Yeah, it’s to protect them from disease. In almost all circumstances a place with tap water from a municipal source is fine.
Premature infants might be advised to only get sterile water for a bit as an extra precaution, and people might also hold off a little longer on well water.
Those are entirely different. Peano developed a system for talking about arithmetic in a formalized way. This allowed people to talk about arithmetic in new ways, but it didn’t show that previous formulations of arithmetic were wrong. Godel then built on that to show the limits of arithmetic, which still didn’t invalidate that which came before.
The development of complex numbers as an extension of the real numbers didn’t make work with the real numbers invalid.
When a new scientific model is developed, it supercedes the old model. The old model might still have use, but it’s now known to not actually fit reality. Relativity showed that Newtowns model of the cosmos was wrong: it didn’t extend it or generalize it, it showed that it was inadequately describing reality. Close for human scale problems but ultimately wrong.
And we already know relativity is wrong because it doesn’t match experimental results in quantum mechanics.
Science is our understanding of reality. Reality doesn’t change, but our understanding does.
Because math is a fundamentally different from science, if you know something is true then it’s always true given the assumptions.
Not quite. Science is empirical, which means it’s based on experiments and we can observe patterns and try to make sense of them. We can learn that a pattern or our understanding of it is wrong.
Math is inductive, which means that we have a starting point and we expand out from there using rules. It’s not experimental, and conclusions don’t change.
1+1 is always 2. What happens to math is that we uncover new ways of thinking about things that change the rules or underlying assumptions. 1+1 is 10 in base 2. Now we have a new, deeper truth about the relationship between bases and what “two” means.
Science is much more approximate. The geocentric model fit, and then new data made it not fit and the model changed. Same for heliocentrism, Galileos models, Keplers, and Newtons. They weren’t wrong, they were just discovered to not fit observed reality as well as something else.
A scientific discovery can shift our understanding of the world radically and call other models into question.
A mathematical discovery doesn’t do that. It might make something more clear, easier to work with, or provide a technique that can be surprisingly applicable elsewhere.
We discovered one of the postulates was really interesting to fuck with.
It’s better to say that we’ve discovered more math, some of which changes how we understand the old.
Since Euclid, we’ve made discoveries in how geometry works and the underpinnings of it that can and have been used to provide foundation for his work, or to demonstrate some of the same things more succinctly. For example, Euclid had some assumptions that he didn’t document.
Since math isn’t empirical, it’s rarely wrong if actually proven. It can be looked at differently though, and have assumptions changed to learn new things, or we can figure out that there are assumptions that weren’t obvious.
Fundamentally, I agree with you.
Because the phrase “Wikipedians discussed ways that AI…” Is ambiguous I tracked down the page being referenced. It could mean they gathered with the intent to discuss that topic, or they discussed it as a result of considering the problem.
The page gives me the impression that it’s not quite “we’re gonna use AI, figure it out”, but more that some people put together a presentation on how they felt AI could be used to address a broad problem, and then they workshopped more focused ways to use it towards that broad target.
It would have been better if they had started with an actual concrete problem, brainstormed solutions, and then gone with one that fit, but they were at least starting with a problem domain that they thought it was a applicable to.
Personally, the problems I’ve run into on Wikipedia are largely low traffic topics where the content is too much like someone copied a textbook into the page, or just awkward grammar and confusing sentences.
This article quickly makes it clear that someone didn’t write it in an encyclopedia style from scratch.
A page detailing the the AI-generated summaries project, called “Simple Article Summaries,” explains that it was proposed after a discussion at Wikimedia’s 2024 conference, Wikimania, where “Wikimedians discussed ways that AI/machine-generated remixing of the already created content can be used to make Wikipedia more accessible and easier to learn from.” Editors who participated in the discussion thought that these summaries could improve the learning experience on Wikipedia, where some article summaries can be quite dense and filled with technical jargon, but that AI features needed to be cleared labeled as such and that users needed an easy to way to flag issues with “machine-generated/remixed content once it was published or generated automatically.”
The intent was to make more uniform summaries, since some of them can still be inscrutable.
Relying on a tool notorious for making significant errors isn’t the right way to do it, but it’s a real issue being examined.
In thermochemistry, an exothermic reaction is a “reaction for which the overall standard enthalpy change ΔH⚬ is negative.”[1][2] Exothermic reactions usually release heat. The term is often confused with exergonic reaction, which IUPAC defines as “… a reaction for which the overall standard Gibbs energy change ΔG⚬ is negative.”[2] A strongly exothermic reaction will usually also be exergonic because ΔH⚬ makes a major contribution to ΔG⚬. Most of the spectacular chemical reactions that are demonstrated in classrooms are exothermic and exergonic. The opposite is an endothermic reaction, which usually takes up heat and is driven by an entropy increase in the system.
This is a perfectly accurate summary, but it’s not entirely clear and has room for improvement.
I’m guessing they were adding new summaries so that they could clearly label them and not remove the existing ones, not out of a desire to add even more summaries.
So, I wasn’t referring to enjoyment. I spoke of engagement or interest. It’s why programming is more appealing than data entry.
You’re just doubling down on the false dichotomy I spoke of. It’s not at all uncommon to find someone with plenty of experience who can easily and honestly tell you why they think what the company they work for does is interesting.
Asking someone why they think working at the job they’re applying for is appealing isn’t “hiring for enthusiasm”, and it’s honestly odd that you keep casting it that way.
