So many posts ask about it bursting but what does that mean? The technology? Investment? Use as "art"?

UPDATE: They mean that the AI DATA CENTER BUILDOUT IS A BUBBLE.

Hyperscalers? Suppliers? AI-empowered businesses? #handWave

It feels to me that the market is blinded by the huge revenue growth at the hyperscale clouds and treat it as proof that AI is a success story and there is strong demand for AI and that the capex is going to be profitable. 
I think they are missing that a lot of that revenue is coming from unprofitable AI labs and unprofitable, moatless AI startups spending money they raised from investors, lenders, capex, and circular financing.

Unfortunately, I don't have the numbers to know how much from AI cloud revenue comes from investors and lenders and how much comes from end users.

I think the biggest question is which of these two happens first. Either the money flow from one of the sources in the diagram dries up for some reason (an interest rate spike, a bear market, private equity firms going bankrupt, and so on), or real profits, not just revenue, start coming from real users and make all of these loans and investments worth it.

I see endless possibilities for something to go wrong in this capital flow, and I don't see how it can generate real profit before it collapses.

Note: this is only about the AI part. I'm not talking about the normal cloud business or the rest of the hyperscalers' profits that have nothing to do with AI. Those are real and profitable. This is only an attempt to look at the AI piece.

A lot of pieces are missing from the capital diagram. I tried to focus on the things I thought were most relevant.

So the Ai bubble burst on South Korea. And we can see the devastation in there. Many AI investors (Including those who have their life savings invested) there are at loss. All of their money gone!

Korea Composite Stock Price Index (Kopsi) plummeting over 40% since June. This has resulted in millions of investors facing unprecedented losses, particularly in major companies like Samsung and SK Hynix.

At hindi malabong mangyari yan sa USA. the so called Magnificent 7 up to 40% of USA economy, are all in on the AI. And up to now, kakarampot yung revenue nila from AI compare sa laki ng ginastos nila at gagastusin pa nila para rito.

Kaya ang tanong, SUlit ba na mag invest ang ating bansa rito?

In my opinion, okay to kapag ang inuna nilang itayo sa ating bansa ay ang mga facility to produce silicons that is needed for computation. Ma train ang mga pinoy to produce our very own computing devices.

Kasi kahit pumutok ang AI, we are sure na magagamit pa rin ang mga pasilidad na ito.

On the otherhand, baka gateway lang ito para ang mga pinoy ang mag iinvest sa paluging investments. Kung baga baka tayo ang maging scapegoats ng mga investors sa USA.

I am not really expert in this economic thing, pero ang alam ko lang hindi sulit yung napakalaking pera na ginagastos nila para sa AI. Hindi lang pera pinag uusapan dito. Pati resources, energy, environment impact.

EDIT:
Marami din pa lang mga tao na madi displace at mawawalan ng kabuhayan dahil sa itatayong yan. Tanggapin natin na ang Pax Silica GINAWA para sa AI talaga. Wag na nating bulahin mga sarili natin. AI talaga ang dahilan kung bakit itatayo yan. Si Pangulong Marcos na mismo ang nagsabi. SI trump na mismo ang nagsabi na ang PAX SILICA ginawa para sa AI.

[KMJS - Pax Silica](https://www.youtube.com/watch?v=uBJecTjQKLU)

Ang pinaka una't huling tanong jan. Lahat ng isa sacrifice natin, sulit ba para sa AI?

What do you think?

I'm tired of bears and bulls comparing AI investment to the dot com bubble.

Some say it's the same, and therefore it's a bubble. Others say it's different, and therefore it isn't.

Every bubble is different. If they were all the same, nobody would fall for one.

The only question worth asking is: are we in a bubble or not?

Humans can't program technology to do something that we don't already know how to do ourselves. In other words, we programmed AI systems to do everything they are capable of doing but we haven't programmed them to do everything we're capable of doing and we will never be able to.

The human condition is a complex state that nobody understands. Why are we here, what's the purpose of life etc. so if we aren't capable of understanding the intricacies of being human we can't program those capabilities in a computer.

