Tag: ai bubble
Boom? If AI Sales In The US Go South, Let's Not Bail Out Big Money Bettors

Boom? If AI Sales In The US Go South, Let's Not Bail Out Big Money Bettors

I was struck by a graph showing OpenRouter’s measure of AI usage this year. (It appears in a newsletter published by Deutsche Bank’s chief economist, Jim Reid.)

There are two striking features to the graph. The first is that usage of Chinese AI passed the usage of U.S. AI in the last week in May. This had also happened for the last week in March, but the U.S. went back into the lead in April. However, this time around, the Chinese models extended the lead through June so that for the first week in July, they look to be about 40% higher. That might be great news for Chinese AI, but not so good for U.S. makers.

The other feature to the graph that is even more striking is that usage of U.S. models actually fell in the most recent week. The story of a huge AI boom is usage increasing at an extremely rapid, and maybe even increasing, pace. A decline in usage is not supposed to be in the cards.

To be clear, this is just one week, and perhaps there were unusual factors that depressed AI usage in the first week in July, like the holiday. But even if the one-week fall can be dismissed, total usage was roughly back to where it was four weeks ago, as there was very little growth in the prior two weeks. That is clearly not a story of an AI boom, or at least a boom in U.S. AI. We have to wonder how many weeks of weak sales will it take before some of the big AI investors get worried?

If there is any possibility that the massive investments the AI companies will pay off, usage has to increase hugely from current levels. The fact that it levels off for even a short period should be concerning, as should the rapid growth in the usage of Chinese AI. The U.S. companies have to both be able to sell a huge amount of their AI, and they also have to be able to sell it at a high price. Chinese AI that is comparable in quality for most uses and sells for a fifth or even a tenth the price will pose a serious obstacle.

Can the Big Money Folks Really Be That Clueless?

It may seem hard to imagine that people who manage tens, or even hundreds, of billions of dollars in pension funds or hedge funds can be totally clueless about the market prospects for the companies on which they are placing big bets. But the housing bubble wasn’t that long ago.

Back then, huge funds were prepared to believe that securities that were backed by subprime mortgages, often made with no money down, were a safe bet. And AIG, the largest insurer in the world, was prepared to back up these bets with hundreds of billions of dollars in credit default swaps. When the bubble burst, its bankruptcy was a certainty had it not been for a massive government bailout.

And it was only four years ago that the geniuses who ran Silicon Valley Bank had to be taught that the value of bonds falls when interest rates rise. Of course, they also got a government bailout, so maybe that is the lesson the big money folks learned.

Anyhow, it would be good if we could get the rich to show a little respect for the market. If the AI bubble bursts, there should be some real career consequences for the folks who lost tens of billions for their clients, no “who could have known?” amnesties. And no government bailouts for the swashbuckling AI barons. Let them eat their losses.

Dean Baker is a senior economist at the Center for Economic and Policy Research and the author of the 2016 book Rigged: How Globalization and the Rules of the Modern Economy Were Structured to Make the Rich Richer. Please consider subscribing to his Substack.

Why We Don't Need (Or Want) Bernie Sanders' AI Sovereign Wealth Fund

Why We Don't Need (Or Want) Bernie Sanders' AI Sovereign Wealth Fund

I’m a big fan of Sen. Bernie Sanders (I-VT). He has done an enormous amount to move American politics and especially the Democratic Party to the left. He constantly stands up to the rich in the name of ordinary working people.

But I have to disagree with him on the idea of an AI sovereign wealth fund. This strikes me as wrong-headed from every angle.First and foremost, Donald Trump is doing his best to show us why it is often a bad idea to have the federal government directly involved in running private businesses. He is using the power of the government to stuff his and his family’s pockets in every way imaginable.

He also is using the government to force private businesses to suppress criticism as you’ll see on the Colbert show tonight. Why on earth would any progressive want to give this demented jerk more power?

We can say that Trump is an aberration, which we should all hope he is. But we elected this aberration twice. Does anyone want to say it can’t happen again?

