1
00:00:00,000 --> 00:00:02,517
I keep asking my friends, when does the

2
00:00:02,600 --> 00:00:04,877
asymptote arrive and when does the curve

3
00:00:04,960 --> 00:00:08,037
slow down? We've not seen it yes yet.

4
00:00:08,120 --> 00:00:12,357
There will be one, right?
It is actually true that there is a

5
00:00:12,440 --> 00:00:14,397
limit to our craziness. >> [laughter]

6
00:00:14,480 --> 00:00:17,317
>> We have not found it yet.
The next thing

7
00:00:17,400 --> 00:00:19,557
that's really interesting and terrifying

8
00:00:19,640 --> 00:00:21,597
also is recursive self-improvement, but

9
00:00:21,680 --> 00:00:24,517
we don't have it yet. What we do have

10
00:00:24,600 --> 00:00:28,797
Guys, Eric Schmidt just gave a banger
interview during an AI conference last

11
00:00:28,880 --> 00:00:33,197
week. Eric talked about the upcoming
AI and its dangers for humanity. And he

12
00:00:33,280 --> 00:00:36,837
said if we don't control AI now,
it could become an existential threat to

13
00:00:36,920 --> 00:00:38,997
humanity in the coming years. Guys, I

14
00:00:39,080 --> 00:00:41,637
must say here that Eric is one guy who's

15
00:00:41,720 --> 00:00:43,917
been warning us about AGI for a very

16
00:00:44,000 --> 00:00:46,277
long time now. In a recent interview, he

17
00:00:46,360 --> 00:00:48,997
literally said that uncontrolled AI has

18
00:00:49,080 --> 00:00:51,077
the potential to become a bigger problem

19
00:00:51,160 --> 00:00:53,717
for us comparatively to nuclear bombs.

20
00:00:53,800 --> 00:00:58,397
So, I mean, he's been the CEO of Google
and when he says AI is a bigger threat

21
00:00:58,480 --> 00:01:02,037
than nukes, it should be enough
to open everyone's eyes. Let's watch the

22
00:01:02,120 --> 00:01:04,357
interview and I'll give
my opinion as we go.

23
00:01:04,440 --> 00:01:08,877
So, let's start with a a question that uh

24
00:01:08,960 --> 00:01:13,077
I'd love to hear you expand on, which
is we're living through a historic moment

25
00:01:13,160 --> 00:01:15,877
right now. Right? Um

26
00:01:15,960 --> 00:01:18,917
could you define the moment we're in and

27
00:01:19,000 --> 00:01:24,197
give us sort of a a state of the
union of what's going on in AI?

28
00:01:24,280 --> 00:01:28,237
We're 10 or 15% into the impacts of

29
00:01:28,320 --> 00:01:31,677
this. And you can see it.

30
00:01:31,760 --> 00:01:36,477
You can feel it. And some
of it will happen, some of it

31
00:01:36,560 --> 00:01:39,397
will take longer, right? So,
for example, hardware takes longer than

32
00:01:39,480 --> 00:01:44,597
software. So, the robots take longer
than digital systems uh on traditional

33
00:01:44,680 --> 00:01:46,397
hardware, things like that.

34
00:01:46,480 --> 00:01:49,797
Um we've not um

35
00:01:49,880 --> 00:01:53,877
the next thing that's really interesting
and terrifying also is recursive

36
00:01:53,960 --> 00:01:57,677
self-improvement. >> Mhm.
It's not happening yet.

37
00:01:57,760 --> 00:02:01,997
And so, it's easy to convince yourself
that you're going to have human agents

38
00:02:02,080 --> 00:02:05,357
uh sorry, computer agents that are
human-like completely within a year or

39
00:02:05,440 --> 00:02:07,877
two. We don't have the science for that

40
00:02:07,960 --> 00:02:10,077
yet. People are working on it. I can

41
00:02:10,160 --> 00:02:13,077
describe how I think it'll play out. But

42
00:02:13,160 --> 00:02:15,677
we don't have it yet. What we do have is

43
00:02:15,760 --> 00:02:18,517
reasoning systems that are perfect

44
00:02:18,600 --> 00:02:22,757
partners for human beings for good
and bad. Right? And that has a lot of

45
00:02:22,840 --> 00:02:26,957
implications. So if we stopped today,
which we're not, and it's not stoppable

46
00:02:27,040 --> 00:02:30,877
or controllable by any government
or any single individual or corporation,

47
00:02:30,960 --> 00:02:35,317
we would still have advanced humanity
because of these reasoning agents. How

48
00:02:35,400 --> 00:02:39,317
fast do you imagine
this is going to accelerate?

