A while ago, I taught CS for a year in a local high school. I can very much relate to the notion of "astonishing facts were presented without astonishment": as a teacher, you don't have the freedom to teach whatever you want (of course), but you're very tightly bound to a curriculum that's developed by the state government. And for CS, this curriculum was so uninteresting and uninspiring (what a surprise: 13 year old kids don't care about the history of computers), that I couldn't blame any of my students not to show much interest in my classes.
As a matter of fact, I gave up after just one year. It wasn't any fun for anyone, not for the students, not for me.
they might just remember it all once they're adults!
imagine that!? an historically informed populace???
you'd need more expensive lies and higher quality fakes... the government would be costlier to run.
ideally, in the long term this would make the national currency's value in the international money market rise up. but why wait for that when one can directly manipulate money through trade fraud and covert military ploys?
The history of English is taught in English classes. Historical context is important and interesting. You don't really understand a subject without knowing a bit of its history.
My favourite classes were those where we didn't just get taught facts and theorems but we also got taught a bit about who proved the theorem for the first time, who discovered this fact, what this algorithm was first used for, etc. So much easier to remember too.
This is one of the best things about studying law: the very nature of it makes it impossible to teach it without the historical context.
The key part to me is the "before they could read". I think the history of computing is probably far more interesting when you have more context as to where that history got us.
Those curiculums developed by sould-dead gremiums in consensus on the minimum knowledge you goto have are a blight on western civilization. Instead of giving students the ability to discover a topic, or built something they are interested in themselves and then give them a understanding and fascination with the discoverers who have gone before them. Instead they kill the subject..
I must confess, it gives my dry old heart some joy, to see the anti-education masses coming from this, voting and storming the fortresses that produced the paywall around education, that only money with tutors could or accidental intrinsic motivation could overcome and burn & salt those outposts of classists academia.
Yes, definitely, destroying education as we know it without any plans for what the next thing is will definitely work.
Developed countries really need a come to Jesus moment, because the disdain for everything that made them great places is unbelievable. People will understand, after great suffering, that destroying stuff is much easier than building it.
We're in the destroying phase right now. Unless you live in China - I hear they're mostly doing well. Or middle of nowhere Africa, where there's nothing to destroy because there's nothing there.
But systems can rot from within too, or just decay naturally, and don't need to be destroyed. What if the core ideas that built our current civilization were ideas of the past, that we don't have any more, and we don't know what to do when The Machine Stops? Doesn't have to be a literal machine - it's a good metaphor for how democracy fell apart.
> People will understand, after great suffering, that destroying stuff is much easier than building it.
"It is easier to destroy than to create" doesn't tell you when something should be torn down.
You can have a house that provided shelter for your family for generations, but if it's water damaged, the floors are rotting and it's full of toxic mold, the person who shows up with a bulldozer isn't necessarily wrong.
Forgetting that it was the anti-education forces that created the curriculums. The war on public education goes back a long time; teachers lost the freedom to teach decades ago. and it has been the same forces behind it all along.
Ok... what would you do differently? Keep in mind you have to educate millions of students across an enormous spectrum of abilities, socioeconomic backgrounds, and interests.
I would build a "intrinsic motivation" first curriculum, where knowledge is handed as powertools to a already existing passion and the self-thought "expansion" of knowledge is the most important gift to be made.
If the child is fascinated by video games- i would help it make video games, the curriculum be damned. All knowledge holes can be filled later, but the passion to wanting to know, can never be restored unless the want for knowledge remains intact.
I think the whole teaching the history of computers is a big failure at an attempt to Segway into computer organization and architecture.
Nonetheless, I get what is happening. If it’s a pure Computer programming class then the goal maybe to have them understand the “basics”…like what is the hard drive vs RAM (memory allocation) or what is a transistor (Boolean logic) and what is a punch card (mnemonics and abstractions of those mnemonics to what is now just a computer programming language).
> have them understand the “basics”…like what is the hard drive vs RAM (memory allocation) or what is a transistor (Boolean logic)
You must understand these things at least conceptually if you want to really understand how to write efficient programs. Maybe not at the level of how memory can electronically "remember" a 1 or a zero, or how a hard drive can magnetically do it, but at least the relative speeds e.g. register vs. cache vs. RAM vs. disk.
Personally, I struggled a lot in my earlier CS/Informatics education, partly because I never felt like I understood what was actually happening/how we got here, everything was just factoids in a void. When I took a gap semester between my A.S. and B.S., I finally studied/explored a bit of the history and it put a lot finally in perspective.
Well, you need to come up to something like analysis to appreciate something that's seemingly simple like the number line and that's a loot of math if done only in spare time.
This is very much a tangent, but I think it's nearly certain that "segway" will end up overtaking "segue" as the predominant spelling for the word that is defined as: "to make a transition without interruption from one activity, topic, scene, or part to another"
The "mistake" happens so often, partially because "segway" is a much more straightforward spelling if one has only heard the word said aloud, that I think it will eventually become the actual way it is spelled!
Actually it's not an absurd take at all. The absurd take is that we "should not bend language around ignorance."
That's precisely how language changes over time. Language is not a strict set of rules. It's based on understanding and consensus, so sometimes things that are "wrong" do end up being accepted.
I am not a native speaker, but the two words do not sound even remotely the same.
How does this mistake happen so often? Can you explain people's thought process a bit? Is it just: "Something something 'seg...' ... ah I know, I will simply use another random word that starts with the same 3 letters and doesn't make sense in this phrase!"?
Was that the point? Don't forget that you're on hackernews, not reddit. Strawmans are less accepted in this community. Individually, you are neither a consensus that was described nor did anybody in this thread implied that "all errors of usage are correct" and accepted. Your sarcasm is unwarranted and provides little value to this conversation.
Most mistakes remain mistakes, and do not become part of the language. The idea that mistakes generally get accepted as correct is simply untrue, which is what you are implying.
I am sure people will make the mistake, as they sometimes do today. But it is a mistake, and will likely be recognised as one.
It is likely that the language gets more cemented by automatic spelling and grammatical correction, including using AI. For example, there are a number of grammatical and spelling changes that have been cemented by American spelling/grammar checking programmes ie. by MS Word.
> The idea that mistakes generally get accepted as correct is simply untrue, which is what you are implying.
I did not imply that at all. I said sometimes, so it's not that absurd that it could happen. It does happen though, and a quick google search will give you pages of examples.
Precisely. In English, while mistakes usually get corrected back to common or traditional usage, they are also the fuel for almost every change to English that becomes common usage (and I only add the almost qualifier because I can't decide if categorizing things like "cromulent" as a mistake should count; it was an intentionally made up word in a context where the joke was made up words but may have fallen into common usage because people using it because they were in on the joke were dwarfed by people who didn't know it was a joke and absorbed it as a real word).
With machines looking over our shoulders now and so much of language being typed instead of handwritten, odds are such drift might actually decrease in English... On the other hand, the introduction of AI leaves an interesting avenue for people to begin acting as if something is common usage and have the AI begin confirming that as common if it consumes that action. And then, of course, there's the effect of the machine itself... Most of us have a way to type "résumé", but we don't bother because the machine makes it too much work to do so, So the alternate spelling without accent, which was called out in my high school days as wrong, has fallen into common usage in a generation of people having to submit their resumes online (example: https://www.linkedin.com/help/linkedin/answer/a510363).
English is spelled phonetically. Just not Modern English phonetically but Middle English phonetically. And then it froze into ideography because of printing press.
FWIW, I did a quick search of our local slack and found 2x the the number of instances of "segue" compared to "segway". And most of the instances of "segway" (around 60%) refer to the actual device, with only a handful of mistakes (around 4). So I'm not sure that this spelling is more common in a corporate environment—maybe do a search for yourself and see!
This is why most good teachers don’t use the books but find creative ways to still meet the standards. More work though, so fewer do it now with pay being so shit.
I can really relate to your experience, even though mine was from a parent's perspective rather than as a teacher. I found a similar thing when tutoring one of my children in trigonometry. The way the material was being presented in school didn't click with him, but astonishingly, despite having studied it decades ago both at school and university, explaining it to him, it finally made sense to me. The unit circle definition of a tangent is a thing of beauty. I had the time to get my child to appreciate it as well, because of the extra time I had to spend with him, whereas the teacher had to hit curriculum benchmarks.
I also think this is where things like intergenerational math-phobia come from: parents who don't grasp core concepts and are scared off, and can't help their own children, creating an ongoing cycle.
> I also think this is where things like intergenerational math phobia come from: (elementary) teachers who don't grasp core concepts, are scared off, and can't help their own students, creating an ongoing cycle.
I hope you appreciate my addition of the other common path of math phobia.
Absolutely, I do appreciate that addition — I definitely had teachers like that.
It’s probably why, when I got to university and tackled subjects like probability theory, discrete math, and theoretical CS, I did extremely well — they weren’t reliant on the shaky algebra and trig foundation I had from school. Once the focus shifted to logic and conceptual thinking, without the baggage of poorly taught fundamentals, everything clicked
I basically found this in college too, I quickly gave up on computer science as a major. I'd rather just go out and learn how to build what I want to build versus hearing a 3-hour lecture about how the jvm works.
