AI AND "REALISM IN POLITICS" (II)

 

La mayoría de los teóricos sociales de los siglos XIX y XX parten del supuesto naturalista de que los hombres están determinados causalmente, que son individualmente débiles y potencialmente omniscientes, que tan solo el conocimiento desvelará de forma progresiva su melancolía y su absoluta dependencia con respecto a una red de factores causales identificables, que el resto es megalomanía y engaño.Esta yerma doctrina no está basada en la observación o experiencia del comportamiento humano ni en el experimento social o en cualquier método empírico, sino en una vasta analogía con el resto de la naturaleza.Los estadistas de más éxito en la historia de la humanidad por lo general han asumido, lo supieran o no, lo opuesto: que los individuos eran en ocasiones fuertes (porque eso piensan de sí mismos y de sus principales oponentes), en gran parte ignorantes (ignorantes de la mayoría de los factores con los que se veían obligados a tratar, que eran asumidos sin que hubiera una conciencia de ello y con los que se trataba casi en la oscuridad) y, dentro de algunos límites,libres.Mientras los supuestos contrarios sean defendidos  por aquellos que creen en las reformas radicales en nombre-falsamente invocado- de la ciencia y la razón y de la observación pura de la naturaleza, los hombres seguirán siendo víctimas de teorías y abstracciones que son una forma de idolatría -y de sacrificio humano- más fría y más destructiva que las ilusiones y engaños inteligibles de anteriores generaciones, y por la que las generaciones futuras, con incredulidad e ira, condenarán justificadamente a nuestra época.

Isaiah Berlin (Realism in politics. Traducción Clara Morán Calvo-Sotelo) 

 

Grok Conversation

Replying to @ruiz_zapatero

• This post features an artistic overlay of Alexander Herzen's 19th-century quote critiquing authoritarian system-builders on Ambrogio Lorenzetti's 1339 fresco "Allegory of Good Government," visually linking medieval ideals of just rule to warnings against oppressive expertise.
• As part of a thread by Spanish lawyer Guillermo Ruiz Zapatero, it follows references to Lorenzetti's utopian Siena imagery and Manuel García-Pelayo's analysis of political myths, forming a meditation on freedom versus tyranny amid 2025's global political shifts.
• Herzen's line, from his exile writings and echoed in Isaiah Berlin's essays, underscores a liberal insight: true societal progress demands creators untainted by carceral mindsets  

TRUMP’S DILEMMA: TO BAILOUT OR NOT TO BAILOUT THE AI BUBBLE

JustDario 

Clearly, the major cause of concern lies in the overvaluation of all stocks tied to the AI bubble, starting from Nvidia, which drove the vast majority of the stock market gains for quite some time. Back in January, in “THE REAL ERA OF AI BEGINS, THE ONE OF THE AI CHARLATANS ENDS“, I warned about how the direction taken by US companies towards putting all their efforts into overbuilding a massive data center infrastructure, while ignoring the importance of software and data quality in the development of AI, would ultimately yield very little if not negligible returns despite the biblical amount of money being invested and planned to be invested in such an effort. Back at that time, investors did not immediately dismiss the huge DeepSeek breakthrough in achieving what the likes of OpenAI did with a fraction of the cost, but it did not last long, and after the April stock market rout, the euphoria was back in charge.

Acknowledging that China’s approach to building AI was the right one would have thrown a wrench into the whole narrative that allowed the likes of Nvidia and OpenAI to achieve unimaginable valuations. As a consequence, everyone on the western side of the world spent an incredible amount of resources to hide the truth and convince the investor audience of the opposite. All I am describing was corroborated by the biggest revenue round-tripping scheme among mega-cap companies ever orchestrated. A scheme that is still being called by the milder term “circular financing” that nobody dares to deny anymore. The ultimate result of all this reckless behavior, which, let’s be honest, had the sole purpose of inflating public and private companies’ valuations as much as possible, was what I described in: “THE DATA CENTERS FRENZY WILL BE REMEMBERED AS THE LARGEST WASTE OF CAPITAL IN HISTORY“

 Currently, the US government has almost $1 trillion of resources in the US TGA account. Do you think they will keep this money out of the market, watching the bubble collapse, or, like the Biden administration did twice, will they be willing to drain the US TGA account all the way down to zero in an ultimate effort to support the stock market and avoid the burst of the bubble as long as possible (ideally till US midterm elections)?

 

Politically speaking, spending public money to socialize losses of a sector that has already set itself on a path doomed to fail, that will require immense energy resources to run, and that will ultimately cause severe employment problems, won’t bode well with voters. The ultimate proof of how wrong US companies’ approach to building AI has been is demonstrated by 80% of the startups in the US currently using open source Chinese models to build their tech, not US ones (“China is quietly upstaging America with its open models“).

 

The dilemma the US administration is currently facing—to bailout or not to bailout its prominent AI players—will have to be resolved sooner or later. In my opinion, the greater the market correction caused by the bubble deflating, the greater the pressure on the US administration to do something, especially when stock losses start significantly impacting retirement savings. But for sure, whatever they will be doing will only bring temporary relief, compounding the problems in the future caused by the never-ending misplacement of capital caused by public bailouts of companies that instead should be let fail, allowing the system to cleanse and to put itself back on a more stable and sustainable footing upon which it can resume sustainably growing in the long run.

Unbearable lightness of the AI bubble

Satyajit Das 

The AI investment bubble is much bigger than those around dot-coms or sub-prime assets in the 2000s. Many aspects—from the technology to its finances—are not squaring up

 

Capital expenditure on AI is expected to total up to $5-7 trillion by 2030. It has added around 40 percent or a full percentage point to 2025 US growth. AI companies accounts for 80 percent of US stock returns. AI startup valuations based on the latest round of funding were $2.30 trillion, up from $1.69 trillion in 2024, and up from $469 billion in 2020. But AI’s capacity to generate cash and returns on the large required investment remains questionable. 

 

 Revenues would have to grow over 20 times from the current $15-20 billion a year to cover the current investment in land, building, rapidly depreciating chips, and power and water. Revenues totalling more than $1 trillion may be required to earn an adequate return. Microsoft’s Windows and Office, among the world’s most used software, generates less than $100 billion in commercial and consumer revenue. Less than 3 percent of its 800 million users currently pay to use ChatGPT.

 

In the first half of 2025, OpenAI, owner of ChatGPT, generated $4.3 billion in revenue, but spent $2 billion on sales and marketing and nearly $2.5 billion on stock-based compensation, posting an operating loss of $7.8 billion.

 

AI investment may be 17 times that of the 2000 dot-com and four times the 2008 sub-prime housing bubble. Rather than equity, it is funded by debt with the amount tied to AI totalling around $1.2 trillion, 14 percent of all investment-grade debt.

Investors have convinced themselves that the greater risk is underinvesting, not overinvesting. Amazon founder Jeff Bezos hails it a “good kind of bubble”, arguing that the money spent will bring long-term returns and deliver gigantic benefits to society—the tech-bro’s persistent bromide. But the share of used fibre-optic capacity is around 50 percent and the average global network use is 26 percent. When that boom ended, Microsoft, Apple, Oracle, and Amazon fell 65, 80, 88 percent, and 94 percent, respectively, taking 16, 5, 14 and 7 years to recover their 2000 peaks.

Consensual hallucinations notwithstanding, it would be surprising if the ending is different this time.