John BS @johnabs@qoto.org

@freemo 2 whole seconds?? At that point just take a picture, it'll last longer :P

The general rule is "If the amount of time you're looking would damage your retinas from looking at the sun at noon during summer, it's too long of a glance". There is a difference between "noticing", "looking", "staring", and 2 solid seconds is straddling the line of the latter two, and the first is universally fine, but that's like 0.5-0.75 seconds.

As an aside, nearly all (more on this below) women know what they're signing up for when the go out dressed a certain way, so don't ask, don't stare, but a passing glance, even if she notices, is likely acceptable, though this depends on the woman and her understanding of male psychology as a function of her dressing habits.

I had to have this conversation with my (then girlfriend) wife about how she was drawing attention to herself with her very tight fitting crop-tops and short shorts. Her mom did some strange parenting to her daughters, so my wife didn't know until I spelled it out and then she was mortified at how men were looking at her. She just thought they were "being friendly"

@queenofhatred No problem lol

I'm just trying to make some friends and learn stuff, but you don't need to feel sorry or obligated. Thanks for considering it though

@queenofhatred Well I'm also trying to figure out lisp and be a better programmer (though not doing raytracing, admittedly).

If you want to do some programming together sometime so we can both learn some stuff, I'm down, and it may help us both build some better habits :)

@queenofhatred

I can 10000% relate. I had to change my career path about 6 years ago (twice), and now I'm just like "WHY IS THIS SO HARD WHEN EVERYONE ELSE MAKES IT SEEM SO EASY???"

And then I realize that, despite having 12 years of academic research experience, only 4 of those are in my new field (and I don't have a bachelors/masters in it either)...so then I feel at least a better about it. And then the cycle repeats the next week lmao.

What projects are you working on rn? Are you doing them in lisp or something else? Either way, I believe you can do it!

@queenofhatred @lispi314 Agreed, I just wish their documentation was better

@lispi314 I was just being silly, I agree that practically every language needs a REPL, especially as a lisp fan, lol.

@lispi314 It's because the devs hate anagrams, and frankly I agree

@freemo Gotcha, just wanted to double check what units since the typo was ambiguous.

I used to teach dimensional analysis problems from the perspective of baking/buying stuff, and I got some of my nursing/agriculture students working out estimates mentally pretty quickly! It improved one girl's test scores by a whole letter grade after the tutoring sessions, so I took that as a win :)

@freemo
> morality of an acid.

Seems like you took a trip from chemistry into ethics with that one, though please do tell how you derive ethical maxims and cracked the "is-ought" problem

(But forreal, did you mean molarity or molality? They should know that well before O-Chem...)

@freemo While I like the idea considering the STEM focus of the group, I would argue the name of the group demands a more philosophically oriented logo.

Perhaps something like Qo | ɟo where the t and o are mirrored, indicating the selfie reflective nature of the intended members, as well as the barrier that exists between coming to personal understanding of truth and conveying it to the rest of the world.

I can sketch something up later, but it’s my bedtime soon lol.

@tiago

Can we please have a reasonable, polite discussion where we operate under the assumption that "the other person may be reasonable but acting under a different set of axioms, hence why they're drawing a different conclusion from my own"?

If you'd actually like a response to your post, I'm more than willing to continue the discussion, but if the comments about your views on my "deep confusion", "being ridiculous", and "projection" don't stop, I'm done. I have not acted in such a manner toward you, and I will no longer tolerate it.

Spoilers for if you decide to continue: this is not "abstract utility theory", this is about multi-criteria optimization, and the mathematical fact that vectors don't have an order unless someone imposes one, which is precisely what you are doing when making accuracy the primary/only metric by which you judge a model.

@hvwaldow @tiago

I would say that this statement is reasonable, and I like it!

But from a multi-objective optimization perspective, you would need to find a way to pick "the best" model in terms of accuracy which would lead you to constructing a Pareto set of model's performance in your K-dimensional decision space.

In that case, I assume Tiago would want to either find/construct a model that dominates the Pareto set (based on his prior comments) or would prefer to know with confidence the entire Pareto set, the corresponding Efficient set of models and their relative performance on all the K metrics so he could select one that suits his needs from the set.

Good comment, IMO!

@tiago

Disregarding your internet psychoanalysis of my "deep confusion" on something that didn't even come up in the conversation, it seems that you actually agree with me:

> Personal beliefs are arbitrary. A person can believe that the moon is made of cheese, and that they are napoleon, etc.

To clarify, the personal belief I was referring to was your equating a model's accuracy with its utility. That IS a personal belief, and is the belief we disagree on, as I think accuracy is only one aspect of utility, not the whole enchilada.

> The utility of a model is not arbitrary. Although it is not universal — it depends on the situtation — they are not *arbitrary*.

