Not exactly on topic, but I have to endorse mise; it's a really, really great tool that solves a number of different problems.
Example: I was recently working on a large project that needed a specific version of Python, and there's a lot of ways to solve that, but mise was an easy and robust one. But also, the project needed a bunch of different tools to build it, deploy it, do local dev, perform certain maintenance tasks like rotating secrets, work through certain operational runbooks, etc., and mise was an easy and robust way to solve that too. Once you know everyone on the team will have the same tools available, if a runbook would be simpler if you could assume everyone has jq installed, well, just add it your the project's mise config, and now they do. And then when I switched to working on a Java service, and then later a Node service, well, obviously mise was an easy and robust solution there too.
By contrast, I made an effort a year or two back to adopt nix, which (despite starting from a very different place) solves a lot of similar problems, but found it a bit daunting (large, complex, poorly documented, and felt hard to partially adopt), and while I love the concept of nix, as a practical matter I ended up abandoning the effort. But mise was really easy to understand, adopt, and progressively add to an existing project without unduly impacting other team members. (Example: Mise will read existing verion manager configs from tools like sdkman, which makes adopting it over time easier.)
It's got to the point now where I'm using mise in place of Homebrew or other system level package managers for basically all CLI tools. Which feels weird when I think about it, but mise genuinely just feels like the better solution. If mise has a flaw, I haven't stubbed my toe on it yet.
> Jani Patokallio runs gyrovague.net in order to harass people who provide useful public services.
I mean...investigating who runs secretive yet popular websites is a useful public service, generally called "journalism". And your comments in this thread could be seen as an attempt to harass Jani.
I do not, to be clear, think you're doing anything morally wrong, but I'm also not sure I see how you can draw a bright line between your actions and Jani's. By the rather stretched logic and loose standards you've been using in these comments, it seems like you run your HN account to harass people who provide useful public services, no?
I'm absolutely open to the argument that Jani has does something wrong, but nothing you've said has really even accused them of anything.
If you want to define doxing narrowly (as it was historically) then I would agree that all (or nearly all) such cases are wrong, but this is by no means clearly doxing. If you want to define doxing widely (as is common lately), then I'll accept this is clearly an example of doxing, but note that there's nothing inherently wrong with doxing.
Just saying "doxing" does not establish that the underlying actions are immoral, and so it does not follow that the target not appreciating it is relevant. If I take the last parking place in a crowded lot, the driver behind me certainly won't appreciate it, but I have no obligation to give it up. If you think Jani has done something incomparable to taking a parking place, you need to make the case.
> When Amazon can buy stuff on your own website thats out of stock for wholesale prices without your knowledge, it's time to get your shit together. Your shop software is at least misconfigured.
I really wish the article had dug into that more, because it made very little sense.
Odd story. If you strip out the "Amazon" and "AI" stuff, the core seems to be that there's a tech company offering a service called Buy For Me which crawls various merchants who operate their own storefronts, lists the products they find for Buy For Me's users, and have a button the users can press which...buys the product.
Which is a little odd, and the value is questionable, but fundamentally seems...fine? You're a merchant, you're selling pencils on the internet, people are buying your pencils from you. And historically the way this might have been built would be something like a desktop application that users install, and which then goes and loads websites, displays them, fills in payment info, etc. Which of course is exactly what the web browser does already.
And all of the complaints about how it should be opt-in also feel odd. If you install WooCommerce and put a storefront up on the public internet, you've pretty obviously opted in to "selling your products on the internet". You don't need to tell Firefox that it's okay for people to use it to buy your stuff!
Of course, this isn't a desktop app, it's agentic AI run by Amazon, which certainly makes it feel different, but I'm not entirely sure how different it should make our analysis.
But also, the story raises a bunch of interesting questions and then doesn't answer any of them:
> Chua also received at least several orders for products that were either out of stock or no longer existed on her website.
How exactly did this happen? The story is that the orders are being placed through the normal storefront, right? So how exactly?
Or:
> Gorin sells wholesale through a password-protected section of her website, where retailers must submit resale or exemption certificates so orders are properly exempted from sales tax. She said she was still able to complete a “Buy for Me” purchase of a product pulled from her wholesale site despite never opting into the program — a scenario that could expose her business to tax liability if individual shoppers were able to place tax-exempt orders. Gorin also worries that surfacing wholesale pricing could undermine profit margins, allow competitors to undercut her prices or bypass minimum order requirements designed to keep wholesale sales viable.
