Vivian Wang

And so the government can't just say, okay, this is the particular direction that you need to go.

We're going to throw money at this particular problem and we will suddenly be the world's AI leaders.

You really need to give scientific minds and researchers kind of the space and freedom to experiment and to kind of follow where their scientific intuitions or their research is leading them.

There's a longstanding stereotype that might be a bit of an overgeneralization, but a lot of people tell me that they think it still holds true, which is that China is really good at the 1 to 10 perspective.

of scientific research, which is taking some kind of scientific discovery and finding the ways to just apply it everywhere and really make it useful.

But it's not as good at the zero to one, which is just getting to that breakthrough discovery in the first place.

And I think that's where the political environment does play a little bit of a role.

There are two other really major areas.

So one is chips and another one is talent.

So on chips, which are the powerful hardware that's necessary for training AI models, the fact is that Chinese chips are just not as powerful as American ones.

So Chinese AI companies are still really reliant on chips from NVIDIA to make the best AI that they can.

NVIDIA, an American company.

An American company.

Right.

AI researchers every year.

But without the sort of open, innovative environment that we were just talking about, many of them may choose and do choose to go to the United States.

And so Chinese companies and Chinese policymakers have talked very openly about how a shortage of talent is another problem that they have to face.

I think if the end destination of all of this AI is indeed AGI, this superhuman intelligence that is just going to run the world, then I do think American companies are closer to that.

I do think Silicon Valley is closer to the cutting edge of technology.

But it is important to point out that China is not that far behind.