49
00:02:39,400 --> 00:02:42,997
Um the there's a thing
which I call the San

50
00:02:43,080 --> 00:02:46,917
Francisco consensus. And the reason I
call it is cuz everyone in San Francisco

51
00:02:47,000 --> 00:02:51,477
believes this. Uh everyone
I know anyway, which is that

52
00:02:51,560 --> 00:02:53,637
it it it's easy to understand.

53
00:02:53,720 --> 00:02:57,877
Uh this is the year of agents, which
we can discuss why agents will take over

54
00:02:57,960 --> 00:03:00,197
everything this year. Mhm. During this

55
00:03:00,280 --> 00:03:05,077
year, the scaling of the use of agents
and reasoning will sort of grow at this

56
00:03:05,160 --> 00:03:08,357
enormous rate. Everybody's out of
hardware, everyone's out of electricity.

57
00:03:08,440 --> 00:03:11,717
It's a real boom, right? It's like
the biggest boom I've seen, and I've been

58
00:03:11,800 --> 00:03:15,677
through three or four
of these in my career.

59
00:03:15,760 --> 00:03:20,517
Um the in this thinking,
once you have recursive

60
00:03:20,600 --> 00:03:24,517
self-improvement, where the system
can begin to improve itself, you have

61
00:03:24,600 --> 00:03:28,757
intelligence learning on its own. And it
will in this argument, it will learn

62
00:03:28,840 --> 00:03:32,517
faster than we can cuz
we're biologically limited.

63
00:03:32,600 --> 00:03:36,397
And the way this is expressed in San
Francisco, and I'll give a simple

64
00:03:36,480 --> 00:03:38,037
example, you have a tech company with a

65
00:03:38,120 --> 00:03:43,157
thousand fantastic AI researchers. Um

66
00:03:43,240 --> 00:03:46,437
so one day they turn on AI research,

67
00:03:46,520 --> 00:03:50,637
that is an AI research agent. Well,
how many AI research agents do you

68
00:03:50,720 --> 00:03:55,917
have? >> Mhm. Well, as many as you're
limited by electricity, right?

69
00:03:56,000 --> 00:03:58,317
You don't have to feed them, they don't
need housing, there's no more housing in

70
00:03:58,400 --> 00:04:00,837
San Francisco, you know, all that kind
of stuff, right? You don't have those

71
00:04:00,920 --> 00:04:04,477
problems. You don't have an HR
department for them, if you will.

72
00:04:04,560 --> 00:04:07,557
Uh and you don't have to pay them, you
just have to feed them electricity. So,

73
00:04:07,640 --> 00:04:08,997
how many could you have? Well, maybe a

74
00:04:09,080 --> 00:04:11,637
maybe a million of these agents.

75
00:04:11,720 --> 00:04:14,837
Now, in AI, the way you determine you've

76
00:04:14,920 --> 00:04:18,397
made progress is you have clear metrics

77
00:04:18,480 --> 00:04:20,037
that the reasoning or testing or

78
00:04:20,120 --> 00:04:22,197
whatever the evaluation framework is

79
00:04:22,280 --> 00:04:26,317
better, right? So, that's what happens.

80
00:04:26,400 --> 00:04:29,717
So, in that scenario, the slope goes like

81
00:04:29,800 --> 00:04:34,077
this because you're already at this slope,
then you add more people, then

82
00:04:34,160 --> 00:04:38,437
you get the agents and you go like
this, and this is essentially um a

83
00:04:38,520 --> 00:04:40,797
superintelligence moment.

84
00:04:40,880 --> 00:04:42,437
The belief in San Francisco is this

85
00:04:42,520 --> 00:04:45,837
occurs within 2 to 3 years.

86
00:04:45,920 --> 00:04:49,037
The evidence in favor

87
00:04:49,120 --> 00:04:51,797
goes something like this. Um Claude code

88
00:04:51,880 --> 00:04:56,077
came out a couple months ago, the the
latest one, Opus, whatever it is. 4.5,

89
00:04:56,160 --> 00:04:58,957
yes, thank you. And

90
00:04:59,040 --> 00:05:01,437
everyone I know in the Bay Area that's

91
00:05:01,520 --> 00:05:04,637
doing software says it was 80/20, now

92
00:05:04,720 --> 00:05:06,517
it's 20/80.