The answer is it's magic and no one cares, now let's go build some games
Firstly, and this is worth pointing out, "computer science" is not about programming. It's about science, in this case specifically the science that makes computers work.
At school I thought "computer science" meant "programming" - which it doesn't. So well done for recognizing this before wasting your much time. (Seriously, not sarcastic.) programming can easily be learned outside college.
To other general readers here though I'll say that understanding the science can be really helpful over a career. It's not terribly applicable in getting that first job, but as you progress more and more of those theoretical fundamentals come into play.
Ultimately there are a small fraction of people who need to understand how it all works, all the way down, because those people build the things that programmers use to build everything else.
This is a myth. Computer science absolutely is about programming. The science that makes computers work is called physics.
There are theoretical parts of computer science, but it is fundamentally a practical subject. All of it is in service to programming. Type systems are about typing programs. Algorithms are implemented using programs. Data structures are for use in programs.
The very worst computer science lecturers are those that forget it is a practical subject and try to teach it like abstract mathematics, because they believe (whether they realise they believe it or not) that it is more prestigious to teach abstract concepts than practical concrete things.
It is the same in mathematics, where unfortunately there has developed a tradition since Bourbaki of trying to teach abstract notions as fundamental while concrete problem solving is left to the engineers. The result is that many engineers are much stronger mathematicians than many mathematically-trained students, and those students have to relearn the practical foundations of the subject before they can make progress at the graduate level. If they don't, they get stuck doing what looks like maths, but is actually just abstract roleplaying.
This might be just a semantic argument, but if you mean "programming" as in "configuring a machine to implement one or more algorithms" (which I would assert most people do when they use the term), computer science is emphatically not about programming, although programming is taught for much the same reason that artists learn how to use a pencil. Computing, as a discipline, predates the machine (although the machine justified the existence of a whole discipline for studying it because the force multiplier it represented made it worthwhile to dive deeply on the subject of algorithm development and execution, the nature of algorithms, the nature of computability, formal logics, etc... Before the machine, it was just a subset of mathematics).
This was a point repeatedly driven home in my undergraduate curriculum, and in fact, they made a point of having multiple classes where a computer was completely uninvolved.
Yeah, I'm more in this camp too. We did a lot of practical modules, things like OS development, databases and so on. So yeah, learning programming was the first couple months, then programming becomes the tool to express progress in knowledge depth.
It's probably fair to say that although we learned some history, we had the privilege of learning at a time the field was exploding. That history you learned, I lived and worked through that. It's somewhat surreal to realize that my career is your history class.
As mentioned above though, it'll vary a lot from one school to another.
It depends on where you took computer science. I took a few foundational classes at community college.
It very much felt like a Wikipedia article on the history of computers somehow stretched out over an entire summer.
I have my own issues with the way college is generally setup. Do students really need a massive amusement park when self study along with 3 or 4 exams would provided the same value. Will spending 70k per year in total cost of attendence at said amusement park serve them?
I don't really like boot camps either, personally I'd like companies to be more open to actually training people again. I doubt it'll happen though.
Well, yeah. That's true for any field of study. Every college has strengths and weaknesses- its the opposite of a franchise.
>> I took a few foundational classes at community college.
A few foundational classes is somewhat different to classes you take in prep for a major. I did a foundational class in astronomy, designed for students who were just looking for an introduction. It was very different to my comp Sci classes in tone and style.
Yes there was some math involved, but not much in the comp science classes. Math was a pre-requisite though so we got our math in, well, math.
This is one of the only skills you can learn for practically nothing. A cheap laptop is all you need. I taught myself enough to get a middle class job with nothing but free time and 3$ iced coffees.
I just don’t like the idea of gate keeping it behind an expensive degree. The source code for most popular frameworks and tools is free for anyone to read.
It’s not like medicine or something where you need to drop 300k on education.
No, it's certainly not like medicine or law. And you can certainly aquire skills on your own.
Of course, in this field, learning is continuous. You're not going to use just one language (much less one framework) over a decades-long career. It's also likely that your domain will change, your focus area and so on.
A good college course doesn't prepare you for programming in one language, but all of them. (In the sense that once you understand the theory of programming, language is just syntax.)
You get exposure to different types of languages (imperative, functional etc).
I think for me the critical takeaways though were research, critical thinking and communication. The "skills" are easy to learn yourself, but the formality in which you place that learning is harder to do yourself.
Which is not to say a degree is a requirement- it's clearly not. But it's helpful because it builds a strong foundation on which the self-learning can rest.
What a horrendous crime, to turn a fascinating subject into a boring curriculum to be forced on teachers and children.
I've received great intellectual satisfaction from various well-taught subjects. I would rather chop off a finger than lose them. So curriculum committees that make subjects boring are doing something worse than chopping off millions of children's fingers.
With any kind of history especially, its just rote memorization of facts and not the connections between those facts.I hated history in school because of that, but now I actually find it interesting to learn that x happened because of y that also led to z and such. Or just rote memorization of technical facts, like how many wires does a PATA cable have. Or why must kids memoroze how an ethernet frame is built up? Sure go over it in class and show it as a lesson in how to read how binary protocols are defined. Because either you forget it anyways because its not relevant to your job, or you can look it up and memorize it over time as you use it often enough.
I really wish that teaching of history will get better for current and future kids.
My fork in the road with hard tech hard science versus biology was in high school. It seemed that students that wanted to become doctors took AP biology and students that wanted to be engineers took physics and chemistry. I had wanted to be an engineer since I was 12 years old so I felt the decision was already made. But all studying neural networks in college in the 80s I realized that there was this tremendously rich domain of real neurons which I knew nothing about. I worked as a software engineer for a couple years after graduating but then went back to school to study Neurophysiology. I did not pursue it as my area of work or research, but I am grateful for having had the opportunity to look at the world from the perspective of a biologist.
If you're an engineer and early in your career and feel there's something missing from your intellectual space, I encourage you to go back and get a graduate degree in something totally different. Humans live a very long time so don't feel like you're wasting time.
I would love to do something like this but simply cannot afford it. I think it is good advice but going back to school for a degree one does not plan on utilizing is not as feasible today as it was in the 80's, largely due to the sizeable increase in tuition without reciprocal increases in wages.
A lot of companies will pay for at least part of whatever college classes you take, without auditing whether or not it would be good for your specific job.
I encourage people to look into it, it's a benefit a lot of people have but don't use and it's leaving money on the table.
Plus usually the employer wants it to be related to ones job, from their very limited perspective of the world and management decisions. For example I couldn't even take a language course for education vacation, as the employer did not make any use of my language skills.
I had a job with an education budget listed as benefits.
However, to use it there are constraints:
1. The topic should be related to technologies used by company. Cannot get a Google cloud certification as they are using aws.
2. To get it you need approval by line manager, hr, and director of the office.
3. If it is more than €250 you need to sign up loyalty agreement for a year. Meaning if you will return some amount of you quit.
With all that strings attached it is just a marketing bullshit to attract new hires.
Can you say more? What kind of company would so such a thing? Maybe I live in a bubble but that's so far outside of what I've seen that it just sounds fantastical.
Ok, both of these comments made me doubt my memory so I just checked and my current employer, a very large consumer company, and the limits of the program are that you get a C or above, and the class is "related" to your job or any job you can get at the company. But I've gotten classes paid for that only tangentially related to my job with no problem. So I concede that you might not get a biology degree as an engineer but my particular company does a lot of different things so my guess is in practice you'd have no problems. I also worked at a now-defunct mid-size startup and a hospital system with similarly loose requirements but I don't have access to their docs anymore.
My company uses guildeducation.com and we can use basically $5k a year (I think, it might be semester), a lot of if it is just individual classes, but there are also some degree programs. I don't know if they preselect which courses are available to us or if we have access to the whole catalog. I suspect it's somewhat curated, because we are a medical company and most of it is medical stuff. There is a CS bachelor's program but last I checked there wasn't an MS CS program.
I would assume most companies with 100+ office workers (essentially big enough for an HR department) usually offer something like this in western countries.
Depending on where you live, and what you want to study, you might be able to take a couple courses at the community college in areas of interest without spending a lot of money.
I was paid to get a PhD in Biology, albeit just enough to live on. Most people in PhD programs are, either through being a TA (teacher's assistant) or RA (research assistant). The real financial cost is the opportunity cost of 5-6 years of your life.
Whether or not broad support for training scientists holds up during and after the current administration remains to be seen.
In this day and age, you can do this for FREE and on the side, whenever you have time!
There are tons of very well-done professional level video courses on Youtube.
There are more organized courses that only ask you for money for the "extras", like some tests and a certificate, but the main parts, texts and videos, are free.
You could start with a really good teaching professor (Eric Lander, MIT) and his course: https://www.edx.org/learn/biology/massachusetts-institute-of... (the "Audit" track is free, ignore the prices; also ignore the "expires" - this course restarts every few months and has been available in new versions for many years now)
It's very engaging!
There's similar courses for everything in the life sciences, there on edX, on Youtube, many other places.
