MurphyA/hacker-news huggingface dataset:
by visarga | 2025-09-28 16:46:42+00:00
> assumes that 10x coding speed should 10x productivity

This same error in thinking happens in relation to AI agents too. Even if the agent is perfect (not really possible) but other links in the chain are slower, the overall speed of the loop still does not increase. To increase productivity with AI you need to think of the complete loop, reorganize and optimize every link in the chain. In other words a business has to redesign itself for AI, not just apply AI on top.

Same is true for coding with AI, you can't just do your old style manual coding but with AI, you need a new style of work. Maybe you start with constraint design, requirements, tests, and then you let the agent loose and not check the code, you need to automate that part, it needs comprehensive automated testing. The LLM is like a blind force, you need to channel it to make it useful. LLM+Constraints == accountable LLM, but LLM without constraints == unaccountable.
by timmytokyo | 2025-09-28 16:47:20+00:00
>What is this limit on AI?

Data. Think of our LLMs like bacteria in a Petri dish. When first introduced, they achieve exponential growth by rapidly consuming the dish's growth medium. Once the medium is consumed, growth slows and then stops.

The corpus of information on the Internet, produced over several decades, is the LLM's growth medium. And we're not producing new growth medium at an exponential rate.
by cgriswald | 2025-09-28 16:47:34+00:00
There are a lot of stupid techs. Back in the day we had a tech of a consulting firm run l0phtcrack on our network and then brag about it to a bunch of our firm’s employees. He wasn’t even doing it to steal data, which is probably why he thought it was okay.

The thing about stupid people is they don’t know they’re stupid. They are either wholly delusional about the legality, morality, or consequences or they reason that because they couldn’t catch themselves there is no way anyone else could catch them.
by _1tem | 2025-09-28 16:48:16+00:00
Sounds like you are out of touch with consumers. EU consumers would not be happy if they had to travel to another country to buy Apple devices.

Apple has far more leverage than the EU in this case. Millions of unhappy EU consumers are a much more powerful motivator than a few billion lost in revenue for a company as rich as Apple.

Apple would recoup most of the lost revenue through black market and secondhand sales anyway.
by wtallis | 2025-09-28 16:48:24+00:00
> And according to the European Commission, under the DMA, it’s illegal for us to share these features with Apple users until we bring them to other companies’ products. If we shared them any sooner, we’d be fined and potentially forced to stop shipping our products in the EU.

That's still about withholding specific features, not about abandoning entire product lines in the EU. And it's quite the opposite of a threat from Apple to the EU.

Hasn't Apple been pretty consistent in choosing to ship with fewer features where necessary rather than not ship at all? Given that, the "If we shared them any sooner" bit only makes sense as an explanation for why Apple's choosing their usual course of action, not as a threat to change course and pull out of the EU market.
by __MatrixMan__ | 2025-09-28 16:48:35+00:00
If a buyer has access to the stored knowledge of trusted peers--peers who have knowledge of trustworthy sellers--supply can meet demand without involving an arms race between predatory middlemen.

The modern web was designed by predatory middlemen who want a cut of transactions they otherwise have no business being involved in. It's a textbook case of rentier capitalism.

So what needs to change is that we need to identify the design decisions made by those middlemen, rip them out root and branch, and fix the gaps with something that takes as an input the trust graph of the users so that the only way the middlemen can stay relevant is to personally gain the trust of each user whose transaction they've gotten in the middle of, and we need to publish the result as a protocol, not a platform, so it can be used without us (the authors of the protocol) being at risk of becoming the problem we're trying to solve.
by labcomputer | 2025-09-28 16:48:57+00:00
Amazon is not a good example of contextual ads, though. It doesn't generalize:

1. You can easily argue that these "context sensitive" ads are actually personalized ads: They're personalized based on the search query you just made! Amazon context ads are the same as Google/Apple App Store "context ads". Suppliers are paying for higher ranking.

2. It's a shopping website! Of course those context ads are going to have high ROI because they're showing an ad relevant to the thing you're shopping for!

