asgraham

To be clarify for everyone: both of the cited articles argue in favor of HPV vaccination. I assumed they would be arguing against since the comment is arguing against, but that is not the case.

In particular, you've mistaken the result of the second study.

The vaccinated patients were even older, which makes it even worse, because those are older women who have had more time to be pregnant.

^ this is incorrect. Indeed according to the study, the vaccinated patients are younger (33.1) than the unvaccinated patients (37.4), which could easily explain the difference in gravidity. The authors do not report having controlled for age when computing the gravidity effect.

Note also that the entire study was conducted with a population of patients seeking fertility care, so the study can't support the general claim "gravidity is halved for the HPV vaccinated" even were the significance level to survive age-controlling statistics (which it likely would not).

Sure, sure. I’m not arguing for removing drivers for uncommon devices, or even rare devices. But there’s a line somewhere. Maybe it’s at “devices that no longer exist.” But I think it’s somewhere before that. And I have no idea how you’d figure out which devices fall where around this hypothetical line. I can only hope that they had good justification for these removals.

Is the parent really being sarcastic? I read it as genuine.

There’s presumably plenty of code bloat in the kernel, and while no human would ever scan for bugs in a corner of the kernel that hasn’t been used or touched in decades, AI 100% will. And while those bug reports might be useless as bug reports, they seem promising as “why is this code even here?” flags.

They can determine how much each work contributed based on those weights, so it's dishonest for them to argue it isn't possible.

I don’t know about impossible but it’s definitely not a straightforward read from the post-training weights as you’re implying, unless you’re aware of some technique I’m not aware of.

The closest you could get would be the weight differential from training with a given work. But that’s massively dependent on training order, so that it’s certainly not at all a good measure of “contribution.”

My first impression when the Leaf image loaded was that you were being overdramatic. The Ferrari website created the impression of a similar but fundamentally more elegant car (not elegant, just more elegant).

Then the Ferrari image loaded. Wow.

It really is a game of spot the difference. A difficult game.

edit: I don't want to reduce hypercars purely to their "Wow!" factor, but a huge huge part of their value is definitely the feeling they evoke when you see one out of the corner of your eye and your head snaps around. This Leaf/Luce side-profile similarity is completely antithetical to that "Wow!" factor.

Ignoring the spiritual part, emotional state does have a well-known feedback loop with physical state. There’s a (largely incorrect) idea in pop psychology that just as happiness leads to smiling, smiling leads to happiness. It’s not nearly that simple, but there are some more straightforward examples: lots of tense emotional states (anger, anxiety) lead to tense muscles (jaw being the classic example). Relaxing your jaw can lead to a (temporary) relaxation of your emotional tenseness. I’ve never heard of a similar result for the lower back, but it’s not hard to imagine. If nothing else, they must be correlated through sedentary lifestyle.

Requires the MacOS desktop app. Windows "coming soon," but still no word on an official Linux app.

The good is hidden: court systems are already overwhelmed. If the arbitration cases were added, then it’d take even longer to get a court date.

(Which isn’t to say I think the system as it is is good, just that there is a good)

Are you arguing that eventually a competitor will emerge that does support OpenClaw with a subscription model? Wouldn’t that just be more expensive for the exact same reason Anthropic is banning it?

I know for a fact [1] that the neuroscientific discoveries were not independent of physics: the people doing the developing were largely former physicists. They likely didn't cite anything because why would you cite phase transitions or criticality? You learn about them in class as a physicist. I strongly suspect the ecology results weren't independent either, but all the theoretical ecologists I know are relatively young (if mostly former physicists) so no first person accounts.

The part of this that could totally be true is that a clinical application somewhere along the way "independently" "reinvented" it. There's a hilarious collection of peer-reviewed journal articles out there inventing a "new" method of calculating the sizes of shapes and areas under the curve. The method involves adding up really small rectangles. (I think a top comment already mentioned the Tai article [2])

[1] source: my doctoral advisor was a really really old theoretical neuroscientist who trained as an electrical engineer and mathematician. If you want a more concrete example, the work of Bard Ermentrout on neural criticality starting in the 70's or 80's. He read a lot of physics textbooks.

[2] https://science.slashdot.org/story/10/12/06/0416250/medical-...

The irony is that youth are simulatenously the biggest consumers of (new) social media, and the staunchest haters [EDIT: this is directly contradicted by the research article I found below…]. I can’t find the source so take it with a grain of salt, but I’ve read that something like 80% of TikTok users under some age think they’d be happier if it didn’t exist and/or wish it didn’t exist.

I don’t think this is really an issue of censorship to a lot of people (though that may be how it shakes out in the government) but rather of control over their digital environment and sanity.

EDIT: I don’t think this is what I’m remembering, but it has concrete numbers somewhat lower than I thought (48% of teens think social media harms people their age, but only 14% think it harms them personally) https://www.pewresearch.org/internet/2025/04/22/teens-social...

I was so with you the first half of that. But the notion that everything should be capitalism is just as wrong as the notion that nothing should be capitalism (or, that capitalism only leads to bad things; obviously wrong but somehow a broadly accepted truism).

