I'm in the building sciences. The biggest unanswered question we come up against almost daily is "what the fuck was the last guy thinking?". And we avoid, daily, admitting we were the last guy somewhere else.
this post was submitted on 12 May 2024
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Asklemmy
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This sounds like software engineering in a nutshell.
Software engineering is the study of constantly calling your predecessor an idiot.
Rules of Tech Support:
Rule T18 - You are incompetent. You just don't know it. At least, that's what your replacement will think.
Rule T18A - You will have to deal with techs who are incompetent.
Rule T18B - Sometimes, you really are incompetent.
Especially when you are that predecessor
I feel inappropriate near all the very universal questions here, but as a paleontologist specialised in some reptilian groups, the question would probably be "where the fuck do turtles come from?!" The thing is that fossil evidence points to different answers when compared to genetic evidence, and thez separated long enough from other extant groups that we keep on having new "definitive" answers every year
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How to get supervisors, superintendents, school boards, and even politicians to let teachers teach. It’s understood that overtesting reduces learning. It’s understood that rigid curriculums don’t work, and you really should be tailoring lessons to the capabilities of the class. All kinds of educational philosophy is understood well and in depth… but being permitted to apply any of it?
As someone who does hiring for tech, the problem is things are metric driven. You can't extract metrics from letting teachers "teach their own way" without standardized tests, and if you don't have metrics, you don't know if "teaching their own way" is working in practice (you can extend this logic down to understand the rigid ciriculums).
By the way, I think this is all bullshit, but that's why
Oh yeah, I fully understand why the stupidity happens/happened. I don’t know how to fix it or if it can be fixed… that’s why I posted it here, in the unsolved problems in your field thread!
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Is P, NP?
Guys I swear this actually makes sense...
I solved this in undergrad.
P = NP when N=1. I don't understand what the big deal is.
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Trying to prevent bacteria from developing antimicrobial resistance. At these rates in 30 years antimicrobial resistant bacteria are projected to kill more people than cancer.
Clearly you need to figure out how to give antibiotic resistant bacteria cancer.
Uncontrolled dividing of the most dangerous bacterias known to man? What could go wrong?
I've been around the AMR space for a while, but only as a collaborator. Have helped do some bacterial assemblies and help find methods of detecting ICE. I'm a bioinformatician so I get to jump onto a bunch of different projects.
AMR is scary and not really in the public knowledge of upcoming issues. I think about it every time my son had an infection while he was very young and hope he didn't get a resistant strain.
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I'm an IT auditor. "What the fuck?" is the main question, we ask it daily
I do other audits, mostly safety and environmental, and my big question is usually "nobody made you write this, why would you write this down if you don't want to do it?"
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It'd be interesting to see that answered scientifically.
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When I was a graduate student, I studied magnetism in massive stars. Lower mass stars (like our sun) demonstrate convection in their outermost layers, which creates turbulent magnetic fields. About 1 in 10 higher mass stars (more than ~8x the mass of the sun) host magnetic fields that are strong and very stable. These stars do not have convection in their outer layers (and thus can’t generate magnetic fields in the same fashion as the sun), and it is thought that these fields are formed very early in the star’s life. Despite much effort, we haven’t really figured out how that happens.
I love how you stopped to explain stuff like what a big star is, but not the funny magnetism itself
My brother works in molecular biology; he tells me the field’s understanding of peptides have only just begun and it’s only through machine learning that they are now starting to make progress. 99% seem to be post-translational garbage, the other 1% is likely to be the basis of a revolution of treatment options.
Probably not the most complex, but in programming, the salesman problem: intuitive for humans, really tough for programming. It highlights how sophisticated our brains are with certain tasks, and what we take for granted.
Also, related xkcd.
I once accidentally worked myself into trying to solve the traveling salesman problem. I was doing some work on a very specific problem, and I got to a point where I couldn't figure out a way to efficiently link up a bunch of points. The funny thing is that I knew about the TSP, but I just didn't realize that the problem I was trying to solve was a case of the TSP. After a couple of days trying to figure it out, I realized what it was, and that it was futile.
It was a good lesson to always try to find the most abstracted version of the problem you are trying to solve cause someone smarter has either tried and failed or tried and succeeded.
If the solution to a problem is easy to check for correctness, must the problem be easy to solve?
For instance, it is easy to check if a filled sudoku grid is a valid solution. Must it therefore be easy to solve sudokus?
Most people would probably intuitively answer "no", and most computer scientists agree, but this has still not been proven, so we actually don't know.
That’s actually the simplest and clearest description of the P/NP problem I’ve ever read.
Well, there's counterfactual examples of this, so it must not be true.
In pretty much every single relationship worldwide, one person can very easily determine if the recommendation from the other for where to eat or what to watch is correct or not.
And yet successfully figuring out where to eat or what to watch is nigh impossible.
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How does immunology work?
Pro tip: nobody understands immunology and anyone who tells you otherwise is lying
After covid, this strikes me as a dangerous thing to say. Are you an immunologist and could you expound on this?
My field of expertise is bacterial pathogenesis with a particular interest in pneumococcal pneumonia.
And it's true, immunology is ridiculously complex that no one person can ever hope to fully understand it. Immune cells are helpful or detrimental depending on the context, and sometimes even both. And we don't really fully know why. The problem is that pathogens and humans have been in an evolutionary arms race for billions of years, and unraveling all of that evolutionary technical debt is Fun™
To give an example, Toll-like receptors are one of the most important pathogen-detection mechanisms, and they were discovered just about 25 years ago and people only really figured out their importance about 20 years ago. There are researchers who have spent the majority of their careers before the discovery of one of the most crucial immune pathways.
We really don't know what's going on with immunology and to say otherwise is, as I've said, an outright lie. People seem to overestimate how much we know about the immune system, not knowing that we are still very much in the "baby phase" of immune research. The fact that we are able to do so much already is really kind of a testament to human ingenuity than anything
My personal experience is that people who claim to know completely about how the immune system works is more likely to be a science denier (or more likely, naive)
Thanks, that was a great answer! I had no idea it was so complicated. I was definitely in the naive camp there.
Ya'll think you have real unsolved problems. I'm here with "naming variables" (⌐■_■).
As a software engineering researcher, I strongly agree. SE research has studied code comprehension for more than 40 years, but for that amount of time, we know surprisingly little about what makes really high-quality code. We are decent in saying what makes very bad code, though, but beyond extreme cases, it's hard to come to fairly general statements.
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I think it's dark matter. There are so extremely many theories around it and it's very hard to measure experimentary.
No one really knows how osmosis works.
I had to derive osmotic pressure for my statistical mechanics exam in my bachelor's. So in what sense don't we know?
We don't know what molecular mechanism creates the pressure.
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We still don’t understand quite how the brain works or how consciousness comes from neurons.
I'm only a professional scientist in the loosest sense of the term but for years we've tried to figure out why Joe can't leave the break room to fart and who the fuck does he think he is?
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How to accurately estimate signal crosstalk and power delivery performance without FEM/MoM simulators.
For people and companies that can't afford 25k-300k per year in licence and compute costs, there is yet to be a good standard way to estimate EM performance. Not to mention dedicated simulation machines needed.
That's why these companies can charge so damn much. The systems are so complex that making a ton of assumptions to pump out some things by hand or with bulk circuit simulators often doesn't even get close to real world performance.
If someone figured out an accurate method without those simulations, the industry could also save a shit ton of compute power and time.
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