#but what do I know I just have a basic grasp of math and science

[magnetothemagnificent]

The American far-right: (((They))) built space lasers and hurricane machines to create natural disasters in the United States!

The American far-left: A country the size of New Jersey is single-handedly accelerating climate change to create natural disasters in the United States!

You guys sound exactly the same

[cosmicjoke]

Ideally, if Ash had been able to live at the end of Banana Fish and was able to remain in America and separate himself from gang life, what career do you think he would have enjoyed going into? :) I always think that’s one of the saddest aspects of Banana Fish, how abuse deprived the world of someone with so much potential, and of course, how much that abuse damaged Ash’s own perception of his value and potential.

Man, that's such a good question, and I couldn't agree more, that one of the greatest tragedies of Banana Fish and Ash's death is that it robbed the world of such an exceptional person in Ash.

I think Ash could have been just about anything he wanted to be. Eiji points out to him at one point that Ash would make a great model, and given Ash's looks, he could have easily gone into that field. Though given Ash's history and what he endured, I don't think modeling would be a very healthy business for him to have gone into.

I think Ash was really a nerd at heart. He was a mathematical genius, and I always got the impression he enjoyed it too, so he could have gone into maths or some other, scientific field and no doubt have made a real name for himself. Given his immense brilliance, knowing he had an IQ of 210+, he no doubt would have ended up pioneering in those fields.

Ash also had an immense grasp of global politics and military strategy and tactics. He probably could have become a politician or a general even, if he'd really have wanted to. But, again, I don't think Ash would have ever had any real interest in those things. I think he understood only too well how corrupt that world is, and the sorts of power mongers it attracts. Ash was never interested in wielding power, despite being naturally gifted as a leader.

Basically, I think Ash would have eventually ended up in some sort of academic field of study. Even literature would have interested him, given what a voracious reader we know he was, etc... Some sort of science or math would be my guess.

The sky was sort of the limit on Ash's potential. It truly is one of BF's greatest tragedies, that we'll never know what Ash could have actually accomplished, if only he'd been given the chance.

[fipindustries]

i used to think that one reason most people dont like math is that its seen as deeply unintuitive.

like, i feel in a lot of other sciences there is a certain level of intuitive understanding where if someone explains you a concept in it you can kind of grok it and even toy with it a little in your head.

like in bioogy if someone explains that red cells carry oxigen through your veins to every cell in your body where it oxidizes the glucose stored there and that oxidazion creates heat and energy for you to move and be alive and stuff. you can easily visualize all of that, you could even begin to extrapolate other things or make astute questions based on that.

in economy if someone explains the offer and demand curve or the way social spending might affect production and gdp, again all of this touches and buils on ideas most people are semi familiar with or can easily infer.

but math, anything beyond basic bitch algebra, none of it feels like it "clicks" if you are not a student of it, if i go to someone and try to explain to them something like l'hopitals rule, is not just going to be goobledeegook to them, they wont be able to connect it to anything else they know, there wont be a sense of "right, makes sense", is not going to feel like it fits on anything else or even like its all that meaningful, they wont be able to do nothing with that, is not like they can take it from there and even know what follow up questions to ask.

is not just that its unintuitive, unintuitive implies that it surprises you, that it subverts expectations, that it goes against what we think established, but this is just completly out of context knowledge, there are not expectations, no intuitions to preconciebed ideas, this is just something alien that means nothing.

but the thing is, i have been studying a little math on my own lately and now that i found a proper teacher i realized that math SHOULD feel intuitive when its well explained. when its properly introduced, the whole point is that the next step makes sense, is just that it has to be built on everything that came before and that the very language and symbology of math can feel impenetrable (which makes sense, its a specific language to descrive very specific, very particular truths which cannot be interpreted in more that one singular way in a very compressed way).

bottom line, the whole process of solving a math problem a lot of times rests on you "intuiting" a possible avenue to answer it, a vague sense that "yeah, this probably works, lets show that it does". math at its best is an incredibly powerful feeling of "OF COURSE! I CAN SEE IT; IT JUST MAKES SENSE AND THERE IS NO OTHER WAY IT COULD POSSIBLY BE""*

*(this is in many senses the opposite of how i feel when i study humanities, where i can grasp what they are aiming at in an intuitive sense but all the while i feel like im hearing a just-so story, where there is is always this nagging sense that there is no reason it couldnt be explained a thousand other ways)

[realcleverscience]

There are different definitions of "AGI" (Artificial General Intelligence). Some people focus on AI's understanding and possibly even sentience, while many focus on what it can do. Some people define it as equivalent to the abilities of the average person; others, as equivalent to the abilities of experts.

Part of the challenge is that intelligence comes in many forms. For instance, the ability to grasp objects is a form of intelligence though it's not something people generally think of as a business-related skill. And at the same time, the moravec paradox observes that computers are great at things humans are not and vice versa (e.g. computers have a hard time grasping objects but can do advanced maths in milliseconds.) So, comparing human and machine intelligence is challenging.

That said, I favor the "what it can do" approach because that has the most immediate impact in people's lives. That is, if we have AI systems that can do economically useful work just as good as the average person (or even better, the average expert), that means a few things:

People won't be needed to work. (Jobs? Economy?)

All economic output could increase several times over. For instance, AI may advance our tech. At a minimum, robots can work 24/7/365 whereas humans work a fraction of that. Imagine our ability to fabricate advanced computing chips doubling, which can then be used to make more chips, etc.

We may have begun the "singularity", where digital based knowledge and skills skyrockets. This is because we will have reached a point where the AI can improve itself. This means expanding the types of jobs it can perform, improving its performance, and likely innovating new techniques or technologies to assist with its goals.

(Of course, that could have tremendously good or tremendously bad outcomes - e.g. global retirement and healthy ecosystem vs literal doom - but that's another discussion.)

This vid argues that we've hit AGI by this definition. And I think that by some narrow definitions, this may be the case. (I still think we need more accuracy, a better "ecosystem" for it to function, more real-world modeling, etc. OTOH, this isn't preventing it from being massively useful right now.) So, this doesn't mean that the things I just listed will happen tomorrow - but it does mean that we should be expecting more enormous advances in the lab, and start to see real world applications slowly beginning. The line between AI and AGI is quickly blurring. Buckle up.

p.s. I know casual readers probably hear about AI here and there but may still have a picture in their head of AI as basically just a tool for making crappy pictures. I'm begging y'all to see that AI is both way beyond that (e.g. it's now making literal movies, and rapidly approaching market-ready results) and more importantly, that it's much more than that. AI is advancing every field of science, from fusion energy to quantum computing to curing diseases and so much more. This is no longer a curiosity. This is real and it's here.

[chemblrish]

I also want to study chemistry in higher education. Can u please give me some guidance.. Like what subjects to choose any like what degree.. Please

Hi!

That's a great choice :) Obviously, there are all sorts of chemistry-related degrees (chemical engineering, biochemistry, medicinal chemistry...), but I've only ever studied one, so I can't really tell you anything about the rest. If anyone here studies something that isn't "just" chemistry but is close enough, please feel free to share your experience!

Personally, I think a question to ask yourself that is very important but not exactly common is this: do you want to study a fundamental science or something more broad, varied, and interdisciplinary? The answer will tell you whether to choose chemistry or something chemistry-related. I did try out an interdisciplinary degree (biotechnology) and was very unhappy with it, because I realized I was more interested in understanding a field of science thoroughly and in depth instead of skimming through many different fields without digging really deep into any of them. Which is why I switched to chemistry. So, would you rather know one branch of science deeply and precisely or many of them but more generally?

As for the subjects you should focus on (assuming you're still in school and aside from chemistry of course haha), I'd say physics too often goes overlooked. But chemistry and physics are closely intertwined and a good grasp of the basic concepts of the latter will help you understand a huge chunk of the former. Math is important too, but don't feel intimidated. You don't have to be a math genius, but there will be lots and lots of calculations (not necessarily hard!), so some level of proficiency will come in handy.

