waywardfleet-blog

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This is by far the best thing ever!

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sometimes I’m like “my therapist doesn’t really tell me anything I don’t already know” but then I remember that I used to eat scrambled eggs every single morning because I hated them but I hated them less than I hate all other breakfast food on weekdays (don’t @ me waffles are a weekend food and they Do Not start me on a productive path) and my therapist said, “why not eat a lunch food?”

and I said, “explain”

and she said, “you know you’re allowed to eat whatever food you want in the morning. you are not bound by law to the traditional american breakfast.”

my father’s insurance pays a hundred dollars an hour for a woman to give me permission to eat a pb&j at six in the morning 

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he protecc

he attacc

but most importantly

HE COMIN BACC

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♥

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I grew up in a poly household. My mother was married to two men who loved her dearly and they were the best of friends. I use past tense due to the fact that one of my fathers passed away a few years back.

I grew up in one of the most stable, loving households I can imagine. I had tons of support from all three of my parents, I never felt alone, and I never felt confused about my parents relationship.

Were other people confused when I told them about my parents? Sure. Did it take some time for them to understand my parents relationship? Yep. And the reaction I got every single time from other kids once they understood? “That’s so awesome!”

Growing up in a poly house did not hurt me, confuse me, or make my life difficult. It sure as hell wasn’t abusive.

Healthy poly relationships do not hurt children.

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things my boyfriend has done

- urgently marched into A&E and said ‘we’re having knee pain!!’ to the confused receptionist. i had to explain that it was only my knee and that he was just worried

- when asked to tag me in a meme of ‘what water are you?’, said ‘you are the ocean: home to all friends’

- loved ‘filthy gorgeous’ and, rather than learning the words, learned ‘all three parts in the song where they ring a triangle’

- after we had an argument about him not ‘getting’ my ADHD, i caught him halfway through a three hour playlist of lectures on ADHD, with a pen in hand, taking notes

- he suffered a TBI last summer and he did not like the orienting questions they ask (’what year is it? what day is it?’ etc). when asked ‘do you know where you are?’, he cracked one eye open and angrily said ‘in bed!’

- he played knack 2 and hated it. when i asked why he was still playing it, he said ‘so i never have to play it again’. he got every achievement and as soon as he got the last one he stood up, ejected the disc and returned it to the store

- lately he’s given up on making lunch so he just drinks huel which is a meal replacement shake, except huel is kind of boring so he sometimes puts nesquick strawberry powder in there

- my favourite drink is pepsi max. when asked about his dreams for the future, they often involve ‘being rich enough to find a way to pump pepsi max directly into our house’

- one time in our first year of dating i hadn’t seen him in weeks, whereas we normally saw each other all day every day, so i was gonna go stay with him for a couple days. he had a temporary job (i’m talking 2 weeks total) at the time and i was bummed that i was gonna be alone at his for a bit, but w/e. he was texting me like ‘work is going okay, in the line for the canteen right now’ while i got on the bus. i found the key where he said it was, i found a note on the table like ‘hi love! the wifi code is [password], I’ll be back at 5!’, and then I went into the lounge and he was there. he was lying on a fold-out bed with Marvin Gaye playing. the TV was on a powerpoint slide that said ‘Welcome, Jess. I quit my job.’ he was entirely naked except for a cushion with the letter ‘D’ over his crotch. im 95% sure there were candles

- we play the game Rimworld, where you micromanage a colony of people on an alien planet. he uses it entirely to simulate a peaceful colony, mostly of women, who have a large number of animals they care for and train. one time he got this random event where all the women in the colony got a psychic mood boost and he was like ‘honestly that’s my life goal’

- when he was in hospital and his cognitive functions were slowly coming back, he looked up from twitter with horror and said ‘jess… is the american president a racist?’

- we were playing Articulate, which is a game where you have to describe a word without saying the word itself. His partner said ‘when you’re beginning sex, you are…’. he, without a second of hesitation, yelled ‘FOREPLAY’. the answer was actually ‘initiating’, but my ego grew like fourteen times

- one time he asked me what guacamole was, and i told him, and he said ‘if it’s made up of things that already have names why does it have a different name?’ i have not let him live this down yet

- i used to have an eating disorder, and whilst i’m good 99.9% of the time now i occasionally do have wobbles. one time i’d eaten some mini-donuts and i told him ‘i kind of want to check the calories on those…’, so he immediately pulled the label off and ate it

- i lost him for like twenty minutes at a uni event, and when i found him he presented me with a pepsi max badge and said ‘i rode this mechanical bull to try and win you a year’s supply but i fell off pretty quickly. sorry.’