I feel the true Internet is soooo underutilized by most people! Forget news sites, opinion blogs, or social media. Knowledge is there for the taking, free. Only the organized stuff, where you end up with a certificate costs money, but they usually still provide the actual content for free.
Time and energy are also at a premium in the current economy. Good luck learning biochemistry by watching YouTube videos after 8+h of coding and meetings plus commute plus making dinner plus cleaning up.
My current tuition is under 500 CAD per class. The opportunity cost of not working full time is the real bulk of the cost of studying in places that have a functional government.
Same. Biology was an elective in high school and I never took it. I took Earth Science (basically introductory geology) and then went into the Chemistry/Physics track (two years of each). Never felt I missed it, last time I had any real biology education was a unit in 8th grade science and I didn't care for it then.
I know. I questioned that word choice, but it's sort of a play on words - as most of the biological things that I ended up doing are soft and squishy :)
I've been programming since I was eight, but truly fell in love with biology in 12th grade chemistry: the first introduction to organic chemistry and biochemistry. It was the first time I truly started grokking the application of systems-level thinking to the biological world; how do trees "know" to turn red in the autumn? How do fetuses assemble themselves from two cells?
I decided to purse a double major in biochemistry and evolutionary biology and it was one of the best decisions I've made in my life. The perspective you gain from understanding all life in terms of both networks and population dynamics of atoms, molecules, cells, tissue, organisms and populations -- and how every layer reflects the layer both underneath and above it in a fractal pattern -- is mind-expanding in a way I think you just don't and can't get designing software systems alone.
I work as a software engineer / founder now, but always reflect wistfully on my time as a biologist. I hope to get back to it some day in some way, and think what the Arc Institute team is doing is inspirational [0].
Has anyone seen content that used this multiscale networking and population dynamics as an instructional approach?
For small example, there was a Princeton(?) coffee-table book which used "everyday" examples to illustrate cell/embryonic organizational techniques - like birds equally spacing themselves along a wire. Or compartmentalization, as a cross-cutting theme from molecules to ecosystems.
I've an odd hobby interest in exploring what science education content might look like, if incentives were vastly different, and massive collaborative domain expertise was allocated to crafting insightful powerful rough-quantitative richly-interwoven tapestry.
The breakpoint was molecular biology around 1986 with the introduction of PCR. Once that happened, biology went from being alchemy to being science.
I loathed biology as taught prior to that. Once I got a molecular biology course, I thought biology was amazing and wondered "Why the hell did we teach all that other crap?"
Well, that was because the tools we had for biology sucked prior to PCR. My problem was that I recognized that even as a child.
I would love to do this, I just cannot afford it as others have already stated. It's depressing to feel like I spend so much of my life at my day job and yet require it to afford the tiny portion I get left. I wish things were different.
Much, much easier to do when you're young. I was just married so no kids yet. We moved to Toronto so I could attend UT and we treated our stay as an extended honeymoon.
I took some programming courses in college. I loved computers and was very interested. However, the classes were a guy reading from a book about C. That was pretty much it. You did what the book said and hoped something stuck in your head.
This was early days of the internet, the book(s) were largely the only resource. The instructors were folks who just understood coding in C naturally and had no idea how to communicate with those who did not. No joy in anything, just raw code.
I dropped out.
Decades later after age 40 I was at a career crossroads and took a web development class. I loved it, I could make things quickly, the instructor actually understood how to teach / introduce concepts. I've been happily coding professionally and personally since then.
How things are presented sometimes makes all the difference.
I remember my first interaction with computers was on one of those ancient ones way back when. Our teacher showed us how to make a circle appear on the screen. I was preoccupied with how the computer was actually able to render that circle, what exactly was happening under the hood and what kind of physics was happening for all this to come together as a circle on the screen and not that particular function of whatever program they were using at the time. That turned me off to wanting to mess around with computers for awhile.
> Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover, and mutation.
Rosalind.info has free CS algorithms applied bioinformatics exercises in Python; in a tree or a list; including genetic combinatorics.
https://rosalind.info/problems/list-view/
FWICS there is not a "GA with code exercise" in the AP Bio or Rosalind curricula.
YouTube has videos of simulated humanoids learning to walk with mujoco and genetic algorithms that demonstrate goal-based genetic programming with Cost / Error / Fitness / Survival functions.
Mutating source code AST is a bit different from mutating to optimize a defined optimization problem with specific parameters; though the task is basically the same: minimize error between input and output, and then XAI.
The post by James Somers that this article references at the top inspired me to buy the David Goodsell book The Machinery of Life. I would seriously recommend that to anyone who doesn't have a background in biology (like me). The phrase is a bit of a cliché, but it genuinely blew my mind, to the extent that I had to read it slowly because there's so much fascinating stuff packed into such a small book. It's obvious to me now, but the fact that so much of this stuff is about physical shapes locking into each other, and doing it at an almost unimaginable speed, was absolutely enthralling.
I think one of the things I love most about biology is its uncertainty. Things like Math and engineering are all rigid and rules based. Life is wibbily wobbly, lifey-wifey. An enormous soup of changing alleles cast as probabilities over eons all creating endless interactions you can't ever comprehend.
You have to become comfortable with the fact that there is uncertainy and there are parts of it you can't control. So instead you have to be obsessed with introducing order where you can. It is so refreshing to see a beautiful experiment that can wrestle a clear signal from the endless noise.
> Things like Math and engineering are all rigid and rules based
Depends where in math, in things like particle physics things get all wibbly wobbly is my cat dead or alive. In things like engineering quite often what you're dealing with is probability based, but you just stack the deck so far in your favor the probability is 1.
As they say, building a bridge that doesn't fall down is easy. Building a bridge that barely doesn't fall down is much harder.
Every scientist does that at some point. I've easily crossed my fingers and hoped numerous times that code I'd written would work, especially on the first time. Even more rewarding in the superstition when the project is hard, and you're a bit daffy at the end.
It's a human thing.
Surely Feynman made jested comments before running experiments. I'm sure some digging in his wonderful books and letters will find many examples.
A lot of experimental and applied physics operates this way. If you are synthesizing material, for example, it takes a lot of time and effort to get high yields of what you want. Before that your processes can be very probabilistic.
In fact, just finished listening to a talk where a experimentalist was talking about how to get the fabrication yields of superconducting qubits from currently low double digit to 99.99+.
Biology is messy at a macro level is all I'm saying. I don't need a hundred people butting in saying "butt aschully phsyix and code is also messy and harder at a quantum level." I know. We know.
I am sure the author is a fine person, but this is an incredibly self-entitled piece. A number of biologists managed to make it through these classes just fine, and are paid much less for pursuing their passion (and making the breakthroughs the author enjoys reading about while on vacation).
A title like "I wish I had enough attention to get through the boring parts of high school biology, I now find pop biology interesting" may have had less impact, though.
Computer scientists and programmers are very intelligent people who often have grossly unrealistic projections of their competency in other fields, and this is a fine example of the phenomenon.
The author did fine in another field, but might have picked biology instead if they had gotten the switch flipped earlier in life. That some people get through bad classes isn't a proof that those classes are good; you get those few who would survive no matter what, and those whose brain-wiring is conducive to the way the bad classes are structured. This has a tendency to reduce diversity of thought over time, and contributes to academic ossification.
Secondly, fields really do need cross-discipline collaboration. Finding passionate CS people is fantastic because they bring a different skill set. I have often found that when we get diverse experts together, we can have everyone do the "easy part" and get results which would be otherwise unobtainable.
Yes, some people have 'engineers disease' and fail to appreciate the depth of knowledge and skills of folks who have spent their life in another domain... But the author doesn't seem to be one of these. Many of their favorite stories appreciate the combination of insight and hard work in the history of the field.
It does, indeed, suck that people working in biology get paid less than computer engineers. Blame capitalism...
As a biologist with a tech background (but actual biotechnology majors) - please we have enough tech bros who think they're biology's saviors. They'll just come in fascinated by some technological problem, call it the only blocker to solving aids and cancer and take away a billion dollars in funding over decades and show nothing of actual consequence. Like the entire protein folding field. It's a tool. Not the solution. Even today there was this hyperbolic piece on NBC about how this Harvard scientist working on microscopy image processing is being deported and now we are not going to cure cancer.
I feel bad for them, but I can assure you, as someone who did the research in the exact same field, they're curing nothing and are more likely to make cures slower by sucking away funding from more pertinent projects.
I've been working my way towards a biololgy degree very slowly (can only really fit one-class-at-a-time alongside working full time). I'm maybe 70% to a bachelor's degree in it. Been writing code for ages, but I've saved enough to accept a lower salary if it means I get to work on a real problem for once in my life. So I guess I'm one of those people you're frustrated with.
Do you have any advice for how to not be that kind of problem? For now I'm just focusing on my coursework, but at some point I'll be biologist-enough to help out with research. How do I approach it without being that guy?
In my (possibly not the best) opinion the most important quality will be to not delude oneself with the idea that their method or field is the most important field in all of science. Unfortunately academic structures force you to think and believe that and then proselytize that way. But if you stay above it at least in my books you're above most folks. But then I'm a lowly guy in a corner lol.
