A hurricane seems about to hit the nests of the black angels (to use the ravings of Peter Thiel) and upset them, plunging them into the misery into which they will overwhelm all those who have invested in their follies. --- Artificial intelligence --- Artificial Intelligence (AI) isn't intelligent: it's based on linear inferences and owes its appeal to the speed and number of chips that, working in parallel, allow for a huge number of calculations and comparisons to be performed in a timely manner. AI isn't even artificial, since it relies on logical operations very similar to those performed by the human brain. Again, the difference lies in the number of operations that can be performed in a short time. AI is also different from the programming we're used to: in a certain sense, it relies on analogies that don't guarantee the correctness of conclusions (in this sense, it's very similar to natural human reasoning ). However, we're seeing huge and growing investments, especially in the US, in the belief that it will have a huge impact on many areas of human activity.
Among others: Microsoft, pioneer and main funder of OpenAI, which has integrated AI into its entire range of cloud products and services; Alphabet (Google), which through Google DeepMind and the Gemini family of models, is a historic and current pillar of AI research and application; Amazon Web Services (AWS), which provides large-scale cloud infrastructure and dedicated services for the development and deployment of enterprise AI; and Meta, which develops and releases the open-source Llama model suite , integrating artificial intelligence into its social media platforms.It's worth remembering that these are parasitic companies that feed their "creatures" by plundering billions of data produced by universities and other public institutions, including researchers, writers, journalists, and others, without paying any royalties, in defiance of intellectual property protections.
Added to these are the companies that produce the hardware needed to run the various codes, first and foremost Nvidia, the world leader in GPU production, which relies on the Taiwanese TSMC (Taiwan Semiconductor Manufacturing Company), and the Dutch ASML, still the only company capable of producing nanoscopic chips that allow for great execution speed thanks to the development of lithographic techniques in the extreme ultraviolet: to give an idea of the complexity required, the machine developed by ASML involves almost half a million components and requires the use of elements produced by other German and American high-tech companies.
So far, the stock market growth of companies involved in AI development has been the result of a Ponzi scheme (chain letter) in which revenue comes primarily from the sale of products needed to build new data centers from one company to another, rather than from the final use of the software by external companies .
The only example of a resounding success of AI techniques comes from the prediction of the spatial shape of certain polymers, which has enabled the development of new drugs and the treatment of chronic diseases: Eli Lilly has benefited in particular.
Outside of this case, there are no reports of significant improvements in the efficiency of large companies (those that would guarantee greater profits). Currently, AI appears to be having a significant impact only on micro-companies, startups, where individuals are able to do the work that previously required a pool of workers.
China
Adding to the uncertainty surrounding the actual success of AI is the presence of a formidable competitor for the United States: China. For starters, the success of AI is almost a matter of life and death for the US: currently, AI is responsible for 40% of US GDP growth and contributes to 80% of stock market capitalization. A potential collapse would have unimaginable consequences for the American (and global) economy. The same cannot be said for China, which hasn't invested comparable amounts of money in this sector.
Specifically, China's Achilles heel has been the performance of individual chips. To maintain their advantage, Trump and then Biden had already imposed bans on the sale of the most advanced chips. But as often happens, the resulting shortage pushed China to launch a sort of Manhattan Project (formerly developed by the US to develop nuclear weapons) to develop artificial intelligence, the Next Generation AI Development Plan. This attracted investment in research and workforce training, intensifying cooperation between the government and the technology industry with significant public investments in data centers, power transmission, and semiconductor production.
Through a combination of industrial espionage, reverse engineering, and the development of innovative techniques, the Chinese are now able to produce far-ultraviolet beams at the same frequencies as the ASML. The problem is the lack of reliability that impedes mass production (too much waste).
Although the gap with the US has not yet been closed, the quality of Chinese semiconductors has improved to the point that China itself has banned the purchase of the penultimate-generation American chips, the H20s, which Trump had authorized. This has put Nvidia in a difficult position, as it has had to give up a significant portion of its market share. It should also be noted that Beijing controls the entire supply and production chain and is therefore not subject to blackmail.
