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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!

Transcript

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.

Interactive Summary

The discussion covers the US government's recent export controls on GPUs, particularly those in the Nvidia ecosystem, aimed at preventing their acquisition by China. It acknowledges the difficulty of enforcing these controls and the potential for them to spur China's development of its own semiconductor and algorithmic innovation, with a timeline of 10 years seen as a significant period for potential Chinese success. The conversation then transitions to the emerging field of AI agents, highlighting a company called Manis and the significance of the Model Context Protocol (MCP) for standardization. It concludes by noting that while agents could have a negative impact on human employment, the primary limiting factor for their widespread adoption will be the availability of sufficient compute resources.

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