Practically what this means is that you should decide what you truly want to change (not necessarily what you can change with your current expertise) and pursue it across whatever fields necessary. If it's curing a disease, you have to decide what is the most important thing that's stopping us from curing that disease and pursue that exact topic. More often than not it's not anything software related. You have to grab a pipette at some point and guillotine a few mice at another lol.
I once met a scientist who spent a week traveling to where there was a powerful x-ray laser. He used it to blast a thin film of something or other that was floating on the surface of some water. He left with a flash drive full of data and some FORTRAN titled LSQREFL, which allegedly could decode the laser results. He then spent the next 6 months trying to make it actually do that. Turns out you had to have a folder with today's date on it on your desktop, otherwise the program would crash. This was documented nowhere, he just eventually puzzled it out from the code.
I offered to put it on github for him, so that at least he didn't have to be the sole caretaker for this endangered bit of software, but he was afraid of running afoul of the original author's rights, so endangered it will stay.
This was maybe an unlikely occurrence, falling neatly in the not part of your:
> More often than not it's not anything software related
But it makes me think that there is still some juice left to squeeze out there. I mean, I'm having a good time with my one-class-per-semester, I'd just prefer to not have to do it for another decade before I'm enough of a biologist to get my hands dirty.
Sounds like he was doing an xray diffraction experiment? The last time (in my opinion) XRay diffraction based structure results meaningfully changed scientific discourse that affects human life was probably in the 80s or 90s. While it's important work it's no more important for Healthcare than some physics guy doing things with a random metal alloy. The point is there are interesting things but one shouldn't delude that this is the thing that's keeping us from unleashing human health prosperity.
There's two kinds of ignorance which come into contact when people work across disciplines.
In my own work helping ecologists, I see plenty of CS/ML folks who think they'll change the world by throwing a transformer at the problem. (which problem? you think we haven't tried that?) It takes some time and exposure to figure out what kinds of problems you can meaningfully contribute on.
On the other hand, I've met lots (most?) of ecologists who underestimate the impact of looking at their work through CS/ML lenses. Effective automation can greatly improve iteration speed, which ultimately leads to better outcomes than a slow but 'perfect' process. (and, indeed, the 'slow-but-perfect' process may not be sufficiently benchmarked, and not be perfect at all...)
You can do a lot of good by working closely with a practitioner, and identifying the places where they are spending a lot of time doing 'boring' stuff, and finding ways to automate or approximate the outcomes of that boring work. As you work with more people, you'll be able to identify boring stuff that everyone in the field is stuck doing.
So, in short, an excellent goal is to find ways to save people time through bottleneck analysis. Improve iteration speed and you improve the speed at which we can accumulate knowledge / make discoveries / etc. When you're done, it's "just a tool", but beforehand it's a problem holding back discovery.
There were https://en.wikipedia.org/wiki/Galectin proteins embedded in a thin lipid layer on the surface of the water. The goal was to understand what conditions triggered various conformational changes. I'm under the impression that such details end up in databases and get selected for further inquiry by drug design processes, particularly those targeting autoimmune diseases. Or at least, that's what I got from his talk on it. I'm still working my way up to the biochemistry classes.
But yeah I get your point about avoiding that delusion. Honestly I'd be happy enough to be doing something that I suspect is not actively harmful (this should be easy but SaaS tends to converge on products that control their users and not the other way around). I don't need to be humanity's savior. More helpful than harmful will be enough.
I admire your stance but consider this hypothesis: nothing is better than nonsense. Most research leads to nothing. Knowledge is better than ignorance but research funding isn't unlimited. I estimated the average biology paper to cost several hundred thousand dollars if it didn't involve animals and a million if it did. Does the parameter you find or establish even justify such a cost? Most of my and my colleagues work really didn't change anything in my opinion. Even if some of us didn't want to be useless like this, we had no choice. The system just forces you to do these projects. The only way to beat this system is to get out of it. That's what I did. I hope to start a garage lab sometime and do whatever I want as you say. At least I won't be taking public funding and I hope I might find something better without those limits after all.
What does the author claim entitlement to? Or what real-world malign effect are you expecting from this piece that warrants the charge? I went in expecting the type of piece you describe, since I know the type, but I've failed to read it as you do except with a disqualifying squint.
The post is not about becoming a professional academic/researcher in biology, so it's not clear why your comments (this and the earlier deleted one) focus on competency, calling the author "not cut out for biology", etc.
The post is simply about what you call enough attention to get through the boring parts of high school biology — should biology in school be only for those who have that ability? Even if being a professional biologist requires those attributes, shouldn't the teaching of the science of life—which is full of wonder—have a bit of something for everyone else too? Even people who don't become biologists ought to love biology, surely?
That's what the post (like the earlier one by Somers) is about; it's not about “I could have become a biologist” (as you seem to be implying). You can call it pop biology, but it's missing from school where “astonishing facts were presented without astonishment”. I see nothing self-entitled about this.
It's the same in mathematics, say: even if being a professional mathematician requires (say) thinking long and hard and being willing to struggle with difficult problems, manipulating things in one's head, etc — surely there is value in exposing more students to pop mathematics / beautiful results (enjoying which is very different from actually doing mathematics, sure), so that more people could love mathematics recreationally, whether or not they become professional ones?
Well, this is incredible:
"The gene sequence had a strange repeating structure, CAGCAGCAG… continuing for 17 repeats on average (ranging between 10 to 35 normally), encoding a huge protein that’s found in neurons and testicular tissue (its exact function is still not well understood). The mutation that causes HD increases the number of repeats to more than forty – a “molecular stutter” – creating a longer huntingtin protein, which is believed to form abnormally sized clumps when enzymes in neural cells cut it. The more repeats there are, the sooner the symptoms occur and the higher the severity"
Not the only sequence model that exhibits stutters on repetitive inputs...
If you want to be fascinated with biology just go to nature, or a park and stay there for a while. After a while you ll start to wonder about the birds, the plants the snails, the cats. Biology is descriptive science , nothing wrong with it
I don't know if just going to nature is sufficient to get fascinated with biology. In my opinion it takes a fundamental reset in how you think about anything you see. Humans while smart have obviously had to learn to "ignore" thinking about how things work. You don't think too hard about how anything works really. I mean at a cursory level sure, but by vastly different interpretations of the word "cursory", you can change your thirst to know how things you see work at more and more fundamental levels.
You don't need to go into nature to get this curiosity except for the possibility that it makes you more meditative. You can look at your arm and think what the hell happens in there at a molecular level to make you move the muscles. Or when someone says nerves conduct electricity what the hell does that mean?
When I think like that I'm just curious why OP and others blame teachers or whoever else for not inducting the curiosity in them. Like it's someone else's job to make you curious? In my opinion you're either born that way or you're not. Some airport store book isn't gonna make you the next whatever scientist you adulate.
I sometimes skywatch late at night, marveling at the vastness of what's out there, and the glimpse of it we get over here. That gives me a sense of wonder about space, but did not make astronomy any more appealing to me.
Gaining an appreciation for nature is good, getting fascinated with biology is also good, but one is not necessarily related to the other in practice.
I was lucky to have a great AP Biology teacher in high school. I ended up minoring in the field and it has shaped my career. Now my child is a little biologist. It is a fascinating subject and so core to everything we are and everything we do.
In high school I was all math>physics>chemistry>biology. So I didn't take biology. Much to my peril. I didn't learn that I wasn't just a brain on a stick until I was 25! At some point "The Inner Life of the Cell" blew my mind.
I invested a great deal of effort over 30+ years to learn biology, which I started to love in high school when a teacher introduced us to molecular biology. Over time I've come to appreciate that biology is a huge field and people who master one area often know little to nothing about many others.
To be proficient in biology you need to have "Extra" skills: extra ability to work with ambiguity,ability to memorize enormous amounts of descriptive information, and highly abstract representations. Digital biology often loses many aspects of biological reality, and then fails to make useful predictions.
Over the years, I've come to realize I know less and less about biology- that I greatly underestimated the complexity and subtlety of biological processes, and have come to admit that my own intelligence is too limited to work on some problems that I originally thought would be "easy engineering problems".
A great example of the rabbit hole that is modern biology is summed up here: what is the nature of junk DNA? To what extents are digital readouts like ENCODE representative of true biology, rather than just measuring noise? What is the nature of gene and protein evolution?
https://www.cell.com/current-biology/fulltext/S0960-9822(12)...
(note that while I disagree strongly with Eddy in many ways, I've come to recognize that I simply don't understand the modern view of evolution outside the perspective of molecular biology (IE, what geneticists like Eddy think).
Also, recently, Demis Hassabis postulated that if he is successful, we will come up with silver bullet cures in 10 years time simply using machine learning. It's amazing how many computer scientists (I call him that rather than a biologist, although he has worked into neuro) make this conclusion.
Appreciate the sarcasm, but... it's really 3 billion years of evolution, with astronomical levels of actual entities living and dying in a dynamic world environment. Chemical reactions happening in nanoseconds. Polymers have extraordinarily complex behavior!
