a

00:40:35

fresh. Yes, I can. Yes, I can imagine.

00:40:39

>> I got some bricks. Oh, I got some bricks

00:40:41

right here. Let's go. Yum, yum.

00:40:44

>> That way Sachs can come.

00:40:46

>> Yeah, Sax is like, I'm never setting

00:40:48

foot in California, but I will.

00:40:52

You know, we're doing a couple live

00:40:53

events. Are you coming to them?

00:40:54

>> Liquidity or something different?

00:40:56

>> Liquidity. And then there's the the

00:40:57

all-in summit happens in September.

00:40:59

>> Yeah, I'm going to do those, too.

00:41:00

>> All right. Big tech smashed their

00:41:02

earnings on Thursday. Google, Microsoft,

00:41:05

Amazon, and Meta all reported. I don't

00:41:07

know why they do this on the same night,

00:41:09

folks, but they do. And performance was

00:41:11

spectacular. It was great. However, the

00:41:14

capex announcements were really the

00:41:19

story here. Let me just cue this up and

00:41:23

show the chart.

00:41:25

$725 billion in capex guidance in 2026

00:41:30

from but four companies. Amazon,

00:41:32

Microsoft, Google, and Meta. Amazon

00:41:34

leading the pack with 200 billion, 190

00:41:37

billion each for Microsoft and Google,

00:41:38

145 billion for Meta. You add Grock, you

00:41:42

add OpenAI and some other players to

00:41:45

these plans. And we haven't heard from

00:41:46

the new Apple CEO yet, but he's going to

00:41:48

be taking over. And he's going to have

00:41:50

some plans here. I'm sure we are going

00:41:53

to see the large a trillion dollars a

00:41:55

trillion dollars in buildout over the

00:41:57

next year. I don't know if this is even

00:41:58

possible, but this is all being driven

00:42:02

by AI and cloud computing. Google Cloud,

00:42:06

which includes the Google Suite, that

00:42:08

grew 63% year-onear.

00:42:11

Let that number sink in. 63% on 20

00:42:14

billion in revenue. That's in a quarter.

00:42:16

Microsoft cloud, that includes Azure,

00:42:18

Windows Server, SQL Server, they bundled

00:42:20

some things together there to get the

00:42:22

number to go up. Uh that grew 30% on

00:42:25

34.7 billion in revenue. Amazon Web

00:42:28

Services, the original cloud, that grew

00:42:31

28% on 37.6 billion in revenue. That's a

00:42:34

bit of a pure play. Just counts Amazon's

00:42:37

web services. Obviously, these are all

00:42:39

moving to NeoClouds. These are all

00:42:41

serving AI jobs and tokens now. They

00:42:44

have a massive customer base and the

00:42:46

customers from the smallest startups all

00:42:48

the way to the biggest frontier models

00:42:49

cannot get enough compute and it is

00:42:52

going to the bottom line. But this is

00:42:54

shrinking Chimath cash flow massively.

00:42:57

These were free cash flow machines, the

00:43:00

largest money printing machines in the

00:43:02

history of humanity. But they are giving

00:43:05

up on free cash flow, stock buybacks and

00:43:07

dividends and the focus on those three

00:43:11

to invest in infrastructure. Amazon's

00:43:13

free cash flow down 97%

00:43:16

Google, Microsoft and Meta down 12, 12

00:43:18

and 8% respectively. your thoughts on

00:43:21

this free cash flow, the end of the free

00:43:23

cash flow deluge and the massive massive

00:43:27

investment we're seeing in capex.

00:43:30

I think we're seeing a very important

00:43:33

structural shift in the capital markets.

00:43:36

I think the last 20 or 30 years, well 20

00:43:39

years, it's been that the mag 7 just

00:43:42

kind of ran away with it. that these big

00:43:45

companies got bigger and bigger and it

00:43:47

absorbed all of these investment dollars

00:43:49

and the biggest reason was that it had

00:43:52

these very assetike business models,

00:43:55

right? You just built some more software

00:43:56

and it just has all this leverage and it

00:43:58

all just kind of worked except maybe for

00:44:00

Amazon cuz they needed physical

00:44:01

infrastructure for warehouses and

00:44:03

delivery and whatnot. But by and large

00:44:04

it was a very asset light investment

00:44:07

cycle. Now all of a sudden the pendulum

00:44:09

is swinging violently in the other

00:44:11

direction. And there's something that I

00:44:13

think people misunderstand which is as

00:44:15

it moves back to these asset heavy

00:44:18

infrastructure investments.

00:44:22

The hyperscalers are signing checks that

00:44:25

I mean I suspect their body can cash but

00:44:27

there's a world in which they can't.

00:44:29

I'll give you an example. You know when

00:44:31

Microsoft convinced the owners of three

00:44:33

Mile Island to turn their

00:44:37

>> nuclear site back on?

00:44:38

>> Yeah.

00:44:39

>> Do you know what their Ford purchase

00:44:41

agreement was? It was for more than 2x

00:44:43

the prevailing spot rate for energy.

00:44:45

More than 2x. The problem is that's not

00:44:47

for an enormous percentage of their

00:44:50

overall energy needs.

00:44:53

So if you play that out and you think

00:44:56

these five or six companies all of a

00:44:58

sudden are not just spending Jason 700

00:45:01

billion a year of capex which they are

00:45:05

but then from an operating cash flow

00:45:07

they're going to be spending 2x the

00:45:09

prevailing spot rate because they just

00:45:11

want guaranteed demand into the future.

00:45:15

Where's all this cash going to go? It's

00:45:18

not going to go

00:45:20

to the shareholder and it's not going to

00:45:22

stay on the balance sheet. These

00:45:24

companies will now get levered. They're

00:45:26

going to get highly sophisticated around

00:45:29

the financial engineering. They'll have

00:45:30

more debt. They'll have all kinds of

00:45:33

different vehicles and term loans and

00:45:35

revolvers and all of this stuff.

00:45:37

And so, they're going to look like this

00:45:39

big bulky industrial business in five

00:45:41

years. And I'm not sure that there's a

00:45:44

good valuation case to be made at that

00:45:46

point.

00:45:47

And so I think it may be simpler and

00:45:50

this is what I tweeted to just follow

00:45:52

the dollars like a trillion dollars a

00:45:55

year going out of the hyperscalers.

00:45:57

Where is it going? Just follow those

00:45:59

dollars and buy those companies because

00:46:00

those companies are already underpriced.