The economics on this look even worse. The job-killing effect of AI exists much more in the minds of our political elite than in the data. Productivity growth, the measure of job killing, has been extremely weak the last two quarters. Quarterly data are erratic and perhaps the future will be different, but if AI is killing off large numbers of jobs, it is doing a great job concealing the evidence.

Most likely the AI sector is in a massive bubble. At its peak value, Nvidia’s market capitalization was roughly 20% of U.S. GDP. In the late 1990s tech bubble, Microsoft’s market cap peaked at less than 6% of GDP.

An AI sovereign wealth fund is likely to end up being a mechanism to shovel yet more money to Elon Musk, Mark Zuckerberg, and the rest of the right-wing billionaire gang. We have already given this crew enough money.

I doubt that we will see massive AI-related job displacement, but if we do, we have old remedies that should work just fine.

1) a workable corporate income tax at a higher rate, for all companies. The best way to do this is to require companies to turn over non-voting shares equal to the targeted tax rate (e.g. 25% of shares for a 25% tax rate).

2) serious anti-trust enforcement. It is likely that Chinese AI will be very competitive, and probably much cheaper, than the domestic stuff. We let in Chinese-manufactured goods to screw large segments of the blue-collar workforce. We should not have protectionism to keep Elon Musk and Mark Zuckerberg ridiculously rich.

3) Stronger labor standards. We set the 40-hour workweek 90 years ago and have not changed it since. Other countries have shortened the work week/work year. If AI is going to give us the promised boom in productivity, let’s lower the threshold to 32 hours, or possibly even lower. We can also double the overtime premium to 100% rather the 50%.

We have all the tools needed deal with an AI productivity boom; we just lack the political will to use them. The sovereign wealth fund idea is a massive leap in the wrong direction.

Dean Baker is a senior economist at the Center for Economic and Policy Research and the author of the 2016 book Rigged: How Globalization and the Rules of the Modern Economy Were Structured to Make the Rich Richer. Please consider subscribing to his Substack.

Expert Warns That AI Bust Is Now Inevitable -- And Will Sink Trump's Economy

Expert Warns That AI Bust Is Now Inevitable -- And Will Sink Trump's Economy

The Wall Street Journal and other industry observers keep saying artificial intelligence investment is the one thing “saving” President Donald Trump’s stock market time and again, as Trump’s economy plateaus or tanks other stocks. However, Asad Ramzanali, director of AI and technology policy at the Vanderbilt Policy Accelerator, says AI overinvestment and risky financial engineering have made an AI crash more likely.

“I started [my research] not assuming we’re in a bubble, but that if we are, we should be prepared. As I got deeper into this, I became convinced that we are in a period of overinvestment where the money going out the door in the industry, which is primarily for data centers and chips, doesn’t match the money coming in,” Ramzanali told Washington Monthly podcast senior editor Anne Kim.

Ramzanali said research shows “$2 trillion is what the annual revenue from AI will have to look like to recoup” all this investment — and that’s not what can happen in the real world. So, prep for the inevitable bust.

Companies that build data centers -- Amazon, Microsoft, Google, Meta, and Oracle -- are making estimates in the 2026 capital expenditures that promise “higher percentage of GDP than the Manhattan Project, the expansion of electricity, the Apollo space program, the building of the interstate highway system, the broadband build out in the ‘90s, everything but the Louisiana Purchase. This nets out to about $700 billion of investment this year,” said Ramazanali.

In other words, curb your enthusiasm. But tech companies now make up one third of the stock market, and banks are invested in those tech companies in big ways like private credit, structured finance and endless pools of capital all funneling into similar investments.“[W]hen you’re talking about something that is this large, this high of a magnitude of our whole economy, that’s where I start to get worried about the spillover effects into the rest of the economy,” said Ramzanali.

What this means for the Trump stock market — which is practically all Trump has left to brag about — is nothing good for Trump.

The New York Times reports Trumps largely steady stock market keeps assuming it “will always be saved” by the government and that markets are “not properly pricing risk, because they really don’t have to.”