I've got a background in neuroscience and transitioned to data science a few years ago. Your comment about the rabbit hole of modern biology is spot on. I've been hearing for 10+ years about how ML like computer vision will revolutionize medical diagnosis and treatment. It hasn't happened yet and I think that enthusiasm comes from the fact that we built computer systems from the ground up and therefore know them deeply, whereas biological systems aren't fully understood.
A complex three dimensional organism self-assembling from a single cell is 100% magic, especially given how resilient it is to disruption. You can kill one of the two cells produced by the first division and still get a fully formed organism (that's one of the actual early experiments in morphogenesis theory).
This article really strikes a chord: going through high-school biology I was shocked by the dessication of life in the way everything was presented, as if death itself had written the curriculum. I focussed on maths and suspected this was the hidden agenda: only present man-made constructs, treat the rest as if it were just wrong maths.
My father, who was a teacher considered teaching classes to be a kind of performance art. For getting information, you are better off with a book (or other media). His goal was to put up a performance good enough to get students interested, and ideally, read the books later.
The field of biology was created by people who love to classify/name things. This has resulted in what we have now: A subject where the prerequisite to understanding is the ability to read long passages of text littered with jargon and visualize what that might represent. Even if everyone's reading skills were where they should be, the second part is not a super common skillset.
It's one of the reasons why I work in visualization for life sciences education: I think we're missing out on people who might otherwise make massive contributions to the field because they failed to memorize what the "endoplasmic reticulum" does. Much of biology you don't have to actually remember what things are called in order to understand the processes (at least at a basic level like what a middle schooler might be taught). Once you're exposed to the fascinating complexity of life at that level, for many people it can be interesting enough to build the motivation for the memorization/etc.
>Much of biology you don't have to actually remember what things are called in order to understand the processes
But even that's besides the point of the fact that all these things are nothing more than abstractions created by humans, and ultimately it's all one giant soup of interacting molecules.
> The field of biology was created by people who love to classify/name things.
More to the point, the field of biology is so complex that for the longest time we could only name and classify things. Understanding came later, when we'd accummulated enough data and had hints from chemistry and other fields.
The problem is that once we gain that understanding, we add that as one more chapter to our textbooks, one more lesson tacked on, instead of rethinking the curriculum around our understanding.
The use of latin doesn't help either. "Cytoplasmic net" (or better yet "plasma net") is a lot easier to understand, visualise and remember than "endplasmic reticulum".
If you are an English speaker. If you are native in a Latin-based language, "reticulum" is pretty clear (reticolo, retículo, réticule etc). So, it's just a point of view and dictaded by the most used language within research/education at a particular point in time.
I do quantitative biology now, although my background is in theoretical physics. Biology is fascinating, but ultimately there is a cultural divide between the scientific "language" used in biology and the scientific language of e.g., engineers, physicists (very famously described in "Can a biologist fix a radio?" https://www.cell.com/action/showPdf?pii=S1535-6108%2802%2900...)
I do find the author's point weird. "I thought high school biology was just memorizing facts, but I began to appreciate it when I read some pop science books and went scuba diving." So the only problem for the author was the topic of the classes, not the style. Why shouldn't one have the same problem with high school physics ("it's just about boring ramps and pulleys"), etc.? Personally I find the style to be a more important distinguishing factor, in that biology is much less quantitative than other science disciplines. Instead the author's problem is that biology should be even less quantitative and more literary or poetic...?
Ultimately science journalism/popularization is not the same thing as science. High school science classes (try to) teach the latter not the former.
High school physics and chemistry equips students to make (a very limited set of) predictions. High school biology super doesn't. When you're learning chemistry and physics, it feels like you're learning a systematic set of rules that let you approximate and model the world around you. Biology...doesn't, not really. Life is just more complex and higher order, and it's that much harder to actually use the study of it to understand the world immediately around you in any meaningful way.
It's still super cool, but it makes learning about it as a science less satisfying, since it's less friendly to the standard scientific method.
Love biology. I appreciate purist mathematician/logicians prefer chemistry and physics and it seems to be an inside joke in the professions that biology isn't on the same level when it comes to axiomatic things.
I'm a classic INTJ but left school and built biology-online.org 25ish years ago. I think it's had a couple of thousand years of reading hours. I sold it on thinking I lack the expertise the topic deserves (it ranked well on Google for lots of biological terms)
I love the lack of agency about biology/evolution, it found a way to create ourselves as well as the huge tree of life around us purely through biological/ecological pressures. And here we are. We owe a lot to how biology has expressed things over the past 4 billion years and will likely find out a whole lot more.
> Despite its popularity, the MBTI has been widely regarded as pseudoscience by the scientific community.[1][3][2] The validity (statistical validity and test validity) of the MBTI as a psychometric instrument has been the subject of much criticism.
> Many of the studies that endorse MBTI are methodologically weak or unscientific.[13] A 1996 review by Gardner and Martinko concluded: "It is clear that efforts to detect simplistic linkages between type preferences and managerial effectiveness have been disappointing. Indeed, given the mixed quality of research and the inconsistent findings, no definitive conclusion regarding these relationships can be drawn."[13][72]
>The test has been likened to horoscopes, as both rely on the Barnum effect, flattery, and confirmation bias, leading participants to personally identify with descriptions that are somewhat desirable, vague, and widely applicable.[10][73] MBTI is not recommended in counseling.[74]
Any survey (as opposed to horoscopes which aren't up to user choice) can be used to convey information about a person, even if that information is what they think about themselves. "I took a survey and I'm a Slytherin" conveys plenty, and no one feels the need to point out that that's unscientific.
I'm just going to recommend the biology books written by Lewis Thomas. The books are collections of essays rather than science or text books. They blew my mind and opened up a deep respect for the field of biology and gave me a deep appreciation of life in all its forms, so many of which I didn't know existed.
Look for:
The Lives of a Cell: Notes of a Biology Watcher
The Medusa and the Snail: More Notes of a Biology Watcher
I've recently been delving into paleobiology, but what inspired it was very different from what's described in the post. I ingest a lot of pop educational stuff, mostly just for entertainment; but after a few years of just hearing the highlights and fun facts it became frustrating not being able to put all of it into context.
So I pushed myself a little out of my comfort zone and ordered a textbook and enrolled in a course. It made me realize how I've forgotten how to learn without it being entertainment. But, after some acclimation, I also realized that I don't really need an engaging presentation, because I really do just enjoy learning. So in a way my journey has been kinda the opposite of the author's - the 'fluff' around the information made it less appealing, not more. Though I suppose I might not have taken the leap to delve deeper into these topics in the first place if it weren't for the accessible versions.
Either way though, I think the real takeaway isn't that there's a right way to be interested in a topic - whether through stories and history or otherwise - but rather that school isn't the best environment for figuring out if something interests you, and it's worth re-visiting topics you might have written off with a fresh approach.
>I think the real takeaway isn't that there's a right way to be interested in a topic
I think a different perspective can sometimes illuminate though, it's not just about the person - it's them having an epiphany that motivates them to do something, like learn more.
>pop educational stuff,
I watch a lot of that as lazy entertainment, so much of it is factually incorrect (on YouTube etc). But I know better I guess.
My interest in biology isn’t driven at all by stories, history, or “adventure”, but rather by the awe-inspiring complexity and majesty of all the microbiological processes and their interplay.
Yes, it’s pop science, but last be year I read through Philipp Dettmer’s “Immune”, and the description of how the immune system continuously generates random/arbitrary sequences of nucleotides, builds the proteins that those sequences encode, and then subjects the resulting proteins to a “is this a ‘me’ protein or an ‘other’ protein?” gauntlet, the latter path of which allows the body to create antibodies for completely novel proteins... is just incredible.
I have an idle fantasy that, in the afterlife, I’ll be able to ask God questions like “so what are quarks made of?”, “why is the speed of light what it is and not any faster/slower? What would the universe have been like if the speed of light were several orders of magnitude faster/slower?”, “is there a single force that unifies all the ones that humans know about? What would the universe have been like if the weak nuclear force were just a tiny bit weaker?”, etc etc etc etc etc etc etc.
same inspiration but I wouldn't devolve it to 'pop science', it's simply less axiomatic than physicists and mathematicians would like. The fact there's 4 billion years of ecological change beyond the biological change just makes stuff hard to prove empirically.
esp. when physicists use things like the anthropic principle to describe our own universe.
I can really relate to this — in school, biology felt like dry memorization. It never clicked with me, and I wrote it off for years. If I could recommend one subtopic of biology to math and physic people, it would definitely be mycology!
It's like real-life Pokémon GO and field mycology has a "collect 'em all" vibe. You get out into nature, identify and catalog fungi — it scratches the same itch as exploring an open-world game.
Fungi are discrete, classifiable entities with tons of metadata: GPS location, substrate, time of year, morphology, spore prints, photos, microscopic features. Perfect for structured data nerds.
Unlike many branches of biology, you don’t need to go to the Amazon. You can walk into your backyard or a nearby forest and find species newly known for your country and sometimes even new for science.
Microscopes, macro lenses, chemicals, even DNA sequencing. There’s a hacker spirit in mycology.
