The AI Bubble

[John F Sowa]

se amounts of $$$ have been poured down the AI drain in hopes that something spectacular will happen.   This kind of overinvestment has caused periodic Boom & Bust cycles ever since the term 'artificial intelligence' was invented -- about 70 years ago.

But the amount of investment in this LLM cycle has been overwhelmingly large, and the return on investment has been underwhelmingly bad.  The AGI gang (Artificial General Intelligence) has been the worst performer.  I attended the first few meetings of that group, and I recommended some cautionary issues.   But I stopped participating when that gang kept making outrageous claims with zero evidence to support them.

Following is the start of a newsletter about the issues.   To continue reading, it's necessary to become a subscriber.  I didn't bother because I know why this bubble is going to burst:  LLMs, by themselves, are useful for generating hypotheses (educated guesses or abductions), but GOFAI (Good Old Fashioned AI) makes predictions (deductions) about those guesses, tests those predictions, saves the validated information (induction) and repeat with more abductions, deductions, testing, and inductions.

The AGI gang and the investors who are spending huge amounts on Nvidia chips are not doing the necessary deduction and testing.  They will go belly up sooner or later, but I don't know exactly when.  As they say, don't get any of it on you.

John

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The AI Bubble is Far Worse Than We Thought 

Everyone who isn’t a tech bro weirdo can see that the AI industry exists in a bubble. The big question so far hasn’t been “if” there is a bubble, but how large it is, when it will pop, and who it will affect. Sadly, because no one has a crystal ball, we can never hope to figure out when shit will truly hit the fan. But we have also struggled to pin down the size of this bubble, as the reality of AI economics has become muddied by Big Tech propaganda. Likewise, these corporations have propagandised their finances to the point of unreality, making it nearly impossible to figure out who is actually connected to the bubble. However, recent analysis has cut through this cloud of doubt, and reality is far more terrifying than we thought possible. This isn’t a bubble — it is a financial nuclear bomb.

Let’s start with the truly gut-flipping findings of Julien Garran.

Garran is an analyst for MacroStrategy Partnership, an independent research firm that advises 220 institutional clients. He also previously led UBS’s commodities strategy team. Needless to say, he understands his subject material. But his recent analysis discovered that the AI bubble was 17 times the size of the dot-com bubble and four times larger than the 2008 housing bubble!

How did he arrive at that figure?

Well, he calculated it in a very similar way to how I did in a previous article (read here), but with far, far better economic analysis.

Like me, Garran pointed to the efficient compute frontier and the diminishing returns of AI, causing costs to skyrocket and progress to stagnate. This is why ChatGPT-3 cost $50 million, ChatGPT-4 cost $500 million, and ChatGPT-5 cost $5 billion, yet the improvement between these generations has been so slim it is almost unnoticeable. This wouldn’t be a problem if theEse AIs had reached a point of usefulness, but they haven’t. Like me, Garran points to the plethora of studies that prove AI deployments offer practically no benefit, aren’t profitable, and actually make companies less efficient. As such, the AI industry and the gargantuan investment behind it are a dead end, creating a bubble.

[End of free preview.  I wouldn't bother paying for the rest, since I already believe it.]

[https://www.planetearthandbeyond.co/p/the-ai-bubble-is-far-worse-than-we

[Mike Peters]

Hi John
I agree with you 100% about the growing economic dangers inherent in the AI bubble.

Mike Peters
-----------------------------------
Ajabbi
New Zealand
Software Engineering www.blog.ajabbi.com
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[Nadin, Mihai]

Dear and respected colleagues,

The twin brother of euphoria is dysphoria. All I want to say is that dedication to science results in our obligation to avoid extremes and base our judgments on facts.

Progress is evident, although at a scale different than that trumpeted (for reasons that have to do with more exposure and more larger funding). The dangers are also real. And probably not even fully understood. To be honest: I am more worried about the long-term consequences of being tethered to cell phones than being replaced by some chimeric technology.

 

Mihai Nadin

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[John F Sowa]

I agree about the long term consequences.

But the near-term consequences are likely to be a violent economic upheaval.  The reaction against AI could destroy many good projects along with the bad.

That has happened many times in the past 70 years.  But the huge $$$ investments in the current bubble could cause an economic disaster.

John

 

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From: "Nadin, Mihai" <na...@utdallas.edu>

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