When people talk about context ads, they mean "Why doesn't Facebook or the local newspaper use context ads?" They don't mean "Why doesn't Target put up a coupon for beans in the beans aisle?"
by sudosteph | 2025-09-28 16:49:01+00:00
I think it's normal for the parents to resent the NHS for this, but from what I've read about about patient experiences, many US doctors believe "chronic lyme" is not a real diagnosis, and that TDOT blood test she took is not standard of care, so private insurers, wouldn't cover it either. So in the US, a patient would likely end up paying up to their deductible for all those tests that ruled out other things, and then still pay out of pocket for a specialist. I'm open to hearing otherwise, but just because the NHS experience was bad, doesn't give me confidence that the average US experience isn't also bad.
by tinyplanets | 2025-09-28 16:49:31+00:00
Wow, you've really got it out for Carl Sagan (of all people)! Why is it required that he be something other than a "mediocrity" in philosophy and theology? He was an astronomer and (more importantly in my opinion) an incredible science communicator. That doesn't necessitate also being an expert in the study of religion, faith, and philosophy.
by danlitt | 2025-09-28 16:49:54+00:00
I am constantly astonished that articles like this even pass the smell test. It is not rational to predict exponential growth just because you've seen exponential growth before! Incidentally, that is not what people did during COVID, they predicted exponential growth for reasons. Specific, articulable reasons, that consisted of more than just "look, like go up. line go up more?".

Incidentally, the benchmarks quoted are extremely dubious. They do not even really make sense. "The length of tasks AI can do is doubling every 7 months". Seriously, what does that mean? If the AI suddenly took double the time to answer the same question, that would not be progress. Indeed, that isn't what they did, they just... picked some times at random? You might counter that these are actually human completion times, but then why are we comparing such distinct and unrelated tasks as "count words in a passage" (trivial, any child can do) and "train adversarially robust image model" (expert-level task, could take anywhere between an hour and never-complete).

Honestly, the most hilarious line in the article is probably this one:

> You might object that this plot looks like it might be levelling off, but this is probably mostly an artefact of GPT-5 being very consumer-focused.

This is a plot with three points in it! You might as well be looking at tea leaves!
by Inufu | 2025-09-28 16:50:20+00:00
Author here.

The standard way to do this is Reinforcement Learning: we do not teach the model how to do the task, we let it discover the _how_ for itself and only grade it based on how well it did, then reinforce the attempts where it did well. This way the model can learn wildly superhuman performance, e.g. it's what we used to train AlphaGo and AlphaZero.
by threemux | 2025-09-28 16:50:47+00:00
Where is this quote from? The person you're replying to didn't say that at all.

They merely highlighted the fact that Perham attempted to punish RubyCentral for their "platforming" of DHH by pulling funding, but instead managed to consolidate power in the hands of those loyal to DHH. Had a bit of a Game of Thrones appeal which is I think why it has had such staying power on HN over the last week.
by danpat | 2025-09-28 16:50:48+00:00
> And you will never know code as well as a reader and you would have as the author for anything larger than a very small project.

This feels very true - but also consider how much code exists for which many of the current maintainers were not involved in the original writing.

There are many anecdotal rules out there about how much time is spent reading code vs writing. If you consider the industry as a whole, it seems to me that the introduction of generative code-writing tools is actually not moving the needle as far as people are claiming.

We _already_ live in a world where most of us spend much of our time reading and trying to comprehend code written by others from the past.

What's the difference between a messy codebase created by a genAI, and a messy codebase where all the original authors of the code have moved on and aren't available to ask questions?
by nativeit | 2025-09-28 16:51:53+00:00
I’m struggling to understand how they are asserting one follows from the other. I’m not a SWE, but do a lot of adjacent types of work (infrastructure automation and scripting, but also electronics engineering, and I’m also a musician), and the “thinking” part where I get to deploy logic and reasoning to solve novel challenges is certainly a common feature among these activities I certainly enjoy, and I feel it’s a core component of what I’m doing.

