Photo by Mads Eneqvist
Before we catch up on the game, here are the latest numbers on market capitalization and P/E ratios:
It’s the fourth quarter and the game is tied, but it’s not clear the odds are even. Silicon Valley jumped out to a quick 28-0 lead but then let Chinese AI rack up 28 straight points. They haven’t been able to get a first down since early in the second quarter. Making matters worse, Coach Trump keeps switching quarterbacks and benching his star running back.
With the start of the football season, the analogy seems to be a reasonably good description of what we are seeing with AI development. There is no doubt that two or three years ago the Silicon Valley AI team was far ahead, with China nowhere in sight. Then there was the DeepSeek moment last winter, when the startup produced an open-weight model that had performance in the ballpark of the leading Silicon Valley models, and selling at a small fraction of the price.
Since then, Chinese AI companies have produced a string of models that come ever closer, and in some areas surpass, the leading Silicon Valley models. They also maintain their enormous cost advantage, typically selling tokens for less than one-fifth the price — and often less than one-tenth the price.
If this is hard to grasp, imagine you’re Elon Musk trying to sell Teslas for $50K a piece. Suppose there are Chinese models that are every bit as good selling for $5K. How do your business prospects look? That is the question US AI producers, as well as everyone in the supply chain, needs to be asking.
And this story should be well known to anyone putting money on the table. That picture doesn’t really seem to be in dispute by people who follow the industry closely. The basic story is the same everywhere. The Chinese AI companies haveattained comparable performance as the best US models. In addition to being far cheaper, the open-weight Chinese systems also have the advantage that they can be downloaded and run on a company’s own computers. This means both that the systems can be customized, and they don’t have to worry about OpenAI sharing their customers’ data with the highest bidder.
As a result of the lower prices and greater flexibility, Chinese AI is rapidly gaining the bulk of the world market. According to data from OpenRouter, Chinese AI went from less than 10 percent of world AI usage at the start of 2025 to more than 60 percent in early July.
What’s the story that turns this around in the US favor? As much as Donald Trump might like to win the AI race, he doesn’t seem like he is helping the cause. He can’t decide whether he wants China to buy Nvidia chips or not. The answer is likely to depend more on campaign contributions than on the health of the industry.
In the same vein, he tried to kneecap Anthropic, the leading US AI company by most measures, by declaring it a supply chain risk. This would have seriously hampered sales — not just to the military, but to businesses across the economy. Fortunately for Anthropic and fans of US AI, the courts seem to have nixed this effort, although Trump may appeal the ruling.
China has a whole fleet of nimble AI companies that are constantly producing new cutting-edge models. It has a near limitless supply of electricity (thanks largely to wind and solar), and it vastly outnumbers the US when it comes to scientists working in AI-related areas. In this world, how does the United States prevent China’s near parity from turning into a total rout? Coach Trump seems to be going 180 degrees in the wrong direction right now with his wars on wind and solar energy, and his attacks on immigrants.
Just to remind folks: Many of the scientists working on AI are not white, and a good number are immigrants. They may not relish working in a country where white nationalism has become the official religion, especially when there are many other countries that are happy to reward their skills.
The Deficit Whiners Disagree with Wall Street on AI
I learned arithmetic in grade school. I will always stand by it since it has always stood by me. As I’ve noted in the past, if we are not seeing a bubble, the huge stock market valuations of AI-related companies imply that the economy will grow far more rapidly in the next decade or so than is projected by most professional forecasters, including official forecasters like the Congressional Budget Office (CBO).
If you were one of the people sharing in the national scare over the debt hitting $40 trillion, then you must accept that the economy will continue to grow relatively slowly, and we will not see the massive AI growth dividend implied by the current valuation of AI-related stocks.
If the economy grows at a 3.5 percent annual rate over the next decade, which assumes that AI raises productivity to around 3.0 percent annually (the rate we had from 1947 to 1973), then the economy will be 41 percent larger in 2036 than it is today. The CBO projections assume the economy will be less than 20 percent larger. The gap between 41 percent growth and the growth projected by CBO comes to almost $7 trillion annually, measured in 2026 dollars.
Can anyone with a straight face say how we are supposed to be terrified by paying $1 trillion a year in interest on the debt, when AI is giving us $7 trillion to play with? Mr. Arithmetic says that’s crazy.
This is far from the first time where policy debates have been impervious to simple arithmetic. In the 1990s, the central theme in the Social Security debate was generational equity.
One story that the deficit hawks came up with to justify cuts to Social Security was that the Consumer Price Index (CPI) was substantially overstating the true rate of inflation. The usual range was 1.0-1.5 percentage points annually.
The problem with this complaint is the CPI is our yardstick for comparing real income over time. If our yardstick is broken, and actual inflation is 1.0-1.5 percentage points less than our measures show, then real income is rising 1.0-1.5 percentage points more rapidly than we had thought. It also would rise 1.0-1.5 percentage points more rapidly in the future than the projections show. That would mean that most Social Security beneficiaries had grown up much poorer than we recognized at the time and that future generations of workers would be far better off than we ever could have hoped. How can that be an argument for cutting Social Security?
However, this arithmetic eluded most people in the debate. I was once on a show with Wyoming Senator Alan Simpson, who passed as an intellectual in policy circles. He went on a diatribe where he said some economists tell him that the CPI overstatement could even be 2.0 percent — and then added that our grandchildren will be living in chicken coops.
Anyhow, however much Washington policy types and Wall Street investors may resist the notion, arithmetic cannot be defeated. If AI is going to deliver a growth boom, there is no reason to be worrying about the deficit. In my own case, I’m not betting on a massive growth boom, but I still don’t think the deficit is much to worry about. But if you do buy the AI boom story, don’t make yourself look foolish by yelling about an unsustainable debt.
This first appeared on Dean Baker’s AI Bubble Monitor.