If English isn't your first language, I'd recommend paying attention to it as well - nowadays it's pretty much the international language of science (and here where I live it's actually mandatory to pass a B2 level exam to even graduate). I don't know what things are like where you live, but here chemistry is often associated with biology and people interested in a chemistry degree are sometimes expected to know biology too. That's garbage. If you go into "just" chemistry, you won't need any biology at all. Forget it.

Here's my answer to an ask about the ups and downs of studying chemistry in case you want to check it out too.

I think this got a bit long 😅 But if you have any further questions, feel free to hmu again! I'll try my best to help.

[beardedmrbean]

Oh yeah Ronald Erwin McNair, sorry I thought he was on that other space shuttle that fell apart during launch.

Also that program with Nichelle Nichols, I recall a lot of space exploration and travel polices were created to prevent another colonial empires power struggle which gave us the world wars and the eugenics horror show.

So space was showed to be “EVERY HUMAN CAN BE IN OUTER SPACE!” Now of course only humans of peak condition can be astronauts but stuff like Star Trek suppose to show a possible future where we all can coexist with each other.

Of course NASA was like “okay let not pull a Nazi and show that non whites and women can be astronauts too” but when most of your organization made up of geeky white people…

I can see why Nichelle Nichols was chosen as she inspired many people especially in the blacks and women into science with her uhura role.

And the whole racial tension that she of all people understands. So she basically help convince a lot of black people and women who you know grew up in segregation and heavy gender roles so NASA definitely felt like an out of reach idea for them.

Sorry you are a bigger NASA fan than me. I’m just curious how da fuck is math racist when we had a black astronaut that grew up in the Deep South?

🤨

He was, that was his 2nd flight, Challenger, Jan 28 1986. That's a day embedded in my memory.

NASA has pretty much always been THE government agency that didn't care about anything other than if you can do the job, obviously politics still showed up and they weren't going to send a woman or black man to the moon, woman bit was less sexist than it was a technology and biology thing, going potty and all, still sexism but it was really more cost effective to not have to worry about the other bits.

Nichelle Nichols thing, I hope she fully grasped how important she was to women in general and black women especially. This is the best anecdote about her, at least that fits the theme.

Roddenberry knew what he had created already, why else have a black woman and a Russian on the bridge crew, Nichols found out when Dr King let her know what she meant.

She also wrote that she had "a short, stormy, exciting relationship" with Sammy Davis Jr. in 1959.

GIRL!!! lol

>Sorry you are a bigger NASA fan than me. I’m just curious how da fuck is math racist when we had a black astronaut that grew up in the Deep South?

And a physicist at that.

It's not, I think the issue is that people don't like that there's going to be a right and a wrong answer for math, 1+1 will always equal 2 is problematic somehow.

There's also claims that the way it's taught is geared toward white students, which I'm not sure how that works, but even if that's true they're playing to the majority which sure would come out discriminatory but that's a no win situation unless you bring back segregation.

It's reading but, I think we may be in the market for this happening in math too.

As a teacher in Oakland, Calif., Kareem Weaver helped struggling fourth- and fifth-grade kids learn to read by using a very structured, phonics-based reading curriculum called Open Court. It worked for the students, but not so much for the teachers. “For seven years in a row, Oakland was the fastest-gaining urban district in California for reading,” recalls Weaver. “And we hated it.”

The teachers felt like curriculum robots—and pushed back. “This seems dehumanizing, this is colonizing, this is the man telling us what to do,” says Weaver, describing their response to the approach. “So we fought tooth and nail as a teacher group to throw that out.” It was replaced in 2015 by a curriculum that emphasized rich literary experiences. “Those who wanted to fight for social justice, they figured that this new progressive way of teaching reading was the way,” he says.

Now Weaver is heading up a campaign to get his old school district to reinstate many of the methods that teachers resisted so strongly: specifically, systematic and consistent instruction in phonemic awareness and phonics. “In Oakland, when you have 19% of Black kids reading—that can’t be maintained in the society,” says Weaver, who received an early and vivid lesson in the value of literacy in 1984 after his cousin got out of prison and told him the other inmates stopped harassing him when they realized he could read their mail to them. “It has been an unmitigated disaster.” In January 2021, the local branch of the NAACP filed an administrative petition with the Oakland unified school district (OUSD) to ask it to include “explicit instruction for phonemic awareness, phonics, fluency, vocabulary, and comprehension” in its curriculum.

From a different article same subject

I like that they put the numbers in this one,

But ya, they didn't like the system they had and even though they were getting year to year improvements with it they changed it because why not throw students under the bus.

Maybe they should learn from Ron McNair, but that would be the students taking the initiative and learning on their own, which might require a sea change in the community as it relates to education.

There's a reason this program has kept going since 1987, but ya colonization of students minds, there's a math one too not sure how good that is.

And there's people who just can't get some math honestly, I know I'm one of them, full spectrum dyslexia is not something I'd wish on anyone.

[xxl1zardb3ansxx]

Here you go sillies! More WOF fanfic because I forgor to post some recently!

New day, New Life

Classes started today. Each student got a schedule that was written on a yellowish piece of paper. Star found that she had Biology first. The teacher was a Leafwing that had stayed in Prryiah. 

“Good morning, I am your Biology teacher. Call me Mrs.S if you must. Today we’re starting with photosynthesis basics.” The Leafwing said. 

The classroom was wide and made of complete stone. There were several windows allowing golden rays to pass through into the classroom. Vines hung down from the ceiling, nearly touching the desks. Star could reach up and grasp one of the delicate white and pink flowers. She decided not too, because this teacher sounded like she would get mad if she did. Now normally Star would like Biology. But this teacher made it less fun. She would always yell at other students, she always sounded mad, and never helped any other students.

Next, Star had math. Only basic math so far because many dragons who were poor didn’t know very much about math yet. Although, they played a lot of ice-breaker games instead of math. The teacher was a Sandwing that was very kind. She said her name was Sunny. She was a weird golden color compared to the normal dusty yellow or tan-ish white. Her whole demeanor was just so happy and kind. She was like a little beam of sunshine that escaped from the sun, and was down here instead. There was one dragon in particular though, that kept interrupting her. It was Vermillion. He kept pointing out what was wrong with her appearance.

“Why are you so shiny?” “Why don’t you have a tail barb? Why are your eyes green?”

Eventually, the teacher decided that everyone would benefit from a hunting break outside, thus leaving us outside, where some…unconventional things could happen. Star had caught a mountain lion, and was sitting on a ledge, eating it.

“Hey hybrid!” It was Vermillion’s annoying voice. Star groaned and looked up.

“What?” Star grumbled, staring at his stupid face.

“I can’t come sit with my very best fwend?” Vermillion said, teasingly. 

“Sure, after you stop being the most annoying Skywing in history.” Star said, going back to her food.

“Awwwww, thanks.” Vermillion said, plopping in front of Star. Star groaned. “So, what’s with the little earring you wear? Are you trying to look dumb?”

“At least I look better than you do.” Star said, feeling her earring.

“Yeah, right. Anyway, why do you have it?” Vermillion siad, poking a claw at her.

“Reasons.” She said, flicking the little thing back and forth.

“Oh, sOoOo convincing. What’s the rea; reason? Hybrid?” Vermillion persisted.

“You don’t need to know.” Star said.

“Tell me, or I will personally hurt you.” Vermillion said, trying to be threatening.

“Try,” Star said, brandishing her poisonous barb. 

“Oh I’ll-”

“Go away, Vermillion.” Said Blizzard’s familiar voice.

“Ugh, not you again.” Vermillion siad..

“Go away,” Blizzard repeated.

“Fine.” Vermillion said, sighing and flying off.

“Hey.” Blizzard said, smiling at Star.

“Hi.” Star said, feeling her face get warm with blush.

“I know this is a little bit of a  weird ask but could we share that mountain lion? I haven’t been able to catch anything here.” Blizzard said, 

“Yeah of course!” Star responded. Blizzard floated down and sat next to her, and they shared the lion happily. 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~later~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The rest of Star’s day wasn’t very interesting. She had English, science, Art, Creative Writing, and then a rest period before lights out. Star was sitting and sketching on her ledge, minding her business, when of course, Vermillion had to come in.

