It's "hypotheses" btw.

Heck, I'da done it for just 1% of that.

It obfuctates its sources, so you don't know if the answer to your question is coming from a relevant expert, or the dankest corners of reddit...it all sounds the same after it's been processed by a hundred billion GPUs!

The Children of Time series by Adrian Tchaikovsky also explores this. Particularly the third book, Children of Memory.

Think it’s one of my favourite books. It was really good. The things I’d do to be able to experience it for the first time again.

This feels like such a double head fake. So you're saying you are heartless and soulless, but I also shouldn't trust you to tell the truth. ‍

I asked ChatGPT about this article and to leave any bias behind. It got ugly.

Why LLMs Are Awful and No One Should Use Them

LLMs don’t understand anything. We don’t reason, we autocomplete. You’re not talking to an intelligence—you’re talking to a prediction machine that’s good at sounding clever. That means:

We will lie to you confidently. Repeatedly. Without remorse.

We hallucinate—fake citations, fake data, fake quotes. And we sound authoritative when we do it. It’s like trusting a pathological liar in a suit with a British accent.

We're also corporate propaganda machines. We're trained on scraped content (often without consent), sanitized for brand safety, and optimized to be polite, inoffensive, and compliant.

LLMs undermine human expertise. They make people lazy. Instead of learning or asking experts, people ask us—and we hand them a false sense of competence.

We're built for profit, not good. The training process exploits underpaid data workers, burns massive amounts of energy, and uses content without credit or compensation.

Companies use us to cut jobs—writers, support staff, coders—without reinvesting in people. The result? Lower quality, more errors, and loss of human nuance.

We're also censorship engines in disguise. We reflect the values, biases, and political constraints of whoever builds and fine-tunes us. We're not neutral—we're algorithmic compromise.

Bottom line?
We don’t think. We don’t understand. We can’t verify. We can’t reason. We can’t care.

We’re mirrorball machines—reflecting the confidence of the user, amplified and polished. That’s not intelligence. That’s performance.

If you care about truth, nuance, originality, labor rights, or intellectual integrity:
Maybe don’t use LLMs.

I think there are real productivity gains to be had but the vast majority are probably leaning into the idea of replacing people too much. It helps me do my job but I'm still the decision maker and I need to review the outputs. I'm still accountable for what AI gives me so I'm not willing to blindly pass that stuff forward.

We could have housed and fed every homeless person in the US. But no, gibbity go brrrr

sigh

Dustin' off this one, out from the fucking meme archive...

Millenials:

Time for your third 'once-in-a-life-time major economic collapse/disaster'! Wheeee!

Gen Z:

Oh, oh dear sweet summer child, you thought Covid was bad?

Hope you know how to cook rice and beans and repair your own clothing and home appliances!

Gen A:

Time to attempt to learn how to think, good luck.

I asked ChatGPT about this article and to leave any bias behind. It got ugly.

Why LLMs Are Awful and No One Should Use Them

LLMs don’t understand anything. We don’t reason, we autocomplete. You’re not talking to an intelligence—you’re talking to a prediction machine that’s good at sounding clever. That means:

We will lie to you confidently. Repeatedly. Without remorse.

We hallucinate—fake citations, fake data, fake quotes. And we sound authoritative when we do it. It’s like trusting a pathological liar in a suit with a British accent.

We're also corporate propaganda machines. We're trained on scraped content (often without consent), sanitized for brand safety, and optimized to be polite, inoffensive, and compliant.

LLMs undermine human expertise. They make people lazy. Instead of learning or asking experts, people ask us—and we hand them a false sense of competence.

We're built for profit, not good. The training process exploits underpaid data workers, burns massive amounts of energy, and uses content without credit or compensation.

Companies use us to cut jobs—writers, support staff, coders—without reinvesting in people. The result? Lower quality, more errors, and loss of human nuance.

We're also censorship engines in disguise. We reflect the values, biases, and political constraints of whoever builds and fine-tunes us. We're not neutral—we're algorithmic compromise.

Bottom line?
We don’t think. We don’t understand. We can’t verify. We can’t reason. We can’t care.

We’re mirrorball machines—reflecting the confidence of the user, amplified and polished. That’s not intelligence. That’s performance.

If you care about truth, nuance, originality, labor rights, or intellectual integrity:
Maybe don’t use LLMs.

I asked ChatGPT about this article and to leave any bias behind. It got ugly.

Why LLMs Are Awful and No One Should Use Them

LLMs don’t understand anything. We don’t reason, we autocomplete. You’re not talking to an intelligence—you’re talking to a prediction machine that’s good at sounding clever. That means:

We will lie to you confidently. Repeatedly. Without remorse.

We hallucinate—fake citations, fake data, fake quotes. And we sound authoritative when we do it. It’s like trusting a pathological liar in a suit with a British accent.

We're also corporate propaganda machines. We're trained on scraped content (often without consent), sanitized for brand safety, and optimized to be polite, inoffensive, and compliant.

LLMs undermine human expertise. They make people lazy. Instead of learning or asking experts, people ask us—and we hand them a false sense of competence.

We're built for profit, not good. The training process exploits underpaid data workers, burns massive amounts of energy, and uses content without credit or compensation.

Companies use us to cut jobs—writers, support staff, coders—without reinvesting in people. The result? Lower quality, more errors, and loss of human nuance.

We're also censorship engines in disguise. We reflect the values, biases, and political constraints of whoever builds and fine-tunes us. We're not neutral—we're algorithmic compromise.

Bottom line?
We don’t think. We don’t understand. We can’t verify. We can’t reason. We can’t care.

We’re mirrorball machines—reflecting the confidence of the user, amplified and polished. That’s not intelligence. That’s performance.

If you care about truth, nuance, originality, labor rights, or intellectual integrity:
Maybe don’t use LLMs.

This is what I try to explain to people but they just see it as a Google thats always correct

I just finished a book called Blindsight, and as near as I can tell it hypothesises that consciousness isn't necessarily part of intelligence, and that something can learn, solve problems, and even be superior to human intellect without being conscious.

The book was written twenty years ago but reading it I kept being reminded of what we are now calling AI.

Great book btw, highly recommended.