The same cannot be said of the United States, given that semiconductor production requires highly refined rare earths. Last year, in 2025, the US showed off, imposing unreasonable tariffs on products from China. As a result, the Chinese blocked the sale of rare earths, forcing the US into an embarrassing backtracking, so significant that the tariffs on Chinese products fell below their value when the orange clown took office. Months have passed, and the Americans have begun reintroducing various bans on Chinese products, resulting in Beijing once again restricting exports of rare earths used in dual-purpose products (both civilian and military). The division is highly subjective, and it's reasonable to assume the Chinese could tighten the reins as needed. Speaking of Achilles' heels, this one seems much more critical than the Chinese one.
However, the speed of a single chip isn't everything, even within the context of hardware. Data processing systems work in parallel with chips that operate simultaneously, but which must exchange information. Traffic management is an equally significant issue. Virtually the entire world uses CUDA (Computer Unified Device Architecture), a platform developed by Nvidia and typically implemented in graphics cards. At the same time, the Chinese have developed CANN (Computer Architecture for Neural Networks), which, in addition to being independent of the American company, appears to be able to optimize communication traffic between the various individual chips by exploiting a three-dimensional structure. This result was also achieved thanks to a national effort (the so-called Manhattan Project) that coordinated giants such as Alibaba, Tencent, and Huawei.
Along the way, we arrive at the software. The Chinese have chosen an open source or open source approach , which can be downloaded, modified, and used freely, unlike the proprietary, encrypted software typically developed in the US. This American choice, in the past (and currently), has forced users to buy blind and purchase updates. This is the choice that allowed Microsoft to become what it is today, imposing a first-night tax on PC purchases. But this choice also worked thanks to its European vassals, who, despite having developed competitive open source software in the 1990s (UNIX, which later gave birth to Linux), preferred to pay protection money and give priority to Microsoft software in public administrations.
But China is not the EU, and has not only developed open source models, but is working to distribute them to the rest of the world, because the potential commercial success of AI depends on the number of users, and clearly, the ability to tweak the code as needed represents a strong incentive for development.
Another factor to consider is the time required to train the AI for a specific task. AI isn't born learned; it needs to be trained, and training requires time and, above all, energy (electricity). To give an idea of the expected consumption, the American Stargate program, which involves the largest investment funds (Black Rock, Vanguard, State Street), predicts the need to install 10 Gigawatts within 5 years to operate the various data centers: this is more power than what is currently installed in Japan.
Therefore, energy is expensive (a small reminder for the inept European governments who are doing everything they can to commit energy suicide), and it is therefore essential to save on training costs: even if the software is free, any developer must cover the costs of developing the code itself.
Here, another factor seems to emerge in favor of Chinese models, particularly Deep Seek, which appears to require much less time (presumably related to the logical structure of the codes).
Added to this is Qwen (Alibaba): one of the most popular and downloaded language models in the world on platforms like Hugging Face, constituting a very valid alternative to US products. We can also add GLM (Zhipu AI), which provides advanced models (e.g., GLM-5.2) with permissive licenses (often MIT), offering excellent coding capabilities and support for very general contexts.
Remaining in the context of software, the potential of a given AI platform requires skilled developers to be realized, and here another sore point for the US emerges. China produces 5.357 million STEM (scientific) graduates each year, compared to 820,000 Americans, many of whom later leave the country or are forced to do so by Trump's policies. The gap isn't just virtual: Tsinghua University produces more computer science patents each year than MIT, Stanford, Princeton, and Harvard combined.
A final distinctive feature of the Chinese approach concerns the type of objectives. Unlike US companies, which are mobilizing resources to develop a futuristic yet "abstract" type of artificial intelligence (General Artificial Intelligence) that mimics the workings of the human mind, Chinese companies focus on pragmatism and direct it toward the execution of specific functions (Narrow Artificial Intelligence), especially in the fields of surveillance, public administration, education, and the high-tech industry. This is demonstrated by the gigantic complex built by Xiaomi, which, by integrating artificial intelligence into fully robotic production processes, produces an electric car every 76 seconds. This policy has made the Chinese artificial intelligence sector far more accessible. However, the experimental application of AI in some schools near Shanghai among primary school students (ages 6-10) is disturbing. Helmets with electrodes are being fitted to students to monitor their attention span across different subjects to guide their future academic careers.