Projects like iNaturalist, Mushroom Observer, and FungiMap are full of real scientific contributions from everyday people. The barrier to entry is low, the impact can be surprisingly high, and the community is genuinely welcoming. Many leading contributors — even those publishing in cutting-edge scientific journals — are passionate autodidacts rather than formally trained biologists.
High intra-species variance, subtle features — perfect playground for machine learning wich is not nearly "solved" here.
Cordyceps that zombify insects. Giant underground networks that share nutrients between trees. Bioluminescent mushrooms. Many weird stories.
Mycology is also becoming a computational frontier - projects like FungiNet use graph networks to map symbiotic relationships, and citizen science platforms generate massive datasets perfect for ML applications beyond just classification. The unsolved phylogenetic relationships and complex biochemical pathways of fungi represent some of the most interesting computational problems in modern biology.
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[ 5.1 ms ] story [ 212 ms ] threadAs a matter of fact, I gave up after just one year. It wasn't any fun for anyone, not for the students, not for me.
imagine that!? an historically informed populace???
you'd need more expensive lies and higher quality fakes... the government would be costlier to run.
ideally, in the long term this would make the national currency's value in the international money market rise up. but why wait for that when one can directly manipulate money through trade fraud and covert military ploys?
My favourite classes were those where we didn't just get taught facts and theorems but we also got taught a bit about who proved the theorem for the first time, who discovered this fact, what this algorithm was first used for, etc. So much easier to remember too.
This is one of the best things about studying law: the very nature of it makes it impossible to teach it without the historical context.
I must confess, it gives my dry old heart some joy, to see the anti-education masses coming from this, voting and storming the fortresses that produced the paywall around education, that only money with tutors could or accidental intrinsic motivation could overcome and burn & salt those outposts of classists academia.
Developed countries really need a come to Jesus moment, because the disdain for everything that made them great places is unbelievable. People will understand, after great suffering, that destroying stuff is much easier than building it.
But systems can rot from within too, or just decay naturally, and don't need to be destroyed. What if the core ideas that built our current civilization were ideas of the past, that we don't have any more, and we don't know what to do when The Machine Stops? Doesn't have to be a literal machine - it's a good metaphor for how democracy fell apart.
"It is easier to destroy than to create" doesn't tell you when something should be torn down.
You can have a house that provided shelter for your family for generations, but if it's water damaged, the floors are rotting and it's full of toxic mold, the person who shows up with a bulldozer isn't necessarily wrong.
Their interests are built by what they are taught. "Socioeconomic background" is a tautology. Their backgrounds are irrelevant.
If the child is fascinated by video games- i would help it make video games, the curriculum be damned. All knowledge holes can be filled later, but the passion to wanting to know, can never be restored unless the want for knowledge remains intact.
You must understand these things at least conceptually if you want to really understand how to write efficient programs. Maybe not at the level of how memory can electronically "remember" a 1 or a zero, or how a hard drive can magnetically do it, but at least the relative speeds e.g. register vs. cache vs. RAM vs. disk.
The "mistake" happens so often, partially because "segway" is a much more straightforward spelling if one has only heard the word said aloud, that I think it will eventually become the actual way it is spelled!
That's precisely how language changes over time. Language is not a strict set of rules. It's based on understanding and consensus, so sometimes things that are "wrong" do end up being accepted.
I suggest this as a great introduction into what languages are and how they evolve over time https://www.amazon.com/Language-Families-of-World-audiobook/...
How does this mistake happen so often? Can you explain people's thought process a bit? Is it just: "Something something 'seg...' ... ah I know, I will simply use another random word that starts with the same 3 letters and doesn't make sense in this phrase!"?
Also this is the first time I see it.
Pronounced correctly, “segue” sounds just like “Segway” – not like “seg-oo”, as you might have assumed.
I am sure people will make the mistake, as they sometimes do today. But it is a mistake, and will likely be recognised as one.
It is likely that the language gets more cemented by automatic spelling and grammatical correction, including using AI. For example, there are a number of grammatical and spelling changes that have been cemented by American spelling/grammar checking programmes ie. by MS Word.
I did not imply that at all. I said sometimes, so it's not that absurd that it could happen. It does happen though, and a quick google search will give you pages of examples.
With machines looking over our shoulders now and so much of language being typed instead of handwritten, odds are such drift might actually decrease in English... On the other hand, the introduction of AI leaves an interesting avenue for people to begin acting as if something is common usage and have the AI begin confirming that as common if it consumes that action. And then, of course, there's the effect of the machine itself... Most of us have a way to type "résumé", but we don't bother because the machine makes it too much work to do so, So the alternate spelling without accent, which was called out in my high school days as wrong, has fallen into common usage in a generation of people having to submit their resumes online (example: https://www.linkedin.com/help/linkedin/answer/a510363).
In more forgiving of mixing up homophones, even if one of them is a registered trademark (Segway).
I suggest you yourself take a second and explore why you think being smarmy on the internet is a way of getting people to agree with you.
Looking it up in https://en.wikipedia.org/wiki/Segue they even warn about that!
I also think this is where things like intergenerational math-phobia come from: parents who don't grasp core concepts and are scared off, and can't help their own children, creating an ongoing cycle.
I hope you appreciate my addition of the other common path of math phobia.
It’s probably why, when I got to university and tackled subjects like probability theory, discrete math, and theoretical CS, I did extremely well — they weren’t reliant on the shaky algebra and trig foundation I had from school. Once the focus shifted to logic and conceptual thinking, without the baggage of poorly taught fundamentals, everything clicked
The answer is it's magic and no one cares, now let's go build some games
At school I thought "computer science" meant "programming" - which it doesn't. So well done for recognizing this before wasting your much time. (Seriously, not sarcastic.) programming can easily be learned outside college.
To other general readers here though I'll say that understanding the science can be really helpful over a career. It's not terribly applicable in getting that first job, but as you progress more and more of those theoretical fundamentals come into play.
Ultimately there are a small fraction of people who need to understand how it all works, all the way down, because those people build the things that programmers use to build everything else.
There are theoretical parts of computer science, but it is fundamentally a practical subject. All of it is in service to programming. Type systems are about typing programs. Algorithms are implemented using programs. Data structures are for use in programs.
The very worst computer science lecturers are those that forget it is a practical subject and try to teach it like abstract mathematics, because they believe (whether they realise they believe it or not) that it is more prestigious to teach abstract concepts than practical concrete things.
It is the same in mathematics, where unfortunately there has developed a tradition since Bourbaki of trying to teach abstract notions as fundamental while concrete problem solving is left to the engineers. The result is that many engineers are much stronger mathematicians than many mathematically-trained students, and those students have to relearn the practical foundations of the subject before they can make progress at the graduate level. If they don't, they get stuck doing what looks like maths, but is actually just abstract roleplaying.
This was a point repeatedly driven home in my undergraduate curriculum, and in fact, they made a point of having multiple classes where a computer was completely uninvolved.
It's probably fair to say that although we learned some history, we had the privilege of learning at a time the field was exploding. That history you learned, I lived and worked through that. It's somewhat surreal to realize that my career is your history class.
As mentioned above though, it'll vary a lot from one school to another.
It very much felt like a Wikipedia article on the history of computers somehow stretched out over an entire summer.
I have my own issues with the way college is generally setup. Do students really need a massive amusement park when self study along with 3 or 4 exams would provided the same value. Will spending 70k per year in total cost of attendence at said amusement park serve them?
I don't really like boot camps either, personally I'd like companies to be more open to actually training people again. I doubt it'll happen though.
Well, yeah. That's true for any field of study. Every college has strengths and weaknesses- its the opposite of a franchise.
>> I took a few foundational classes at community college.
A few foundational classes is somewhat different to classes you take in prep for a major. I did a foundational class in astronomy, designed for students who were just looking for an introduction. It was very different to my comp Sci classes in tone and style.
Yes there was some math involved, but not much in the comp science classes. Math was a pre-requisite though so we got our math in, well, math.
I just don’t like the idea of gate keeping it behind an expensive degree. The source code for most popular frameworks and tools is free for anyone to read.
It’s not like medicine or something where you need to drop 300k on education.
Of course, in this field, learning is continuous. You're not going to use just one language (much less one framework) over a decades-long career. It's also likely that your domain will change, your focus area and so on.
A good college course doesn't prepare you for programming in one language, but all of them. (In the sense that once you understand the theory of programming, language is just syntax.)
You get exposure to different types of languages (imperative, functional etc).
I think for me the critical takeaways though were research, critical thinking and communication. The "skills" are easy to learn yourself, but the formality in which you place that learning is harder to do yourself.
Which is not to say a degree is a requirement- it's clearly not. But it's helpful because it builds a strong foundation on which the self-learning can rest.
I've received great intellectual satisfaction from various well-taught subjects. I would rather chop off a finger than lose them. So curriculum committees that make subjects boring are doing something worse than chopping off millions of children's fingers.
I really wish that teaching of history will get better for current and future kids.
- Paul Valéry
Speaking for myself, and I’m sure many others on hn, I was very interested in the history of computers at 13!