00:46:03

This is uh obviously reminiscent of

00:46:05

something we all experienced. Uh Nick,

00:46:07

can you pull up the Cisco chart I just

00:46:08

sent you and put it at max? uh we had a

00:46:11

massive buildout of the infrastructure

00:46:14

of the internet in the late 1990s and

00:46:17

into 2000. And what that caused was a

00:46:20

lot of aggressive companies to do

00:46:21

massive amounts of spending, a lot of

00:46:23

retail investors to embrace these stocks

00:46:25

like we're seeing with people trying to

00:46:28

get into these private companies and

00:46:30

saxs. Look at the 2000 peak of Cisco.

00:46:33

This is the most extraordinary chart

00:46:35

ever. It took them 25 years to get back

00:46:37

to that peak and uh they had a lost two

00:46:41

decades and we had a massive amount of

00:46:44

fiber that wound up getting bought. We

00:46:45

talked about that a couple years ago on

00:46:47

the program. But there's something for

00:46:48

you to build off of here when you look

00:46:50

at this massive infrastructure. You

00:46:52

think it's going to be Cisco systems all

00:46:54

over again, World Warcom, etc.?

00:46:55

>> No, I really don't. The issue we had in

00:46:58

2000 was dark fiber. You had all this

00:47:00

infrastructure being built out and it

00:47:02

wasn't being used. There's no dark GPUs

00:47:05

today as you know Brad Gersonner likes

00:47:07

to say. So what's driving the capex now

00:47:11

is the voracious demand for compute for

00:47:15

tokens and the demand is now pulling

00:47:19

forward this additional um investment in

00:47:22

infrastructure. So I think what's

00:47:25

happened here is that the bull thesis

00:47:26

for AI just got validated in a single

00:47:30

afternoon. I mean again you got

00:47:31

Microsoft Azure, Google Cloud, Amazon

00:47:34

AWS, Meta, they're all basically

00:47:37

exceeding expectations, exceeding

00:47:39

guidance in terms of where their cloud

00:47:42

revenue would be and therefore how much

00:47:44

they're going to reinvest in capex this

00:47:47

year. I think we were supposed to have

00:47:48

660 billion of hyperscaler capex up from

00:47:52

350 last year. I think there's now the

00:47:54

new estimate is it's going to be over

00:47:55

700. So this is you know again it's more

00:47:58

than 2% of GDP. This is a huge tailwind

00:48:00

to GDP. There's another article saying

00:48:02

that I think in the last quarter

00:48:05

AI was 75% of GDP growth. And by the

00:48:08

way, this is just the capex part. This

00:48:10

is the physical infrastructure. This is

00:48:12

not the economic impact of the tokens

00:48:14

that are generated inside the token

00:48:16

factory. This is the building of the

00:48:18

factories. How do those tokens get used?

00:48:20

like we're seeing they're being used not

00:48:23

just to do research or to answer

00:48:25

questions but to create code. And so

00:48:29

we're seeing this explosion of

00:48:31

productivity in software development.

00:48:33

And we're seeing an explosion of bespoke

00:48:36

software being created and that's going

00:48:38

to accelerate every part of the economy.

00:48:40

Every business that now wants to get

00:48:42

code will be able to get code for the

00:48:44

first time. Before they couldn't even

00:48:45

hire the engineers, they needed to

00:48:47

generate it. Now they will be able to.

00:48:49

So that is a huge unlock of productivity

00:48:52

across the economy. Then you're getting

00:48:54

into these new use cases like the the

00:48:56

co-working use cases and agents, right?

00:48:59

So the the workflow automations that are

00:49:01

happening, it's still early. I don't

00:49:04

believe that this is going to replace

00:49:05

humans. We had that um in the past week,

00:49:06

we had that crazy case of an agent

00:49:09

deleting a production database in 9

00:49:11

seconds because because of a bug. Look,

00:49:13

what that said to me is that

00:49:16

>> it's not that agents aren't valuable.

00:49:18

They are valuable, but they have to be

00:49:19

supervised. You know, this idea that

00:49:21

you're just going to be able to like

00:49:22

automate all the jobs away. It is a

00:49:24

massive amount of handwaving over the

00:49:27

real technical problems and issues. The

00:49:29

agents have to be supervised. Someone

00:49:31

has to be accountable. It's not going to

00:49:33

be the CEO. The CEO doesn't want to be

00:49:35

accountable for thousands of agents. You

00:49:38

need people

00:49:38

>> despite what Jack had block said.

00:49:40

>> Yeah. Thousand direct reports is a great

00:49:43

like goal, but it's not realistic. Yeah,

00:49:46

>> you need IT people who are savvy who can

00:49:49

supervise this and make sure it's

00:49:50

working. They have to be accountable to

00:49:51

the CEO. Someone has to drive the

00:49:53

productivity. It's like Bology always

00:49:56

said, AI is not end to end is middle to

00:49:58

middle. You have to have someone to do

00:49:59

the prompting and you have to have

00:50:00

someone to do the validating and I would

00:50:02

add the supervision and accountability.

00:50:04

So anyway, the larger point though is

00:50:06

I'm speaking to the fact that I don't

00:50:08

think there's going to be this huge job

00:50:10

loss associated with this productivity

00:50:12

boom that we're going to get. And in

00:50:13

fact, I think what's actually happening

00:50:15

now is that AI is becoming synonymous

00:50:18

with the American economy. I mean, the

00:50:20

fact that it's generating 75% of GDP,

00:50:23

you have this capex explosion, this

00:50:26

energy explosion that feeds it, and

00:50:28

again, just the beginning of the

00:50:31

applications that are being unleashed by

00:50:33

these new token factories. I think it's

00:50:35

all a very, very positive thing. and all

00:50:38

these doomers who are trying to throw a

00:50:40

wet blanket on it or constantly scaring

00:50:43

the daylights out of people. I mean,

00:50:45

what do they want the American economy

00:50:47

to do? Just to stop I mean, they just

00:50:49

don't want any progress. I mean, like

00:50:51

again, you know, when you talk about

00:50:52

stopping AI or halting AI progress? What

00:50:55

you're really doing is stopping the

00:50:57

American economy now. You're basically

00:50:59

saying you don't want economic growth.

00:51:01

AI is now synonymous with the growth of

00:51:04

the American economy. And if there's no

00:51:06

economic growth, there's not gonna be

00:51:07

money to pay for all the social

00:51:08

programs. There's not gonna be money to

00:51:09

pay down the national debt. There's not

00:51:11

gonna be money to basically build up our

00:51:13

national defense. All these things we

00:51:14

want to spend money on. We have to have

00:51:16

a vibrant economy. And that is now

00:51:19

synonymous with AI. So I know that AI

00:51:21

may not be popular. I see those polls.

00:51:23

But having a strong economy is popular.

00:51:26

And I believe that those things are now

00:51:28

synonymous. It's almost like there was

00:51:30

some architect or ZAR who set up the

00:51:33

chessboard in the first year of this to

00:51:35

make sure that it was ultra competitive.