93
00:05:06,600 --> 00:05:09,997
The best analysis I can come up with is

94
00:05:10,080 --> 00:05:12,677
it's not the Claude code part, it's that

95
00:05:12,760 --> 00:05:16,957
the that the underlying LLM can produce

96
00:05:17,040 --> 00:05:19,437
more reasoning over time, better quality

97
00:05:19,520 --> 00:05:22,557
tokens over time. It's a deeper thinker,

98
00:05:22,640 --> 00:05:26,557
right? And all the labs now are
competing for that. This is not just the

99
00:05:26,640 --> 00:05:29,397
size of the context window,
it's actually the reasoning skill and the

100
00:05:29,480 --> 00:05:33,797
length of which it can think.
It can just think longer and produce more

101
00:05:33,880 --> 00:05:36,437
stuff, right?
I'm going to pause here for a

102
00:05:36,520 --> 00:05:39,037
bit, guys. I've been hearing tech people

103
00:05:39,120 --> 00:05:41,277
on podcasts saying that the recursive

104
00:05:41,360 --> 00:05:46,277
self-improvement is exponential. That's
wrong. Recursive self-improvement is not

105
00:05:46,360 --> 00:05:49,917
exponential. Just because a system can
improve itself doesn't mean that it does

106
00:05:50,000 --> 00:05:54,357
so by a constant factor each time. In
fact, technology generally tends to show

107
00:05:54,440 --> 00:05:56,397
diminishing improvements as it matures.

108
00:05:56,480 --> 00:06:00,117
Yes, a better model can make
improvements faster, but this ignores

109
00:06:00,200 --> 00:06:03,917
the current state of things that is being
improved upon. And as it improves,

110
00:06:04,000 --> 00:06:08,517
it gets harder and harder to improve,
which can cancel out the fact that the

111
00:06:08,600 --> 00:06:10,957
models are better and better at improving.

112
00:06:11,040 --> 00:06:14,157
>> I watched this stuff
when I was I moved about

113
00:06:14,240 --> 00:06:18,597
the Bay Area when I was 21.
And I was a programmer in high school

114
00:06:18,680 --> 00:06:21,917
way back when.
And I was pretty good programmer.

115
00:06:22,000 --> 00:06:24,037
And I watch what it does and I go, my

116
00:06:24,120 --> 00:06:26,877
god, I'm over, you know. There's there's

117
00:06:26,960 --> 00:06:32,117
not a thing that I could do that it
cannot do. So, when they wrote a C

118
00:06:32,200 --> 00:06:35,157
compiler in Rust,

119
00:06:35,240 --> 00:06:39,957
I got it's over, you know, like declare
success. So, I think part of this part

120
00:06:40,040 --> 00:06:43,477
of this is because the people who
are building it are also seeing the

121
00:06:43,560 --> 00:06:46,237
diminution of their own skill.

122
00:06:46,320 --> 00:06:49,197
They're being forced to go from
programmers, which is what I'm very

123
00:06:49,280 --> 00:06:54,277
proud to have been, to being
the the director of a programming system.

124
00:06:54,360 --> 00:06:59,237
Right? And the most likely scenario, by
the way, there's a lot of implications for

125
00:06:59,320 --> 00:07:02,477
this. One is that it's always been true,

126
00:07:02,560 --> 00:07:06,517
speaking as your local arrogant
programmer, that the very top

127
00:07:06,600 --> 00:07:10,557
programmers were worth 10 times more
than the ones right below. There's

128
00:07:10,640 --> 00:07:14,637
something special about the mathematical
reasoning skills of programmers.

129
00:07:14,720 --> 00:07:17,397
Those people will become more valuable,

130
00:07:17,480 --> 00:07:21,677
not less valuable, because these systems
need to be controlled by humans at the

131
00:07:21,760 --> 00:07:25,517
moment. Those people will be capable
of grasping the parallelization and

132
00:07:25,600 --> 00:07:29,317
activities of this. But I do have
a proposal for universities, those of you

133
00:07:29,400 --> 00:07:31,717
who are associated with universities,
you should stop everything else you're

134
00:07:31,800 --> 00:07:36,197
doing in the university right now
and design a course for freshmen, men and

135
00:07:36,280 --> 00:07:37,997
women, uh

136
00:07:38,080 --> 00:07:40,957
uh who starting in September,

137
00:07:41,040 --> 00:07:43,997
which is a prompt engineering class.

