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China is building its own Nvidia – and US trade policy is forcing their hand!

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China is building its own Nvidia – and US trade policy is forcing their hand!

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127 segments

0:00

Do you think that there's any issues?

0:01

There was a a bunch of companies added

0:03

to the export control list two days ago.

0:05

Some were in quantum computing.

0:07

Generally, a lot of it though was in the

0:09

Nvidia ecosystem. So, I think that the

0:11

the US government is really trying to

0:13

make sure that these nextg GPUs don't go

0:15

directly to China, but also don't go to

0:17

countries that could then redirect them

0:19

into China. Did you get a chance to look

0:20

at that or did your team look at that

0:22

yet? Oh, yeah. And I think this will be

0:25

part of you know the upcoming

0:26

negotiation between America and China.

0:29

But it is hard you know it's like if we

0:32

can't you know if America cannot keep

0:34

illegal drugs out of you know out of our

0:38

own country these GPUs are arguably

0:42

dramatically more valuable per unit. you

0:46

know, like a black well is like, you

0:47

know, the size of this and it's just

0:51

hard. Particularly like, you know,

0:53

America, we're trying to keep drugs

0:55

out here. China is trying to bring the

0:58

GPUs in and it's kind of significantly,

1:02

you know, I think harder to prevent than

1:04

than, you know, smuggling of illegal

1:07

drugs. Now, everybody does their best,

1:09

but um yeah, the United States, I think

1:12

it's always going to be kind of a game

1:13

of cat-and- mouse until you get some

1:15

sort of grand bargain. And right now,

1:17

they they're allowed to sell certain

1:19

kinds of GPUs into China. And I'm sure

1:21

they'll be Should we be doing that,

1:23

Gavin? Is is this going to be an

1:25

effective strategy? You know, if you

1:27

were advising the president, would you

1:28

say, "Ah, just let Nvidia sell them.

1:31

It's a fool's errand to try to stop them

1:32

because they're all going to Singapore

1:33

or wherever Vietnam and and routing

1:36

their way around. I think we're putting

1:38

enough friction into the

1:41

system that it does theoretically give

1:45

America an advantage at the cost of

1:49

creating tremendous incentives for China

1:53

to develop their own semiconductor

1:56

ecosystem and you know pressure to kind

2:00

of you know necessity is the mother of

2:01

innovation and these export controls are

2:05

creating an immense incentive for China

2:07

to really algorithmically innovative and

2:09

you saw that with Deep Seek where there

2:10

were some real algorithmic innovations.

2:13

Yeah. So said another way, if we squeeze

2:16

too tightly on letting them buy the

2:18

Nvidia chips, they might make a better

2:21

Nvidia. I mean, become resilient. I

2:24

think they're doing it now. They're

2:25

trying now. So that's Well, they're

2:26

trying, but I guess what are the chances

2:28

they succeed in your mind, Gavin, in

2:30

creating something competitive with or

2:32

better? And then what would that say

2:34

about the AI race in the next five

2:36

years? is I think zero. I think it's

2:38

really really hard, but over the 10

2:40

years, who knows? And if you're the CCP,

2:43

10 years isn't that long. If you're

2:45

America, 10 years is an eternity. Yeah,

2:48

they're thinking in centuries and we're

2:50

thinking in decades. Yeah, that's

2:52

probably correct. Hey, um let's pivot

2:54

over to AI agents since we're in the AI

2:57

and obviously there's other big topics

2:58

this week. We'll get to you doing

3:00

politics and uh signal and all that kind

3:02

of good stuff. But we have a company

3:07

that seems to be, you know, having a

3:10

moment. It's called Manis, uh

3:13

Mus. It's currently in private beta, but

3:15

they're creating agents, and we've been

3:17

talking about this agentic revolution.

3:20

Basically, little, you know, jobs going

3:23

out. We used to call them crown jobs

3:24

back in the day, but going out and doing

3:26

things for you. and it seems to be

3:28

working and it's pretty impressive. What

3:30

do you think about this company

3:32

specifically, if anything? And are we

3:35

getting to a point where we're going to

3:38

have the same chat GPT 2.5 moment, but

3:41

with agents? And then if we do have

3:43

that, Gavin, what will that look like in

3:46

terms of employment and how companies

3:47

are run? Look, I do think uh

3:50

if agents materialize as a reality and

3:54

you know, Manis is maybe a little bit of

3:56

a chat GPT moment for that. I would say

3:59

OpenAI and Enthropic. Enthropic

4:01

developed something called the model

4:02

context protocol that OpenAI just

4:05

adopted. I think it will become a

4:06

standard and it makes it really easy for

4:09

an LLM like Stripe can just integrate

4:12

with MCP and then any LLM that uses MCP

4:16

can you know interact with

4:19

Stripe and this is solving a big big

4:22

problem for agents um in terms of just

4:25

making them you know much easier to use

4:27

much more

4:29

standardized but if agents become a

4:32

reality one the ROI on AI high in

4:35

Blackwell is going to be very high and

4:38

two what will it's not good for human

4:42

employment but what will be kind of I

4:45

would say the rate limiting factor is

4:47

just compute in a world where we all

4:50

have agents doing things for us all day

4:53

long it's going to be a long time before

4:56

we have enough compute in the ground for

4:59

that to be a really really widespread

5:02

reality and I think that's why you know

5:03

open AI was talking pricing their first

5:05

agents at $2,000 to $20,000 a month.

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