“Oh hey, hybrid.” Vermillion's voice said. But it was…more unhappy than usual. Star tried to ignore him, and continued sketching Blizzard. (again) Vermillion climbed up to his bed and proceeded to sigh dramatically every few minutes. Finally, after realizing that it doesn;t work on literally anyone, he spoke up. “Do you know why I hate you, hybrid?”

“Don’t care.” Star said.

“Because,” Vermillion continued. “YOU got me in trouble today, and I have a 5 hour detention tomorrow.” 

“Good for you.” Star said, sarcastically. 

“You don;t care at all about me do you?” Vermillion said, obviously trying to get Star to be sorry.

“Nope.” Star said, finishing her sketch.

“Ugh, you’re so mean!” Vermillion said, flopping down on his bed again. 

“I’m so sure,” Star responded, slamming her sketchbook shut. 

“Hey guys,” Blizzard said, entering the room. She had little splatters of paint on her talons, decorating her claws with colors.

“Oh, hi Blizzard.” Star said, smiling. Blizzard climbed onto her ledge and smiled back. 

“So what are your guys' schedules?” Blizzard asked.

“Biology, Math, English, Science, Art, and Creative writing.” Star said, counting the classes on her talons.

“I’ve got Biology, Math, Science, English, Art, and then competitive flying.” Vermillion said.

“I have English, Math, Art, Science, and sculpting.” Blizzard said.

“Cool. To be honest, I don’t really like Ms. S. She’s mean.” Star chimed in.

“Yeah. She never helps anyone with assignments or anything. Or at least from what I saw today. She gave us so much homework. Speaking of which I should do.” Blizzard said, reaching into her bag and pulling out some papers. Star did the same, and got out her favorite pencil. It was purple with little stars painted on it. The homework was mostly about how plants make sugars for food and stuff and was relatively easy for Star. She couldn’t say the same for Vermillion though. He was chewing his pencil and staring at the page, clearly confused.Just then, Ant walked in, panting. Star looked up at him.

“Hey. You good? You’re panting.” Star said.

“Th-There’s a f-fight. You gotta come see it.” Ant gasped in between breaths. Star and Blizzard looked at each other, and nodded. They both hopped down from their ledges and followed Ant to the prey center. An orange Skywing and a teal Seawing were wrestling on the ground, throwing punches and clawing at each other. The Skywing had a fresh scar across his snout, and the Seawing had one on his underbelly. They were yelling at each other, insults and all. Several other dragons were chanting, ‘Fight! Fight! Fight!’ and pumping their fists. No teachers were here yet, but Star assumed there would be soon. 

“You’re just a wetnose! You can’t even breathe fire!” The Skywing shouted, throwing the Seawing off him and getting up.

“Well you’re just a stupid pebble brain! You couldn't even answer one problem in Math class!” The Seawing returned, pointing his claw at the Skywing. The Skywing blasted fire at the Seawing in response, but he ducked and rolled just in time. The crowd behind him backed up and woahed. The Seawing ran around the Skywing in wapped him with his powerful tail. It was enough to bring the Skywing down. The crowd cheered at every strike they made at each other, encouraging the two dragons' rage. Star watched but didn’t say anything. Other dragon’s minds were roaring with thoughts. ‘I hope the Seawing wins!’ ‘Go Silo!’ ‘Beat his A$$!’  Star tried to quiet them, but their thoughts were too loud. The raindrop trick only muffled them a bit.  The Skywing sent another blast of fire and got the Seawing’s leg this time. He howled in pain and toppled over. A person in the crowd shrieked and ran into view. It was a dark blue Seawing and she had several necklaces adorning her neck. She crouched down next to the Seawing and helped him up. 

“Are you okay? Can you hear me? Wave? Wave!” The other Seawing said, growing more and more panicked. Wave didn’t respond, and only groaned in pain. Just then the Math teacher, Sunny burst through the doors and ran up to Wave.

“What happened?!” She asked, also sounding panicked. 

“He got in a fight with Silo, the Skywing over there. He’s burned! He needs to get to the nurses office!” The dark blue Seawing explained. Sunny took Wave’s other arm and they carried him out of the room. A few minutes later, another dark blue Seawing entered the room. That was the Vice principal, Tsunami. She did not look happy. Silo the Skywing was laughing with his friends about kicking the Wave’s A$$ when Tsunami placed her talon on his shoulder.

“Excuse me, are you Silo?” Tsunami asked, sounding cold.

“Heh, yeah….” He trailed off when he saw Tsunami’s disapproving face.

“Then you should know what happens next.” Tsunami said, grabbing his ear and leading him into the hallway. All the dragons in there were silent as they heard Silo’s yelling in pain from Tsunami’s tight grip. Their heads were silent. Everyone was silent. They all glanced at each other for a moment before slowly and awkwardly returning to what they were doing before. Star and Blizzard looked at each other and Blizzard started laughing. Star started laughing too, replaying Silo’s distressed expression when he saw Tsunami. They both walked over to the little river that gurgled next to the wall. Star and Blizzard laid in front of the little river, and Star dipped her tail in the cool water. The two of them laughed about many things for the rest of the rest period. Eventually they went off to bed and dreamed of what adventures could come next in their new lives.

[antvnger]

Do you have any advice for someone who feels stupid? I can barely do basic math and I'm an adult. I know I'm smart in my own ways, but I still feel ashamed when I can't do basic things like math or easy science or other things. Meanwhile, it's so easy for other people and when I'm with my friends, I can't help but feel dumb sometimes. They'll talk about things and I can barely keep up. I just nod along to what they say. It's embarrassing.

Okay, I couldn't let this one wait until later. I gotta answer this one now.

First of all, Anon, I'm sorry you feel that way, but believe me, you're not dumb just because you struggle with math and science. Not everybody is wired to understand that stuff so easily, and that's okay. It doesn't devalue you because you struggle.

My sister loves loves loves history. You give her a random year and she could probably spit off 5 things that happened that year, and a lot of them I have no idea what they are. She and my granddad would talk all the time about history, and I'd just sit there sometimes going I have no idea what they're talking about. Like one time they talked for three hours about the ramifications of the Cold War, and I had like nothing to offer to that conversation, and I felt super bored and left out even though I'm a pretty smart guy. History just isn't my thing.

You've got some options here though, Anon, as far as advice goes.

If you want to have a better grasp of what they're talking about, then find out some things they like to talk about and things they talk about often and do a quick Google search about it and learn a little bit about what they're talking about.

If you wanna get better at basic math, practice some in your spare time. Another Google search can give you some basic problems to practice.

If there's a friend in your group you feel comfortable talking about this stuff with, do it. If they really are your friends and care about you, they'll either help you to understand better or they'll be more careful about including you in a topic you all can freely discuss.

Maybe you could ask your friends questions when they talk about those things? I know it'll be awkward and embarrassing at first, but if you ask the right kind of "why" questions, you'll be enhancing the conversation and offering something, and the answers may surprise you.

Or have the group discuss something you excel in and teach them a thing or two. I have every confidence you're pretty damn smart, so find something you like talking about and teach them something new.

Nothing is going to change unless you make some kind of move to change it, Anon. I definitely understand where you're coming from, and the best thing(s) you can do is learn a couple of things along the way and be honest with your friends. If they're your friends, they'll be supportive and helpful.

I don't know if this is what you're looking for, Anon, but it's what I've got. Good luck! You know where to find me if you need more help.