138
00:07:44,080 --> 00:07:47,437
Why Why Why university?
Why not high school?

139
00:07:47,520 --> 00:07:49,557
God, you're so aggressive, Peter.

140
00:07:49,640 --> 00:07:51,517
>> [laughter] >> All
right, let's start with

141
00:07:51,600 --> 00:07:55,837
universities. You can improve my idea.
I I thought 18-year-olds would be would be

142
00:07:55,920 --> 00:07:58,317
young enough.
Maybe you think it's younger.

143
00:07:58,400 --> 00:08:02,997
Here's the most important thing. Spend
Spend Spend a quarter or a semester, the

144
00:08:03,080 --> 00:08:07,237
first thing they learn in university
is how to use these tools.

145
00:08:07,320 --> 00:08:10,237
Universities are completely
opposed to my idea, as usual.

146
00:08:10,320 --> 00:08:14,277
>> Yeah. Because it violates every one of
their tenets. But if you think about the

147
00:08:14,360 --> 00:08:16,477
student, and I mean every student,

148
00:08:16,560 --> 00:08:18,997
liberal arts, you know, math, whatever,

149
00:08:19,080 --> 00:08:21,757
they're going This platform will be the

150
00:08:21,840 --> 00:08:24,517
expression platform for their art, their

151
00:08:24,600 --> 00:08:27,077
music, their writing, and so forth. Why

152
00:08:27,160 --> 00:08:28,997
wouldn't you teach them immediately?

153
00:08:29,080 --> 00:08:32,037
Peter, improve my proposal. No, I I just

154
00:08:32,120 --> 00:08:35,117
I just feel like we're that AI is going

155
00:08:35,200 --> 00:08:38,957
to impact every student in high school

156
00:08:39,040 --> 00:08:41,877
today. Yeah. And that they're they're

157
00:08:41,960 --> 00:08:45,117
living an unnatural life by not engaging

158
00:08:45,200 --> 00:08:50,477
with it. And when they hit universities,
for those that still exist, um

159
00:08:50,560 --> 00:08:53,437
Well, plus your kids are that age,
and so they're literally right now

160
00:08:53,520 --> 00:08:56,517
>> Yeah. doing exactly what you're
describing, so. People here who have

161
00:08:56,600 --> 00:08:59,237
teenagers, you know what I'm talking
about, cuz they're all in it already. So

162
00:08:59,320 --> 00:09:02,957
So I think you're That's an improvement
to my argument. There's a problem of age

163
00:09:03,040 --> 00:09:07,237
restriction. Uh you really have to think
about vulnerable teenagers with this

164
00:09:07,320 --> 00:09:10,637
technology. Um I did [clears
throat] some some analysis

165
00:09:10,720 --> 00:09:13,277
of where the real problems
are with this stuff.

166
00:09:13,360 --> 00:09:17,197
Um A simple summary is that at some point

167
00:09:17,280 --> 00:09:20,837
there will be jobs impact from this stuff.

168
00:09:20,920 --> 00:09:23,677
We're seeing it in software, and we're
seeing it in certain customer service

169
00:09:23,760 --> 00:09:27,157
industries, not across the board.
At some point that will happen. That's an

170
00:09:27,240 --> 00:09:28,237
issue.

171
00:09:28,320 --> 00:09:33,197
Another one is how do we as a country

172
00:09:33,280 --> 00:09:35,237
maintain our moral values while we're

173
00:09:35,320 --> 00:09:37,757
also racing against China? Another one

174
00:09:37,840 --> 00:09:41,037
is the impact on um um

175
00:09:41,120 --> 00:09:45,597
uh young people. It is not okay
for 13-year-olds to be committing suicide

176
00:09:45,680 --> 00:09:48,557
because of an LLM.
It's just not okay. It should

177
00:09:48,640 --> 00:09:51,997
It's It's It needs to be addressed.
It needs to be addressed right now. For

178
00:09:52,080 --> 00:09:55,557
sure. Uh and there's all sorts of other
issues. The other one I came up with was

179
00:09:55,640 --> 00:09:59,157
in agent orchestration.
Agents can be combined.

