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The World's Evilest Company

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The World's Evilest Company

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451 segments

0:00

Can you trust them?

0:01

No, seriously.

0:04

Can you trust them?

0:06

To understand what I'm talking about,

0:07

you first must know who Palantir is.

0:09

Now, if you're not familiar with

0:11

Palantir, Palantir, best known for

0:13

surveilling um

0:15

the whole world and every last person.

0:17

Yeah, that company uh led by the way by

0:19

Alex Karp, which can do this sweet move,

0:22

and also is known for being

0:23

geographically monogamous, which is in

0:25

fact the definition of not being

0:27

monogamous. Well, that Alex Karp of

0:29

Palantir has called the AI industry

0:32

effing insane in a 20-minute kind of uh

0:36

crash out on CNBC. But, here's the thing

0:39

is that he made a lot of good points,

0:41

okay? And can you trust them? The them

0:43

in this situation, the model providers,

0:45

can you actually trust them?

0:48

I don't know. I'm watching you, Dario.

0:51

Also, can we sidebar here for a second?

0:53

So, if if you're being accused of

0:55

shenanigans by Palantir, I feel like you

0:57

got to you know

0:59

take a moment and ask yourself some

1:00

pretty tough questions.

1:02

>> Are we the baddies?

1:04

>> So, we're going to actually look at some

1:06

of this kind of crash out, this mental

1:08

breakdown that Alex Karp had on CNBC.

1:10

And shockingly, I actually agree with a

1:12

whole bunch of it. And even more

1:14

importantly, the things he actually

1:16

said, well,

1:17

I actually think they have they're

1:18

they're happening. They're they have

1:20

happened. Like, what he is saying is

1:21

actually correct. And I'll show you

1:23

exactly what I'm talking about after we

1:24

talk about Alex Karp himself. So, first,

1:27

we got to say thank you to the sponsors.

1:29

>> I've personally conducted hundreds of

1:30

interviews, and I know how hard hiring

1:32

is. And that's not even what today's

1:34

problems of fake AI profiles, resumes

1:37

that are difficult to read, and senior

1:39

engineers who have never even read code.

1:42

G2i fixes that. Not the reading code

1:44

part, the hiring part. G2i can help you

1:47

hire front-end, back-end, and even AI

1:49

engineers.

1:50

Because they have pre-vetted 8,000-plus

1:53

engineers through real technical

1:55

interviews. So, you can review quality

1:57

candidates in days, not months. Check

1:59

out g2i.co/prime

2:01

and take the headache out of hiring. All

2:03

right, so the first thing he talks about

2:04

is token maxing. Now, if you're not

2:06

familiar with token maxing, just imagine

2:08

you go into a boat store and you're

2:10

like, "Yo, I would like to get a fishing

2:11

boat." And the fishing boat store was

2:12

just like, "Yeah, well, why why get a

2:14

fishing boat when you can get a yacht,

2:15

right? Like you can fish on a yacht, you

2:17

know that, right?" And you're like,

2:18

"Well, I don't know about that." And

2:19

they're like, "Yeah, but why even get a

2:20

100-ft yacht when you can get a 300-ft

2:22

yacht? Like you get a mega yacht. You

2:23

get like the world's biggest yacht. Like

2:25

why

2:26

why would you ever want a fishing boat

2:27

when you can get a yacht?" To us, that'd

2:29

be quite obvious what they're trying to

2:30

do. They're trying to sell the most

2:31

amount of money. But for some odd

2:33

reason, when it comes to token spend,

2:35

spend maxing as the kids call it, we

2:37

just have zero care.

2:38

>> I just I'm not throwing shade at them,

2:40

but something has gone completely wrong.

2:41

And the basic view among enterprises in

2:44

this country is I'm going to chillax and

2:47

waste my time with tokens. I'm going to

2:49

get no value, and they're going to get

2:50

my IP.

2:50

>> Okay, that sounds like shade.

2:52

>> First off, it's very strange for me to

2:54

watch the news. Yeah, the this this

2:56

little news segment right here. Why why

2:58

why is this sounding like a Twitch

2:59

stream? Okay, who is saying chillax and

3:02

shade on CNBC? Okay, I want the business

3:04

news to be the business, not some sort

3:06

of weird zoomer millennial coded

3:09

language. What's happening to the news?

3:11

But this was just an unusual experience,

3:13

but what he said was so dang correct.

3:15

First off, token maxing and getting

3:17

little value. It is obvious the value

3:19

you get out of token maxing. When you

3:20

incentivize employees to just use as

3:24

much as you possibly can, that is not

3:26

good because really, as he kind of

3:28

alluded to, like the really big kind of

3:29

piece of feedback wasn't the fact that

3:31

you're spending a whole bunch and

3:32

getting little value. It's the fact that

3:34

what you're spending is on all of your

3:36

business strategy. You are handing over

3:39

to Claude, you're handing over to OpenAI

3:42

all of the alpha, as they keep saying.

