skysight-inc/HackerNews huggingface dataset:
> Tried it. It's still quite limited, not comparable to gpt. Google does fall far behind.

in what ways?
And this is the type of shit that should have been snuffed out during the IPO vetting process, and something VC firms with any brains at all would have taken a huge objection to before investing.

"So, your whole business model is effectively a digital pill mill for ADHD stimulants and antidepressants, and the mechanism for service delivery involves putting your service providers into debt so they can cut corner after corner to get more and more people taking this medication faster than if a customer went through the traditional evaluation-and-prescription model with a real doctor?"

Yeah, that's fucking dumb. I'd nope out of that so quickly. ADHD pills are over prescribed (often to the wrong people), and that's super dangerous. I have pretty severe ADHD and even I don't think these pills should proliferate as much as they have society-wide.
Depends on which naming convention you subscribe to. Most people just use H. neanderthalensis for convenience rather than writing out H. s. n. since everyone knows what they mean either way. Neither classification is obviously correct either, hence the introduction of more nuanced categories like "allotaxa" that aren't reflected in binomial nomenclature (yet?).
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> Politicians however have no incentive to manipulate math, physics, engineering, etc.

IMHO, Wikipedia's main problem isn't with politicians (though, IIRC there's likely a fair amount of state-actor editing), it's with zealots.

You have to be deeply, deeply weird to be a Wikipedia editor, especially in a controversial topic area. My feeling is most of those editors are motivated by blatant ideological POV pushing, and their bad-faith motivations are only sublimated by Wikpedia's policies. Most of the conflict is in the form of elaborate passive-aggressive bureaucratic walls of text, which only the truly insane would willingly participate in.

Over time, as the editor population dwindles, it will become less and less diverse and more and more biased.
Another reason to use buttons: if you wanted to automate the button pushing, it's easier to create a computer vision function to look for round rectangles vs going full-blown machine learning trying to identify things that could be buttons. (Source: I make software and robots for pushing buttons.)
It's not officially part of the Neovim project. However they distribute it with the Windows installer.

Neovim-Qt and Neovide both work the same way, one is not more privileged or official or well-integrated with Neovim than the other.
I like a lot of what they're saying, but I actually find all of their redesigns to look worse than the original. I don't prefer the typeface they've selected, and their boxy buttons look two decades old.

I agree that the terms agree/disagree aren't well differentiated, I don't agree with their solution

I find their photos redesign to be much worse than the original. Buttons are an affordance that you use to instruct users on new or rare behavior. If a user regularly does something or uses something you can strip it down like the back button.
LLMs are Markov chains in latent space, it's the latent representation that give them their power, but ultimately there's not as much difference as one would suspect.
Physical objects being physical things that you can touch is the feedback. Mass, inertia, and friction
there's a perspective where the consumer is not much of a factor at this stage, this is just a push to get modernized renewable infrastructure, and much more of it. its still very likely that the owners of each site will unilaterally price their power at higher rates over time, based on demand growth and competition in that area.
There has been a large amount of open source to improve window management, I'd say check again!
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For most conversations I get: "I'm just a language model, so I can't help you with that.", "As a language model, I'm not able to assist you with that.", "
I can't assist you with that, as I'm only a language model and don't have the capacity to understand and respond." — whereas ChatGPT gives very helpful replies...
When asking for help/advice it's useful to start off by doing some research and covering everything you've tried thus far, instead of expecting others to do everything for you.

I've searched everywhere and posted to various forums and included all the info I've found thus far.

SSGs have been discussed on HN but not in-depth like this and not targeted towards noobies. But I've seen that many people on HN are very knowledgeable about SSGs and even created ones themselves. So this seems to be a good place to post about this.
I first learned about Markov chains in the late 90s when I ran across a Markov chain bot on IRC. The person who wrote it was nice and answered my questions about it. I managed to write my own shitty copy but was pleased enough with myself. Same as you I thought it was one of the coolest things I came across in programming.

Also same as you why I've been very cool to LLM hype. Not that LLMs aren't feats of their own but they're not nearly as smart as their hype suggests.
Initial takeaway for me is that the quality holds up despite generating the images significantly faster than top paid models. Content filtering is pretty annoying but I imagine that improves over time.

https://i.imgur.com/kEa0z4y.png
Imagine being triggered by people
assuming someone’s species.
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It would have been interesting to see the different-sex first vs remarriage chart broken down by sex like they did with the same-sex group. My guess is that women more often get remarried than men, regardless of sex vs different sex marriage.

I don't know, most of the metrics seemed unsurprising. Was there anything you found surprising in these datasets?
Thanks for the extra information.
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I think that arguably Mary Poppins was so popular because she was incredibly mean and acerbic in the books (if memory serves from reading them as a kid.)

The movie Disnified the character just like so many Grimms tales.
> supported by cranky, strongly opinionated and difficult to deal with individuals. The answerer would never recommend anybody use these products.