180
00:09:59,240 --> 00:10:02,997
I I've always been worried that when you
put the agents together, especially if

181
00:10:03,080 --> 00:10:05,517
they're from non uh non-compatible

182
00:10:05,600 --> 00:10:07,997
vendors, you get unpredictable effects.

183
00:10:08,080 --> 00:10:12,677
>> Mhm. Yeah. So So these are problems
to be solved. So we herald the future and

184
00:10:12,760 --> 00:10:14,157
we solve the problems that it brought.

185
00:10:14,240 --> 00:10:18,357
So we're we're going to talk about
China and government and jobs.

186
00:10:18,440 --> 00:10:22,397
But before we do that, um I want to say
I'm I'm in this savor-the-moment's kind

187
00:10:22,480 --> 00:10:25,397
of mode right now because I feel like
the world to a year from today will be

188
00:10:25,480 --> 00:10:27,917
nothing like the world today. And all

189
00:10:28,000 --> 00:10:29,757
everything we're doing right now,

190
00:10:29,840 --> 00:10:32,637
I've enjoyed so much for so long. And I

191
00:10:32,720 --> 00:10:37,077
just want to savor the moment.
But reminisce for 1 minute about the fact

192
00:10:37,160 --> 00:10:40,997
that while you were running Google,
the Transformer got invented there,

193
00:10:41,080 --> 00:10:45,957
the TPU got invented there,
Demis Hassabis solved protein folding,

194
00:10:46,040 --> 00:10:49,157
which is now universally used.
You know, it does the

195
00:10:49,240 --> 00:10:50,917
work in I think it's does the work in an

196
00:10:51,000 --> 00:10:54,317
hour that used to take a PhD student 4

197
00:10:54,400 --> 00:10:57,197
years 4 years. Yeah. It's like 300

198
00:10:57,280 --> 00:11:01,557
million times more efficient. Um all of
that and all the diaspora from that, all

199
00:11:01,640 --> 00:11:04,237
the people working in the field in San
Francisco as you mentioned, they all

200
00:11:04,320 --> 00:11:08,757
were your people. Yeah. And so you
were there at the creation of everything

201
00:11:08,840 --> 00:11:11,597
we're experiencing right now.
Is there anything anything like that

202
00:11:11,680 --> 00:11:14,717
profoundly strikes you about that moment?
I mean, did you even realize at

203
00:11:14,800 --> 00:11:18,717
the time that I think when you're making
history, you typically don't know it.

204
00:11:18,800 --> 00:11:22,357
Um I give a lot of credit
to Larry and Sergey.

205
00:11:22,440 --> 00:11:24,077
Because they were ahead of me. I'm I'm

206
00:11:24,160 --> 00:11:27,597
an operating CEO. And they pushed pushed

207
00:11:27,680 --> 00:11:29,877
and pushed for excellence.

208
00:11:29,960 --> 00:11:31,837
And I'll give you an example. In the

209
00:11:31,920 --> 00:11:34,797
early years of Google, Larry would uh my

210
00:11:34,880 --> 00:11:37,037
favorite interaction was one day I said

211
00:11:37,120 --> 00:11:40,237
we need to hire some people doing Java.

212
00:11:40,320 --> 00:11:44,837
And Larry and Sergey said, "This is the
stupidest idea we have ever heard." And

213
00:11:44,920 --> 00:11:47,557
and I could never tell with them were
they were being serious or not or they

214
00:11:47,640 --> 00:11:51,317
were just joking with me. But their
argument was that real programmers were

215
00:11:51,400 --> 00:11:52,957
programming one level lower. Today

216
00:11:53,040 --> 00:11:55,117
Google has many thousands of everything.

217
00:11:55,200 --> 00:11:59,957
But they but they were so precise
and so driven to excellence

218
00:12:00,040 --> 00:12:03,597
>> in technology. Yeah. >> Right?
That I could not fool them. I

219
00:12:03,680 --> 00:12:07,877
couldn't market around them. I needed to
have the technical expert. And they say,

220
00:12:07,960 --> 00:12:09,357
"Oh, that's boring. Don't do that.

221
00:12:09,440 --> 00:12:10,907
That's another one of your ideas."

222
00:12:10,990 --> 00:12:14,437
>> [laughter] >> Right?
We want a new idea. Wow. And I

223
00:12:14,520 --> 00:12:15,597
give them a lot of credit for it.