That's just begging for an explanation. Is Amazon is somehow using stolen credentials to obtain price information? Or is Goren mistaken and the info isn't password protected at all? (And if not, why not?)
I'd also be interested in unpacking a bit more the legal and contractual implications of agreements like Mochi Kids has signed. The brand apparently doesn't allow its products on Amazon, and doesn't allow partners like Mochi Kids to sell on Amazon, but...Michi Kids isn't? Mechanically someone is buying the products at retail and effectively relisting them. Which...I dunno, feels legal? Is any agreement actually being violated here? Does the brand have a course of action? Does Mochi Kids have an actual legal obligation to opt out? Does Amazon have a legal obligation to let vendors opt out? Is Amazon legally buying anything from Mochi Kids, or is the customer the person using Amazon? Given the payment info being used is the customer's, I'm not sure Amazon has a commercial relationship with the brand or the vendor?
And so on. It feels like too much of the story is being carried by it being about Amazon and AI, which means the author felt fine just glossing over the details.
I mean, the S in CFS stands for "syndrome", which is "a set of medical signs and symptoms which are correlated with each others [...] When a syndrome is paired with a definite cause this becomes a disease." (From wikipedia.)
So I mean, yeah, that literally does mean "we don't know what this is, and we don't know what's causing it, so we're dumping everything that looks like it in a bucket while we do more research". But that doesn't mean it's not a real thing; it means that we don't know what it is or what's causing it (and that it may well not be a single thing at all).
That's pretty different than saying "it's not a thing at all".
I don't think that's quite right? There's been a fair amount of evidence pointing at possible issues, but there's no clear answer due to poor (or just different) study design, small sample sizes, different criteria across studies, different sample groups, etc.
> ...it is difficult to establish the role of mitochondria in the pathomechanisms of ME/CFS/SEID due to inconsistencies across the studies. Future well-designed studies using the same ME/CFS/SEID diagnostic criteria and analysis methods are required to determine possible mitochondrial involvement in the pathomechanisms of ME/CFS/SEID. [...] There is consistent genomic research suggesting that ME/CFS/SEID is not a primary mitochondrial disorder, however, mitochondrial decline might occur due to secondary effects of other disrupted pathways. [...] As population samples were small, these results should be interpreted cautiously.
I wouldn't summarise that as "no evidence". It's more like "ME/CFS doesn't seem to be a genetic disorder causing defective mitochondria, and the mitochondria look the same, but they seem to function differently for some reason even if we lack enough data to figure out why yet". Note that, eg, of the 19 studies reviews, 5 tried to check for differences in mitochondrial respiration between ME/CFS patients and healthy controls, and 4 of the 5 found notable differences; one study was able to reliably detect if a cell sample came from a ME/CFS patient or a healthy control based on measuring mitochondrial respiration.
I don't know that's enough to fully reject the null hypothesis just yet, but it's certainly not clear we can accept it either.
> A strapping newborn baby boy is understood to have set a New Zealand record, weighing in at a whopping 6.85kg (15lb 1oz) - the equivalent of nearly seven 1kg blocks of cheese.
I mean, the kilogram is an SI unit, but uh, I do not know if clarity has been added here.
Fundamentally both "gambling" and "insurance" are about trading a stream of small guaranteed payments for a chance at receiving a large payment. More generally, it's about trading risk. In insurance the risk is transferred to the insurance company; in gambling the risk is trasnferred to the gambler.
They're precisely the same transaction, just packaged in different ways, and with tons of overlap. What differs is the participants.
Individuals don't tend to want or need a lot of risk, so a transaction where risk is transferred from an individual to a large company (like an insurance company) is generally good, and one where risk is transferred from a large company (like a casino) to an individual is generally bad.
The problem is that Google forces actual good cooks to make their recipes look like worthless blogspam, but a good original recipe is not actually worthless blogspam, even when disguised in the way Google requires.
I sympathise with the author and agree that there are some pretty terrible stories and numbers floating around, but the unstated premise of the article seems to be:
The game industry is monolithic, it has recently undergone a sweeping change, but no further change is possible, therefore it is safe to make a linear projection based on what's happened over the last six months out to infinity. And I'm skeptical that those are good assumptions to make.
