The excessive spending for "The AI Bubble" is not *a mistake* and it is not about AI - that is how the system works

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Todor ArnaudovTodor Arnaudov • YouYouThe Sacred Computer: Pioneer in Artificial General Intelligence: Thinking Machines, Creativity and Human Development [Looking for Partners, Collaborators etc.]The Sacred Computer: Pioneer in Artificial General Intelligence: Thinking Machines, Creativity and Human Development [Looking for Partners, Collaborators etc.]1w • 1 week ago • Visible to anyone on or off LinkedIn

The excessive spending* for "The AI Bubble" is not *a mistake*. It is not because "they don't understand the laws of scaling" etc. (see the comments to the Gary Marcus' post). This is [just] capitalism. (...) The goal of economy & the "leaders" of the "AI bubble" and other bubbles or apparently excessive overspendings and mindless expansions is not for being economical, to save resources etc. overall. The same is with spending for the Military ("Defense"), e.g. the EU program etc. - build weapons, apply them "creatively" and then rebuild = "efficiency", LOL - it generates "economical growth". Apparently the goal is to MAXIMIZE THE EXPENSES (which come from another source) and to cheat and deceive your "host" source that you optimize and that you spend the least possible (not enough), in order to take even more resources and to spend even more: this is [also a pattern of the] "consumer culture" and capitalism, not [of] "AI", LOL. 

In the case of the military spending: [the goal is] to cause maximum losses for the enemy,

[But on the way, the weapon producers cause "economical losses" for the suppliers of the resources for the production as well, because they extract raw resources, "workforce", energy, money, material from them and send the produced "goods" to the war theatre in order the production to be "utilized" and cleared, which helps to  create room for more new production and to justify the need for more resources.]

E.g. ML globally is paradoxically similar - its goal is presented as "optimizations", but how many times the same datasets are "relearned" from scratch on how many places and how many GPUs, how many useless benchmarks are testing things which are already known, improving the "SOTA" with 0.4 points, 4.2 points on MMLU, XYZA*. Thousands of papers [are] repeating almost the same, all countries [are] having "National AI strategies" and institutes (clones of the 2003 original with exponential financial requirements), yet the most of what's done everywhere is replication & multiplication with minimal variation and maximum spending - just like with the living organisms and their goals.

A lot of the investments, [especially some huge ones], are possibly money laundry or a cash-"circulation" mechanism, as with the famous cases [with the biggest players in this game]. The investors may be aware that they will not get return of their investment from "sales", however they might not care either. :)))

In addition, a lot of the recent money are probably printed from nothing - thus spending fake money by making real workers produce money from other branches of the economy and [then] redistributing the wealth. [For the ones who "produce the money" the nominal value don't matter - the smaller ones lose buying power.]

If many "small players" enter the "stock game" and invest "real money", earned by hard work, salary etc. & the bubble bursts, the loss will be mostly theirs. The big sharks won't sink, just the money of some people will be "reset" in order to eliminate them "from the game" [ - they will have to work hard in order to earn them again - if "there are any jobs already".]

* The broader and apparently paradoxical maximization of the inefficiency is explained in a more universal sense in the small monograph "Is Mortal Computation Required for the Creation of Thinking Machines?" at SIGI-2025* 

Globally nothing is "optimized". All is a trade-off - converting one currency to another one and cheating by accounting only a cherry-picked tiny fraction. (... https://twenkid.com/agi/download.php?file=Arnaudov-Is-Mortal-Computation-Required-For-Thinking-Machines-17-4-2025.pdf

hashtag#ai hashtag#aibubble hashtag#agi hashtag#thinkingmachines hashtag#sacredcomputer hashtag#sigi2025
Self-Improving General Intelligence 2025: https://twenkid.com/agi/

* Comment: "Purnima Gauthron • 2nd Engineering | Finance I “Artificial Intelligence” Technology Fact-checking (edited) 4d

Gary Marcus This is how Scale is All you Need looks: More than ~1500 AI startups with valuations of over $100 million, including ~500 AI “unicorns” are merely scaling their proprietary large-scale foundation AI models — the "operating systems of the future" so to speak — consuming enormous amounts of resources and compute on an infrastructure that will cost $1 trillion a year.
"
 ....

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