Capitalism works when a market works; capitalism fails when a market fails. Healthcare is a great example, because there’s an obvious and inherent imbalance in demand vs supply. Firefighting is another great example. These also have externalities to the community as a whole that everyone gets, even when you don’t pay/need the service; so it makes sense to make everyone pay (taxes). Even if you never have a child, even if you send your kids to private school, you live in a society that could only exist because of a (formerly, relatively) high standard of public education. So everyone pays for schools.

The idea of government bureaucrats lining their pockets is also (formerly, relatively) ridiculous: who would get into US government bureaucracy to make money? They are all (formerly, relatively) doing it almost uniformly because they believe in the mission, because they would almost all make more money going private.

Lots of good suggestions. However for Svelte in particular I’ve had a lot of trouble. You can get good results as long as you don’t care about runes and Svelte 5. It’s too new, and there’s too much good Svelte code out there used in training that doesn’t use Svelte 5. If you want AI generated Svelte code, restricting yourself to <5 is going to improve your results.

(YMMV: this was my experience as of three or four months ago)

Those prices seem geared toward people who are completely price insensitive, who just want "the best" at any cost. If the margins on that premium model are as high as they should be, it's a smart business move to give them what they want.

Interesting! I imagine speech-related motor artifacts don't help matters either, even if noise starts mattering less at scale.

Really cool dataset! Love seeing people actually doing the hard work of generating data rather than just trying to analyze what exists (I say this as someone who’s gone out of his way to avoid data collection).

Have you played at all with thought-to-voice? Intuitively I’d think EEG readout would be more reliable for spoken rather than typed words, especially if you’re not controlling for keyboard fluency.

This isn’t really “Show HN” so you might want to remove that, but looks really awesome!

https://news.ycombinator.com/showhn.html

I was initially skeptical of this claim because I’d previously learned that to cross the blood-brain barrier particles need to be ~200nm (PM2.5 = 2500nm). However, PM2.5 does seem to be an important category of particles for brain damage: somehow these particles can access the brain [1]. Obviously, yes, it depends on exactly the particle whether it will be “neurotoxic,” but generally “unnatural” particles in the brain are not going to do good things. (I am not an expert in particulates) it seems like things larger than this don’t penetrate the blood-brain barrier, so they can’t be neurotoxic. So PM2.5 is probably at an intersection of large enough to be unhealthy but small enough that the blood brain barrier doesn’t help (probably some evolutionary argument to be made here).

[1] https://pmc.ncbi.nlm.nih.gov/articles/PMC9491465/#:~:text=PM...

Doesn’t this mean browser sandboxing is secure, not JS? Or are you referring to some specific aspect of JS I’m not aware of? (I’m not aware of a lot of JS)

It’s maybe a nit-pick, since most JS is run sandboxed, so it’s sort of equivalent. But it was explicitly what GP asked for. Would it be more accurate to say Electron is secure, not JS?

It’s partially that for sure, but I think it’s also a kind of “common sense” feeling of the public that if people use technology to commit a crime, there must therefore be a record of that crime and therefore the police should be able to use that record to easily stop technology-crime. See: every police show ever.

That was never possible before. Historically, conversations didn’t leave records, and when they did, they were trivially burned. There was no sense that the police should have access to the records because there were no records.

The technical and ethical problems of this “common sense” are far from obvious to most whose primary exposure to and mode of thinking about policing and technology is what we see on TV.

First of all, you absolutely cannot release an OS with a known zero day. IANAL but that feels a lot like negligence that creates liability.

But even ignoring that, the gulf between zero days and plain-text LLM prompt injection is miles wide.

Zero days require intensive research to find, and expertise to exploit.

LLM prompt injections obviously exist a priori, and exploiting them requires only the ability to write.

If you can write tests fast enough, you can specify those business rules on the fly. The ideal case is that tests always reflect current business rules. Usually that may be infeasible because of the speed at which those rules change, but I’ve had a similar experience of AI just getting tests right, and even better, getting tests verifiably right because the tests are so easy to read through myself. That makes it way easier to change tests rapidly.

This also is ignoring that ideally business logic is implemented as a combination of smaller, stabler components that can be independently unit tested.

I totally agree that the agent is essential, and that right now Claude Code is semi-unanimously the best agent. But agentic tooling is written, not trained (as far as I can tell—someone correct me) so it’s not immediately obvious to me that a third-party couldn’t eventually do it better.

Maybe to answer my own question, LLM developers have one, potentially two advantages over third-party tooling developers: 1) virtually unlimited tokens, zero rate limiting with which to play around with tooling dev. 2) the opportunity to train the network on their own tooling.

The first advantage is theoretically mitigated by insane VC funding, but will probably always be a problem for OSS.

I’m probably overlooking news that the second advantage is where Anthropic is winning right now; I don’t have intuition for where this advantage will change with time.

I don’t know about your first point: at some point the three-year difference may not be worth the premium, as local models reach “good enough.”