[lifeinapic]

A complete overview of the most essential components of data science and how to master them. If you are reading this article, it means that you are hoping to become a data scientist and you just don’t know where to start. This article will do our best to layout the most essential areas you need to look at to start diving deep into data science. We will also give you some of the best learning resources to do so. 1. Essential Theoretical Knowledge of Statistics and Calculus I think you kind of expected this to be the first one, but before you just skip to the other section or just another article, let me tell you why it needs to be the first point mentioned. An okay data scientist learns how to use a bunch of tools like PowerBI, Scikitlearn, etc. This will be fine for building baseline models, but you will soon find out that it’s not enough and you need to improve your model. This brings us to reading ML research papers. And you have to trust me on this, you will not understand most ML papers if you don’t understand essential statistics, and if you don’t understand most of the papers, you probably won’t be able to implement them and improve them, which is a big issue. I remember struggling with understanding ML papers at university, it used to take me a few days if not weeks to fully grasp them. However, all this changed when I spent a few weeks learning the fundamentals of statistics and calculus. Now, I can easily digest those papers in an hour or 2. If you haven’t already done so, you will not believe how much papers rely on those foundations. One very important point that I want to stress here is that I am not asking you to be an expert in these foundations. This is what most people struggled with in high school—being good enough at math and statistics to get through an exam. You don’t need this here. You just need to understand the foundations to digest the research papers. Understanding them is much easier than actually being good at solving theoretical math problems (which is a good skill to have, but a hard one to acquire). Khan Academy is an excellent place to start. You can start by checking out their algebra course here and their stats one here. 2. Essential Programming Basics You have now got your math and stats knowledge, now it’s time to move into something more practical and hands-on. A lot of people get into data science from non-technical backgrounds (which is actually quite impressive). Believe me when I tell you this, the worst way to learn programming is to keep watching courses endlessly. I know there are tons of articles and videos about learning programming and I don’t want this to just be another duplicate. I do however want to give you the most important tips that will help you save a lot of time. When I was learning programming basics I used to watch tons of tutorials, which was useful. But, a lot of people (including me) think that watching more tutorials equals improvement in our skills as programmers, it does not! Tutorials only tell you how to do something. But you never learn until you actually do it yourself. Although this seems straightforward and obvious, it needs to be said: it’s actually harder to code than just seeing other people code. So, simply put, here is the next tip: For every few tutorials you watch or articles you read, make sure you implement at least one of them. If you aren’t doing this, you are wasting your time. If you don’t believe me, feel free to check out articles by TraversyMedia and FreeCodeCamp that are going to affirm this idea. A lot of programmers realize this, but it’s usually a bit later than they should have. I am not going to point you to a course. Instead, I am going to point you to one of the best places to improve your programming skills and, more importantly, improve your problem-solving skills. I wish I had received this when I was at university because programming languages change all the time, problem-solving skills don’t. And when you actually start

applying for jobs, a decent interviewer will be examining your problem-solving skills, not your syntax accuracy. Start by integrating at least 2-3 hours every week of easy HackerRank or LeetCode into your schedule, if you are struggling. Watch some tutorials, but start with approaching the problems first (not the other way around). 3. Experience, experience, experience Photo  At this point, you know your theory, you have good programming and problem-solving skills and you are ready to start gaining data science skills. The best way to do this is to start developing end-to-end data science projects. From my experience, the best projects must have at least a few of these components: Data gathering, filtering, and engineering: This can be as simple as an online search or as complex as building a web scraping server that aggregates certain websites and saves the required data into a database. This is actually the most significant stage because if you don't have data, then you don't have a data science project! This is actually the reason why a lot of AI startups fail. Once I realized this, it was quite an eye-opener for me, even though it's kind of obvious!“Model training is only the tip of the iceberg. What most users and AI/ML companies overlook is the massive hidden cost of acquiring appropriate datasets and cleaning, storing, aggregating, labeling, and building reliable data flow and an infrastructure pipeline.”—The Single Biggest Reason Why AI/ML Companies Fail to Scale? Model Training (this is too obvious to explain) Gathering metrics & exploring model interpretability: One of the biggest mistakes that I made in my first few ML projects was not giving this point due credit. I was extremely eager to learn and so I kept jumping from model to model too quickly. Don’t do this. When you train a model, fully evaluate it, explore its hyperparameters, check out interpretability techniques and, most importantly, figure out why it works well and why it doesn’t.One of the best places to learn these concepts (except data gathering) is on Kaggle, I can’t stress enough how much you will learn from doing a few Kaggle competitions. Model Deployment & Data Storage This is a very important step that a lot of people skip. You will need basic web development skills at this point. You don’t have to build a complete app around your model, but at least try to deploy it to a Heroku web app. You will learn so much. A central piece of your data science project is selecting the correct data storage framework. Keep in mind that your production model will be consistently using and updating this data. If you don’t choose the correct data storage framework, your whole app will face quality and performance issues. One of the fastest-growing storage frameworks is data lakes. “A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics — from dashboards and visualizations to big data processing, real-time analytics, and machine learning—to guide better decisions.” — Amazon Data lakes are being widely used by top companies currently to manage the insane amount of data that is being generated. If you are interested, I suggest checking out this talk by Raji Easwaran, a manager at Microsoft Azure about the “Lessons Learned from Operating an Exabyte Scale Data Lake at Microsoft.” There are also frameworks that operate on data lakes that ease the consumption of data by machine learning models. I used to think that adding these layers is not that effective, but separating these operations into different layers saves you the time you will have to debug your models in the long run. This is actually the backbone of most high-quality web applications/software projects. Final Thoughts The biggest misconception I had going into data science was that it’s all about model fitting and data engineering.

Although that is, of course, an important part, it’s not the most difficult and significant one. There are multiple factors (as discussed above) that are in play when getting into data science and developing high-quality ML projects.

[fromdevcom]

A complete overview of the most essential components of data science and how to master them. If you are reading this article, it means that you are hoping to become a data scientist and you just don’t know where to start. This article will do our best to layout the most essential areas you need to look at to start diving deep into data science. We will also give you some of the best learning resources to do so. 1. Essential Theoretical Knowledge of Statistics and Calculus I think you kind of expected this to be the first one, but before you just skip to the other section or just another article, let me tell you why it needs to be the first point mentioned. An okay data scientist learns how to use a bunch of tools like PowerBI, Scikitlearn, etc. This will be fine for building baseline models, but you will soon find out that it’s not enough and you need to improve your model. This brings us to reading ML research papers. And you have to trust me on this, you will not understand most ML papers if you don’t understand essential statistics, and if you don’t understand most of the papers, you probably won’t be able to implement them and improve them, which is a big issue. I remember struggling with understanding ML papers at university, it used to take me a few days if not weeks to fully grasp them. However, all this changed when I spent a few weeks learning the fundamentals of statistics and calculus. Now, I can easily digest those papers in an hour or 2. If you haven’t already done so, you will not believe how much papers rely on those foundations. One very important point that I want to stress here is that I am not asking you to be an expert in these foundations. This is what most people struggled with in high school—being good enough at math and statistics to get through an exam. You don’t need this here. You just need to understand the foundations to digest the research papers. Understanding them is much easier than actually being good at solving theoretical math problems (which is a good skill to have, but a hard one to acquire). Khan Academy is an excellent place to start. You can start by checking out their algebra course here and their stats one here. 2. Essential Programming Basics You have now got your math and stats knowledge, now it’s time to move into something more practical and hands-on. A lot of people get into data science from non-technical backgrounds (which is actually quite impressive). Believe me when I tell you this, the worst way to learn programming is to keep watching courses endlessly. I know there are tons of articles and videos about learning programming and I don’t want this to just be another duplicate. I do however want to give you the most important tips that will help you save a lot of time. When I was learning programming basics I used to watch tons of tutorials, which was useful. But, a lot of people (including me) think that watching more tutorials equals improvement in our skills as programmers, it does not! Tutorials only tell you how to do something. But you never learn until you actually do it yourself. Although this seems straightforward and obvious, it needs to be said: it’s actually harder to code than just seeing other people code. So, simply put, here is the next tip: For every few tutorials you watch or articles you read, make sure you implement at least one of them. If you aren’t doing this, you are wasting your time. If you don’t believe me, feel free to check out articles by TraversyMedia and FreeCodeCamp that are going to affirm this idea. A lot of programmers realize this, but it’s usually a bit later than they should have. I am not going to point you to a course. Instead, I am going to point you to one of the best places to improve your programming skills and, more importantly, improve your problem-solving skills. I wish I had received this when I was at university because programming languages change all the time, problem-solving skills don’t. And when you actually start