00:51:38

>> President Trump set the table on this.

00:51:39

>> Absolutely. With some good advice, I

00:51:41

think. Maybe.

00:51:42

>> Freeberg, your thoughts?

00:51:43

>> It's always good to have good advisors.

00:51:45

>> Always good to have good advisors.

00:51:46

Absolutely. Absolutely.

00:51:47

>> No, but look, I've said it before. The

00:51:49

president just wants America to win.

00:51:50

>> Literally, there are people who if we

00:51:52

were looking at this, you know, I don't

00:51:54

know, a hundred years ago, it'd be like

00:51:56

people were like, "Yeah, you know what?

00:51:57

we shouldn't build the highway system or

00:51:58

we half built the highway system. Let's

00:52:00

stop let's stop building the highways.

00:52:02

>> No, the highway system was funded by the

00:52:04

federal government. There was no

00:52:05

competition. It was the most expensive

00:52:07

on a on a inflationadjusted basis. I

00:52:10

think it was the most expensive project

00:52:11

in US history.

00:52:13

>> Yeah. And the railroads before that like

00:52:15

you can't stop these things. They have

00:52:17

to keep going. It's interesting point

00:52:20

you know there is so much demand for the

00:52:22

resource of tokens of intelligence

00:52:24

freeberg and it's quite different than

00:52:26

the fiber situation as Sax correctly

00:52:28

points out where we built all this but

00:52:31

we didn't actually have an application

00:52:32

here the application is pretty um pretty

00:52:36

wellnown and you've got a large number

00:52:38

of people in businesses who are trying

00:52:40

to vibe code their way to success trying

00:52:43

to push this stuff and we had an

00:52:45

interesting story referenced earlier in

00:52:47

the show

00:52:48

where

00:52:50

uh Claude ate somebody's homework. This

00:52:52

is the nightmare of all nightmares.

00:52:55

Somebody was vibe coding. Uh it was the

00:52:57

founder of Pocket OS. Apparently, they

00:52:59

make software for rental car companies.

00:53:00

He was using Opus 4.6 through Cursor's

00:53:03

AI platform, their coding platform, and

00:53:07

uh you know, which is like the most

00:53:09

expensive tier. Uh and he said he

00:53:12

configured it with enough safety rules,

00:53:13

but the agent was working on a routine

00:53:16

task. They saw some sort of credentiing

00:53:18

mismatch and they decided to fix the

00:53:20

mismatch by deleting a railway volume

00:53:22

without user confirmation and uh they

00:53:25

pushed the code from a repo to a live

00:53:27

app and they deleted everything

00:53:28

including the backups. Literally a scene

00:53:32

from Silicon Valley's HBO clip of Son of

00:53:36

Anton. Hilarious.

00:53:37

>> You gave your AI permission to overwrite

00:53:39

code in the internal file system. Were

00:53:42

you going to tell me about this? No, I

00:53:44

thought that was the company policy

00:53:46

these days.

00:53:47

>> Okay, well, your AI just failed

00:53:50

epically.

00:53:51

>> That's unclear.

00:53:53

>> It's possible the Son of Anton decided

00:53:55

that the most efficient way to get rid

00:53:56

of all the bugs was to get rid of all

00:53:58

the software, which is technically and

00:54:01

statistically correct. But artificial

00:54:03

neural nets are sort of a black box. So,

00:54:05

we'll never know for sure.

00:54:06

>> How did they get that so right, Zach?

00:54:08

Five or six years ago, art and neural

00:54:10

networks are a black box. So, I guess

00:54:11

we'll never know. But technically, it

00:54:14

was correct. Freeberg, when you blow up

00:54:16

a hollow system with your vibe coding,

00:54:19

which you were absolutely showing off in

00:54:21

front of Jensen a couple of weeks ago

00:54:23

about how much code you're pushing, who

00:54:24

are you going to blame? You going to

00:54:26

take responsibility yourself? Are you

00:54:27

going to blame Cla Claude or Kurser? Who

00:54:30

are you going to blame when you blow up

00:54:32

the entire stack over at Ohio?

00:54:36

>> Who you blame?

00:54:37

>> Yeah, I'll blame Dario.

00:54:38

>> You blame Dario. Okay, that's what I

00:54:40

thought. That's a correct answer.

00:54:41

Correct answer. Blame Daario. He's the

00:54:42

one who says it's a doomsday machine.

00:54:44

Uh, come on the prodio.

00:54:47

17th invitio.

00:54:50

>> I mean, I've invited the guy like 17

00:54:52

times. He is totally going to me. He

00:54:54

wants nothing to do with this podcast.

00:54:57

>> Actually, let me speak to that. So, I

00:54:59

think I think that um there's maybe a

00:55:02

misperception that this error occurred

00:55:05

because of, you know, quote unquote AI

00:55:07

scheming,

00:55:09

>> like kind of in that video that the AI

00:55:12

decided that the best way to get rid of

00:55:13

bugs is to basically eliminate the

00:55:14

codebase. This is kind of like the, you

00:55:16

know, AI is going to turn the world into

00:55:18

paper clips type thing where somehow

00:55:19

it'll like miss scheme. That's not

00:55:21

really what happened here. This is a

00:55:22

case of just a of old-fashioned bugs

00:55:26

occurring at an edge case. You know,

00:55:28

you've got the fact that this API was

00:55:30

not designed for permissioned usage.

00:55:34

You've got the fact that a credential

00:55:36

was left kind of lying around. Probably

00:55:38

it should not be. There's kind of like a

00:55:40

perfect storm that caused the AI to do

00:55:42

something or the agent to do something

00:55:43

that didn't quite understand it was what

00:55:44

it was doing. I think that if there is a

00:55:48

systemic problem here rather than just

00:55:50

kind of a like a random edge case is

00:55:53

that AI still doesn't know what it

00:55:58

doesn't know. You know, like a human

00:56:00

would stop before deleting a production

00:56:03

database and just say, "Oh, I'm about to

00:56:04

do something like really serious, really

00:56:06

destructive. Am I sure I want to do

00:56:08

this?" You know, and a human would have

00:56:10

stopped and said, "Oh, wait a second.

00:56:11

like I need to be more confident in what

00:56:13

I'm doing before I take that action. And

00:56:16

AI still has this issue where again it

00:56:18

can be kind of overcon. This is where

00:56:19

like the hallucinations come from is it

00:56:22

doesn't know when it should have a low

00:56:24

confidence in its output, right? But

00:56:26

this is why it has to be supervised. You

00:56:29

know, the longer the time horizon for a

00:56:31

task, the more likely it is to go off

00:56:34

the rails.

