Welcome • User Guide
ToS • Privacy • Canary
Donate • Bugs • License

©2026 Poal.co

1.2K

yes, I generated this, but it's important

The current AI boom is often framed as a technological revolution, but beneath the surface lies a deeper structural problem: the system is being optimized for investor returns, not societal benefit. And because of that, it contains the seeds of its own failure — even if the technology itself succeeds.

A Reflexive Investment Loop, Not a Productivity Revolution

Unlike past tech cycles driven by clear productivity gains, today’s AI expansion is propelled by a self‑reinforcing financial loop:

Investors expect high returns from AI Companies raise capital to chase those returns Capital funds massive data‑center and chip purchases Those purchases signal “success” to the market Investors expect even higher returns

This loop doesn’t require consumer benefit or productivity growth. It only requires continued belief.

Nvidia as the Center of Gravity

Nvidia sits at the heart of this reflexive system. It invests in AI startups that, in turn, buy Nvidia hardware. Hyperscalers do the same. This creates circular demand that looks like organic growth but is partly financial feedback.

It’s not fraudulent — real products are being built — but the structure resembles a vortex. Demand is amplified by capital flows rather than grounded in sustainable economic value.

The Physical World Is Now Feeling the Strain

Unlike software booms of the past, this cycle consumes enormous real‑world resources:

Electricity diversion: Data centers draw power equivalent to small cities, raising consumer rates and delaying grid upgrades. Water diversion: Cooling systems compete with households and agriculture, especially in drought‑prone regions. Chip manufacturing diversion: Foundries prioritize AI accelerators over consumer electronics, raising prices and reducing availability.

These are not abstract concerns. They are measurable, immediate, and already affecting everyday life.

Accelerated Depreciation Means Accelerated Waste

AI chips become economically obsolete in 12–18 months — far faster than traditional hardware. This drives:

more e‑waste more rare‑earth extraction more discarded servers and cooling systems

The environmental footprint grows even as consumer benefit remains limited.

Consumers Are Paying for a System They Don’t Benefit From

The most striking contradiction is this:

The system succeeds financially even as it fails socially.

Consumers face:

higher utility bills higher electronics prices slower infrastructure improvements reduced access to shared resources

Meanwhile, the financial gains accrue almost entirely to investors and hyperscalers.

A System That “Must Fail, Even If It Succeeds”

Even if AI ultimately transforms industries, the current investment structure is unsustainable. It relies on:

capital flowing faster than productivity grows resource consumption outpacing public tolerance hardware cycles outpacing monetization valuations outpacing real demand

This is why the system can “fail” financially or socially even if the technology itself succeeds.

*yes, I generated this, but it's important* The current AI boom is often framed as a technological revolution, but beneath the surface lies a deeper structural problem: the system is being optimized for investor returns, not societal benefit. And because of that, it contains the seeds of its own failure — even if the technology itself succeeds. A Reflexive Investment Loop, Not a Productivity Revolution Unlike past tech cycles driven by clear productivity gains, today’s AI expansion is propelled by a self‑reinforcing financial loop: Investors expect high returns from AI Companies raise capital to chase those returns Capital funds massive data‑center and chip purchases Those purchases signal “success” to the market Investors expect even higher returns This loop doesn’t require consumer benefit or productivity growth. It only requires continued belief. Nvidia as the Center of Gravity Nvidia sits at the heart of this reflexive system. It invests in AI startups that, in turn, buy Nvidia hardware. Hyperscalers do the same. This creates circular demand that looks like organic growth but is partly financial feedback. It’s not fraudulent — real products are being built — but the structure resembles a vortex. Demand is amplified by capital flows rather than grounded in sustainable economic value. The Physical World Is Now Feeling the Strain Unlike software booms of the past, this cycle consumes enormous real‑world resources: Electricity diversion: Data centers draw power equivalent to small cities, raising consumer rates and delaying grid upgrades. Water diversion: Cooling systems compete with households and agriculture, especially in drought‑prone regions. Chip manufacturing diversion: Foundries prioritize AI accelerators over consumer electronics, raising prices and reducing availability. These are not abstract concerns. They are measurable, immediate, and already affecting everyday life. Accelerated Depreciation Means Accelerated Waste AI chips become economically obsolete in 12–18 months — far faster than traditional hardware. This drives: more e‑waste more rare‑earth extraction more discarded servers and cooling systems The environmental footprint grows even as consumer benefit remains limited. Consumers Are Paying for a System They Don’t Benefit From The most striking contradiction is this: The system succeeds financially even as it fails socially. Consumers face: higher utility bills higher electronics prices slower infrastructure improvements reduced access to shared resources Meanwhile, the financial gains accrue almost entirely to investors and hyperscalers. A System That “Must Fail, Even If It Succeeds” Even if AI ultimately transforms industries, the current investment structure is unsustainable. It relies on: capital flowing faster than productivity grows resource consumption outpacing public tolerance hardware cycles outpacing monetization valuations outpacing real demand This is why the system can “fail” financially or socially even if the technology itself succeeds.

(post is archived)

You are currently inside a comment thread.
Click here to see all the comments (4).
[–] • 0 pt (edited )

... How is that confusing, at all? Code, script is still made up of words. Of Tokens. You're asking it for a sequence of these tokens that perform the function you've described. That is the same as me asking it for a story about a cat and a nigger playing jump rope.

This is what "hallucinations" are. By that I mean: only retards are confused as to what an LLM "hallucinating" is and that it's difficult to understand. It's due to the source material these LLMs are trained on. A good chunk of the training data is factual, but most is made up of lies. And because it's only predicting the next token (not word really, a long word is multiple tokens, a special sequence of characters for coding / scripting is multiple tokens etc.) but it's not always drawing from specifically relevant sources. It's drawing from a collective of the internal weightings for each token.

Go read how LLMs work, you don't know, clearly, which is fine. They aren't intelligent, they don't understand what they're generating, the first word (token) doesn't know what the next word or token necessarily is or should / can be like a human speaking does.

This is why GPUs are king: matrix math.

Write me a letter how my HOA president is not eldigable to be on the board, then a product is produced.

That’s not word prediction.

Don't be a fucking charlatan and talk to me, faggot. Go read up about what LLMs do and how they work before you claim a single thing about them.

I'm too retarded to understand the magic and wizardry behind the LLMs so thus the talking heads that are draining my bank account in front of my eyes are trustworthy!!!