But the result of that thinking would hardly ever align neatly with whatever an LLM is doing. The only time it wouldn’t be working against me would be drafting boilerplate and scaffolding project repos, which I could already automate with more prosaic (and infinitely more efficient) solutions.

Even if it gets most of what I had in mind correct, the context switching between “creative thinking” and “corrective thinking” would be ruinous to my workflow.

I think the best case scenario in this industry will be workers getting empowered to use the tools that they feel work best for their approach, but the current mindset that AI is going to replace entire positions, and that individual devs should be 10x-ing their productivity is both short-sighted and counterproductive in my opinion.
by latexr | 2025-09-28 16:52:00+00:00
> I would love to see an anti-AI take that doesn't hinge on the idea that technology forces people to be lazy/careless/thoughtless.

Are you genuinely saying you never saw a critique of AI on environmental impact, or how it amplifies biases, or how it widens the economic gap, or how it further concentrates power in the hands of a few, or how it facilitates the dispersion of misinformation and surveillance, directly helping despots erode civil liberties? Or, or, or…

You don’t have to agree with any of those. You don’t even have to understand them. But to imply anti-AI arguments “hinge on the idea that technology forces people to be lazy/careless/thoughtless” is at best misinformed.

Go grab whatever your favourite LLM is and type “critiques of AI”. You’ll get your takes.
by jen20 | 2025-09-28 16:52:32+00:00
Congratulations on discovering XKCD 538 [1]. Depending on your exact threat model (i.e. barring a very surprise attack), this actually can be defended against in many cases, too.

[1]: https://xkcd.com/538/

[2]: https://daringfireball.net/2022/06/require_a_passcode_to_unl...
by sevensor | 2025-09-28 16:53:08+00:00
Maybe if your C has aggressive test coverage and you’re using Valgrind religiously and always checking errno when you’re supposed to and you’re checking the return value of everything. Otherwise lol. C as it’s written by middling teams is a soup of macros, three-star variables, and questionable data structure implementations, where everybody fiddles with everybody else’s data. I’ll take good C over bad Python, but good C is rare.
by joshdavham | 2025-09-28 16:53:26+00:00
> - Models will be able to autonomously work for full days (8 working hours) by mid-2026. > - At least one model will match the performance of human experts across many industries before the end of 2026. > - By the end of 2027, models will frequently outperform experts on many tasks.

I’ve seen a lot of people make predictions like this and it will be interesting to see how this turns out. But my question is, what should happen to a person’s credibility if their prediction turns out to be wrong? Should the person lose credibility for future predictions and we no longer take them seriously? Or is that way too harsh? Should there be reputational consequences for making bad predictions? I guess this more of a general question, not strictly AI-related.
by hnlmorg | 2025-09-28 16:54:49+00:00
Which domains?

What I’ve seen is that LLMs are very good at simulating an extremely well read junior.

Models know all the tricks but not when to use them.

And because of that, you’re continually have to hand hold them.

Working with an LLM is really closer to pair programming than it is handing a piece of work to an expert.

The stuff I’ve seen in computer vision is far more impressive in terms of putting people out of a job. But even there, it’s still highly specific models left to churn away at tasks that are ostensibly just long and laborious tasks. Which so much of VFX is.
by jacquesm | 2025-09-28 16:55:12+00:00
Yes, because then you'd see that the EU is not the homogeneous entity that you seem to think it is.

You could compare the USA to Switzerland or the Netherlands on a per-capita basis or you could pick Romania or Bulgaria and come away with a completely different impression. The main difference is that countries that have been living under the Russian boot for 50 odd years are still recovering and the remainder is far wealthier than the USA and has a smaller wealth gap between rich and poor. This goes in particular for Germany which is still to this day spending large amounts of money to fund the recovery of the eastern part of Germany, but fortunately, unlike Poland, Bulgaria, Romania and the Baltics they have a large enough industrial base to be able to do so. To lump that all together makes zero sense and shows a lack of appreciation of both history and statistics.
by bobbylarrybobby | 2025-09-28 16:55:18+00:00
The 2019–2020 fires were so hot that eucalyptus trees actually struggled to reproduce. Trees with pyrophilic seeds that normally like a good scorching were instead totally consumed by the fires, and the soil got so hot that seeds already dropped and buried were burned to death. Trees that store energy in their wood (either underground or shielded by bark) got so hot that their normally safe wood burned.