We agree. That is exactly the argument I made: "the situation (read: application, context, and all the other synonyms I used in my prior posts) defines the utility of a model". I'll go even further to say that exceeding the level of accuracy required for a specific need, **particularly at the cost of computational efficiency or other beneficial metrics**, is NOT useful, despite the gains in accuracy. Thus, model selection is not a function of accuracy alone, but of *accuracy, time limitations, acceptable tolerances, etc*.

> the utility of a model of reality is primarily *ALWAYS* connected to how well it approximates it. This is never an irrelevant aspect. To reject this is to reject science.

We agree here. I never claimed that the accuracy of the approximation was irrelevant. I said you can pick and choose which level of accuracy and computational efficiency you need when selecting a model depending on your application. That is not the same thing as saying "accuracy is bullshit and I reject science" or whatever you managed to interpret out of my prior comment. But note that you're now weaseling out of your previous claim by saying utility is "primarily always connected to" instead of "equivalent to" accuracy, as we can see in your first post in the thread. So overall you've agreed on all my points so far.

The one part where we may disagree is:

>It's obvious that the context in question is a scientific one, where one tries to approximate reality.

I agree science is ONE of many contexts in which statistical models may be used. However, alternatives include finance, controls, etc, where we may not need to model a set of aspects of reality, but just one, and maybe not even that accurately. In that case, even simple models can be highly effective and accurate for making decisions or other usecases (see: A random walk down Wallstreet, for example).

@tiago

I did read it, the entire quotations section, and even included a quote from that section (from a book Box authored himself) that contradicts what you're saying. He literally asks "is the model sufficient for our application?". Thus, it is the application that defines the utility, and more applications of models exist than solely the scientific one.

And, clearly, we're not talking about models being right or wrong. It's already assumed they **are all wrong** (and factually, they are), we're talking about the utility of models which are assumed to be wrong a priori, and your *personal beliefs* about what constitutes utility is not universal.

And I find it ironic that you think I'm projecting when you didn't deal with the quote I presented directly from Box's book. Have you considered the possibility that your interpretation of his words may be the incorrect one?

@tiago

It's not about the scientific method; it's about the utility of models *in context*. Models can be used for more than just scientific inquiry, are ARE used for non-scientific purposes more often than the alternative. That is to say, the utility of any given model is not a myopic, one-size-fits-all definition that is universally applicable, but is, in fact, defined by the person(s) who are using it. Hence, "this level of extreme subjectivity" is unavoidable, unless you happen to have a universally applicable definition of utility.

He even says in a quote on the wikipedia page: "All models are approximations. Assumptions, whether implied or clearly stated, are never exactly true. All models are wrong, but some models are useful. So the question you need to ask is not 'Is the model true?' (it never is) but 'Is the model good enough for this particular application?'"

For example, the epicycle model of the geocentric universe was completely wrong, but it was useful for the people who developed it, in that its purpose was to predict (with a surprising degree of accuracy) the behavior of visible planets. Just because it was extremely wrong in terms of being an accurate representation of reality, didn't mean it wasn't useful for the people that developed it and their purposes.

If you use a linear regression to match a logit/probit curve, who cares as long as you know you're going to stay in the semi-linear regime? (this is done all the time in instrument calibration, for example) If you want to reduce your logistics and shipping costs, a TSP approximation is better than waiting 1e9 years for THE answer. So I can still pick and choose the level of utility I need for my application (whether it be absolute truth, or simply an improvement, or a "good enough" approximation), and, as I said in my original comment, you may select the model that suits your needs.

@tiago Or: "all models are wrong and useful to varying degrees, select the one that fits your needs for accuracy and computational efficiency". Not as pithy, but arguably the most accurate.

@freemo I have to say the kid’s not wrong if you look at the absolutely astronomical toll that technical debt and the lack of financial support for keystone FLOSS projects until a bug causes everything to fall apart (see log4j, for example). That’s not to say that some level of technical debt isn’t acceptable, but we have accumulating debt due to running a near constant technical deficit, which is bad for literally everyone and everything except the bottom line.

I suspect the kid (and I) would prefer a “software as craftsmanship” mentality, where you can still charge for your work, but you are compensated for the quality and time spent on a well designed, extensible, thoroughly tested solution rather than on the first PR that makes it into prod that ends up breaking everything because of strict deadlines. This rushed mentality prevents people from actually engaging with and understanding the problem and solution spaces thoroughly and being able to take true pride in refining their work. Imagine comparing custom woodworking from real wood to ikea and preferring the latter because it’s cheaper, even though the latter breaks under some very light loads by comparison.

Reward quality work over “rate at which you can add new features that nobody cares about except management” and I think we get a better software engineering culture.