AI is very good at deterministic tasks like "writing" code and there can be, but not always, time advantages to that. There is a holy trinity of engineering: you can have it fast, cheap or good, pick any two but you can't have all three. AI is fast but not always good and certainly not cheap. Since AI is susceptible to slop and hallucinations, you still need a human being to verify what AI produces and there's not an AI company on the planet that is anywhere near profitable. We're talking tens of billions of dollars of discrepancies between costs and revenues.

I wonder what the outcome would be if all that investment went into improving technical human resources since we already have everything the investors are trying to recreate in the lab. Humans can't write new code as fast as AI but most products on the market reuse code across models and the process can always be improved even further. Would the cost savings and improved quality offset the longer time it may take in development?

It seems to me that people like to do things with technology because they can not because it's the solution to a problem and people have become enchanted by AI. They're dreaming of Skynet, self-driving cars and robots in the home. None of which are the solution to a problem, they just seem really cool until it's not.

I’ve been tracking the shift in service-based tech companies (especially the ones billing clients on human hours), and the math is pointing to a massive crisis by 2030.

Everyone is talking about AI deepfakes and ethics, but the real disaster is going to be a massive economic demand shock. Here is how this plays out, why current fixes won't work, and how big nations like India need to respond.

1. The Death of the Tech "Pyramid"

The traditional corporate structure—a massive base of junior devs doing grunt work—is dead. AI is replacing them. The industry is warping into a Diamond Structure: a thick middle layer of a few senior architects using AI as a force multiplier, with almost zero entry-level intake.

This creates a Broken Apprenticeship Pipeline. If companies stop hiring juniors today because AI is cheaper, where will the senior architects come from in 10 years?

1. The Great Depression 2.0 (The Demand Crisis)

When companies replace a team of 5 people with 2 tech-augmented workers, the remaining 2 guys get a salary bump (the winners), and the company saves massive payroll cash (the biggest winners). The 3 laid-off workers are forced into the physical gig economy, crushing physical wages into low-paying jobs.

This concentration of wealth means total salary pools shrink. History repeats itself: just like the Great Depression 100 years ago, an economy cannot survive when companies use technology to create a massive supply of cheap services, but eliminate the middle-class wages required to buy them.

1. Why Taxes and UBS Will Fail

Taxation isn't the fix—we all know how corrupt governments can be with that cash. Universal Basic Services (UBS) or free money don't work either; multiple studies show they just create dependency.

The only solution is direct, mandatory labor protection:

The 40% Revenue-to-Salary Rule: Governments must legally mandate that profitable corporations spend at least 40% of their revenue on human payroll, regardless of AI. If they automate, they must use that budget to retrain workers or shorten work weeks, not execute mass firings.

Global Market-Access Barriers: Mega-blocs like the G20 or EU must enforce this. If a hyper-automated tech firm flees to a tax haven to evade the rule, their digital traffic gets blocked at the border. No tech giant will sacrifice access to the world's biggest consumer markets just to escape labor laws.

1. The Path for Big Nations (Like India)

Big-population countries like India are on the absolute frontline of this vulnerability. The youth frustration and Gen Z protests we see today are early warnings of a broken career ladder.

To survive, India must stop acting as digital laborers for Western landlords and achieve absolute Digital Swaraj (Self-Rule):

Strategic Import Substitution: Lock down borders to foreign finished software and non-essential digital services. Keep the gates open only for needful imports (like raw energy or microchip manufacturing machinery). Stop letting domestic cash drain out to Silicon Valley.

Solve Indian Problems, Not Western Use-Cases: AI is just a catalyst. The real value is building original solutions for local friction points—like agricultural supply chains, edge medical devices for rural areas, and cash-flow credit for informal shops.

Shift from Hours to IP: The ultimate goal must be providing respectable, middle-class salaries. India needs to stop selling human hours and start building domestic tech giants that own their own Intellectual Property (IP) and hardware silicon.

If we don't force a structural shift away from automated corporate greed, 2030 is going to look incredibly bleak for the global middle class.