00:56:35

>> And a drift. Exactly. And this is why I

00:56:38

think people are starting to realize

00:56:40

that this idea of eliminating all

00:56:41

software developers was the peak of

00:56:44

inflated expectations. Yes.

00:56:45

>> Right. There was actually a really good

00:56:48

tweet on this by Aaron Levy who's got

00:56:50

the right take on this. Aaron retweeted

00:56:53

Matthew Glacius who sort of sardonically

00:56:56

tweeted that 5 months in I think I've

00:56:59

decided I don't want to vibe code. I

00:57:01

want professionally managed software

00:57:02

companies to use AI coding assistants to

00:57:05

make more better, cheaper software

00:57:07

products that they sell to me for money.

00:57:08

>> Just lower your prices. Don't make me

00:57:10

vibe code is the translation.

00:57:13

>> Yeah. I mean, I think like rare win for

00:57:15

for Madaglacius there. Anyway, Aaron

00:57:17

Levy then says

00:57:19

Agent Coding is a huge win for software

00:57:21

developers that want to get more done

00:57:23

and it's fantastic for anyone curious to

00:57:26

learn how to start coding. What it's

00:57:28

less great for is casually building

00:57:30

complex software that you have to

00:57:32

maintain on an ongoing basis and take

00:57:33

all the risk for upgrades, maintenance,

00:57:36

keeping up to date with latest security

00:57:37

issues, you know, the bugs, cyber, those

00:57:40

are taxes on most knowledge workers who

00:57:42

aren't familiar with the system.

00:57:45

>> It's not a tax. It's a huge risk.

00:57:47

>> Yes, it's a risk has to be managed if

00:57:49

you don't. People will get fired because

00:57:52

there will be some public companies

00:57:53

where some goofball tries to vibe code

00:57:55

their way out of something and they're

00:57:56

going to torch the enterprise value.

00:57:58

It's going to be glorious to watch

00:58:00

because we're all going to laugh and

00:58:01

realize that was stupid and should never

00:58:02

have happened in the first place.

00:58:04

>> Yeah. I mean, it's there is a chance

00:58:07

that this improves to the point passes

00:58:10

trial of disillusionment and becomes

00:58:11

super productive and you'll be able to

00:58:13

get an agent to do reasonable things

00:58:15

without deleting your data set. But we

00:58:17

have a way to go. Here is your, you

00:58:20

know, this is the tech adoption chart.

00:58:22

Basically, you got a technology gets

00:58:23

triggered. You have the trial, you have

00:58:24

this peak of inflated expectations. You

00:58:26

go into the trial of disillusionment and

00:58:27

then the slope of enlightenment invest

00:58:29

and eventually it becomes deer and it's

00:58:32

an opportunity. Hey, uh, Freedberg,

00:58:36

you have become reddit tide curious. You

00:58:41

have and also

00:58:43

>> tell me tell me about rea cuz I want it.

00:58:46

I want to get on it. M

00:58:47

>> I want to use it and I need you to tell

00:58:50

Nat that it's okay for me to take it.

00:58:52

>> I I have a friend who has some advice as

00:58:54

well.

00:58:55

>> Freeberg, the coverage is coming out of

00:58:57

this phase three clinical trial data

00:58:59

release that Lily put out last month. So

00:59:01

everyone's going crazy over the data

00:59:05

which continues to show pretty amazing

00:59:08

results. So unlike trazepatide which is

00:59:11

kind of Lily's main

00:59:15

product today, it's a which is a dual

00:59:16

agonist. It's got two peptides in it

00:59:18

that that bind to different receptors,

00:59:20

the GLP1, the GIP receptor. This other

00:59:22

one now also binds to glucagon, which is

00:59:24

a third receptor. And that glucagon

00:59:27

receptor binding peptide causes the

00:59:30

cells to increase their metabolism,

00:59:31

which actually accelerates fat energy

00:59:34

consumption

00:59:36

over what would typically be muscle

00:59:38

energy consumption. It's more likely to

00:59:40

burn up fat early on, which causes more

00:59:44

quick fat loss, but also reduces muscle

00:59:47

loss. And some of the other data that's

00:59:50

now coming out shows non-HDL cholesterol

00:59:53

down 27%, triglycerides down 41%.

00:59:57

>> Liver fat down 80% to

01:00:00

>> 80% reduction of liver fat. A1C drops

01:00:04

from 7.9% to 6% in 40 weeks, which is

01:00:08

amazing, by the way. If you're diabetic

01:00:09

and your A1C drops that much in a couple

01:00:12

of months, it's literally a life-saving

01:00:14

product. The average user in this phase

01:00:17

3 trial saw their weight decline from

01:00:20

214 pounds. They lost 37 pounds. That's

01:00:23

compared to six pounds on placebo

01:00:26

in 40 weeks. And you know, modest side

01:00:29

effects. 20% people felt more nauseous

01:00:32

than the people that were on the

01:00:33

placebo. There's a lot of other separate

01:00:36

studies that are being done now that are

01:00:37

showing significant reductions in

01:00:39

inflammatory signaling molecules. So

01:00:42

systemic signaling of like hey cells are

01:00:46

in distress triggers this kind of

01:00:49

inflammatory process that can have a lot

01:00:51

of other damage to your body can

01:00:53

accelerate aging. And so one of the

01:00:55

other conversations is that retride

01:00:57

might actually be kind of a deaging drug

01:01:00

as well.

01:01:02

Hercules, Hercules, Hercules,

01:01:05

you know, and a lot of the studies, by

01:01:06

the way, are done on the the the very

01:01:08

high dose, 12 milligram dose, but you

01:01:10

could probably get this thing dosed down

01:01:11

to 2 milligrams and still see a lot of

01:01:13

the anti-inflammatory

01:01:14

maintenance and other benefits. I'm no

01:01:16

doctor, but people are going nuts over

01:01:19

this being more widely useful than just

01:01:22

for clinical obesity or type when the

01:01:24

FDA when's the projected date for

01:01:27

>> 2027. Mid 27.

01:01:28

>> That's what they're saying. Could happen

01:01:30

sooner. I mean, the data is in the, you

01:01:32

know, the FDA will take their time to

01:01:36

evaluate it, but I think given the way

01:01:37

this is all looking,

01:01:39

>> could happen sooner, could happen

01:01:40

sometime later this year. Swim Chimath

01:01:43

Swim said it's incredible and that uh

01:01:47

it's living up to the hype in their

01:01:49

experience.

01:01:50

>> Who?

01:01:51

>> Swim.

01:01:52

>> What is that? What is that?

01:01:53

>> Someone who isn't me. Swim.