224
00:12:15,680 --> 00:12:18,517
>> But what what about the TPU in
particular? Like tell that to me cuz I I

225
00:12:18,600 --> 00:12:21,557
didn't even hear about
it until much later.

226
00:12:21,640 --> 00:12:25,317
And it takes you years to to build
design and build your own internal

227
00:12:25,400 --> 00:12:29,077
chips. And now it's it's about to explode.
I don't know how much is public

228
00:12:29,160 --> 00:12:33,277
or not, but it's it's just >>
the TPU version one was essentially a

229
00:12:33,360 --> 00:12:35,357
matrix multiplier of a particular kind.

230
00:12:35,440 --> 00:12:38,397
When they went to version two, they
changed the algorithm in a complicated

231
00:12:38,480 --> 00:12:39,877
way. And it's particularly good for

232
00:12:39,960 --> 00:12:42,037
inference.

233
00:12:42,120 --> 00:12:45,877
Whether it's brilliance or just luck,

234
00:12:45,960 --> 00:12:48,037
those decisions made 10 years ago set up

235
00:12:48,120 --> 00:12:50,477
the TPU as the perfect inference engine.

236
00:12:50,560 --> 00:12:53,277
And for everybody's benefit, inference

237
00:12:53,360 --> 00:12:57,517
is what the reasoning steps that I'm
describing on. So Google is particularly

238
00:12:57,600 --> 00:13:01,997
well positioned. As you know,
Nvidia purchased Croc um

239
00:13:02,080 --> 00:13:04,517
for the reason of getting that in Yeah,
trying to catch up to what you thought

240
00:13:04,600 --> 00:13:06,437
of 10 years ago. >> interesting
about Nvidia, if you look at

241
00:13:06,520 --> 00:13:09,797
them, I was looking
at the Ruben architecture.

242
00:13:09,880 --> 00:13:14,117
They managed to do Nvidia managed to do
what Intel could never do. Intel could

243
00:13:14,200 --> 00:13:18,477
never get control of the complete
server architecture. And they tried.

244
00:13:18,560 --> 00:13:23,037
Nvidia has managed to build real
supercomputers that you can really buy

245
00:13:23,120 --> 00:13:24,957
with enough time and money and so forth.

246
00:13:25,040 --> 00:13:28,037
And it will really be delivered to your
to your And and it just do the whole

247
00:13:28,120 --> 00:13:30,477
thing. These are major industrial

248
00:13:30,560 --> 00:13:35,077
achievements and that's why both
companies will do incredibly well. Okay,

249
00:13:35,160 --> 00:13:38,877
in the following part Eric talks about
robotics and how he fears that China

250
00:13:38,960 --> 00:13:42,997
might defeat the United States in the
robotics race. Guys, one thing is pretty

251
00:13:43,080 --> 00:13:47,117
clear at this point. China is advancing
much more rapidly on the hardware level

252
00:13:47,200 --> 00:13:51,277
compared to the United States. I mean,
if you look at the electric vehicle

253
00:13:51,360 --> 00:13:55,277
production and advancement, they've
outpaced the US with a huge margin.

254
00:13:55,360 --> 00:13:59,597
Guys, China is fundamentally a socialist
country. Their long-term goal is to

255
00:13:59,680 --> 00:14:03,317
reduce labor for the benefit
of the people. Now, if that actually

256
00:14:03,400 --> 00:14:07,877
materializes, which is of course a real
question in itself, but at their core

257
00:14:07,960 --> 00:14:11,997
they believe that the productivity
of the working class is a shared national

258
00:14:12,080 --> 00:14:15,797
good. So, I mean, it's really important
for the United States to understand the

259
00:14:15,880 --> 00:14:17,877
dynamics of our competition with China.

260
00:14:17,960 --> 00:14:21,077
I I read an a Time op-ed piece you wrote

261
00:14:21,160 --> 00:14:25,237
last night. Um China can
dominate the physical AI

262
00:14:25,320 --> 00:14:29,797
future or uh what did you Can you
summarize that for us? It was an important

263
00:14:29,880 --> 00:14:34,357
conversation.
>> in the geopolitical context, um they

264
00:14:34,440 --> 00:14:36,917
and I've said this many
times, I'll say it again.

265
00:14:37,000 --> 00:14:41,797
The American competitor,
not enemy, but competitor is China.