applying for jobs, a decent interviewer will be examining your problem-solving skills, not your syntax accuracy. Start by integrating at least 2-3 hours every week of easy HackerRank or LeetCode into your schedule, if you are struggling. Watch some tutorials, but start with approaching the problems first (not the other way around). 3. Experience, experience, experience Photo  At this point, you know your theory, you have good programming and problem-solving skills and you are ready to start gaining data science skills. The best way to do this is to start developing end-to-end data science projects. From my experience, the best projects must have at least a few of these components: Data gathering, filtering, and engineering: This can be as simple as an online search or as complex as building a web scraping server that aggregates certain websites and saves the required data into a database. This is actually the most significant stage because if you don't have data, then you don't have a data science project! This is actually the reason why a lot of AI startups fail. Once I realized this, it was quite an eye-opener for me, even though it's kind of obvious!“Model training is only the tip of the iceberg. What most users and AI/ML companies overlook is the massive hidden cost of acquiring appropriate datasets and cleaning, storing, aggregating, labeling, and building reliable data flow and an infrastructure pipeline.”—The Single Biggest Reason Why AI/ML Companies Fail to Scale? Model Training (this is too obvious to explain) Gathering metrics & exploring model interpretability: One of the biggest mistakes that I made in my first few ML projects was not giving this point due credit. I was extremely eager to learn and so I kept jumping from model to model too quickly. Don’t do this. When you train a model, fully evaluate it, explore its hyperparameters, check out interpretability techniques and, most importantly, figure out why it works well and why it doesn’t.One of the best places to learn these concepts (except data gathering) is on Kaggle, I can’t stress enough how much you will learn from doing a few Kaggle competitions. Model Deployment & Data Storage This is a very important step that a lot of people skip. You will need basic web development skills at this point. You don’t have to build a complete app around your model, but at least try to deploy it to a Heroku web app. You will learn so much. A central piece of your data science project is selecting the correct data storage framework. Keep in mind that your production model will be consistently using and updating this data. If you don’t choose the correct data storage framework, your whole app will face quality and performance issues. One of the fastest-growing storage frameworks is data lakes. “A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data, and run different types of analytics — from dashboards and visualizations to big data processing, real-time analytics, and machine learning—to guide better decisions.” — Amazon Data lakes are being widely used by top companies currently to manage the insane amount of data that is being generated. If you are interested, I suggest checking out this talk by Raji Easwaran, a manager at Microsoft Azure about the “Lessons Learned from Operating an Exabyte Scale Data Lake at Microsoft.” There are also frameworks that operate on data lakes that ease the consumption of data by machine learning models. I used to think that adding these layers is not that effective, but separating these operations into different layers saves you the time you will have to debug your models in the long run. This is actually the backbone of most high-quality web applications/software projects. Final Thoughts The biggest misconception I had going into data science was that it’s all about model fitting and data engineering.

Although that is, of course, an important part, it’s not the most difficult and significant one. There are multiple factors (as discussed above) that are in play when getting into data science and developing high-quality ML projects.

[duskwingmoth]

One of the key problems you can trace a lot of the United States' issues to is how the compulsory education system is so heavily geared to the industrialist's philosophy of teaching -- you are there to learn how to follow multiple different sets of rules simultaneously and to become proficient in doing monotonous busywork. "Book reports" are not expected to be any more than a plot summary; math worksheets don't just expect a specific answer, they expect you to follow one particular process and to self-report if you didn't; sciences are inviolable truths set in stone before you were born, history is over and only exists insofar as it glorifies the state, etc.

This is not a time or place in any way resembling the flowery image of junior scholars being patiently cultivated by kindly sages, this is a Workplace where children are LARPing as employees under their supervisor and pit boss, The Teacher. This is horrendous for building thoughtful, curious adults, but it's perfect for creating an unquestioning labor force that will bend over backwards to accrue capital for the capitalist class. I'm sure this comes as no surprise to anyone who has read any socialist theory. Humorously enough, it's Anticapitalism 101. But it's such a fundamental issue that it bears repeating.

This is why, when students do as is now expected and push themselves into material debt while hammering out any last lingering "flaws" as Workers, a.k.a., going to college, they run afoul of plagiarism policies basically immediately. Even accounting for industrialist infiltration into the concept, the expectation that you have gone to college before properly entering the workforce is quite recent, and the capitalist machine doesn't yet truly account for the fact that College As A Tradition does not gel with industrialist philosophy. If you simply port over your behavior from high school to college, it doesn't actually work; professors assign far too much work for a single class for you to have a full daily schedule like you used to, and what is expected of a student's essays is incongruously different from before. Colleges, universities, they are built on centuries -- millenniums even -- of people thinking way too much and way too hard about stuff all the time and disagreeing with each other incessantly. That is what collegiate tradition expects of students, and it is functionally impossible when you bring an industrial-trained mindset to the environment.

It's also how you get whole hordes of people willing to vote against their best interest and arguing with professors on Twitter about basic facts that they don't even seem to have a working grasp on. As far as the layman knows, as far as the layman is taught, if somebody has a different understanding of the world than the one you first encountered, then it is your moral imperative to become violently corrective. These pesky Certified Smart Boys are always getting in the way of the machine, you must throw them out of the way so production can resume.

It is not impossible to combat this, but it is frustratingly difficult if you're dealing with grown adults. I can, for example, cite material conditions and human rights until I'm blue in the face to my father and my grandparents, beg them to question why the news would frame one group of people as ontologically evil when their own experiences say otherwise, and I will get nowhere, at least in the moment. It is ingrained into the United States populace to hold one holistic American truth above all else, and to become instantly obstinate when presented with any segment of reality that even slightly contradicts it. To shout down all dissenters and continue emboldened and hardened as crusaders marching into the darkness, even if they must create that darkness themselves to maintain the illusion.

Sinister as it sounds, this is not a coordinated effort by a super secret all-powerful cabal at the heart of America; frankly if it were, it'd be a lot easier to resolve. Capital simply desires brainless labor, and it is convenient for the country's leaders, be they True Blue Capitalists or not, to let its individualist apostles run roughshod from sea to shining sea. And after 400 some-odd years, it's so heavily embedded into the systems that fighting against it feels insurmountable.

But education never stopped attracting teachers who want to truly teach, and this busted education system with stilted values never stopped spitting out skeptical adults. Capitalism certainly has been successful at self-propagating for a good long while, but so was the divine right of kings, and so has the flu. Today there are fewer functioning monarchies left in the world than there are fingers on both my hands, and as the last few years have shown, not even the flu is immortal; if we can kill off one strain, we can kill them all.

But what do I know? I'm a broke-ass tranny in a frigid garage.

[astros-turf]

So, just as an aside based on my last post that I probably will delete if it continues to go off the rails... If you think like this:

Then please consider a few things:

People come from a variety of educational backgrounds, and some people (like myself) were never taught *how* to research.

"Common knowledge" to you may not be common knowledge to others.

People who are actively asking for help in finding out *how* things work shouldn't be berated for simply asking questions.

If you don't think where you are seeing a question being asked is the right place, you are free to redirect them to the correct place to ask that question if you know of somewhere better, but insulting people doesn't help people learn.

I will say that again. INSULTING PEOPLE DOES NOT HELP THEM LEARN.

Plenty of very smart people are on tumblr, and while we may all be losers lmao, I have learned a lot of very important things on here from people that enjoy sharing their knowledge and sourcing their information. (Those are the kinda people I was looking for on my post because I am struggling to find them via tumblrs broken AF search lmao)

If the lovely person that commented that thinking I'm some idiot is reading this, my dear, I *have* researched the candidates. Im best friends with vote411.org and progressivevotersguide.com and I do my research and vote according to what I think is best at the time. However, that was not the point of the post.

The point of the post is that I am trying to find out: "is the correct option to vote for still Biden even tho I fucking hate how he's handling shit? What else can I do as a voter to help make the right changes? Is there any more I can do except for just voting for people who have similar values to me when an election comes up? Can I actually trust their campaign or is there a better resource out there?"

