If you look at the technology sector, you will have already noticed that AI is advancing at a speed that is difficult to sustain. However, economist David McWilliams warns that the industry is building its foundations on what he calls «digital lettuce.»
The expert refers to the GPUs that power the AI models, with very expensive chips that depreciate quickly. He claims that big technology They invest billions in hardware that, in a matter of months, is outdated by the arrival of even more powerful modelscreating a frenetic cycle that could take its toll on the artificial intelligence ecosystem.
The speed with which architectures, manufacturing processes and computational capabilities are renewed makes each generation of GPUs a limited commodity. For McWilliams, this pace of obsolescence turns the expansion of AI into a fragile cycle, sustained by investments that lose value before justifying their cost.
When a technological boom is built on assets that wither so quickly, the possibility of a blowout increases. Even so, he recognizes that other analysts, such as Ed Yardeni, maintain a less alarmist and They believe that the depreciation will not be so devastating. But the debate is already on the table.
The United States and the permanent risk economy
Beyond technology, McWilliams insists that this phenomenon cannot be understood without observing the cultural meaning of money in the United States. He says that all you have to do is arrive in Los Angeles and get in a car to find conversations about Bitcoin, Nvidia, investment funds, startups or stock market movements.
This obsession with money is not superficial, since it has been part of the country’s social structure for more than a century. In his vision, The North American country has been configured as a society that embraces riskwhile Europe behaves as if it always needs an insurance policy.
This cultural contrast is what, according to him, explains why cycles like that of AI can be born, grow and, if necessary, collapse without destroying the system, so risk is not a threat, but rather fuel.
McWilliams even reviews the historical origin of this attitude, where the United States has been built on a mixture of ambition, speed and audacity. For him, this collective capacity to accept that failure and innovation go together is the reason why the country leads the great technological cycles of the last century.
The economist uses a particular approach to analyze these dynamics, where he considers money a technology. Just as fire transformed the way humans evolved, money changed the way we organize societies, productive structures and economic relationships.
That idea is the backbone of his book. History of Moneywhere he combines economics, anthropology and history to explain why financial cycles function as evolutionary processes. Here he incorporates the influence of Joseph Schumpeter and his «creative destruction», and which he mentions in Fortune.
If anything defines dynamic economies, says McWilliams, it is the ability to destroy the old to build the new. That is why he is not afraid of the explosion of AI: he considers it a natural part of the process. If GPUs today are «digital lettuce», tomorrow they will be something else and the country will once again reinvent itself from the remains.
Can AI become too big to fail?
On a political level, McWilliams rejects that the AI industry could become a protected sector like the military-industrial complex. He warns that the only real risk would be that technology companies manage to convince the government to protect chips as strategic assets, but he does not see this as likely.
He even anticipates that a populist profile like Donald Trump would be more inclined to confront Silicon Valley than to protect it. He says it bluntly: In the United States, the rich are not hated, the professional class is despised.. And that cultural element, he maintains, prevents AI from becoming an untouchable sector.
Given this, artificial intelligence advances on a technologically unstable foundation, fueled by hardware that expires too quickly to justify the size of the bubble. But far from seeing it as a systemic risk, he interprets it as another episode of the American economic cycle.
For the economist, the United States will continue to lead global innovation, even if the AI bubble crashes. The reason is simple, because the culture of risk and the predisposition to transform failure into opportunity are part of its economic DNA.
The mix of audacity, speed and irreverence turns the country into an environment capable of rising after each collapse and building the next technological revolution from the ruins of the previous one.