3:45

By the way, the alpha has two meanings.

3:47

Obviously, the first one is like your

3:49

defensible position as a company, your

3:51

trade secrets, the things that make your

3:52

company be able to withstand or

3:54

outcompete your competitors. And the

3:56

second version of alpha is a word you

3:58

hear, and then you know that whatever

4:00

comes next is going to be the dumbest

4:01

thing you've ever heard cuz you're

4:02

talking to a crypto bro. Now, in this

4:04

case, it's the it's the former, not the

4:06

latter. And of course, with this crash,

4:08

Palantir also released a nine-point

4:11

manifesto. Now, I don't know if you know

4:12

this, but manifestos, when it comes to

4:14

tech, pretty much always lead to good

4:17

outcomes. I can't think of a single bad

4:18

thing that has happened, but if you look

4:20

at point three on the manifesto, the

4:21

Palantir manifesto, you'll see that

4:24

token maxing hijacks your value

4:26

orientation and decreases institutional

4:28

fortitude and intelligence. The pursuit

4:30

of high token usage incentivizes

4:32

disposable scripts over robust software

4:35

with the addictive feeling of false

4:37

progress. It is absolutely an incredible

4:39

and insightful point right there. I love

4:44

it. And as somebody who is actively

4:46

trying to do my own token maxing, my own

4:48

looping to really kind of understand

4:50

what these zoomers keep talking about, I

4:52

just seem like I'm spending all my all

4:54

my all my tokens and I'm not really

4:56

getting much value out. But the argument

4:58

for token maxing, at least from his

5:00

perspective,

5:01

you'll notice that it wasn't just about

5:03

the spend. It really was about handing

5:05

over your IP. And he says that best

5:08

here.

5:08

>> So, safe because it doesn't touch your

5:10

underlying data, safe because it

5:11

prevents the large language model from

5:12

caching your data and replicating your

5:14

business,

5:15

safe because it doesn't transfer your IP

5:17

of how to fight, secret data, top secret

5:19

data, or in a in a clinical context.

5:21

>> using the term safe there. What he's

5:22

talking about is the usage of these

5:24

models. How do you make it safe? Well,

5:26

the reality is to make it safe, the

5:28

actual safety that we all need to be

5:30

pursuing is that you need to know who's

5:32

storing your data. Like, as a company,

5:34

are you giving away the secrets? Are you

5:36

giving it all away to these these

5:38

companies to just go off and and be able

5:40

to use all of your hard-fought wisdom

5:43

against you? Now, you're probably

5:44

thinking, "Okay, that's a little

5:45

ridiculous." Is it ridiculous?

5:47

Is it? No company would ever do that.

5:50

That's not actually happened. Well, just

5:52

hold on. We got one more little part I

5:54

want to go over and I think I can prove

5:56

that that notion wrong, okay, buddy? Cuz

5:58

here's the deal.

6:00

If what these big companies were selling

6:02

was actually just able to derive value

6:04

immediately, right? You didn't need the

6:06

token max into potentially just dead end

6:08

spending just a ridiculous amount of

6:11

money. Seriously though, like look at

6:12

Meta. 73.7

6:15

trillion dollars. They're claiming it's

6:16

a two-plus billion dollar a year bill

6:19

that they're spending on AI. Like what

6:21

the What are they even doing over there?

6:24

You can't tell me they're getting two

6:26

billion dollars worth of value out of

6:28

their tokens right now. Nope. Refuse to

6:30

believe it. Unless of course they're

6:31

doing exactly what we're talking about,

6:33

which is getting some information,

6:35

getting that sweet data.

6:36

>> If it was so valuable, let's say I can

6:37

make you a billion dollars right

6:39

tomorrow. Wouldn't I say, "I'll make you

6:40

a billion dollars and I want 30%?" Why

6:42

are they charging for tokens if it's so

6:44

valuable?

6:44

>> So good. Why are they charging for

6:46

tokens if it's so valuable? Like that is

6:48

a very big question because like just

6:50

just really just walk with me on this.

6:51

If AI was so freaking amazing that it's

6:54

going to take whatever revenue you have

6:56

now and triple it. You just have to

6:58

integrate it into your into your system.

7:00

Why would Anthropic even have a consumer

7:02

side? They wouldn't. All they would do

7:03

is simply be like, "Yo, business A,

7:05

here's the deal. We're going to come in.

7:06

We're going to triple your revenue.