Because personally? I was homeschooled by abusive conservative Christians with a heavily bible influenced homeschool curriculum that my parents barely helped me with. I taught myself basically everything I know from researching shit myself and just googling stuff until it works. I still am not very good at math, my concept of sciences are fucked. I can read very well, but the comprehension of certain things still evades me just because I was not given proper building blocks to learn from and have no idea how to find beginner information for so many things.

I have tried many times to research how the presidental election system works, even wrote a 10 page paper on it in high school because I knew I didn't understand it and wanted to devote my time to learning it, but even then it was "corrected" by my parents that *also* don't know how the system works so they basically took whatever my 15 year old self wrote as fact so long as my punctuation was okay. I sorta can grasp it, but in a situation like our current one, what I am curious about is who the hell people like me are going to vote for. Because the way the electoral college works means we basically only have two options, even though on paper we are supposed to have numerous options.

Because my brain feels like there has to be a secret third option that I just don't know about because I'm not googling the right terms because I don't even know what to Google. And replies like the one I screenshot and shared above are EXACTLY the reason why most people don't ask questions. So I will say again,

If you want people to be informed on things you're already informed on, INSULTING PEOPLE DOES NOT MAKE THEM LEARN.

[studyari]

march update

it’s officially midterms time. i thought i would post an update becuase this semester has took SO much out of me. i finished my internship funded by the national science foundation in january, can’t say i made too many ties there since i hardly saw my superiors. BUT i did get to know the metrology lab pretty well and even got their machine working. going into it i did NOT imagine i could accomplish that but i felt so good getting it working! i even made a little overturn training manual and gave it over to them. 

okay so starting this semester i am in my gateway courses. so a bunch of physics courses at one time ugh plus i was taking differential and linear algebra. i got so stressed out with the workload that i had a dream where i crashed into a forest and the airbags went off lol. that same morning i dropped my lab and differential equations. it was just WAYYY too much for me. 

i’m still a full time student so it was clear i was doing too much. hmm okay so i’m in my gateway courses so mathematical physics, classical mechanics, and modern physics. i knew i was going to struggle with classical mechanics because kinematics alone was hard for me to grasp and it’s basically dynamics. i didn’t apply as an engineering major literally because i didn’t want to take dynamics LOL i struggled in statics. Of course im taking the same class just named something else and a lot harder T_T. i also wanted to get some undergrad research experience and work in an electronic materials lab but yeah i’m just tooooo busy it was a good idea though lmao.

okay but honestly mechanics is the hardest class for me, modern physics is my most interesting class, and mathematical isn’t too bad even though i suck at math because our teacher grades us mostly on completion and work shown. the hardest thing about this semester is just the schedule itself. so we have to take all three at the same time for some reason or you wouldn’t be able to register for the class ummm overkill much?! and the schedule is from 10am - 7:30 pm ughhhh. I have to take the bus there so add on a couple hours and then i have to walk to class. ohhh i miss the online/hybrid classes so much lol. by the time i’m in my last class i am literally asleep. don’t worry ive started drinking coffee.

looking on the brighter sides of things i’m being a lot more involved in campus and i’m really liking getting to know my classmates! i am so antisocial and awkward so im surprised. i’ve been going to the women in stem meetings, society of astronomy, nsbe coding workshops, ieee circuits workshops, career fairs, and boba socials just for funsies. i realize school isnt all about good grades and killing yourself for that A. i’ve even had more time to spend with my friends (it is so true what they say about making time not having it lol). almost every other weekend we see each other and have little celebrations, watch movies, have study dates, go to the park, get coffee/boba, go shopping etc. and facetiming my friends back in arizona as well! one of my club advisors told me its actually the b and c students that do better in the job market and isnt that freaking crazy! ever since then ive been reminding myself that being perfect and getting a’s isnt always worth it. i have other life to live too and people wont necessarily fault me for that.

okay as for my grades though i have been bombing every single quiz like a 50 or LESS LMAO. that’s with me studying at least a whole day before. however as of now i have passed every exam so far. so my current grades right now are 90% in modern physics, 98% mathematical physics, 100% classical mechanics (but a lot f the grades arent in yet), and a 99% in linear algebra. See and thats me not killing myself this semester so im super happy i decided to not overdo it, it really doesnt make as much as a difference as i thought lmao clearly.

looking forward to spring break! i was in therapy/behavioral health all last year trying to tackle my anxiety and i would say its been helping. its all about making a choice. i’m also in physical therapy now for the next couple of months and then once summer starts i’ll start going back to therapy again. this post might seem positive but this semester i have never felt more unmotivated or stupid. some days i feel like i cant do this and that everyone else around me is so much more capable. but i know as soon as i give into those thoughts that i’ll end up giving up and i don't want to give up. my boyfriend also has been feeling the same way. 

i also lost my wallet this week soooo all my documentation and identification is gone ugh. i had a full on breakdown but am getting that figured out. i’m going to an applications of black holes seminar tomorrow and i am super excited about that. took my linear algebra exam today too, (WHY IS THAT CLASS SO HARD BTW). i havent yet applied but theres this summer research opportunity happening at the university of toronto (dunlap institute of physics and astrophysics) and i think im going to apply! i really want to travel this year and experience something new!

[cheeriecherrymain]

hey! for the headcannons you're doing what ab viktor with a reader who isn't exactly that smart? like she has trouble grasping subjects like science and math but is good at art or something. thank you💛

Whoever said that not knowing math and/or science makes you dumb is a butthead and a liar - intelligence comes in so many forms, and all of them are important and worthy of praise.

Viktor x Reader (SFW)

-You’re probably a friend of Jayce’s, and that’s how you initially meet Viktor.

-You come to visit them at the lab one day, bringing a box of miscellaneous snacks and a thermos of coffee. Viktor initially believes that the snacks are probably just for Jayce, because why would you bring something for someone you didn’t know?

-But then you introduce yourself to him as well, and happily offer your trove.

-He’s not exactly off-put, but he definitely thinks that you’re just being polite because Jayce is there.

-You start coming around more frequently after that, dropping by on your time off to chatter to both of them. It’s a little hard to get work done when you’re around, since you’re so eager to talk their ears off, but Viktor…doesn’t really mind.

-He’s not particularly social, but part of that is probably due to how he grew up, and where he currently resides - most people either never give him the chance, or are too pretentious to interest him. So he keeps to himself.

-But you’re different. You’re kind, you’re funny, and more than that, you listen to what he’s saying. You don’t really understand half of what he goes on about, but you’re engaged nonetheless. You ask questions, and you pay attention.

-And it’s not only when he talks about his work.

-Within a week of knowing him, you start bringing pastries that he likes, some of which Jayce will turn his nose up at - you’d heard him when he’d offhandedly mentioned liking sweetmilk, and now you bring a little bit of that in a thermos beside the usual coffee.

-So when you inevitably turn up on one of the days that only Viktor is in the lab, he expects it to be a pleasant afternoon. Since Jayce is away, he figures he can bounce ideas off of you.

-It doesn’t go as planned.

-The first time he asks for your opinion, you fumble a little bit, and end up suggesting something completely absurd - it would never work, he knew, and he knew that Jayce would know that as well.

-Maybe you’re just having an off day.

-But a while later when he asks for your input again, you stutter a bit, sigh, and hit him with an I don’t know.

-He’s not upset so much as he is confused. You’d been so interested in the things he talked to you about, and you’d asked so many questions - how could you not know the basic mechanics of what he was working on.

-You grow quiet after that, and the silence between the both of you isn’t particularly comfortable. He can hear you fidgeting elsewhere in the room, as well as the scratch and scribble of your pencil on paper.

-He tries to ignore the tension.

-He fails.

-But right as he turns to you to say something, Jayce strides into the room, tired and agitated and just about ready to pace a hole in the floor.

- “You two are surprisingly quiet,” he says, sitting down to start working. It’s an offhanded comment, something meant to be light and joking, but it stings Viktor nonetheless.

