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So in 2003 or thereabouts, you get this enormous surge of Chinese exports into The US, and people lose their jobs in a very concentrated way. Certain industries just get wiped out. And for the first time in the history of economic study of the effects of trade, you actually see negative effects on workers. But if you look at the size of the China shock, in a twelve year period between 1999 and 2011, the total number of jobs displaced was 2,000,000, which is actually a small number in a huge labor market like The US where there's a lot of churn month to month anyway. And yet the political reaction against trade, against globalization in terms of the swing towards protectionism, frankly, in both political parties was enormous.

And so he imagined Uber way before Uber existed. That was point number one. Point number two, he went to see various entrepreneurs who were in this space, and he checked them out. And he had the discipline not to invest in them. Because although they were kind of going at the right thing, there was some hair on the deal, some wrinkles, some way they were approaching it that just felt like it wasn't gonna be quite right. So he resisted. Uber came to him before Travis was the CEO. And Bill said, I'm not doing that because he didn't think the CEO at the time had what it took. And then there was a internal switch at at Uber. Travis became the leader. Bill meets him and, like, bang, he immediately invests because he's been waiting and waiting waiting for the idea to be paired with the right person.

What's the bare case? I'd say the bare case would be, first of all, that Google DeepMind has the deep pockets of its parent company behind it. A massive kind of consumer surface, which allows it to roll out the models to literally two and a half billion people or something through AI mode in search, AI overviews, AI mode. They can put it into Gmail. They can put it into everything. I think in terms of retail deployment and financial muscle, it's quite tough to go up against Google. So that's one kind of bear case. And the other would be that sort of businesses who are the consumers of all these tokens decide in a couple of years' time the tokens are too expensive while not actually getting as much productivity as we hoped. These things called humans are quite productive after all, and we're just gonna spend less on AI than everybody expected.