01:01:55

>> Oh,

01:01:55

>> this is a Reddit term. Someone who isn't

01:01:57

me said who has a guy swim has a guy and

01:02:02

has cycled on reddatride and does

01:02:06

push-ups and says muscle gain has been

01:02:09

spectacular

01:02:10

no muscle loss and a lowering of fat.

01:02:14

>> If you go on X and you just search up

01:02:16

rea

01:02:17

>> Mhm.

01:02:19

>> it's like incredible. You see these like

01:02:21

65 year old guys that go from a dadbod

01:02:24

to looking like an incredibly ripped

01:02:27

athlete in weeks. And and I

01:02:31

I mean I'm shocked. And then for me I

01:02:34

don't need that help per se, but my

01:02:36

liver health is important to me. My

01:02:37

cardiac health because I'm South Asian

01:02:39

and it just looks like a wonder drug. I

01:02:41

can't wait. When you starve your body,

01:02:43

when you turn off the the appetite,

01:02:45

which is the GLP-1 agonist function,

01:02:47

normally your body goes into this kind

01:02:49

of mode of starvation and you have this

01:02:52

process by which your body tries to

01:02:53

generate energy from your existing

01:02:55

cells. And because muscle is much denser

01:02:59

than fat, you can have a favoring of

01:03:01

muscle tissue being kind of broken up

01:03:03

over fat tissue. But what this new

01:03:05

agonist, this glucagon agonist that they

01:03:07

put into this neutrutide

01:03:10

is it favors fat burning over muscle

01:03:12

burning. And so that actually can drive

01:03:15

short-term use at low dose for people to

01:03:18

cut weight and maintain muscle and get

01:03:20

ripped. And so that's why a lot of

01:03:21

people in the kind of fitness community

01:03:23

are talking about, hey, I want to get

01:03:24

access to this and get on it for a

01:03:26

while. So you'll see a lot more hype

01:03:27

probably in that community as well as

01:03:30

the all the health effects. It just

01:03:32

feels like we're about to have an

01:03:34

absolute avalanche of peptides to choose

01:03:36

from.

01:03:36

>> On November of 2025, Lily cut a deal

01:03:39

with the Trump administration. I saw

01:03:40

this to drop the price on Drespatide

01:03:43

pretty significantly. I think it's like

01:03:44

50 bucks on Medicare.

01:03:45

>> 50 bucks from Medicare. Yeah.

01:03:47

>> Yeah. Which is a pretty cheap price

01:03:48

point, but it starts to make sense as

01:03:50

you think about the portfolio of Lily

01:03:51

products. You get Tzepide for 50 bucks,

01:03:54

but if you want to upgrade, get the

01:03:56

Retatride. That's the high premium

01:03:57

product and that's where they're going

01:03:58

to start the Mercedes to the Honda. I'm

01:04:01

sure if I'm Lily and I'm sitting there

01:04:02

and I'm looking at this data coming out,

01:04:03

I'm like, "My god, people will pay for

01:04:05

this and that starts to become sort of

01:04:07

like the upgrade to the BMW or the Model

01:04:09

S plat if you will."

01:04:10

>> Yeah. The Trappetide is like the one

01:04:12

bedroomedroom messy bed hotel room

01:04:15

>> and the other one's the sweetide

01:04:18

is like the twobedroom suite.

01:04:20

>> Well, you can also, by the way, you guys

01:04:22

know I'm a spokesman for Row. They also

01:04:26

have the Waggoi pill uh row.co/twist

01:04:28

cotwist uh to get your

01:04:31

>> Wait, are you a paid talking about Are

01:04:34

you a paid What are you talking about?

01:04:36

We're putting Charles Barkley and

01:04:38

>> we're not having sales team

01:04:42

and then you come over on Allin and you

01:04:44

start promoting.

01:04:44

>> No, no, no, no. Trust me, we'll get one

01:04:46

of those as well. We'll get a row.

01:04:48

Sponsorship here.

01:04:49

>> What was the ro pill that you had me

01:04:50

get? What was it called?

01:04:51

>> Oh, sparks. Sparks. Sparks. Did you take

01:04:53

it?

01:04:54

>> I have taken it and now

01:04:56

>> Amore please. No, not

01:04:58

>> maybe just a half of a lousy.

01:05:00

>> I want to hear the story. I want to hear

01:05:01

the story. Go.

01:05:02

>> It's so out of control.

01:05:04

>> I told what I told you.

01:05:06

>> So then what happens is Nat and I are

01:05:08

like, you can't you can't just randomly

01:05:09

use it. It's scheduled. We discuss it.

01:05:11

We put it on the calendar.

01:05:12

>> You need a plan.

01:05:13

>> You need a plan.

01:05:14

>> You need a plan. Can't go in

01:05:16

>> because otherwise otherwise it's too

01:05:17

much. You just can't randomly take it.

01:05:19

>> What do you mean?

01:05:20

>> It's going to be a sesh.

01:05:22

>> It's a whole thing, man. It's like I

01:05:24

don't have the energy for that.

01:05:25

>> It's an extended session. You you have

01:05:26

to be well rested. This don't do this at

01:05:29

1:00 a.m. This is like a 10 p.m. This is

01:05:31

like a No, this is more like a This is

01:05:33

more like on vacation, you know, like

01:05:35

>> 10:00 a.m. to 12:00 p.m., you know, to

01:05:37

noon, you know, you got to really

01:05:40

>> you got to really schedule it.

01:05:42

>> Schedule it because kids around

01:05:44

>> otherwise it's got to be empty.

01:05:46

>> Otherwise, it's unfair to her and it's

01:05:48

just a li it's a lie. Put it out.

01:05:50

>> It's a It's a big commitment literally.

01:05:52

>> You You look embarrassed, Jim. Do you

01:05:54

feel embarrassed talking about it? It's

01:05:56

just a lot, man. It's like It's a lot to

01:05:57

handle. It's a lot.

01:05:59

>> It's If you want to get the extra 20% in

01:06:02

your performance,

01:06:03

>> it's a lot, bro.

01:06:04

>> It's a lot. It's basically over time.

01:06:07

>> What happened? What happened was I was

01:06:08

like, "Oh, what is this thing?" Jason's

01:06:10

like, "Dude, you must get it. You must

01:06:11

get it." So, we got it. We tried it and

01:06:14

>> we were like, "What the was that?" And

01:06:17

so, then I've been trying to bleed the

01:06:18

pills out. So, I gave some to Stant

01:06:20

Tang. I'm like, "Stanley, you try it."