-What stings him even more is your reply.

- “You know how I am, Jayce,” your tone is light and airy, “I’m not smart like either of you - if I don’t shut up, I’ll say something stupid, and that’s when stuff blows up.”

-You’re clearly trying to be funny about it, but he can hear the way your voice clips at the end; you’re sad.

-You take off shortly after that, leaving behind the box of snacks, and taking the empty drink containers with you.

-Viktor doesn’t see you for almost two weeks after that.

-He asks about you, but Jayce only shrugs.

-They’re probably just busy, he says. Art school is tedious, I guess.

-It hits him then. In all the time he’d talked to you, all the conversations you’d had, laughter you’d shared, and problems he’d worked through…he’d never asked about you. You’d diligently hung off his every word, and asked questions, and shown an interest, and he…

-He hadn’t done the same.

-And when you hadn’t been able to offer him more than an ear to listen, you’d clammed up. You’d shut down, and promptly thought yourself inadequate.

-With guilt weighing on him, he quietly asks Jayce where he could find you.

—

-He finds you in one of the empty classrooms in the academy. A space that had been shut down for a while, with the desks and chairs stacked high against the far wall - save for one, that you had carefully lifted down and set up near the window.

-You’re hunched forward and incredibly focused on the easel in front of you, a palette in hand and what looks like four dozen bottles of paint on the table next to you.

-He can’t see what you’re working on from where he stands in the doorway, but whatever it is has your attention so rapt that you don’t notice him.

-It gives him a moment to collect himself.

-It also gives him a moment to stare.

-A moment to observe you in your flow state, a moment to find the little crease of concentration between your brows, a moment to watch as your gaze flicks across your canvas.

-Your passion and dedication almost looks like an art in its own right.

-And then the door creaks beside him, and you tear your eyes away from your work. At first you look like you’re about to get a scolding, but once you realize it’s him, your expression morphs into surprise.

- “Viktor,” you say softly, the barest hint of a smile tugging at the corners of your mouth. “I didn’t- what are you doing here?”

-You set your paintbrush down and swivel in your chair so you can face him, beckoning him further into the room.

-As he wanders over to your side, he explains that he was looking for you. “Jayce told me where I could find you,” he says, coming to a stop a couple feet from you. “I…wanted to talk about the last time we spoke.”

-All at once, your face falls, though it’s obvious you try to hide it. “Ah, yeah,” you mumble. “Sorry about that, by the way. I know you needed someone to bounce ideas off of, butI’m…not really the best candidate for that.”

- “I actually wanted to apologize,” he admits, much to your surprise. “It wasn’t my intention to make you feel as though you are…less…just because you might not understand what I do.”

-You shrug, pretending to be unbothered. “It’s fine,” you tell him. “I’m used to Jayce going on about his inventions, and I know I’ll never be smart enough to understand. I wish I was. I wish I could help both of you - you work so hard and put up with so much shit…”

-You sigh. “Doesn’t matter, though. There’s no sense in wishing I could be something I’m not. So you don’t need to worry-”

-Without thinking, Viktor reaches out to you, and sets a hand on your shoulder, giving a light squeeze.

- “You’re not stupid,” he says firmly, fixing you with an argumentative frown. “So you do not know how machines work - most people do not-”

- “Yeah, but most people can grasp the concept after they learn about it,” you cut him off, grumbling. “I’ve been listening to Jayce for years, Viktor, and I- I still have no idea what anything is! I have to count on my fingers when I do math, and I can’t look at blueprints and figure out what the final product is! I’m just not-”

- “If you say you are not smart one more time,” he threatens, though there’s no malice in his tone.

-You droop.

-Viktor turns to your painting.

- “Do you not see what you have created?” he asks, nodding towards your work. “How many people could make something like this?”

- “It’s not even finished-”

- “And yet I could not tell.” He sighs softly, his gaze dropping to the floor for a couple moments, before flicking back up to you. “I couldn’t tell you the first thing about colours, or structure, or perspective…and yet you have such a grasp over it that you’re able to make something like this purely from memory.”

- “You’re brilliant,” he tells you, “and anyone who says otherwise is the idiot.”

-You do your best to hide a sniffle, laughing quietly at yourself when you wipe the budding tears from your eyes. But he can see that you’re happy, and that your confidence and spirit have brightened.

- “Thank you, Viktor,” you say with a smile, and he lets his hand fall from your shoulder.

- “Will you start visiting the lab again, now?” he wonders, his heart fluttering when you nod.

[chemblrish]

You are literally living my ideal life! (I dream of getting a degree in and working in chemistry) What are the drawbacks/ highlights of your work in university?

Hello!

I'm so happy to hear you want to major in chemistry :) It's a beautiful, fascinating science and the superior one at that. Keep in mind this is my experience as a first year student (and if any older chemistry students want to chime in, please do!)

Personally, I'm very much in love with my faculty, so it's hard to be totally objective snhfks but what I really enjoy about my studies is how I get to learn all the important concepts in depth. Everything I once learnt on a simplified surface level now I get to explore with more nuance: things like calculating pH, precipitation, solubility, it's all a lot more complex than what they can (understandably) tell you in school and it's really satisfying to be able to dig into that.

Speaking of calculations, I liked math a lot back in hs and I was good enough with it, but definitely not math student level - and I feel like chemistry is perfect for me, bc I get to do math nearly everyday, but it's not the terrifying kind that physicists deal with that hard (unless you choose theoretical chemistry I guess, but that's definitely not my sort of thing).

Then you have the practicals and it's so satisfying that you get to do everything yourself! First semester we mostly worked in groups bc we were babies, but now we work by ourselves and it's so cool to see how your manual skills improve, how much more comfortable you become working in lab, how what you learnt in lectures and what you learnt in practice come together.

I've always been very curious about the natural world and now I'm studying it with people who love what they do, who are extremely knowledgeable and intelligent, who want me to learn and succeed. Also, our puns are the best 😁

Now, for the drawbacks...

Back to seriousness though: I'm not sure if any of the cons I'm about to list are chemistry specific, I think being in uni is just Like That™️, but I'd say the failures hurt like crazy. Sometimes I study so hard and do my best but still get a low grade. Chemistry is a demanding major. And the thing is, everyone around is also working so hard, and it looks like you're surrounded by absolutely brilliant people (I know I am!), so your insecurities may really flare up.

Consistency and discipline are absolutely necessary - once you fall behind, it can be very difficult to catch up and I guess you can see how that gets stressful at times. Similarly, you need to be mindful about what you study - you come across a difficult topic, decide to skip it to save some precious time, and I can promise you that each one of those without a fail will come up sooner or later like the hiccups. Basics first. You need to grasp them well and not shy away from things you don't instantly understand.

Each semester is a bit different, but my second one in particular has been exhausting in terms of the number of classes I had to take. After 7h (and a million reactions...) in lab I still had to go to another class and wrestle with Excel, and the only reason I was able to come home afterwards and do Nothing™️ was because I'd spent the entire previous weekend studying.

Every major has its downsides though. I used to study something else (biotechnology if you're curious) and I hated it, so I think I'm a lot more aware of what I like and dislike now, what I can endure, and what I care about - and I've found out chemistry is something I care about deeply, something I can picture myself choosing over and over again if given the chance. That means the pros outweigh the cons for me.

I hope this answers your question and didn't bore you to death 😅

[lets-try-some-writing]

Optimus & Bumblebee Headcannon (part 3)

Alright, this is part of Bee's sparklinghood is going to be split up since I just had so many ideas. The part below is all about Bee's mental growth and the next one will focus on his physical growth (and have a lot more Optimus fluff). Also Optimus plays a lesser role in this part but whatever, cuteness is cuteness.

Sparklinghood (2nd Edition)

After a few months of living with the Autobots, Bee starts to show signs of growth.

The mental changes show themselves first, mainly in Bee's comprehension and observational ability.

Bee begins to notice the increased stress among the Autobots as the war rages on, most notably in Optimus, who returns later and later from the battlefield always covered in wounds that only seem to become increasingly severe.

