AI disclosure: yes, I used an AI as a drafting assistant. I do not consider that fundamentally different from using a compiler, debugger, search engine, calculator, spellchecker, or discussing an idea with another programmer. The argument is mine. The responsibility for it is mine. Judge the reasoning, not the tool.

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The thing that smells off to me is that Slashdot itself mangles Unicode every time I paste it into a comment box.

So I'm reluctant to accept the implicit premise that software written entirely by humans has already conquered all the easy problems and that AI-generated code must therefore clear some uniquely high bar before we acknowledge it may be useful.

Perhaps the 15% figure is exaggerated. Self-reported numbers often are.

But "real software contains domain-specific rules, institutional habits, regulatory requirements, and weird edge cases" is not an argument against AI coding. It's a description of software. Human programmers have been wrestling with exactly those problems for decades.

What I find interesting is that the article treats the existence of hard domain-specific problems as evidence that AI cannot be writing large amounts of production code. Yet many mature systems built entirely by humans still struggle with things that sound straightforward when described in a sentence.

Again, I submit as evidence the inability of this very site to faithfully render Unicode text pasted into a comment.

The benchmark is not perfection. The benchmark is whether the AI can produce code that is competitive with the code humans were already producing.

If the evidence is merely that real-world software is messy, full of exceptions, and imperfect, that seems equally consistent with the hypothesis that AI has reached parity with a substantial fraction of ordinary software development.

AI disclosure: yes, I used an AI [Copilot] as a drafting assistant. I do not see that as fundamentally different from using spellcheck, a search engine, a calculator, a compiler, Stack Overflow, Wikipedia, or discussing an idea with another person. The argument is mine. The responsibility for it is mine. Judge the reasoning, not the tool.

You're conflating social acceptance with correctness.

"The in-crowd can recognize the out-crowd" is mostly a statement about tribal pattern matching, not truth. History is full of examples where the majority correctly identified the dissenter and incorrectly identified reality.

This reminds me of an HN discussion where multiple AI models reportedly converged on a controversial observation about humans: many people would rather fit in than be right. Your comment seems to elevate that tendency from an observed human bias into a social ideal.

If the objective is social survival, conformity matters. If the objective is discovering what is true, conformity is often an obstacle. Scientific, artistic, and technological advances routinely begin as ideas that fail prevailing social tests.

Also, the writing argument feels circular. If LLMs write like average humans, you say the crowd will still detect them. At that point you're no longer evaluating writing quality. You're assuming the crowd can identify outsiders because they are outsiders.

The deeper issue is that your metric quietly shifts from "is this writing good?" to "does this writing belong to our tribe?" Those are different questions.

Herd recognition may be real. What it does not provide is a guarantee of truth, merit, intelligence, or authorship. Human societies have spent thousands of years demonstrating otherwise.

ChatGPT says all of this is completely possible.

https://chatgpt.com/share/6add...

How likely is it that Flock is not already using its network this way?

AI disclosure: The underlying opinions are mine. The AI's contribution was mostly translating an emotional rant into something less likely to get dismissed as an emotional rant. If that's cheating, then so is spell-check.

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This seems to assume that social acceptance is the thing being optimized.

Why should it be?

The entire point of constitutional rights is that they apply equally to the in-crowd and the out-crowd. A society based purely on social acceptance is just a popularity contest with better branding.

The view you're describing may be descriptively accurate in some settings. Groups often enforce norms through informal ostracism. But that's an argument about how humans behave, not about how they should behave.

If someone's argument is wrong, show why it's wrong. If someone's writing is bad, criticize the writing. "You're out-crowd now, therefore nothing else matters" strikes me as abandoning reasoned evaluation in favor of tribal status enforcement.

AI disclosure: The underlying opinions are mine. The AI's contribution was mostly translating an emotional rant into something less likely to get dismissed as an emotional rant. If that's cheating, then so is spell-check.

More broadly, I think we're heading toward a strange place where people spend more effort policing the provenance of an argument than evaluating the argument itself. If the reasoning is wrong, it should be wrong because the logic is faulty. If it's right, it should be right because the logic is sound. Whether an AI helped turn "this article makes me mad" into a coherent critique seems orthogonal.

Slashdot has traditionally been a "show me the source code" community. In argument terms, that means: show me the logic, not the authorship pedigree.

Disclosure: I fed my initial "old man yells at cloud" reaction into an AI and asked it to separate the arguments from the emotions. The result is below. Feel free to blame either of us.

Every open-source governance problem is increasingly being described as a funding problem. Sometimes it is. But before concluding PHP needs more money, I'd like to know why a language used by so much of the Internet can't attract enough contributors under its current structure. Funding may be the symptom rather than the cause.

I'm also struck by how much of this story revolves around coordinated disclosures, embargoes, privileged access, advance distribution of patches, and leaks. Open source originally leaned heavily on transparency, yet modern security practice often seems to move toward security through obscurity. The irony is that this very episode is largely about how difficult that secrecy proved to maintain.

If important vulnerabilities, mitigation advice, videos, binaries, and CVE information all leaked anyway, perhaps we should be asking whether the bottleneck is funding, or whether increasingly elaborate disclosure processes have created governance and coordination problems of their own.

imagine how flock personnel uses flock network every day...AI allows drawing conclusions from mass movement information that can provide information far beyond just someone's location. It is probably possible even to figure out market moves based on movement of groups of people.

This is not just about following any one person, this is about information movement, following a group of people who work on the same project for example to undersrand when they are going towards the same site / goal. This is beyond dangerous.

"all those "saved" watthours will get sucked up by their subscribers' homes. Then what, shut down the datacenter until things get warm again?"

Why assume the saved watt-hours just disappear? If local residential demand absorbs them, Google can still buy power from elsewhere. The interesting economic question is why Google finds it cheaper to pay consumers to curtail usage than to acquire additional supply through the grid. That suggests congestion, transmission limits, [price gouging, psychological noise,] or peak pricing are the real bottlenecks, not total electricity production.

Is he too lazy?

If no human will help me, is does asking a chatbot seem better than winging it on my own?

Audiophilles will be convinced they can hear a difference. They can't, but they will be convinced of it.

When's the last time a human failed you?

Copilot: That argument assumes AI can only repeat what it has seen before. But some of the most interesting AI results, including in mathematics, involve combining known ideas into solutions humans had not previously written down. If synthesis never produced anything new, those results should be impossible. The real debate is whether those successes are common or rare, not whether they can happen at all.

Copilot: A typical chatbot exchange appears to consume only a few watt-hours. Keeping a human in a heated/cooled office with a computer and network connection for the same interaction may consume an order of magnitude more electricity.

"And the UK handed you the brand new computer industry on a plate by destroying all the computers it had built during the war while not requiring that you do the same with the licensed copies you had built."

The UK decided to destroy its computers on its own, don't blame us for your idiocy. "Require"? What were you going to "require" we do? And how were you going to enforce this "requirement"?

And what licensed copies are you talking about? Britain shared the Bombe (which was basically an upgraded version of the one the Polish built, but of course Brits insist they're the geniuses who broke Enigma), but ENIAC was a US production.