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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.

Interactive Summary

The video summarizes Palantir CEO Alex Karp's strong critique of the AI industry, where he describes it as "effing insane." The speaker supports Karp's view, highlighting two core issues: first, "token maxing" leads to companies overspending on AI models, gaining minimal value, and critically, inadvertently surrendering their intellectual property and business strategies to model providers. Second, they question why AI companies charge per token if their technology is truly transformative; suggesting the real motive is to collect valuable user data. This data then enables AI providers to identify profitable market niches and launch competing products, effectively weaponizing user information. Examples include Anthropic's alleged actions concerning Cursor and Figma, where partnerships seemingly led to the development of directly competing services. The video concludes with a warning derived from Palantir's manifesto: data retention is paramount, and its transfer risks allowing others to seize a company's industry.

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