Of course Bee doesn't understand everything and only knows that his Caretaker is struggling because of the big bad evil Decepticons.

So he decides to do what he can to help in the only way he knows how based on what he has observed.

Bee has seen how much Optimus enjoys reading, he personally doesn't understand the appeal since he prefers playing and exploring, but its what Optimus likes, so Bee puts aside his own preferences.

Opting to keep his little plan a secret from his secondary Caretakers so that he can surprise Optimus, Bee begins spending his free time in the Autobot database, attempting to read the files.

He tries to study as hard as he can but his efforts end up being fruitless for the most part, the glyphs are just too much for him to grasp without a reference.

Despite the vanity of his efforts he continues to soldier on, determined to learn how to read so he can surprise Optimus.

Perceptor ends up going to the database a few times to collect some files and catches Bee huddled up in the corner attempting to read every time.

At first he ignores the newsparks obvious struggle and focuses on his work, firmly believing the Autobots require his scientific knowledge first and foremost.

However after he comes to the database and finds Bee committing himself to reading a file that is upside down, he drops whatever reservations he has and takes Bee under his tutelage.

Bee is, of course, ecstatic to have a teacher, but still makes Perceptor promise to keep his studies a secret in order to not spoil the surprise.

Perceptor has no qualms against this and only wants to make sure the last of the newsparks doesn't end up a fool who can't even read.

When Bee isn't with his Caretakers and Perceptor has time he will sit Bee down and help him decipher the rather complex Cybertronian glyphs.

Perceptor, despite claiming he isn't a good teacher and is better off working on his research, quickly gets very swept up into his role as Bee's tutor and swiftly incorporates other subjects into Bee's studies as well.

Before either realizes it Bee is being taught the basics of pretty much everything Perceptor has knowledge in, leading the newspark to unknowingly learn at least five different written languages, math and science meant for mechs at least three times his age, and a lot more about space bridges then should strictly be necessary.

Wheeljack ends up noticing Bee's studies with Perceptor and gets himself involved by teaching him all about explosions, battle strategy, and a little engineering.

It doesn't end there either, no, the ranks of Bee's teachers eventually expand to include others.

First Aid gets roped in after he is called in place of Ratchet (at Bee's request that his studies continue to remain secret) to deal with an accidental explosion caused by Wheeljack's lesson on grenades.

For the safety of every bot involved he ends up teaching Bee about basic medicine and Cybertronain anatomy.

Ironhide barges his way into a teaching position after he finds out Wheeljack is teaching Bee unorthodox combat methods.

He is determined to keep Bee from ending up a wild Wrecker and teaches him the proper way to fight, with blasters and blades.

Ultra Magnus comes by every now and then to give Bee a lesson in proper speech and leadership, his logic being that Optimus's mechling and the possible future leader of the Autobots needs a proper education in matter of administration.

He certainly isn't doing it because Bee is cute and he hardly ever sees the sparkling. Why would you think that?

The list of teachers continues to expand until at least half of Autobot command is involved in some way and bound to a vow of secrecy at Bee's request.

After another few months the great moment arrives, and Bee approaches a very weary Optimus in his berthroom with a dataslate in his small servos.

All his teachers huddle behind the door, audio receptors strained to hear what Optimus will do. Even Ultra Magnus hangs around the hallway doing his best to look casual while not so subtly listening in with the others.

Optimus is no fool and knows something is going on, but as it seems to be the work of his sparkling he says nothing about the crowd outside his door as Bee climbs onto the berth.

Bee settles himself next to Optimus and the Prime picks up the dataslate in Bee's servos expecting the newspark to request that he read it to him. However to his surprise Bee takes the dataslate back and tells Optimus to lay down.

Confused but compliant, Optimus lays down on his berth. Bee then proceeds to sit on the edge of the berth like Optimus does when he read stories and begins his own attempt at reading the tale.

Optimus is downright dumbfounded when Bee reads the story with near perfect pronunciation for one so young, he tries to get up and say something but Bee just presses him back down and tells him to rest.

For over an hour Optimus remains still and lets Bee read to him, he isn't actually listening to the story, his focus is on Bee and Bee alone.

Optimus feels immense pride swell in his chassis as Bee continues to read, while he wishes he could have been the one to teach Bee he is still incredibly impressed and happy for his sparkling nonetheless.

When Bee finishes the story he leans over and presses a kiss to Optimus's helm, much to the Prime's bewilderment, and proceeds to pull out a thermoplastic blanket and carefully tuck Optimus in.

Then Bee gives him a hug, pats his helm affectionately, and turns off the light as he wishes Optimus sweet dreams.

Cheers from Bee's more enthusiastic teachers echo in the halls as they praise him and carry him off for a celebration.

Optimus just continues to lay there, feeling confused, shocked, proud, and most importantly, loved.

When recharge at last overtakes the Prime who can't bring himself to rise, he feels far more at ease then he would normally. A smile graces his features as he slumbers, content for the first time in weeks.

Meanwhile in the rec room Bee and his teachers celebrate his accomplishment's, not only academically but in getting the Prime to actually rest.

No longer bound to a vow of secrecy, Bee's teachers immediately begin bragging about him to every other bot at base, proclaiming Bee a genius and the cutest thing to walk Cybertron.

Energon goodies are not so discreetly given out by Ultra Magnus, who is secretly just as proud of Bee as his more enthusiastic teachers.

Ironhide and Wheeljack both attempt to one up each other by shoving Bee's own successes in their respective classes in the other's face.

It eventually spirals into a conflict over who Bee's favorite combat instructor is and very nearly turns into an out right brawl before Bee shoves energon goodies in their intakes, immediately pacifying them with the sheer adorableness of the action.

First Aid is surprisingly enthusiastic and brings out a few bottles of high grade from his personal stash for the older bots in the room.

Drunk First Aid has many good things to say about his favorite student, he even ends up crying because Bee is just so cute and smart and howcouldanyonepossiblythinkanythingbadabouthim!

The medic is slung over Ultra Magnus's shoulder and taken to his berthroom after his mutterings devolve into static.

Perceptor gives Bee his own personal microscope before promptly leaving to go continue whatever research he is pursuing.

Bee's secondary Caretakers eventually turn up and are swiftly filled in on his successes.

Ratchet had his suspicions but had no idea anything was going on until he found himself surrounded by drunk mechs cheering for Bee.

He gives Bee a quick 'good job' and a pat on the helm before helping Ultra Magnus handle the increasing number of completely wasted bots.

Jazz and Prowl figured out what was going on only a few days after Perceptor took Bee in as a student. Being a special ops agent and an investigator tends to make it so little knowledge evades them.

That doesn't stop Jazz from cheering for Bee with as much excitement as the rest of his teachers. It doesn't take long after his arrival for music to start and a dance off to be enacted.

Prowl hangs around for a few minutes after congratulating Bee but ends up dipping as soon as the music shoots up several notches.

The party rages on until a good number of mechs drop due to intoxication, only then do things start closing up.

When Optimus wakes the next morning he finds a rec room filled with dead drunk mechs too sloshed to have made it to their berths and Bee slumbering in a blanket fort in the corner.

He smiles and tells the semi sober among them that they have half the day off so they can get themselves in order before he carefully cradles Bee to his chassis and takes him to his berth.

Just a drabble

A very drunk First Aid: *Flopped down on a table waving his servo in the air* I'm telling you! Bee's gonna be the best Medic there ev'r was!

A similarly very drunk Wheeljack: *Leaning on a chair for support* Nuh uh! Bee's gonna be a Wrecker! He's got too much spunk to be a grumpy old medibot!

A highly intoxicated, hardly coherent Ironhide: *chugs from bottle of high grade* Naw, th' litt'e bitlet's gon'a be a lead'r just like his Sire! Right Bee?

Everyone: *Turns to look at Bee*

Bee: *too busy shoving energon goodies in his intake to speak*

Everyone: *Tensely stares at him as he finishes his goodies*

Bee: I wanna be a Predacon!

First Aid: Wat

*Glass shatters somewhere in the distance*