“ … [But] the new rescuer investors are counting on — artificial intelligence — is vulnerable to the exact risks markets are ignoring,” reports the Times. “This has huge consequences. … This reliance on A.I. looks like an extraordinary concentration of bets” that the Times reports is “likely straining their cash cushions.”

Nobody will want to be president when the only stable stock buttressing Trump’s economy in a time of widely-fluctuating gas and grocery prices suddenly goes wobbly. And Trump has three more years for the wobble to hit him.

The $12.5 Trillion-Dollar Question: When Will That AI Bubble Burst?

The $12.5 Trillion-Dollar Question: When Will That AI Bubble Burst?

I often get that question. I can’t say I have a very good answer.

Going back to the last bubbles, it would be difficult to identify any events in the world that precipitated the collapse of either the 90s tech bubble or the housing bubble in the 00s. Both times the economy seemed to be moving along at healthy clip just prior to the collapse.

There had been warnings in both cases. In the 1990s bubble it was hardly a secret that many totally crazy businesses were raising hundreds of millions of dollars in IPOs. Investors were worried about missing out on the next Microsoft, so they were willing to throw big bucks at seemingly hare-brained schemes, just in case.

In the housing bubble, the fact that many of the mortgage loans being issued were of rather dubious quality was hardly a secret. Lenders were issuing loans at 100 percent of appraised value and sometimes more. In many cases, people were borrowing in excess of the value of their home to cover closing costs or moving expenses. The verification on these loans was minimal. There were frequent jokes about “liar loans” or NINJA loans, with NINJA standing for “no income, no job, and no assets.”

But these warnings came well before the crashes. There is no obvious event that caused the stock market to turn in March of 2000 or the housing bubble to peak in the summer of 2006.

The Federal Reserve arguably played a role in the latter. The federal funds rate rose from its tech recession low of 1.0 percent in the spring of 2004 to a peak of 5.25 percent in the summer of 2006. This made mortgages more expensive, which made it harder for people to pay bubble inflated prices to buy homes. But the increases were gradual and the impact on 30-year mortgages was minimal. Of course, since many borrowers were taking out adjustable-rate mortgages at the time, higher short-term rates did matter.

In the 1990s, there was only a very modest increase in the federal funds rate, rising from 5.5 percent in the fall to 6.0 percent by March. It rose further into the spring, but the market had already turned at that point.

With this history, I don’t know what might cause the bubble to burst. Just to pick up on a point I made last summer, it is very hard to tell a story where the current price of the big AI-related companies makes sense. Nvidia has a current market capitalization of $4.8 trillion. If investors expect a 10 percent nominal return on the stock, in ten years it would have a market capitalization of $12.5 trillion. If we assume its earning have caught up so that it has a price/earnings ratio at that time of 20 (pretty high for a mature company), then its after-tax profits in 2036 would be $620 billion. That would be almost 15 percent of all after-tax profits in the U.S. economy, according to the Congressional Budget Office’s projections.

The idea that one company would have 15 percent of all corporate profits is not impossible, but it doesn’t seem like the most likely scenario. Alphabet, which is obviously an incredibly successful company, currently has about 4.6 percent of after-tax profits, so will Nvidia be more than three times as large relative to the economy in a decade than Alphabet is today?

Furthermore, is that anyone’s best bet? If this is a possible but not likely scenario then people must be expecting considerably higher returns on their investments in Nvidia stock, say 15 percent or 20 percent. In those cases, we would need for the company’s profits to be 25 or 30 percent of all corporate earnings in 2036 to make sense of Nvidia’s share price. This seems to be getting pretty far-fetched.

Who knows when or what will make the bubble burst. Maybe the Chinese competitors get enough market share with their lower-priced AI that it will become clear even to the Silicon Valley geniuses that their big jackpot exists only in their heads. Maybe their revenues will stop meeting projections. But whatever causes it, the story of the collapse is not likely to be pretty.

Dean Baker is a senior economist at the Center for Economic and Policy Research and the author of the 2016 book Rigged: How Globalization and the Rules of the Modern Economy Were Structured to Make the Rich Richer. Please consider subscribing to his Substack.

Reprinted with permission from Dean Baker.

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