With its strategy, China has been able to claim not only that it has closed the gap with US industry, but also that it is growing faster in both AI and chips because the model it has adopted allows for greater pragmatic and open innovation, circumventing US tariff policies that are stifling the market. As a further example, Kimi (Moonshot AI), a company with just 200 employees and an investment of just $6 million, has proven capable of managing massive projects and delivering high-level performance. It is establishing itself as the most competitive AI company, compared to a direct competitor with 5,000 employees that has invested a whopping $100 million to produce a product with equivalent performance.
Looking ahead, China aims to completely exclude the United States from its supply chains, including not only hardware but also US and European software of all types, which will need to be completely replaced with Chinese counterparts, particularly in the critical sectors of finance, energy, and public administration.
The bursting of the AI bubble
According to some reputable analysts who predicted the bursting of the 2008 bubble, a new bubble is brewing, involving AI. Its consequences will be devastating due to the immense amounts of capital invested, whose returns are destined to collapse. The dizzying growth of the AI bubble finds a disturbing parallel in this context. The trending increase in interest rates on corporate bonds issued by companies integrated into the AI ecosystem, combined with the rise in credit default swaps on the major companies operating in the sector, signals growing nervousness among institutional investors. Consider the stock market maneuvers of the Thiel Macro fund (led by Peter Thiel, co-founder of PayPal and Palantir), which has liquidated shares of Nvidia and drastically reduced its exposure to Tesla. Alex Karp and Stephen Andrew Cohen of Palantir, meanwhile, have sold tens of millions of dollars worth of shares in their own company. Similar operations have been carried out by Fidelity, T-Rowe Price, JPMorgan Chase, SoftBank, and Stanley Druckenmiller, a leading speculator who became famous for his 1992 attack on the pound while working with George Soros and Michael Burry. For them, the staggering profits made by companies operating in the sector are based on "one of the most common frauds of the modern era," namely the artificial manipulation of payback periods. Companies spread hardware investments over long periods, given the average "life" of chips of about two years: "To justify the current price multiples, now suspended in the void in some cases, revenues ten times higher than those generated today by artificial intelligence would be needed, and they would be needed very quickly, because the payback cycle for data centers and chips is extremely short: perhaps five years."
Among the causes of the potential crisis, they point to geopolitical and economic uncertainty and excess liquidity that has inflated the value of assets far beyond their fundamentals. The combination of artificial intelligence, high-frequency trading, and investment algorithms that dramatically amplify market fluctuations is creating an overabundance of liquidity, leading markets onto a very dangerous trajectory. What is happening now will lead to a further phase of verticalization among the players operating and managing the market. No one knows when the bubble will burst, but it will eventually happen, and then a run on banks could be triggered.
The implications would be particularly severe for consumption, where growth is already weaker than before the dot-com crash. A shock of this magnitude could reduce it by 3.5 percentage points, translating into a 2-point decline in overall GDP growth, even without considering the decline in investment. The global repercussions would be equally severe.
Foreign investors would also be affected, potentially suffering losses exceeding $15 trillion, equivalent to approximately 20% of global GDP, penalizing holders of US securities, including European and Italian institutional investors. By comparison, the dot-com crash caused losses for foreign investors of approximately $2 trillion, approximately $4 trillion in current currency, and less than 10% of global GDP at the time of the 2008 crisis. This sharp increase in spillovers underscores how vulnerable global demand is to shocks originating from the United States.
The fact remains that the AI bubble is 17 times larger than the New Economy bubble and four times larger than the subprime mortgage bubble that triggered the 2008 crash.
The size and complexity of the AI bubble could collapse the global economy for a decade, so a "public parachute" should be provided for OpenAI's colossal investments in chips, data centers, and related infrastructure to mitigate the financial risks arising from rapid technological change. The fact is that OpenAI, like Nvidia and other high-tech giants, have become too big to fail, like the Wall Street banks bailed out in 2008. In other words, the entire US stock market is at risk of crisis, and with it, much of the economic system.
In other words, the ongoing war between the US and China could be won without a fight, in keeping with the best teachings of Sun Tzu, who stated that the best victory is the one achieved without a fight.
Antonio Politi
https://www.ucadi.org/2026/09/06/ia-ovvero-la-caduta-degli-dei/
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Source: A-infos-en@ainfos.ca
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