266
00:14:41,880 --> 00:14:44,077
I I think it's a By the way, I think
it's an important distinction for you to

267
00:14:44,160 --> 00:14:47,797
make, so thank you.
>> Not Not enemy, competitor.

268
00:14:47,880 --> 00:14:51,837
Um and how do understand
them as a competitor?

269
00:14:51,920 --> 00:14:53,877
They have lots of money. They're very,

270
00:14:53,960 --> 00:14:56,717
very smart. Their work ethic is equal or

271
00:14:56,800 --> 00:14:59,757
stronger than ours and they dominate key

272
00:14:59,840 --> 00:15:01,277
industries.

273
00:15:01,360 --> 00:15:04,437
Right? I- I- With respect to robotics,

274
00:15:04,520 --> 00:15:07,317
we somehow decided it was okay for them

275
00:15:07,400 --> 00:15:11,997
to dominate the electric vehicle industry.
This was an error. T- To be

276
00:15:12,080 --> 00:15:15,717
very clear, it's an error. Why do you
not understand it's an error? Because we

277
00:15:15,800 --> 00:15:19,037
don't allow their cars in.
And spend some time outside of this

278
00:15:19,120 --> 00:15:21,637
country in Chinese cars, trust me.

279
00:15:21,720 --> 00:15:23,277
They are real competitors, they've done

280
00:15:23,360 --> 00:15:26,477
a great job. As I understand it,

281
00:15:26,560 --> 00:15:31,277
China is capable of vertical integration
and build these these gigafactories at a

282
00:15:31,360 --> 00:15:35,197
scale that we can't for all sorts
of reasons. That's got to get addressed.

283
00:15:35,280 --> 00:15:39,197
Mhm. So, if you want to compete, and I
want to compete and win with China, and

284
00:15:39,280 --> 00:15:43,037
the and the and I compete not enemy,
I want us to have the same kind of

285
00:15:43,120 --> 00:15:47,397
system. So, in robotics,
it turns out robotics,

286
00:15:47,480 --> 00:15:50,317
um you can understand robots
as essentially actuators, these little

287
00:15:50,400 --> 00:15:54,517
stepper motors, book click click click
click click, and a brain. Ignoring the

288
00:15:54,600 --> 00:15:58,277
appearance and the Google, you know,
eyes and all that kind of stuff.

289
00:15:58,360 --> 00:16:00,397
It turns out that the industry of the

290
00:16:00,480 --> 00:16:02,997
electric vehicle produces the same kind

291
00:16:03,080 --> 00:16:06,397
of motors and the same kind of systems.

292
00:16:06,480 --> 00:16:09,157
They have an expertise that we don't.

293
00:16:09,240 --> 00:16:13,637
My own view is that at
least for very low cost,

294
00:16:13,720 --> 00:16:17,357
China is going to win that. And that was
what I was trying to say in that piece.

295
00:16:17,440 --> 00:16:21,837
Mhm. And I worry about that. Now, today
these are not particularly useful, you

296
00:16:21,920 --> 00:16:24,757
know, they're they're fun toys, they're
a replacement for the dog if you get mad

297
00:16:24,840 --> 00:16:26,757
at your dog. Sorry, I love I love dogs,

298
00:16:26,840 --> 00:16:30,797
but you get the idea. Um so so we we we

299
00:16:30,880 --> 00:16:34,757
need to address this.
But at the moment, it sure looks to me

300
00:16:34,840 --> 00:16:39,717
like the robotic hardware of China
is the winner at the low end.

301
00:16:39,800 --> 00:16:42,277
I'm not talking about the high end,
I'm not talking about the expensive stuff,

302
00:16:42,360 --> 00:16:44,237
I'm not talking about industrial robots.

303
00:16:44,320 --> 00:16:46,317
And if you're confused, watch the

304
00:16:46,400 --> 00:16:51,317
Unitree um robot dance with the humans.

305
00:16:51,400 --> 00:16:52,877
Yeah. It came out about a month ago.

306
00:16:52,960 --> 00:16:56,077
>> Unitree here in the Tech Hub, and
the co-founder will be on stage with us

307
00:16:56,160 --> 00:16:58,157
later today. Pay pay attention to them.