01:06:22

Literally, he's dealing them like cards

01:06:25

>> but when we're having poker dinner, I'm

01:06:27

like, does anybody want to try these

01:06:28

things? But these what is it? Rose

01:06:30

sparks. Is that rose sparks? Shout out

01:06:31

to my friends out. All right, let's keep

01:06:33

moving here. Freedberg, guys. Friedberg

01:06:36

had his own personal Super Bowl. You see

01:06:38

me getting ready for Nick's playoff

01:06:40

season. I get my courtside. Freeberg had

01:06:43

the equivalence acts. He went to the

01:06:45

Supreme Court in order to hear them talk

01:06:49

about chemicals. This was a big deal for

01:06:52

him. The Supreme Court coming together.

01:06:54

Did you wear it? Yes. The Monsanto trial

01:06:57

happened in the Supreme Court and he

01:06:58

went he got courtside. He went to the

01:07:01

Supreme Court and listened in the

01:07:02

building. Have you guys ever seen a live

01:07:04

Supreme Court hearing?

01:07:05

>> No. I'd love to.

01:07:06

>> I'd love to. Tax, have you been?

01:07:08

>> No, I haven't actually.

01:07:09

>> I mean, honest honestly, I think it was

01:07:11

one of the most amazing experiences I've

01:07:13

ever had. There was a massive protest

01:07:14

out front. We went through the

01:07:16

marshall's office to get in. And that

01:07:18

building, you walk in, it's like sacred.

01:07:20

It's all marble. It's you're not allowed

01:07:23

to talk. You have to be super quiet when

01:07:24

you're in the building. Like they keep

01:07:25

going like you're in some quiet library.

01:07:28

It's like people treat it with this

01:07:30

level of kind of sanctity that that and

01:07:32

respect. And they're like, there is no

01:07:34

politics here. There is no [ __ ]

01:07:36

There is no freedom of speech. This is

01:07:38

the court. When you come into this

01:07:40

court, the justices tell you how you

01:07:43

will speak, how you will behave, what

01:07:44

you will do, and you will not speak

01:07:46

unless spoken to. You put all your stuff

01:07:48

in a locker, you go up the stairs, you

01:07:50

go into the the courtroom. And the

01:07:52

courtroom, it's just so amazing being in

01:07:54

there. They have this amazing marble

01:07:55

freeze above the justices that has some

01:07:57

of the great people of human history,

01:07:59

Moses and these kind of amazing

01:08:01

historical figures. And then below them

01:08:03

are the nine justices and the court

01:08:05

case. If you guys haven't watched the

01:08:07

case, you can listen to them, I think,

01:08:08

online. on you. Is it worth listening

01:08:10

to?

01:08:10

>> Hold on. Wait, wait, wait. I have a

01:08:11

question. So,

01:08:12

>> does Robert sit in the middle cuz he's a

01:08:14

chief? Yes.

01:08:15

>> And then do all of the right justices

01:08:17

sit on the right?

01:08:18

>> No, they're mixed. So, they're I think I

01:08:20

don't know I don't know the exact

01:08:21

seating, but they're mixed in terms on

01:08:24

appointments of the court. Is

01:08:25

>> that right? I think that's right. And

01:08:27

then so yeah, that's right. And then it

01:08:29

kind of goes out from the middle with

01:08:30

Roberts in the middle. Roberts

01:08:32

occasionally will name the justices and

01:08:35

say, "Hey, do you have a question? Do

01:08:36

you have a question?" if no one's

01:08:37

talking, but otherwise the justices will

01:08:39

jump in with their questions when they

01:08:40

want and they'll ask. Now, honest to

01:08:42

God, watching this is like watching

01:08:44

LeBron James play basketball. These

01:08:46

lawyers are so mind-blowingly impressive

01:08:50

on both sides that you would just like

01:08:52

sit there and I was like in awe. It was

01:08:54

so I I felt like my energy was

01:08:57

completely sapped from me at the end of

01:08:58

this process because you were just so

01:09:00

engaged and so caught into the way that

01:09:02

these guys are thinking and talking.

01:09:04

>> Did you take a rose sparks? Did you take

01:09:05

a rose sparks when you were there?

01:09:06

>> No. And if you're familiar if you're

01:09:08

familiar enough with the case or the

01:09:10

case history or the law that's being

01:09:12

debated because again when when you get

01:09:13

to the Supreme Court, you never debate

01:09:14

the case. What you're debating is the

01:09:17

legal interpretation of the the

01:09:19

decisions that were made on the case.

01:09:21

And so is this constitutional? How do

01:09:23

you interpret this particular act, this

01:09:25

law, this federal law? What's the right

01:09:27

way to think about it? So you don't

01:09:28

actually talk about the case. You talk

01:09:29

about the interpretation of American

01:09:31

law,

01:09:33

of our laws, of our constitution, of the

01:09:36

global.

01:09:36

>> You're saying the facts have already

01:09:38

been determined.

01:09:38

>> That's right.

01:09:39

>> Right. At a lower court, there's

01:09:40

questions of fact and questions of law.

01:09:42

>> The facts have already been determined

01:09:44

by the lower court. It's just Supreme

01:09:45

Court is ruling on questions of law.

01:09:47

>> That's right. And so they have a full

01:09:49

briefing with the full history of the

01:09:50

case. And remember, they only hear two

01:09:52

cases a day. So they're one hour each

01:09:54

for each hearing.

01:09:55

>> So you go in and they only do it Monday,

01:09:56

Tuesday, Wednesday on the last two

01:09:58

weeks. and they only hear cases from

01:10:00

October to April. There's only a handful

01:10:02

of cases that are selected.

01:10:03

>> Wow. So you're really on a shock clock

01:10:04

then to make

01:10:05

>> you're on a shot clock and you only have

01:10:06

and it's 30 minutes aside and then the

01:10:08

justices will ask question.

01:10:09

>> So this was Monsanto and Roundup, right?

01:10:11

So what was the law that was being

01:10:13

debated

01:10:14

>> for yours? The regulatory body, the EPA

01:10:18

sets the label for pesticides. Does this

01:10:20

cause cancer or not? What are the

01:10:22

warnings? This can be damaging for birth

01:10:23

defects, pregnancy, all the things that

01:10:25

we're all used to seeing on labels. when

01:10:27

you buy a product, a chemical product

01:10:29

and the EPA and their regulatory

01:10:31

authority determined that Roundup does

01:10:34

not cause cancer. When you sell a

01:10:36

pesticide, you first have to register it

01:10:38

with the EPA, get it approved, and then

01:10:39

the EPA gives you a label. And the label

01:10:41

is written by the EPA. It says exactly

01:10:43

what you're supposed to say. And in this

01:10:45

case, it said all this stuff doesn't say

01:10:47

cancer because they determined it does

01:10:49

not cause cancer. And I'm not going to

01:10:51

debate whether or not it causes cancer,

01:10:52

but that's the case that was made is

01:10:54

that the EPA is the regulatory body

01:10:56

under a federal act called FIFRA,

01:10:59

fungicide, insecttoide or denicide act.