Obviously not every tree died due to the fires, but the death and destruction left in the wake of this fire was on a scale far surpassing past fires. Not to mention the deaths of animals.

Recommended reading: The End of Eden by Adam Welz, which basically covers how global weirding and extreme weather events have pushed species already teetering on the edge of survival over the brink.
by labcomputer | 2025-09-28 16:56:10+00:00
> Then someone came up with idea that people are annoyed with ads because they are not personalised enough

No, that was just the public justification so the public wouldn't think they're so creepy. The actual reason is that they work better.

There's an old saying in the ad biz: "I know I'm wasting half my advertising budget. I just don't know which half."

The point of personalized ads is to cut the wasted half.
by scarecrowbob | 2025-09-28 16:56:26+00:00
As someone very far to the left politically, I agree with the metaphor.

The aesthetic differences in the spectacular politics under Obama/Biden vs Trump are pretty easy to see. Heck, one is blue and one is red- that's an easy to spot difference.

The material differences are much more difficult to find and require enough "nuance" to justify that I haven't been able to hold that distinction in my head for about a decade now.
by Hackbraten | 2025-09-28 16:56:29+00:00
Thanks, now I get why you feel like the type system is fighting your style of programming.

> all of those options are unnecessary busy work for what should be a few simple lines of code

If you re-type your variable often, then how do you make sure you’re really keeping track of all those types?

If you re-type it only a few times, then I’m not entirely convinced that declaring a few additional variables really constitutes busywork.

Small example with additional variables instead of re-typing the same variable:

# pylint: disable=disallowed-name, missing-function-docstring, missing-module-docstring, redefined-outer-name from typing import NewType NEEDS_CHECKING = True NotCleaned = NewType("NotCleaned", str) Checked = NewType("Checked", str) Cleaned = NewType("Cleaned", str) original_foo = ["SOME ", "dirty ", " Data"] annotated_foo = [NotCleaned(item) for item in original_foo] cleaned_foo = [ Cleaned(item.lower().strip().replace("dirty", "tidy")) for item in annotated_foo ] foo: list[Checked | Cleaned] if NEEDS_CHECKING: for idx, item in enumerate(cleaned_foo): if item and (item[0] == " " or item[-1] == " "): raise RuntimeError(f"Whitespace found in item #{idx}: {item=}") if "dirt" in item: raise RuntimeError(f"Item #{idx} is dirty: {item=}") foo = [Checked(item) for item in cleaned_foo] else: foo = list(cleaned_foo) print(foo) # => ['some', 'tidy', 'data']

This survives strict type checking (`mypy --strict`). I don’t feel that renaming the variables introduces much noise or busywork here? One might argue that renaming even adds clarity?
by oivey | 2025-09-28 16:56:39+00:00
> That's your problem right there. Why are random callers sending whatever different input types to that function?

Because it’s nice to reuse code. I’m not sure why anyone would think this is a design issue, especially in a language like Python where structural subtyping (duck typing) is the norm. If I wanted inheritance soup, I’d write Java.

Ironically, that’s support for structural subtyping is why Protocols exist. It’s too bad they aren’t better and the primary way to type Python code. It’s also too bad that TypedDict actively fought duck typing for years.
by nenenejej | 2025-09-28 16:56:52+00:00
OK: AI is slow when using the said loop. AI is like poker. You bet with time. 60 seconds to type prompt and generate a response. Oh it is wrong ok let's gamble another 60 seconds...

At least when doing stuff the old way you learn something if you waste time.

That said AI is useful enough and some poker games are +EV.

So this is more caution-AI than anti-AI take. It is more an anti-vibe-koolaid take.
by Erwyn | 2025-09-28 16:56:58+00:00
Sure but then your mail gets dropped on the other end: The main issue I had the last time I tried running my own setup for mails was basically getting an email to an outlook or live.microsoft address. My mails were dropped for no reason, effectively not landing in my friends mailboxes and without any error on my side to know that my mail was getting rejected.