308
00:16:58,240 --> 00:17:01,877
They're they're very very impressive.
Uh and I spent some time with them last

309
00:17:01,960 --> 00:17:03,957
time I was in China. Uh and they're one

310
00:17:04,040 --> 00:17:07,077
of many. And the way China works is that

311
00:17:07,160 --> 00:17:12,077
they have brutal competition.
Um brutal brutal it's like unbelievable.

312
00:17:12,160 --> 00:17:15,557
I was talking to my friend, we teach
at Stanford, and And said, you know, in

313
00:17:15,640 --> 00:17:17,757
China, we don't have the board dinner.

314
00:17:17,840 --> 00:17:20,877
We have a 2-hour meeting, we get back
to work. And there's no preamble. We're

315
00:17:20,960 --> 00:17:23,677
not, you know, we don't say hello, how
are you, how's the family, that kind of

316
00:17:23,760 --> 00:17:27,437
stuff. We're boom, boom. Right? Uh, it's

317
00:17:27,520 --> 00:17:31,117
just cultural. Yeah.
>> And the workaholic the the the work

318
00:17:31,200 --> 00:17:35,277
ethic, the precision, and the scale
that is possible in China is a real

319
00:17:35,360 --> 00:17:36,717
competitor.

320
00:17:36,800 --> 00:17:39,757
Um, I don't want to lose the robotic

321
00:17:39,840 --> 00:17:44,557
revolution, in my view, the way we
lost the electric vehicle revolution, at

322
00:17:44,640 --> 00:17:48,957
least on >> the low end. Interesting. Cuz
I had the Chinese model very much has a a

323
00:17:49,040 --> 00:17:51,837
well-built out supply chain with many
vendors in the loop. But we you know,

324
00:17:51,920 --> 00:17:56,437
we've been on a worldwide tour of all
of the humanoid robotics companies. And I

325
00:17:56,520 --> 00:17:59,917
just like coincidence, I guess. But when
you look at the Gigafactory and look at

326
00:18:00,000 --> 00:18:03,317
Elon's vertical integration, and also
Brett Adcock at Figure, same thing, it's

327
00:18:03,400 --> 00:18:06,277
all vertically integrated. Why?
Well, cuz there's no vendor.

328
00:18:06,360 --> 00:18:11,037
>> Yeah. I have no choice. I have >>
it appears that to get to again, we're

329
00:18:11,120 --> 00:18:15,037
in this is the abundance group. This is
the abundance club. The way you get to

330
00:18:15,120 --> 00:18:19,197
abundance is you drive prices down and
you get vertically integrated. And Elon

331
00:18:19,280 --> 00:18:21,597
in our country pioneered
that, to his credit.

332
00:18:21,680 --> 00:18:25,277
>> Yeah. Right? You know, the the old joke
about Google was we would build anything

333
00:18:25,360 --> 00:18:29,477
including the buildings. Well,
Elon is actually doing that. Yeah.

334
00:18:29,560 --> 00:18:33,917
>> Right? You know, he's And why?
Not because he's insane, but because he

335
00:18:34,000 --> 00:18:36,437
actually That's how you drive cost down.

336
00:18:36,520 --> 00:18:41,437
>> Yeah. Guys, the Chinese are very
good at scaling at incredible rates. For

337
00:18:41,520 --> 00:18:46,477
example, they built the Tesla Shanghai
Gigafactory in only 168 days. People

338
00:18:46,560 --> 00:18:50,157
point to Boston Dynamics as evidence
that the US is winning, but they're

339
00:18:50,240 --> 00:18:54,037
missing the speed and scale.
Boston Dynamics is basically one of two

340
00:18:54,120 --> 00:18:55,997
advanced humanoid robot companies based

341
00:18:56,080 --> 00:18:58,277
in the US. And they've been working on

342
00:18:58,360 --> 00:19:01,157
Atlas for almost 15 years. China has

343
00:19:01,240 --> 00:19:05,837
dozens and dozens of manufacturers with
advanced humanoid robot solutions that

344
00:19:05,920 --> 00:19:09,277
have sprung up in only two to three years.
Today, they're producing

345
00:19:09,360 --> 00:19:12,757
thousands of robots annually
and deploying them to their megafactories.

346
00:19:12,840 --> 00:19:16,917
At this rate, the US is going to lose
the race just like we did with drones

347
00:19:17,000 --> 00:19:20,477
and electric vehicles. All right, guys,
that's it for today's video. I'll see

348
00:19:20,560 --> 00:19:24,000
you guys next week with another one.