> Epic Games in September laid off over 800 people, almost 15% of the entire company. Epic is one of the most successful and profitable game companies that exist. [...] For years, every other game company has tried to copy Fortnite, and mostly failed at the attempt. This is not enough to ensure job security
Okay, yeah, that's interesting, and no doubt traumatic for the people who were fired, their colleagues we have so far avoided it, and for devs working in the broader industry, and I am sympathetic. But: Sometimes companies overhire, sometimes corporate priorities shift, sometimes a company decides to reorient towards a leaning production model. Sometimes it works; sometimes it doesn't. There isn't any industry where overall profitability is, alone, enough to ensure job security. (And I'd also suggest that putting these layoffs in the context of the broader tech industry and the end of zero interest rates might also yield some useful insights...)
In any case, if Epic fires a bunch of devs, and profitability drops, then that was a mistake and they will try to staff back up. And if it doesn't (or rises) then that suggests that game development is actually more profitable than previously expected and individual game devs are more productive than previous realised, which will of course be cold comfort for the devs laid off, but suggests that overall employment and compensation across the broader industry will be tracking upwards not downwards, which is good news for game devs as a whole in the medium to long term.
To be clear: I do not want for one moment to defend the big studios (who appear, by and large, to have C-suites full of pod people who delight in human misery), or to minimise the very real pain suffered by gave devs, but the idea that an entire industry can somehow run off a cliff in a way which is permenantly non-recoverable is...well, let's say it's a bold claim that needs extraordinary support.
> Games in 2024 and 2025 will be a few labors of love...
Yeah, plausible. But what do you think is going to happen in 2026 and 2027?
People interested in this might also be interested in Orion from the Kagi team: https://kagi.com/orion/
Orion is built on Webkit, has a focus on privacy, built in ad blocking, and runs on macOS and iOS. It also has a lot of other interesting features baked in, although the last time I tried it I ran across a couple of glitches too (to be fair, it's in beta and under active development). Another point of favour of Orion is the Kagi team is clear it's strictly funded by users and there's an "Orion+" thing where you can subscribe and get access to RC builds.
It doesn't seem to be clearly stated, but I think Quetta is built on Chrome? I'm not thrilled with the ongoing march of Chrome as the universal core of every nominally independent browser. And they also seem to be a bit cagey about what their monetisation plans are, which might be an oversight but is a little concerning.
That isn't what your linked graph shows. Slightly different hypothetical:
World 1: Men evaluate women on highly idiosyncratic scales. They "like" women in the top 53% of their personal scale, but it's a different scale for each man. All women are "liked" by 53% of men (but it's a different 53% for each woman). Women also evaluate men on highly idiosyncratic scales. They "like" men in the top 5% of their personal scale, but it's a different scale for each woman. All men are "liked" by 5% of women (but it's a different 5% for each woman). Due to their lower standards, men end up "liking" a lot of women who do not "like" them back, but nonetheless, every man will find a mutual match once in every 100 profiles they look at. Women are more selective, and better at focusing their attention on the type of men who might "like" them back, but overall success rates are broadly similar, and every woman will find a mutual match 1.8 times in every 100 profiles they look at.
World 2: Men rank women on a shared objective measure of attractiveness, and "like" any woman in the top 53% of the scale, so 53% of women are "liked" by all men, and 47% are "liked" by no men. Women also rank men on a shared objective measure of attractiveness, and "like" any man in the top 5% of the scale, so 5% of men are "liked" by all women, and 95% of men are "liked" by no women.
Note that in this model on average, 5% of all "likes" from men to women will be mutual, but 95% of men will "like" women and it will never be mutual while 5% of men will "like" women but it will always be mutual. Similarly, on average, 47% of "likes" from women to men will be mutual, but 47% of women will "like" men and it will never be mutual while 53% of women will "like" men and it will always be mutual. (Further note that since most relationships are monogamous, while a bare majority of women can find a mutual match, an overwhelming majority will not have it progress into a relationship since all women are chasing the same 5% of men.)
World 1 matches the graph perfectly, but describes a situation where merely looking at 100 profiles on Tinder guarantees every man a mutual match no matter how ugly or undesirable you may be. World 2 also matches the graph pretty closely, but dooms the vast majority of men and women to be unable to find a relationship at all.
Neither world seems very similar to our own to me (although I do recognise a specific subgroup of men intuit that world 2 is fairly close!), but the fact of the matter is we can't distinguish between world 1, world 2, or reality based on the graph you linked.
Again, you're assuming that men and women are using the app in the same way, and that a "like" means the same thing. If you assume that women typically only "like" men they would be open to dating, but men will "like" anyone even vaguely plausible with a plan on filtering out poor matches later in the process, you'd see data like this, but it wouldn't support your conclusion. (Is this happening? No idea; again, you'd need more data.)