I get where you’re coming from, and I partly disagree. It doesn’t seem like you’re parsing what I’m saying because of this “either one or the other” attitude though.
No offense intended, but it makes you come across as burnt out and sad. I don’t work for small companies, with inexperienced people, and I’m not constantly shipping broken code that needs rewriting. I’ve been doing this for roughly 15 years and I can honestly say “working in security in general is interesting because it forces you to think about your solution from a different perspective, the attacker, and working at $AuthenticationVendorYouQuitePossiblyUse in specific is appealing because you get to work on problems that are actually new at a scale where you can see it have an impact”.
That’s not gushing with enthusiasm: it’s why I’m not bored everyday. If you’re actually just showing up to work everyday and indifferently waiting to be told what to do because it’s all just the same old slog… That’s sad, and I’m sorry.
I’m lucky that after all these years still get those moments of great enjoyment when at the end of doing something insanelly complex it all works
I just think it’s worth pointing out that that is an example of the work being engaging.
No one is so naive as to think that you work a job for anything other than money. The original post doesn’t even seem to convey that it’s bad to ask about the pay and benefits. It’s saying that if, when directly asked, the candidate has no answer to what seems interesting about the job they might not be a good fit.
You seem to be an experienced software developer. You’re easily qualified to do basic manual data entry. Same working environment, same basic activity. Would you be interested in changing roles to do data entry for $1 more salary?
I’m also a software developer, and I can entirely honestly say I would not, even though it would be less responsibility and significantly easier work.
Even the boring parts of my work are vaguely interesting and require some mental engagement.
It seems there’s this false dichotomy that either you’re a cold mercenary working 9 to 5 and refusing to acknowledge your coworkers during your entitled lunch break, or you’re a starry eyed child working for candy and corporate swag. You can ask for fair money, do only the work you’re paid for, have a cordial relationship with coworkers, and also find your work some manner of engaging.
It’s not unreasonable for an employer to ask how you feel about the work, just like it’s not unreasonable for a candidate to ask about the details of the work.
Sure. I wouldn’t disqualify someone for being ambivalent towards what we’re working on, but the person who seems interested is gonna be better to work with.
Likewise when looking for a place to work, if the tangibles are equivalent I’ll prefer the place with better intangibles.
I’m not in HR or management, so I don’t care about cost effectiveness or productivity beyond “not screwing me over”. From that perspective, it’s generally nicer to work with someone who finds it interesting than with someone who doesn’t.
There’s no point asking “why do you want to work here”, because the answer is obviously a combination of money and benefits, and how food and healthcare keeps you from being dead.
I can’t fault an interviewer who’s clearly trying not to ask the obvious question and instead actually ask how the candidate feels about the work instead of disqualifying them for not volunteering the right answer.
It’s not unreasonable for an employer to ask a candidate how they feel about the work anymore than it’s unreasonable for the candidate to ask about the working environment.
I actually kinda agree with both here.
It sucks working with someone who is utterly disinterested in the work, if it’s anything above rote work.
Asking the candidate what they found interesting about it is at least a basically fine idea. If they can’t answer when you ask, that actually is kinda concerning.
Big difference between asking and expecting them to volunteer the information.
At the same time, if the people interviewing you can’t even pretend to show basic conversational courtesy by asking some basic “what do you do for fun” style questions or anything that shows they’re gonna be interested in the person they’re looking to work with, that’s a major concern.
If it’s developed for the government, even by a private contractor, it’s still considered US government code and is public domain. It’s why sqlite is public domain.
I personally doubt there’s much available in the off-the-shelf fighter HUD system market, personally.
Eh, there’s an intrinsic amount of information about the system that can’t be moved into a configuration file, if the platform even supports them.
If your code is tuned to make movement calculations with a deadline of less than 50 microseconds and you have code systems for managing magnetic thrust vectoring and the timing of a rotating detonation engine, you don’t need to see the specific technical details to work out ballpark speed and movement characteristics.
Code is often intrinsically illustrative of the hardware it interacts with.
Sometimes the fact that you’re doing something is enough information for someone to act on.
It’s why artefacts produced from classified processes are assumed to be classified until they can be cleared and declassified.
You can move the overt details into a config and redact the parts of the code that use that secret information, but that still reveals that there is secret code because the other parts of the system need to interact with it, or it’s just obvious by omission.
If payload control is considered open, 9/10 missiles have open guidance control, and then one has something blacked out and no references to a guidance system, you can fairly easily deduce that that missile has a guidance system that’s interesting with capabilities likely greater that what you know about.
Eschewing security through obscurity means you shouldn’t rely on your enemies ignorance, and you should work under the assumption of hostile knowledge. It doesn’t mean you need to seek to eliminate obscurity altogether.
Well, you probably could. Issue is that you can’t self host the IRS. If they aren’t running the service that accepts the data there isn’t much you can do.
More likely they’ll just turn off or unpublish the API that it depends on.
Could also store our bools as floats.
00111111100000000000000000000000 is true and 10111111100000000000000000000000 is negative true.
Has the fun twist that true & false is true and true | false is false .
I set all 8 bits to 1 because I want it to be really true.
The US has a water system effectively comparable to the ones across Europe, FYI. That includes lead levels, since it wasn’t just the US that used lead pipes.
In most circumstances lead pipes are safe to replace with different materials as part of routine maintenance. It’s only very notable incidents where things go wrong that have driven a push for greater haste, since it highlighted the consequences of things going wrong.