01:11:01

And that's where the EPA is given their

01:11:03

regulatory authority to put the label on

01:11:06

these products. And all of the cases

01:11:08

that have been lost have been state

01:11:11

failure to warn cases. To date, Bayer,

01:11:14

which now owns Monsanto, has paid out

01:11:16

$10 billion in these lawsuits, and they

01:11:19

have reserved 10 billion on their

01:11:21

balance sheet. They have 90,000 cases

01:11:22

still outstanding in the courts. 90,000.

01:11:25

>> Wow.

01:11:25

>> And so, this one case got kind of

01:11:27

appealed up to the Supreme Court. Last

01:11:30

year, the White House solicitor general,

01:11:32

and if the solicitor general steps up

01:11:33

and asks the Supreme Court to take a

01:11:35

case, it's more likely the case gets

01:11:37

taken. So, the White House said, "Please

01:11:38

take this case. We need to have federal

01:11:41

preeemption, meaning the federal

01:11:42

government has the right to set the

01:11:44

label because all of the cases that have

01:11:46

been lost and that are being adjudicated

01:11:49

are in state courts where the state has

01:11:51

a law like in California called a

01:11:53

failure to warn law, which means if a

01:11:55

manufacturer knows that a product

01:11:57

carries a risk, you have to warn the

01:11:59

consumer. And so the the lawyers have

01:12:02

been arguing that Monsanto or Bayer knew

01:12:04

that this product caused cancer and

01:12:06

didn't warn the consumer. And they've

01:12:08

been winning cases. they've been losing

01:12:09

cases, but they've won enough cases that

01:12:12

this has now become a multi-dea billion

01:12:13

dollar problem. And so the argument is

01:12:16

that the EPA says it doesn't cause

01:12:18

cancer and they have federal

01:12:19

preeemption. So the EPA has the right to

01:12:21

determine. So that's the one argument.

01:12:24

But then when the other attorney came

01:12:27

up, this guy was like literally like

01:12:28

watching LeBron James. And so going in,

01:12:30

we're like, "Oh, 63 Bayer's going to

01:12:31

win." And then the other guy comes up

01:12:33

and he was like, "Well, hey, you guys

01:12:36

overturned the Chevron doctrine last

01:12:37

year. You guys remember that case?

01:12:38

>> Yeah. Where basically when the Chevron

01:12:40

doctrine got overturned, it basically

01:12:42

said that no longer

01:12:44

>> does the federal agency get to decide it

01:12:46

has to be a direct reading of the law.

01:12:50

>> Duh. So now, so he's saying like the

01:12:52

states should have a right to read the

01:12:55

law themselves. They shouldn't have to

01:12:57

just defer to the EPA. And that's what

01:12:59

this will come down to. So at the end of

01:13:00

it, we were like, "Oh my god, this could

01:13:02

be a 50/50 coin flip, 54 either way."

01:13:05

And going into it, we were kind of like

01:13:06

trying to say, "Hey, maybe this could be

01:13:08

63." So honestly, the whole experience

01:13:10

was incredible. The case is interesting.

01:13:12

>> These are very complicated matters. How

01:13:13

are these people able to make a

01:13:16

wholesome argument in like one side gets

01:13:19

30 minutes, the other side gets 30

01:13:20

minutes, there's a little Q&A, and then

01:13:21

you're done in an hour.

01:13:22

>> There's this whole art and science and

01:13:24

Sax, you're probably familiar with this

01:13:26

on how do you distill down a Supreme

01:13:27

Court case in the briefing dock? Like

01:13:29

what is it you're petitioning around the

01:13:31

court? and you try and distill it down

01:13:32

to the exact legal interpretation you

01:13:35

want the judges to rule on, not all the

01:13:37

other [ __ ]

01:13:38

>> And this is oral arguments. Yes.

01:13:39

>> Oral arguments, just a discussion. And

01:13:41

then the judges jump in and all they're

01:13:42

doing is asking the lawyer questions,

01:13:44

one lawyer at a time, the one side and

01:13:46

then the other side. And by the way, the

01:13:47

solicitor general came up in the middle

01:13:49

and kind of made a few comments and they

01:13:50

asked her some questions from the White

01:13:52

House and she sat down and then the two

01:13:54

sides kind of went back and forth and

01:13:55

and they just it's like 30 minutes Q&A

01:13:57

each on that one specific legal question

01:14:00

and Katanji Brown Jackson said, "But

01:14:03

what if after the EPA issued the label,

01:14:05

they found out information that it does

01:14:07

cause cancer? Shouldn't they update the

01:14:09

label?" And he's saying, "Well, no,

01:14:10

they're not allowed to. They can only

01:14:11

issue the label the EPA says." And he

01:14:13

says also and it's it's a criminal case

01:14:16

if they find out that it does cause

01:14:17

cancer and they don't report it to the

01:14:19

EPA and then she's saying well what if

01:14:21

the EPA doesn't act and shouldn't the

01:14:23

states have a right to protect their

01:14:24

people? So those are the legal

01:14:26

arguments, the discussions that are

01:14:27

going on in all of this. And there's

01:14:29

interesting implications which is

01:14:30

fundamentally if the states get to

01:14:32

interpret federal law and ignore federal

01:14:35

regulatory bodies, it opens up a whole

01:14:37

new can of worms in terms of like all

01:14:39

the states can start to ignore federal

01:14:41

regula regulatory bodies like the EPA or

01:14:44

the FDA or the USDA or and on and on and

01:14:46

on. So the whole case has a whole bunch

01:14:48

of really interesting implications wound

01:14:50

up in it. when you hear these guys and

01:14:51

they're just talking chimat about that

01:14:53

exact like interpretation of the law and

01:14:55

that's what this comes down to. It's not

01:14:56

the actual case that matters

01:14:58

>> and after the sachs they oral arguments

01:15:01

and then they have like a private

01:15:02

conference where they'll write their

01:15:04

papers and give their final judgment.

01:15:05

Yeah.

01:15:07

>> Saxs.