This is when I decided to stop trying getting through with this and came back to paying a provider.
by dangus | 2025-09-28 16:57:06+00:00
It’s a very confusing and hidden feature. You have to start “deleting” your phone from Find My (which is itself an hidden swipe action) and it’ll tell you that you can’t but you can enable repair mode.

IMO the feature shouldn’t even be in Find My because it’s not really related to finding your phone or activation locking/unlocking it.
by wizzwizz4 | 2025-09-28 16:57:07+00:00
The next two sentences:

> As such, Andre's goal with Ruby Together was characterized as an effort to fund development activities—initially his own, but eventually others—by paying themselves a market hourly rate. I remember being extremely sympathetic to this perspective, having also wasted countless hours of my life maintaining open source for free only for others to benefit from it.

You're misrepresenting the article.
by parineum | 2025-09-28 16:58:17+00:00
You're just talking about Republicans. Having a problem with how immigration was, mask mandates, "forced" vaccination, boys in girls sports, etc are pretty mainstream issues. Despite what the "very online" crowd thinks (including most of the media), those are very normal opinions.

The MAGA crowd aren't the same. MAGA dies with Trump. Nobody is going to get away with saying what Trump did about McCain post Trump. Nobody else is going to try this tariff nonsense. Nobody else is going to send the national guard to American cities.

Trump has extreme solutions to main stream gripes. The gripes will stay, the solutions won't.
by jacquesm | 2025-09-28 16:58:22+00:00
Look, you chose to run with a figure that was nonsense at face value just because it suited your narrative. You then defended the figure and you made up a narrative about how executives should be believed over random commenters, which was - at best - a strawman. You then keep digging yourself into ever deeper holes without simply coming out and saying that you were wrong to believe the initial figure without any critical thought. The longer you keep this up the more silly you look.

> "Given the threat of securities fraud lawsuits, I'm liable to believe them over some random commenter casting doubt with zero evidence."

That was your statement, but - surprise - no exec made the claim that you chose to believe. And if you had thought for 10 seconds you'd have realized that no such claim could have been made because the figure is clearly non-sensical. Oh, and US execs fairly routinely lie, both in court and outside of it. The fact that they get away with it is not proof that they're not doing it.
by LittleCloud | 2025-09-28 16:58:41+00:00
> There's a divide between people who enjoy the physical experience of the work and people who enjoy the mental experience of the work. If the thinking bit is your favorite part, AI allows you to spend nearly all of your time there if you wish, from concept through troubleshooting. But if you like the doing, the typing, fiddling with knobs and configs, etc etc, all AI does is take the good part away.

I don't know... that seems like a false dichotomy to me. I think I could enjoy both but it depends on what kind of work. I did start using AI for one project recently: I do most of the thinking and planning, and for things that are enjoyable to implement I still write the majority of the code.

But for tests, build system integration, ...? Well that's usually very repetitive, low-entropy code that we've all seen a thousand times before. Usually not intellectually interesting, so why not outsource that to the AI.

And even for the planning part of a project there can be a lot of grunt work too. Haven't you had the frustrating experience of attempting a re-factoring and finding out midway it doesn't work because of some edge case. Sometimes the edge case is interesting and points to some deeper issue in the design, but sometimes not. Either way it sure would be nice to get a hint beforehand. Although in my experience AIs aren't at a stage to reason about such issues upfront --- no surprise since it's difficult for humans too --- of course it helps if your software has an oracle for if the attempted changes are correct, i.e. it is statically-typed and/or has thorough tests.
by JackFr | 2025-09-28 16:58:50+00:00
It’s exhausting because most of us like to sit down open an IDE and start coding with the belief that ambiguous or incomplete aspects will be solved as they come up. The idea of writing out the spec of a feature from without ambiguity, handling error states, etc. and stopping to ask if the spec is clear is boring and not fun.

To many of us coding us simply more fun. At the same time, many of us could benefit from that exercise with or without the LLM.