The United States should avoid lagging behind China in AI application and popularization

[00:00.43] But China discounts energy costs for a chip company by 50%.

[00:08.13] That's right.

[00:09.19] They provide free transportation for employees to come out to the factory.

[00:13.70] That's right.

[00:15.03] I mean, you don't, you can't do that.

[00:16.36] Our energy cost is more expensive than theirs in the first place.

[00:19.02] Absolutely. And then they discount it 50%.

[00:21.15] And so it's probably, we'll probably call it four to eight times the cost.

[00:25.66] So tell me, how do you feel about this great competition with China?

[00:32.57] I mean, the government is putting enormous resources underneath their champion.

[00:40.00] We don't do that in this country.

[00:42.40] You know, how do you feel about that?

[00:44.79] Well, before I get there, don't let me not answer that question.

[00:49.30] I'm dying to answer it.

[00:50.36] But let me handicap the next two layers.

[00:51.96] The model layer, the model layer, United States frontier models, our frontier models are unquestionably world class.

[01:03.91] We are probably, call it six months ahead.

[01:06.83] However, out of the 1.4 million models, most of them are open source.

[01:16.66] China is well ahead, way ahead on open source.

[01:20.12] Now, the reason why open source is so important is because without open source, startups can't thrive, university researchers can't do research, you can't teach AI, scientists can't use AI.

[01:33.40] Basically, all of the industry around your economy have no ability to fundamentally advance themselves unless you have open source.

[01:44.56] Without Linux, where would we be? Without Kubernetes, without PyTorch, all of these different types of technologies that made AI thrive are all open source.

[01:54.65] They are well ahead of us on open source.

[01:57.30] And then the layer above that, applications.

[01:59.95] If you were to do a poll of their society and ours, and you ask them, is AI likely to do more good than harm?

[02:12.97] They're going to say, in their case, 80% would say AI will do more good than harm.

[02:19.08] In our case, it'd be the other way around.

[02:21.73] And so that tells you something that's very, very important.

[02:24.66] Socially, socially, we need to be careful not to describe AI in these science fiction movie ways of describing AI and causing people so much concern.

[02:36.88] We want to be concerned, but we also want to be practical.

[02:40.60] AI is about automation.

[02:42.45] And that area, I think that we need to be careful not to fall behind in the application and the diffusion of AI, because in the end, whoever applies the technology first and most wins that industrial revolution.

[02:58.66] As you know, electricity was invented in the UK, but the United States applied it faster, more broadly, and as a result, look where we are.

[03:11.41] And so we have to be a little mindful.

[03:12.74] And so anyways, I just handicapped that stack.

[03:15.40] And I don't think it's—it's important when you're looking at AI not to see it as a holistic thing.

[03:21.77] It's really not about ChatGPT versus DeepSeek.

[03:24.69] You have to look at it across all of the stacks and across all of the industries.

[03:28.67] Does that make sense?

[03:29.47] It's a little bit more complicated than one simple answer.