But the second point seems even less likely to be true: why will Claude code and Gemini cli always be superior? Other than advantageous token prices (which the people willing to pay the aforementioned premium shouldn’t even care about), what do they inherently have over third-party tooling?

Fair enough. Cancer causation is just so weird, I'm going off the heuristic that stuff in your lungs that your lungs aren't prepared for is probably not great, especially with chronic exposure. And your lungs are really only prepared for air (which includes many things within certain tolerances [0]). The "not great" => "cancer" pipeline is really where the hand-waving comes in, and mostly far too early to tell whether the parts of vaping that are "not great" for your lungs will in fact be carcinogenic for your lungs.

So that being said, I'm mostly going to offer citations for "vaping is not great for your lungs." And that being said, I'm just going to offer citations for "specific parts of vaping are not good for your lungs." But my broader argument is that putting stuff in your lungs is going to be bad for your lungs, and these are just the most obvious ones we've found so far. Unfortunately I won't be able to find a citation for that argument.

So, first, the most recent: a study showing disposable vapes had incredibly high level of toxic metal emissions [1]. The non-disposable Juul et al variously have some concerning levels, but the insane numbers are on disposables, which are largely (entirely?) illegal in the US, at least. Still, they're not illegal everywhere, they were used heavily for several years in the US, and several of the top Google results were redditors complaining about the stupid ban and talking about how to get around it. All of this combines to lung damage down the line, and several of the toxic metals are outright carcinogenic, so lung cancer as well.

A more particular example: popcorn lung is a terrifying name, but pretty restricted risk, given the causing chemical is only in certain flavors, and those have supposedly stopped using it [2]. But again, an example of weird chemicals in your lungs cause weird things, and it'll be decades til we figure out all of them.

And finally, a study showing that vaping plus smoking leads to a four-fold higher risk of lung cancer over smoking alone (yes, they adjusted for age, gender, race, location of residence, prevalent comorbidities, and pack-years of smoking) [3].

[0] I was hoping to make a glib point about even high enough pollen concentration being bad for your lungs, but in fact a recent study suggests that allergies reduce risk of lung cancer! I'm chalking that up to allergies being your body's way of keeping non-air particulates from your lungs, but who knows. https://www.frontiersin.org/journals/medicine/articles/10.33...

[1] https://pubs.acs.org/doi/10.1021/acscentsci.5c00641

[2] Not a lot of research on popcorn lung, seemingly. Note that the name is related to its etiology, not its symptoms. https://www.summahealth.org/flourish/entries/2025/03/a-warm-...

[3] https://pubmed.ncbi.nlm.nih.gov/39210964/

I can’t find any complete numbers (most prevalent factors after smoking would be environmental, and therefore underreported, especially when as hard to detect as radon), but national health agencies tend to put the Radon section second, after Smoking [1,2]. An uncited figure on a Hopkins webpage suggests 30% of non-smoking lung cancer cases are caused by Radon [3]. Among the well-known environmental factors (asbestos, secondhand smoke), it seems to be about equal for risk increase [4]. Given that asbestos and secondhand smoke are on the decline, it stands to reason that radon will tend toward being the top cause, barring a rise in prevalence of one of the disease risk factors (asthma, pneumonia, HIV, tuberculosis).

Of course this is all moot because vaping will be revealed to be the current #1 cause of lung cancer in the coming decades, by a long shot. No citation necessary.

[1] https://www.cdc.gov/lung-cancer/risk-factors/index.html

[2] https://www.nhs.uk/conditions/lung-cancer/causes/

[3] https://www.hopkinsmedicine.org/health/conditions-and-diseas...

[4] https://pmc.ncbi.nlm.nih.gov/articles/PMC6777859/

Not to agree with GP, but I think it’s more accurate to say they’re saying “if validation is quick (to code), who cares how long a solution takes an AI because computation is cheap.”

They’re not really making any claims about how quickly the AI can solve relative to the validation, which is what P vs NP is about.

It's actually hard to find a math tutor to proof your vector math program in your late 30s.

They exist, if you know where to look and are willing to pay (source: me, or generally and probably more affordably wyzant.com)

What a wild thing to comment.

a) “professional” writ large often encompasses academic research, even though it’s also often specifically used in contrast. Language is weird like that. Former and current academics like to have a term for all the stuff we’ve been paid to do, and we usually default to “professional experience” (though current academics do usually say “research experience” because you’re right that professional has the default connotation of corporate employment).

b) the project seems to have been over 2000 lines of APL. That’s not the “small” student project you’re implying, in any language, and in APL that’s quite substantial.

re: the arxiv link

Why is it that microarray true positive p-values follow a beta distribution? Following the citations led to a lot of empirical confirmation but I couldn't find any discussion of why.

More to the point of this rebuttal, though: why would we expect the amalgamation of 70k micro-array experiments' abstract-reported p-values to follow a single beta distribution? And what about modeling the bias-induced bump of barely-significant results?

If there's some theoretical reason why the meta-study can use the beta-uniform model, then I could see this being only a mild underestimation of the proportion of false positives (14%), but otherwise I'm confused how we can interpret this.