7:07

You're going to give us 30%. The end."

7:09

Yeah. And you'd say, "Absolutely. Yes,

7:11

sir. Very much. Please. Thank you very

7:12

much. I would absolutely love that." I

7:14

would I would hands down do like no

7:16

company would say no to that. I mean,

7:19

other than Anthropic themselves

7:20

considering they're currently losing

7:22

They they would triple their losses.

7:23

Okay, but besides for them and say

7:25

OpenAI, like the rest of companies would

7:27

clearly jump on and say, "Absolutely. I

7:29

would love to triple my revenue and I

7:31

would gladly pay you for that." And

7:32

that's of course it's because it's about

7:35

the data, the secrets, the hard-fought

7:37

knowledge, the alpha

7:40

I don't like that term. All right, so

7:41

now is the part where I show you real

7:43

world examples. You know, that thing

7:45

which by the way, if I were to tell you

7:46

that these companies were doing things

7:48

that were shady, I think a lot of people

7:49

would just instinctively go, "Yeah, I I

7:51

could probably see that coming." cuz the

7:52

reality is if you have all these users,

7:54

millions upon millions of users making

7:56

queries into your system, you're going

7:58

to be able to see shapes of data in

8:00

which most people will never be able to

8:01

see. You can go, "Okay, this is really,

8:03

really hot. This is what the people

8:05

want. If we go into this industry, we're

8:07

going to win." Well, look at this right

8:09

here. Inside Cursor's wild rise, a lot

8:11

of great new details. CEO Michael Truel

8:14

didn't pay himself for years. Cursor

8:16

once made about 40 to 50% of Anthropic's

8:18

revenue. Anthropic told Cursor that

8:20

Claude Code was just a research effort.

8:23

Well, well, yeah. You know, you know,

8:25

old Claude Code, that old research

8:26

effort. It's not like it's nothing. It's

8:28

just like,

8:29

"Uh we're just trying something out.

8:31

We're not like actually using all this

8:34

data we've gathered. Where did they get

8:35

the data from?" Wait, by the way, thanks

8:37

for all the data. We really do genuinely

8:39

appreciate it. We're not like using it

8:40

all, identifying the fact that there's

8:42

millions upon billions of dollars

8:43

sitting on the table here, and we're

8:44

going to just simply move into that

8:46

industry. There's no definitive proof

8:47

that Anthropic used their position,

8:49

gathered all the data, and said, "Okay,

8:51

this is the exact market we should go

8:52

into." But, it's a point on the graph,

8:54

okay? Oh, by the way, just in case

8:56

you're wondering, our terms of service

8:58

often includes things like, "Hey, you

9:00

can't build competing projects or else

9:02

we're going to drop you." And of course,

9:03

competing projects being Claude AI,

9:05

Claude Pro, and other projects and

9:07

services that we may offer for

9:08

individuals along with any associated

9:10

apps, software, or websites as our

9:12

services. Of course, this is the

9:14

consumer side of the TOS. The commercial

9:16

TOS is worded slightly different. They

9:18

have different affordances. But, this

9:19

David Sachs tweet right here, I didn't

9:22

know about another case. You don't think

9:24

that can happen? That being, "Hey, you

9:26

give away all of your information." Just

9:28

look at Figma. Yes, if you haven't

9:30

looked at Figma, by the way, their stock

9:32

I'm so Hey, Figma employees, I feel for

9:35

you, okay? Anthropic employees, I don't

9:37

feel for you. Look at that. Anthropic,

9:39

your stock looks so good, but man, Figma

9:40

absolutely decimated. Anyways, when you

9:43

jump back here and say, "Just look at

9:44

Figma." According to the information,

9:47

Anthropic blindsided its its then

9:49

business partner with the launch of

9:50

Claude design. Figma's founder said

9:52

Anthropic had not been consistently

9:54

honest with them. Anthropic's chief

9:57

product officer, Anthropic's chief

10:00

product officer, had even served on

10:03

Figma's board until 3 days before the

10:07

launch of Claude design. I did two

10:08

fingers up. 3 days. I meant to do

10:10

threes, not twos. Either way, just think

10:12

about that for a second. If you're on

10:14

the board for a company, you're there

10:16

for the best interest of that company.

10:18

We can all agree to that. Now, whether

10:20

you're working there, if you're just a

10:21

individual engineer, that's a completely

10:23

different story, but if you're on the

10:24

board, your goal is to shepherd the

10:26

company long-term towards success. The

10:29

fact that if if all of this stuff that

10:31

is being reported by The Information is

10:34

correct, which is it is saying that

10:35

Anthropic blindsided its business

10:37

partners. The fact that Anthropic's

10:39

chief product officer knew this was

10:41

going to happen, knew Claude design was

10:43

going to drop, and remained on the board

10:45

for so long just seems completely crazy

10:48

to me. I just can't even imagine that.