Interesting how this also applied to the early GNU project as well, with you-know-who being its creator, and yet the end result turned out to be quite markedly different: GNU and FSF, whatever one's opinions may be on the people behind those things, have had enormous impact.
That was a pseudo-background hack because of a neovim upstream issue I believe. Now it reflects the REAL background color
> they could each be correct, individually

In that case "They could all be right that their market share might be higher". Because they never operate individually, in isolation. Two people can predict opposite outcomes that could be correct for a coin flip but only one is correct.

More on the point, I think they all invest in the same strategy not because they know they'll win but because they know without it they'll lose. Even so it's guaranteed that some of them will lose.
I don't think Adam Smith defined this exactly, can you show me what you're referring to?

I also think your description is very iffy. "A market which approaches a state of perfect competition" depends on what amount of competition you think is perfect. Furthermore, it could be achieved either through regulating or not regulating (depending on what you think "perfect" is), so the term doesn't really say anything about actual policies.

The very intuitive meaning of free market is an unregulated one, IMO. I'm not able to find an ubiquitous or official definition, but most top google results lean in this direction.

I do think that conflating the means (unregulated market) with the end goal (perfect competition market) into the term "free market" is a brilliant marketing move for free market advocates, but it's somewhat dishonest.
> Latinos, which, in addition to their Native American "base", have quite a lot (~20% ?) of European ancestry (and even more culture)

What? You can't just conflate culture or place of origin with ancestry.

Plenty of what you call "Latino" people have zero native american ancestry.
I’m a big fan of YC, HN, and Garry Tan.

I’d love to support Garry politically to get SF back to its roots and to put math back in schools.

Unfortunately Garry has blocked me on X for no good reason that I can think of?
Your thought is a good one, and I think it is a valid approach. The barrier that comes up when doing this is still going to be cheating. How do you separate the people who are cheating on these at-home tests?

Salesforce had a good interview practice a few years back where they invited you to a meeting. Started a recording, then asked you to keep your microphone and camera on and do several simple programming tasks. It was an "open book," and you could use whatever you wanted, but you just had to show how you got to where you were (and you could only use one monitor so that it was clear what you were looking at at all times). The engineer who met you on the call left after just a couple of minutes, and you could work in peace without having to worry about "entertaining them."
I'm the same way. I've tried like a half dozen times over the years to "get into" vim. It seems like the perfect thing for me. I used to love wasting time ricing my Arch install. But you know what happens? I get 3 hours into setting it up and realize I am only marginally closer to what I already have with VS Code. And in VS Code if I want more language support or some fancy new feature, it's like 3 clicks and it's just working immediately.
> What I mean is that a big refactor might take 9 months to do atomically whereas it could have been done in 3 months as a massive single PR. However I guarantee you we'd have spent 6+ months cleaning up unexpected issues that show up after merging the giant PR.

Yes, one of the lessons of process engineering a la Deming is that the important thing is to get the process under statistical control, which typically means minimizing the variance inherent in a process, rather than the mean. Doing a big refactor might minimize the mean time to completion, but it will typically have a long tail which occasionally bites you and costs you dearly. The approach that minimises the variance might take longer in mean but generally when it's done it's done. Fewer unexpected surprises.
In terms of enshittification, a good model would be downranking by number of ads and tracking. That applies some counterpressure.
No one has spent 100M on training Markov chains.
Debian 10 on Arm QNAP TS-21x/TS-22x
If only doing C and C++ dev work you can get pretty far with a very minimal vim config though

But yeah, webdev had me switch to Lunarvim (my favorite among all those nvim distros)
My favorite intro is https://norvig.com/ngrams/ because it shows a variety of applications using simple code. (and uh since I'm in the acknowledgements, ok.)

(The people saying modern LLMs are just fancy Markov chains in practice are being silly, though.)
I know this is only half-serious, but people will often try to use environmental review processes to stop development (both for conservation or just because they don't want something). Especially in California, where the California Environmental Quality Act has a lot of teeth: https://www.theatlantic.com/ideas/archive/2021/03/signature-...

Handbook: https://www.califaep.org/docs/2024_CEQA_Statute_and_Guidelin...

PDF pages 348, 50, and cases in the appendix discuss aesthetic impacts.

Anybody can raise these objections about a development (usually during a public comment period), with or without merit, and if enough people do so over enough comments, it can really mire down a project. Even if all the concerns are ultimately dismissed, it forces the developer and agency to spend time evaluating and rebutting them, and sometimes developers will just give up out of frustration and move onto areas with less regulation.
You're quite right that there's quite a difference when it comes to physical work, especially not too physically demanding work without a large "brain work" component (or done by young, reasonably fit people).

Since we are on hacker news, a forum seemingly overrun by silicon valley devs, I didn't expect your comment to focus on that kind of work. But when we look at physically demanding work with a decent amount of brain work, for example some kinds of woodworking, you can still see that effect. People can work longer hours and more days to a certain extent, but then the rate of accidents goes up (and I'd expect it to behave in a non-linear fashion). And if that effect is true in that direction, why should it not work for less than 40 hours?