Bioinformatics: https://en.wikipedia.org/wiki/Bioinformatics
Health informatics: https://en.wikipedia.org/wiki/Health_informatics
Numerator, denominator?
Does any country's FDA AERS collect unit sales data?
If you're an engineer and early in your career and feel there's something missing from your intellectual space, I encourage you to go back and get a graduate degree in something totally different. Humans live a very long time so don't feel like you're wasting time.
Work for a company that will pay for it.
I encourage people to look into it, it's a benefit a lot of people have but don't use and it's leaving money on the table.
1. Masters degree only, they won't pay for anyone to get a bachelor's or associates
2. Must maintain a B average or better
3. Cannot take any time off, it has to be entirely on nights and weekends
4. Reimbursement after the fact, so you're taking on the initial financial risk up front.
However, to use it there are constraints: 1. The topic should be related to technologies used by company. Cannot get a Google cloud certification as they are using aws. 2. To get it you need approval by line manager, hr, and director of the office. 3. If it is more than €250 you need to sign up loyalty agreement for a year. Meaning if you will return some amount of you quit.
With all that strings attached it is just a marketing bullshit to attract new hires.
Whether or not broad support for training scientists holds up during and after the current administration remains to be seen.
There are tons of very well-done professional level video courses on Youtube.
There are more organized courses that only ask you for money for the "extras", like some tests and a certificate, but the main parts, texts and videos, are free.
You could start with a really good teaching professor (Eric Lander, MIT) and his course: https://www.edx.org/learn/biology/massachusetts-institute-of... (the "Audit" track is free, ignore the prices; also ignore the "expires" - this course restarts every few months and has been available in new versions for many years now)
It's very engaging!
There's similar courses for everything in the life sciences, there on edX, on Youtube, many other places.
I feel the true Internet is soooo underutilized by most people! Forget news sites, opinion blogs, or social media. Knowledge is there for the taking, free. Only the organized stuff, where you end up with a certificate costs money, but they usually still provide the actual content for free.
I decided to purse a double major in biochemistry and evolutionary biology and it was one of the best decisions I've made in my life. The perspective you gain from understanding all life in terms of both networks and population dynamics of atoms, molecules, cells, tissue, organisms and populations -- and how every layer reflects the layer both underneath and above it in a fractal pattern -- is mind-expanding in a way I think you just don't and can't get designing software systems alone.
I work as a software engineer / founder now, but always reflect wistfully on my time as a biologist. I hope to get back to it some day in some way, and think what the Arc Institute team is doing is inspirational [0].
[0] https://arcinstitute.org/
For small example, there was a Princeton(?) coffee-table book which used "everyday" examples to illustrate cell/embryonic organizational techniques - like birds equally spacing themselves along a wire. Or compartmentalization, as a cross-cutting theme from molecules to ecosystems.
I've an odd hobby interest in exploring what science education content might look like, if incentives were vastly different, and massive collaborative domain expertise was allocated to crafting insightful powerful rough-quantitative richly-interwoven tapestry.
I loathed biology as taught prior to that. Once I got a molecular biology course, I thought biology was amazing and wondered "Why the hell did we teach all that other crap?"
Well, that was because the tools we had for biology sucked prior to PCR. My problem was that I recognized that even as a child.
This was early days of the internet, the book(s) were largely the only resource. The instructors were folks who just understood coding in C naturally and had no idea how to communicate with those who did not. No joy in anything, just raw code.
I dropped out.
Decades later after age 40 I was at a career crossroads and took a web development class. I loved it, I could make things quickly, the instructor actually understood how to teach / introduce concepts. I've been happily coding professionally and personally since then.
How things are presented sometimes makes all the difference.
> Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover, and mutation.
AP®/College Biology: https://www.khanacademy.org/science/ap-biology
AP®/College Biology > Unit 7: Natural selection: https://www.khanacademy.org/science/ap-biology/natural-selec...
Rosalind.info has free CS algorithms applied bioinformatics exercises in Python; in a tree or a list; including genetic combinatorics. https://rosalind.info/problems/list-view/
FWICS there is not a "GA with code exercise" in the AP Bio or Rosalind curricula.
YouTube has videos of simulated humanoids learning to walk with mujoco and genetic algorithms that demonstrate goal-based genetic programming with Cost / Error / Fitness / Survival functions.
Mutating source code AST is a bit different from mutating to optimize a defined optimization problem with specific parameters; though the task is basically the same: minimize error between input and output, and then XAI.
And then tests for convergence given different metaparameters and resource costs.
[1]: Although he just retired from it. Janet Iwasa will continue the project.
You have to become comfortable with the fact that there is uncertainy and there are parts of it you can't control. So instead you have to be obsessed with introducing order where you can. It is so refreshing to see a beautiful experiment that can wrestle a clear signal from the endless noise.
Depends where in math, in things like particle physics things get all wibbly wobbly is my cat dead or alive. In things like engineering quite often what you're dealing with is probability based, but you just stack the deck so far in your favor the probability is 1.
As they say, building a bridge that doesn't fall down is easy. Building a bridge that barely doesn't fall down is much harder.
I have seen molecular biologists (jokingly) shake the voodoo "molecular biology maracas" over the PCR machine to try and replicate their result.
It's a human thing.
Surely Feynman made jested comments before running experiments. I'm sure some digging in his wonderful books and letters will find many examples.
In fact, just finished listening to a talk where a experimentalist was talking about how to get the fabrication yields of superconducting qubits from currently low double digit to 99.99+.
Biology is messy at a macro level is all I'm saying. I don't need a hundred people butting in saying "butt aschully phsyix and code is also messy and harder at a quantum level." I know. We know.
A title like "I wish I had enough attention to get through the boring parts of high school biology, I now find pop biology interesting" may have had less impact, though.
Computer scientists and programmers are very intelligent people who often have grossly unrealistic projections of their competency in other fields, and this is a fine example of the phenomenon.
Secondly, fields really do need cross-discipline collaboration. Finding passionate CS people is fantastic because they bring a different skill set. I have often found that when we get diverse experts together, we can have everyone do the "easy part" and get results which would be otherwise unobtainable.
Yes, some people have 'engineers disease' and fail to appreciate the depth of knowledge and skills of folks who have spent their life in another domain... But the author doesn't seem to be one of these. Many of their favorite stories appreciate the combination of insight and hard work in the history of the field.
It does, indeed, suck that people working in biology get paid less than computer engineers. Blame capitalism...
I feel bad for them, but I can assure you, as someone who did the research in the exact same field, they're curing nothing and are more likely to make cures slower by sucking away funding from more pertinent projects.
Also relevant xkcd https://xkcd.com/1831/
Do you have any advice for how to not be that kind of problem? For now I'm just focusing on my coursework, but at some point I'll be biologist-enough to help out with research. How do I approach it without being that guy?
Practically what this means is that you should decide what you truly want to change (not necessarily what you can change with your current expertise) and pursue it across whatever fields necessary. If it's curing a disease, you have to decide what is the most important thing that's stopping us from curing that disease and pursue that exact topic. More often than not it's not anything software related. You have to grab a pipette at some point and guillotine a few mice at another lol.
I offered to put it on github for him, so that at least he didn't have to be the sole caretaker for this endangered bit of software, but he was afraid of running afoul of the original author's rights, so endangered it will stay.
This was maybe an unlikely occurrence, falling neatly in the not part of your:
> More often than not it's not anything software related
But it makes me think that there is still some juice left to squeeze out there. I mean, I'm having a good time with my one-class-per-semester, I'd just prefer to not have to do it for another decade before I'm enough of a biologist to get my hands dirty.
In my own work helping ecologists, I see plenty of CS/ML folks who think they'll change the world by throwing a transformer at the problem. (which problem? you think we haven't tried that?) It takes some time and exposure to figure out what kinds of problems you can meaningfully contribute on.
On the other hand, I've met lots (most?) of ecologists who underestimate the impact of looking at their work through CS/ML lenses. Effective automation can greatly improve iteration speed, which ultimately leads to better outcomes than a slow but 'perfect' process. (and, indeed, the 'slow-but-perfect' process may not be sufficiently benchmarked, and not be perfect at all...)
You can do a lot of good by working closely with a practitioner, and identifying the places where they are spending a lot of time doing 'boring' stuff, and finding ways to automate or approximate the outcomes of that boring work. As you work with more people, you'll be able to identify boring stuff that everyone in the field is stuck doing.
So, in short, an excellent goal is to find ways to save people time through bottleneck analysis. Improve iteration speed and you improve the speed at which we can accumulate knowledge / make discoveries / etc. When you're done, it's "just a tool", but beforehand it's a problem holding back discovery.
But yeah I get your point about avoiding that delusion. Honestly I'd be happy enough to be doing something that I suspect is not actively harmful (this should be easy but SaaS tends to converge on products that control their users and not the other way around). I don't need to be humanity's savior. More helpful than harmful will be enough.
The post is simply about what you call enough attention to get through the boring parts of high school biology — should biology in school be only for those who have that ability? Even if being a professional biologist requires those attributes, shouldn't the teaching of the science of life—which is full of wonder—have a bit of something for everyone else too? Even people who don't become biologists ought to love biology, surely?