Further, and much more importantly, you're looking at data showing how often men and women like potential partners, but you're trying to deduce from it how often men and women are liked by potential partners. It's interesting that women apparently only "like" 3.2% of the men they see, but that does not in any way suggest that only 3.2% of men will be "liked" by a woman.
Consider two hypothetical worlds:
In world 1, each woman is very selective (and is only open to dating 1% of men), but every woman has selected a different 1% to be interested in.
In world 2, women are unselective (and are open to dating 30% of men), but all women have chosen the same 30% of men to pursue.
Obviously both worlds seem to differ signiicantly from our own, and each has some challenges! But fairly obviously despite women in world 1 being 30 times pickier, all men could at least in theory find a partner who wanted to date them, whereas in world 2 the majority of men would never do so. And yet if you replicated the graph you linked for world 1, it would have the red bar for the female line take up 99% of the graph. It's really not showing what you think it is.
(Again, I have to stress: I am not trying to claim I know how dating or attraction works, or what the median experience for using a dating app is actually is like; I am instead pointing out that nobody seems to know this, because we lack data.)
Absolutely not. If anything, that's further evidence of my point, and I literally almost mentioned it before deciding my comment was getting a bit rambling already.
Anyhow, assuming for the sake of argument that OKCupid's data is valid and replicates, then there's two responses:
The short and somewhat silly argument is that women also say they care about attractiveness a lot less than men do, so it all averages out. Men care about attractiveness and have an accurate perception of it; women don't care about it and have an inaccurate perception of it. Neither a big deal nor surprising.
The longer point though is that yes, men, judging women's attractiveness, say very different things than women do, when judging men's attractiveness (again, if we believe OKCupid's data). But that doesn't tell us anything about how men and women perceive attractiveness, it just tells us how they talk about attractiveness, and in the exact same way that we might be skeptical when a man says "there's literally no one to date" (and suspect they mean there's just no one they feel meets their standards who will date them), we might be skeptical of a woman that marks most men down as being below average attractiveness. Is there, say, some bit of cultural conditioning pushing women to rank men as unattractive when they don't want to date them for a non-appearance reason? Or to rank men as unattractive to avoid seeming too eager, even when they do find them attractive? How often do women end up dating men they rank as unattractive, and how does this rate compare to the rate of men dating women they rank as unattractive? And we could go on, but the point is that when you start to dig into it, the pattern falls apart, suggesting this is a quirk of the survey design at best, and not an real insight into meaningful differences betweem male and female bahaviour.
Such statistics can be difficult to parse. Hypothetical:
Person A chats with five people. Two seem okay, two seem like poor choices, one seems unhinged and is quickly blocked. Of the two good options they go on a date with each, selects one of them, and forms a relationship.
Person B is deluged with messages, many of them vulgar. After some filtering, they end up trying to hold coversations with twenty different people, but struggle to form a connection with any of them. Eventually they go on a date with the person who seems the best, it goes okay, and they form a relationship.
In this example, is person A or B able to be "choosier"? Which experience would you prefer if you could choose? I would argue that quantity is not valuable independent of quality. Or to put it another way, I suspect you would find that most single women would argue they have no greater number of acceptable choices than single men do.
The (obviously real) difference in the number of men sending women unsolicited pictures of their genitals compared to women sending men such pictures isn't really relevant.
Example: I was recently working on a large project that needed a specific version of Python, and there's a lot of ways to solve that, but mise was an easy and robust one. But also, the project needed a bunch of different tools to build it, deploy it, do local dev, perform certain maintenance tasks like rotating secrets, work through certain operational runbooks, etc., and mise was an easy and robust way to solve that too. Once you know everyone on the team will have the same tools available, if a runbook would be simpler if you could assume everyone has jq installed, well, just add it your the project's mise config, and now they do. And then when I switched to working on a Java service, and then later a Node service, well, obviously mise was an easy and robust solution there too.
By contrast, I made an effort a year or two back to adopt nix, which (despite starting from a very different place) solves a lot of similar problems, but found it a bit daunting (large, complex, poorly documented, and felt hard to partially adopt), and while I love the concept of nix, as a practical matter I ended up abandoning the effort. But mise was really easy to understand, adopt, and progressively add to an existing project without unduly impacting other team members. (Example: Mise will read existing verion manager configs from tools like sdkman, which makes adopting it over time easier.)
It's got to the point now where I'm using mise in place of Homebrew or other system level package managers for basically all CLI tools. Which feels weird when I think about it, but mise genuinely just feels like the better solution. If mise has a flaw, I haven't stubbed my toe on it yet.