> I doubt many people can sustain their work output over 16 hours for most jobs. But that's not really what we're talking about here.

Apparently, I'm no good at making myself clear. It's probably the language barrier, I'm decent enough at understanding English, but I lack any sort of conciseness, I believe. This was meant to be an extreme example, to make the point more obvious, but let's use a similar, more normal one.

Let's say instead of moving to a 4 day workweek, we move back to a 6 day workweek. Daniel you believe that you get 20% more output than before? Even with physical jobs that don't involve too much brainwork, I believe that this is not the case, as there are diminishing returns when the time for recreation is cut too short.

That depends on the individual of course, younger people need less than older people in general, and things like children, disabilities, a long commute and a host of other factors can change the equation, too.

> I don't understand the argument that working less doesn't mean you get less work done in general.

The argument is basically that for brain work, if you spend 20% more time per week at work, you might only produce less than 5% more output, since your brain will otherwise produce too many errors, which cost time to correct.

That is seen as an inefficient use of an employee's time. Also, his implies that maybe we could get almost the same output from people who work a 4-day-workweek. Now the question is, where is the sweet spot, as it is unlikely to be the status quo (that's what I clumsily tried to imply with the remark about the 40-hour-workweek not being"god-given")?
This can't scale forever, of course, or we'd all be working 1 hour a week and be extremely productive in that hour :D

But maybe the 4-day-workweek is that sweet spot. And since wages haven't kept up with corporate profits for a while, a lot of people - myself included - are eager to find out.
GitLab minimises generated files in merge-requests
It would be appropriate for someone with a tech blog. I'm not a "techie", nor do I have a tech blog. I'm seeking advice from knowledgeable people. See my other recent comment.
I had this experience recently and realised I had crippled my day to day system with a slow DNS resolver. Suddenly everything was snappy.
I have sort of a contrarian take on this, at least by traditional academic standards. I think applicability is extremely undervalued in modern mathematics. Tao references algebraic geometry in the interview, but the people who do algebraic geometry in applied settings ("applied" is also being quite generous here, in my opinion) are doing math that is basically unrelated to algebraic geometry as practiced by theoretical mathematicians. Even in connections to computer science, the people studying algebraic circuit complexity-which a priori should benefit a lot from algebraic geometry-basically can't use any modern algebraic geometry theory because (to my understanding) the theoreiticians choose to work in a setting that is so elegant it rules out interesting algebraic circuits. And circuit complexity is still quite far removed from applications the way I think of it.

I think the best and most beautiful mathematics is driven directly by applications, and made better for the pressure to apply to a real problem (not a problem that just mathematicians care about).

A quote from Milind Tambe's 2018 AAAI keynote talk sums up why:

> Deploying the algorithms in the field often gives us new insights into what might be wrong with our models and provides us new research directions.

If you've never heard of Tambe's work, you should really check it out. He literally sends his grad students to do field work to study how their algorithms are performing.

Too many mathematicians consider "applications" as "can be used in other, purely theoretical academic papers," and based on my research for my next book (pmfpbook.org) I find that large swaths of what is claimed to be applied math is actually not useful for solving the real world problems they claim to be useful for. A math thing will be tried in production, to much acclaim and fanfare, and then it will be quietly discarded in favor of simpler, more holistic, or less complicated solutions that end up performing better. But the academic publications praising it persist for decades, and nobody seems to get the message that it's not used.

One thing Tao gets right is that the best math is interdisciplinary. Connecting ideas across different theories is one great way to demonstrate the power of a theory. I would add that, to be great a theory needs to _grounded_ in a practical setting, where it's not just mathematicians judging the math for its beauty but an external reality pushing back. For my aesthetic, a pretty theory is just not enough.
in the accessibility settings of iOS one can enable “button shapes” which renders hyperlink-style underlines on buttons masquerading as text. very handy for me. also appreciate differentiate without color, on/off labels, and high contrast: it is much faster for my ADHD brain to navigate iOS with these affordances, relevant details are more salient and my brain has more chance to build a visual hierarchy.
"That is a problem if you’re a dishonest designer. After all, how do you tell your client that you’ve just reinvented the wheel? You can’t just use boring old buttons in your shiny new product."

The core problem is that people have trouble differentiating between the desire to improve something and the desire to change something.
So if the neanderthals were "top flight predators" that predated on the scrawnier yet intelligent homo sapiens I can't help but be reminded of the passages of the Bible referencing the Nephilim.

From Genesis 6:4

> The Nephilim were on the earth in those days—and also afterward—when the sons of God went in to the daughters of humans, who bore children to them. These were the heroes that were of old, warriors of renown.

Some higher power or the inscrutable workings of evolution and planetary change, spared us.