That's what the post (like the earlier one by Somers) is about; it's not about “I could have become a biologist” (as you seem to be implying). You can call it pop biology, but it's missing from school where “astonishing facts were presented without astonishment”. I see nothing self-entitled about this.
It's the same in mathematics, say: even if being a professional mathematician requires (say) thinking long and hard and being willing to struggle with difficult problems, manipulating things in one's head, etc — surely there is value in exposing more students to pop mathematics / beautiful results (enjoying which is very different from actually doing mathematics, sure), so that more people could love mathematics recreationally, whether or not they become professional ones?
The other top-level thread that talks about how this happens in CS education too (https://news.ycombinator.com/item?id=43764315) seems to get the point of the post: it's the equivalent of Lockhart's A Mathematician’s Lament (https://worrydream.com/refs/Lockhart_2002_-_A_Mathematician'... ).
Not the only sequence model that exhibits stutters on repetitive inputs...
Critiquing my own code, though, it should really be a check against 'can_reproduce()' rather than 'is_dead()'.
You don't need to go into nature to get this curiosity except for the possibility that it makes you more meditative. You can look at your arm and think what the hell happens in there at a molecular level to make you move the muscles. Or when someone says nerves conduct electricity what the hell does that mean?
I revisit this feynman video of him explaining (or not) magnets every few months and I think it's relevant to this question. https://youtu.be/MO0r930Sn_8?si=CkWYfiGoGCgAANwP
When I think like that I'm just curious why OP and others blame teachers or whoever else for not inducting the curiosity in them. Like it's someone else's job to make you curious? In my opinion you're either born that way or you're not. Some airport store book isn't gonna make you the next whatever scientist you adulate.
Gaining an appreciation for nature is good, getting fascinated with biology is also good, but one is not necessarily related to the other in practice.
To be proficient in biology you need to have "Extra" skills: extra ability to work with ambiguity,ability to memorize enormous amounts of descriptive information, and highly abstract representations. Digital biology often loses many aspects of biological reality, and then fails to make useful predictions.
Over the years, I've come to realize I know less and less about biology- that I greatly underestimated the complexity and subtlety of biological processes, and have come to admit that my own intelligence is too limited to work on some problems that I originally thought would be "easy engineering problems".
A great example of the rabbit hole that is modern biology is summed up here: what is the nature of junk DNA? To what extents are digital readouts like ENCODE representative of true biology, rather than just measuring noise? What is the nature of gene and protein evolution?
https://www.cell.com/current-biology/fulltext/S0960-9822(12)... (note that while I disagree strongly with Eddy in many ways, I've come to recognize that I simply don't understand the modern view of evolution outside the perspective of molecular biology (IE, what geneticists like Eddy think).
Also, recently, Demis Hassabis postulated that if he is successful, we will come up with silver bullet cures in 10 years time simply using machine learning. It's amazing how many computer scientists (I call him that rather than a biologist, although he has worked into neuro) make this conclusion.
https://en.wikipedia.org/wiki/Segmentation_gene
It's one of the reasons why I work in visualization for life sciences education: I think we're missing out on people who might otherwise make massive contributions to the field because they failed to memorize what the "endoplasmic reticulum" does. Much of biology you don't have to actually remember what things are called in order to understand the processes (at least at a basic level like what a middle schooler might be taught). Once you're exposed to the fascinating complexity of life at that level, for many people it can be interesting enough to build the motivation for the memorization/etc.
But even that's besides the point of the fact that all these things are nothing more than abstractions created by humans, and ultimately it's all one giant soup of interacting molecules.
More to the point, the field of biology is so complex that for the longest time we could only name and classify things. Understanding came later, when we'd accummulated enough data and had hints from chemistry and other fields.
The problem is that once we gain that understanding, we add that as one more chapter to our textbooks, one more lesson tacked on, instead of rethinking the curriculum around our understanding.
Not a lot of point in spending time researching something, only for no one to know what you're even referring to.
I do find the author's point weird. "I thought high school biology was just memorizing facts, but I began to appreciate it when I read some pop science books and went scuba diving." So the only problem for the author was the topic of the classes, not the style. Why shouldn't one have the same problem with high school physics ("it's just about boring ramps and pulleys"), etc.? Personally I find the style to be a more important distinguishing factor, in that biology is much less quantitative than other science disciplines. Instead the author's problem is that biology should be even less quantitative and more literary or poetic...?
Ultimately science journalism/popularization is not the same thing as science. High school science classes (try to) teach the latter not the former.
It's still super cool, but it makes learning about it as a science less satisfying, since it's less friendly to the standard scientific method.
I'm a classic INTJ but left school and built biology-online.org 25ish years ago. I think it's had a couple of thousand years of reading hours. I sold it on thinking I lack the expertise the topic deserves (it ranked well on Google for lots of biological terms)
I love the lack of agency about biology/evolution, it found a way to create ourselves as well as the huge tree of life around us purely through biological/ecological pressures. And here we are. We owe a lot to how biology has expressed things over the past 4 billion years and will likely find out a whole lot more.
https://en.wikipedia.org/wiki/Myers%E2%80%93Briggs_Type_Indi...
> Despite its popularity, the MBTI has been widely regarded as pseudoscience by the scientific community.[1][3][2] The validity (statistical validity and test validity) of the MBTI as a psychometric instrument has been the subject of much criticism.
> Many of the studies that endorse MBTI are methodologically weak or unscientific.[13] A 1996 review by Gardner and Martinko concluded: "It is clear that efforts to detect simplistic linkages between type preferences and managerial effectiveness have been disappointing. Indeed, given the mixed quality of research and the inconsistent findings, no definitive conclusion regarding these relationships can be drawn."[13][72]
>The test has been likened to horoscopes, as both rely on the Barnum effect, flattery, and confirmation bias, leading participants to personally identify with descriptions that are somewhat desirable, vague, and widely applicable.[10][73] MBTI is not recommended in counseling.[74]
There’s a funny irony that you’re using a rhetorical device, as opposed to a rigorous scientific methodology, to try and navigate that criticism.
Look for:
The Lives of a Cell: Notes of a Biology Watcher
The Medusa and the Snail: More Notes of a Biology Watcher
The Youngest Science
...and a couple of thers.
So I pushed myself a little out of my comfort zone and ordered a textbook and enrolled in a course. It made me realize how I've forgotten how to learn without it being entertainment. But, after some acclimation, I also realized that I don't really need an engaging presentation, because I really do just enjoy learning. So in a way my journey has been kinda the opposite of the author's - the 'fluff' around the information made it less appealing, not more. Though I suppose I might not have taken the leap to delve deeper into these topics in the first place if it weren't for the accessible versions.
Either way though, I think the real takeaway isn't that there's a right way to be interested in a topic - whether through stories and history or otherwise - but rather that school isn't the best environment for figuring out if something interests you, and it's worth re-visiting topics you might have written off with a fresh approach.
I think a different perspective can sometimes illuminate though, it's not just about the person - it's them having an epiphany that motivates them to do something, like learn more.
>pop educational stuff,
I watch a lot of that as lazy entertainment, so much of it is factually incorrect (on YouTube etc). But I know better I guess.
Yes, it’s pop science, but last be year I read through Philipp Dettmer’s “Immune”, and the description of how the immune system continuously generates random/arbitrary sequences of nucleotides, builds the proteins that those sequences encode, and then subjects the resulting proteins to a “is this a ‘me’ protein or an ‘other’ protein?” gauntlet, the latter path of which allows the body to create antibodies for completely novel proteins... is just incredible.
I have an idle fantasy that, in the afterlife, I’ll be able to ask God questions like “so what are quarks made of?”, “why is the speed of light what it is and not any faster/slower? What would the universe have been like if the speed of light were several orders of magnitude faster/slower?”, “is there a single force that unifies all the ones that humans know about? What would the universe have been like if the weak nuclear force were just a tiny bit weaker?”, etc etc etc etc etc etc etc.
esp. when physicists use things like the anthropic principle to describe our own universe.
It's like real-life Pokémon GO and field mycology has a "collect 'em all" vibe. You get out into nature, identify and catalog fungi — it scratches the same itch as exploring an open-world game.
Fungi are discrete, classifiable entities with tons of metadata: GPS location, substrate, time of year, morphology, spore prints, photos, microscopic features. Perfect for structured data nerds.
Unlike many branches of biology, you don’t need to go to the Amazon. You can walk into your backyard or a nearby forest and find species newly known for your country and sometimes even new for science.
Microscopes, macro lenses, chemicals, even DNA sequencing. There’s a hacker spirit in mycology.
Projects like iNaturalist, Mushroom Observer, and FungiMap are full of real scientific contributions from everyday people. The barrier to entry is low, the impact can be surprisingly high, and the community is genuinely welcoming. Many leading contributors — even those publishing in cutting-edge scientific journals — are passionate autodidacts rather than formally trained biologists.
High intra-species variance, subtle features — perfect playground for machine learning wich is not nearly "solved" here.
Cordyceps that zombify insects. Giant underground networks that share nutrients between trees. Bioluminescent mushrooms. Many weird stories.