01:15:07

>> Yeah. Yeah, I think what happens is that

01:15:10

so I guess there's some discussion that

01:15:12

happens behind closed doors and they

01:15:14

figure out where the majority is and

01:15:16

then the chief gets to assign who writes

01:15:18

the opinion for the majority

01:15:19

>> in that meeting nobody is allowed in and

01:15:22

in fact you have a double door system

01:15:24

where like if anything needs to come in

01:15:25

and out you have to like kind of like

01:15:27

knock on the door you're led into this

01:15:28

anti chamber then

01:15:29

>> oh is it an airlock is an airlock

01:15:31

>> it's effectively we I had I don't know

01:15:34

if you were there Jason but we had Ted

01:15:35

Cruz come to play in the poker game

01:15:37

>> uh And Ted Cruz clerked for William

01:15:40

Ranquist and if you want to have an

01:15:42

incredible dinner, ask him about the

01:15:45

Supreme Court and Bill Ranquist. He's a

01:15:48

real student of the Supreme Court and it

01:15:50

just makes the Supreme Court free to

01:15:51

your point sound like the most

01:15:53

incredible body that's ever been created

01:15:57

anywhere. By the way, more than the

01:15:59

White House, more than the Capital

01:16:01

Building, more than any of these other

01:16:03

big agencies, this place has it's almost

01:16:06

like being in England, it has these kind

01:16:08

of ways that people operate. The the the

01:16:10

security is so different. They kind of

01:16:12

stand there in the court and they all

01:16:14

exchange places every 20 minutes. It's

01:16:16

very coordinated. They're dressed very

01:16:18

differently than any other

01:16:19

>> courtroom listening.

01:16:20

>> Maybe like 150, I would say. How do you

01:16:23

take it? Are they on

01:16:24

>> I actually think everyone is a guest of

01:16:26

a clerk or someone that works at the

01:16:27

court. I don't think that it's like very

01:16:29

publicly available to get in there.

01:16:30

>> You can't line up. There's no lineup.

01:16:32

>> There's I don't know if there's a

01:16:33

lineup. Um this was a connection through

01:16:36

we got in through the chief justice. Um

01:16:38

he gave us the pass, but I think it was

01:16:40

like very um

01:16:42

>> I think at the Elon versus Open AI case

01:16:45

there's you can line up and then the

01:16:47

judge gave like 30 tickets to the press

01:16:50

court. No, no. Yeah, but I think there's

01:16:52

a lineup for the Supreme Court as well.

01:16:54

There's some public access that they're

01:16:55

>> It did not look like anyone from the

01:16:57

public was in this court. Everyone,

01:16:59

everyone is dressed respectfully. I

01:17:00

mean, this court has an incredible

01:17:02

amount of like,

01:17:04

>> you know, cool experience.

01:17:07

>> I would I would just say uh enjoy it

01:17:09

while you can. I mean, I think the

01:17:11

Supreme Court is one of the last highly

01:17:12

functional institutions in the United

01:17:14

States. And%

01:17:16

>> you know at some point we're going to

01:17:17

have like 13 or 21 or some crazy number

01:17:20

of justices up there

01:17:23

and get jersey

01:17:25

after justices there and so enjoy it

01:17:28

while it's still

01:17:29

>> in the current in the current form it's

01:17:31

in.

01:17:32

>> Can you imagine showing up with jerseys

01:17:34

with the justices names on them and like

01:17:36

having sections and like somebody

01:17:38

selling cracker jacks

01:17:40

>> theocracy version of the Supreme Court

01:17:43

>> version. Exactly.

01:17:45

>> The popularity of the court really

01:17:47

depends on whether it's issuing

01:17:51

decisions that people agree with. That's

01:17:52

what it comes down to. If like if you

01:17:54

ask people whether they like the Supreme

01:17:56

Court or not, it really just depends on

01:17:58

whether they agree with the decisions

01:17:59

are recency as opposed to

01:18:02

>> the process of the decisions and how

01:18:04

well argued it is and all these things

01:18:05

that you're pointing to. And actually

01:18:08

the the court I mean I just checked the

01:18:09

numbers. The court is relatively popular

01:18:12

right now. I think that it got as low as

01:18:16

35% in the 2024 Gallup survey, but I

01:18:19

think it's back up to, you know, like 44

01:18:23

to 50% favorability, which for something

01:18:26

that's involved in politics is

01:18:28

relatively high, right? Like you look at

01:18:30

Congress or

01:18:31

>> any particular politician, they're going

01:18:33

to be lower than that typically. I just

01:18:35

felt so assured of like the institution

01:18:40

when I visited and saw these guys

01:18:41

interact and behave and how they behave

01:18:43

the process. It was like

01:18:45

>> man this what an amazing country. Yeah.

01:18:48

>> Well, the reason I say what I say is

01:18:49

there was an interview with James

01:18:50

Carville recently. Did you guys see

01:18:52

this? He saidaw he said look when we get

01:18:54

power we're packing the court.

01:18:56

>> So we're not even going to we're not

01:18:57

going to worry about it.

01:18:58

>> And we're going to get to 13, right? He

01:19:00

said we're going to make

01:19:01

>> I think Yeah. They're going to go from 9

01:19:02

to 13 and then they're going to create

01:19:04

some new states and all the rest of it.

01:19:06

So that'll be that.

01:19:07

>> Uh

01:19:08

>> enjoy enjoy while it last. Enjoy.

01:19:10

>> Enjoy while it lasts.

01:19:11

>> Uh by the way,

01:19:12

>> end on a high note.

01:19:13

>> Wait. Yeah. It's the end of the empire.

01:19:15

That'll be that.

01:19:16

>> By the way, there is uh a Supreme Court

01:19:19

on I was correct. There is an online

01:19:21

ticketing lottery. So we can all sign up

01:19:24

and you can get a fourack of tickets. I

01:19:26

think they should make this I we should

01:19:28

talk to Howard Lutnik. Maybe he can make

01:19:30

this an auction. We get a revenue stream

01:19:31

from the US. We could sell like 10 of

01:19:33

the tickets as courtside seats for 20

01:19:35

grand.

01:19:35

>> Jason, you're exactly what they're

01:19:37

trying to protect against.

01:19:38

>> Exactly. Like, how can we how do we

01:19:40

monetize the Supreme Court?

01:19:43

>> All right, everybody. That's it. That's

01:19:44

the world's greatest podcast for you for

01:19:46

Chimoth Poly Hatia, David Freeberg, and

01:19:48

David Saxs. I am the world's greatest

01:19:51

moderator. We'll see you chief justice.

01:19:54

>> I'm like the chief justice of the allin

01:19:56

podcast.

01:19:59

We'll let your winners ride.

01:20:01

>> Rainman David

01:20:06

and it said we open sourced it to the

01:20:08

fans and they've just gone crazy with

01:20:09

it.

01:20:10

>> Love you queen of

01:20:13

winners.

01:20:19

>> Besties are gone.

01:20:21

>> That is my dog taking a driveway.

01:20:26

>> Oh man. My habitasher will meet.

01:20:29

>> We should all just get a room and just

01:20:30

have one big huge orgy cuz they're all

01:20:32

just useless. It's like this like sexual

01:20:34

tension that you just need to release

01:20:35

somehow.

01:20:40

>> Your feet.

01:20:42

We need to get Mercury's already.

01:20:52

I'm going all in.

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