10:50

That is like being not just stabbed in

10:52

the back, you're being stabbed in the

10:53

front. You're getting right just sitting

10:55

there, looking in your eyes, and

10:57

stabbing you, and you don't even know

10:59

about it until 3 days after they quit.

11:01

Think about all of that juicy data they

11:03

got from Figma, too. Mhm.

11:05

The data must have been absolutely fine,

11:08

like a nice delicious French wine. Okay,

11:11

I'm not a I don't Do they do French

11:13

people drink wine? I assume so. This

11:14

This seemed like they drink the wine.

11:16

That's not even a good French accent. I

11:18

don't even know how to do a French

11:19

accent. I don't even know what that

11:21

accent is. But now we have two points on

11:24

a graph, and two points on a graph makes

11:26

well, a line. And if you zoom out just a

11:28

bit, you'll notice that Anthropic also

11:31

stole the world's books. So, it's not

11:34

like this is the first time that they

11:36

have been inside of the data stuff. And

11:38

plus, if you really zoom out and think

11:40

about it, they also stole the world's

11:42

knowledge. I mean, that's a that's a

11:45

pretty big straight line if you ask me.

11:48

Now, there's no definitive proof or like

11:49

papers written up how they used Figma's

11:51

data and then said, "Oh, okay, yeah,

11:53

hey, that's us now. We're we're now

11:54

Figma." Instead, I think it's pretty

11:57

obvious to say that they saw the success

11:58

of Claude Code. They saw them moving

12:01

into the coding space. They saw how

12:02

popular the design space is that's

12:04

paired with the coding space and said,

12:06

"We need to move into that." And they

12:07

could see the usage already. They

12:09

already had the proof. They already had

12:11

the pudding to know if they could just

12:13

put the little toes again. Also, the

12:15

pudding and the toes, that's that's not

12:18

an analogy. This is not one. They

12:20

probably have many other things that are

12:21

in the works that is being designed off

12:23

the data that is being handed to them so

12:25

that they can commandeer parts of the

12:26

industry and then effectively be able to

12:29

push people out with their terms of

12:30

service. This is a very unusual

12:33

experience. Now, I can't say all of this

12:35

is actually happening or what is all of

12:36

their motivations behind things, but it

12:38

does seem like this is exactly what you

12:40

would use the data for. You would use it

12:42

as a means to determine which industry

12:44

you're going to capture because if you

12:46

have unlimited token spend, you can

12:48

effectively slop together any product

12:50

you want to be able to be close enough

12:52

with its competitors because you know

12:54

that the most amount of people are in

12:56

this realm. So, you can use all of your

12:58

insider information. You can use all

13:01

that hard-fought knowledge. You can see

13:02

how people are doing stuff in an

13:04

industry and you can build the product

13:06

that best matches other people's desires

13:08

because you have the data. All the data.

13:11

You have every single prompt and every

13:12

single answer, every single re-prompt.

13:14

It's crazy what they actually have

13:16

available. Now, this Alex Karp clip goes

13:19

on for about 20 minutes and yes, it's

13:21

absolutely legendary some of the things

13:22

he has to say. You should definitely

13:24

watch the thing. I really am on Alex

13:27

Karp's side. I can't believe I'm saying

13:29

that. I'm on the geographically

13:31

monogamous side of Alex Karp, which

13:33

Wait, I shouldn't say it that way. That

13:35

That's not That's not what I meant. I am

13:37

definitely on the geographically

13:38

monogamous Alex Karp's side of this

13:41

argument, which is that the AI industry

13:44

is effing insane because the effing

13:46

insane part isn't the fact that they're

13:47

losing a bunch of money, which I think

13:49

is what everybody points to right now.

13:50

It's the complete destruction of so many

13:53

companies and the data they're able to

13:54

yield and potentially able to weaponize

13:57

against other people to be able to

13:59

capture industries. Very, very

14:01

interesting. And again, the nine-point

14:03

manifest on AI sovereignty probably says

14:05

it the best. Data retention is your

14:07

treasure. Transfer it at your own peril.

14:10

Your ability to win is dictated by your

14:12

ability to recognize and use your unique

14:14

edges, and you keep winning by

14:15

compounding the underlying data to

14:17

generate new insights. Transferring that

14:19

data hands over access to your

14:21

pre-existing winning plays and yields

14:23

the means of production for new ones.

14:25

Meaning, somebody else can figure out

14:28

how to win your industry based on your

14:30

data. The name

14:33

is the primogen.

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