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.
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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.
Former intoxicology tech, was both guys daily lol.
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?
That sounds like a quick way to make super tumors
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.
So are there any good news in this respect?
There was a paper back in December about a new class of antibiotics being discovered thanks to the use of Deep Learning.
This looks like a decent writeup about it, the paper itself is not open access
This is very welcome as it has been a long time since the last new class of antibiotics was discovered. Here's a good paper that talks about the timeline of antibiotics
It's been a little while since I took the AMR course, so I'll let the papers speak for themselves instead of trying to quiz myself here on Lemmy.
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.
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.
That’s actually the simplest and clearest description of the P/NP problem I’ve ever read.
I think my favorite troll statement to a mathematician/comp scientist is:
"Actually, P > NP - there exist problems where it's harder to verify a solution than to arrive at one"
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?"
I work in IT and haven't had to go through an audit yet knocks wood
Any war stories you can share?
Mostly cybersecurity strugles. If you invest millons in a castle with a gigantic lock and a pit full of piranas, would you leave the service entrance open and give everyone in town the key? Yeah, more commom than not.
But an IT audit is only necessary if your company goes public or is the owner wants it, maybe if you are a tech company.
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?
He's the president!
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!
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.
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.
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
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.
As someone on the outskirts of Data Science, probably something along the lines of "Just what the fuck does my customer actually need?"
You can't throw buzzwords and a poorly labeled spreadsheet at me and expect me to go deep diving into a trashheap of data to magically pull a reasonable answer. "Average" has no meaning if you don't give me anything to average over. I can't tell you what nobody has ever recorded anywhere, because we don't have any telepathic interfaces (and probably would get in trouble with the worker's council if we tried to get one).
I'm sure there are many interesting questions to be debated in this field, but on the practical side, humans remain the greatest mystery.
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.
I don't think you passed
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.
I work in computational biophysics. The field has been slowly chipping away at the structure and function of every protein for decades (it's a solvable problem, it's just going to take a lot of time and energy) and recently a bunch of clueless SF tech bros have bumbled their way into the field and declared that they've solved everything.
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.
We still don’t understand quite how the brain works or how consciousness comes from neurons.