- we won the ‘best couple’ award in our year at uni, but neither of us were there to collect it because i was ill and he left halfway through to come home and take care of me

- one time he wasn’t paying attention while making lunch and he cracked an egg directly into the bin. the look of confusion on his face was priceless.

- on the rare occasions when i wake up before him, when i kiss him/ touch him he makes these little like… activation sounds? you know like when you touch a cat? it’s like those

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If you’re trying to catch a housecat that’s gotten outside, don’t forget: they’re an ambush predator and you’re a persistence predator. You have several times more endurance than they do - use that to your advantage! Don’t run after them; that’s playing to the cat’s strengths, and vigorous pursuit may cause them to hide. Instead, follow them at a brisk walking pace until they get tired and need to have a lie-down, at which point you can simply pick them up and take them home.

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me: man i love people maybe i’m not as introverted as i thought, i can be around people forever

me exactly one hour later: oh my god no

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When algorithms surprise us

Machine learning algorithms are not like other computer programs. In the usual sort of programming, a human programmer tells the computer exactly what to do. In machine learning, the human programmer merely gives the algorithm the problem to be solved, and through trial-and-error the algorithm has to figure out how to solve it.

This often works really well - machine learning algorithms are widely used for facial recognition, language translation, financial modeling, image recognition, and ad delivery. If you’ve been online today, you’ve probably interacted with a machine learning algorithm.

But it doesn’t always work well. Sometimes the programmer will think the algorithm is doing really well, only to look closer and discover it’s solved an entirely different problem from the one the programmer intended. For example, I looked earlier at an image recognition algorithm that was supposed to recognize sheep but learned to recognize grass instead, and kept labeling empty green fields as containing sheep.

When machine learning algorithms solve problems in unexpected ways, programmers find them, okay yes, annoying sometimes, but often purely delightful.

So delightful, in fact, that in 2018 a group of researchers wrote a fascinating paper that collected dozens of anecdotes that “elicited surprise and wonder from the researchers studying them”. The paper is well worth reading, as are the original references, but here are several of my favorite examples.

Bending the rules to win

First, there’s a long tradition of using simulated creatures to study how different forms of locomotion might have evolved, or to come up with new ways for robots to walk.

Why walk when you can flop? In one example, a simulated robot was supposed to evolve to travel as quickly as possible. But rather than evolve legs, it simply assembled itself into a tall tower, then fell over. Some of these robots even learned to turn their falling motion into a somersault, adding extra distance.

[Image: Robot is simply a tower that falls over.]

Why jump when you can can-can? Another set of simulated robots were supposed to evolve into a form that could jump. But the programmer had originally defined jumping height as the height of the tallest block so - once again - the robots evolved to be very tall. The programmer tried to solve this by defining jumping height as the height of the block that was originally the *lowest*. In response, the robot developed a long skinny leg that it could kick high into the air in a sort of robot can-can. 

[Image: Tall robot flinging a leg into the air instead of jumping]

Hacking the Matrix for superpowers

Potential energy is not the only energy source these simulated robots learned to exploit. It turns out that, like in real life, if an energy source is available, something will evolve to use it.

Floating-point rounding errors as an energy source: In one simulation, robots learned that small rounding errors in the math that calculated forces meant that they got a tiny bit of extra energy with motion. They learned to twitch rapidly, generating lots of free energy that they could harness. The programmer noticed the problem when the robots started swimming extraordinarily fast.

Harvesting energy from crashing into the floor: Another simulation had some problems with its collision detection math that robots learned to use. If they managed to glitch themselves into the floor (they first learned to manipulate time to make this possible), the collision detection would realize they weren’t supposed to be in the floor and would shoot them upward. The robots learned to vibrate rapidly against the floor, colliding repeatedly with it to generate extra energy.

[Image: robot moving by vibrating into the floor]

Clap to fly: In another simulation, jumping bots learned to harness a different collision-detection bug that would propel them high into the air every time they crashed two of their own body parts together. Commercial flight would look a lot different if this worked in real life.

Discovering secret moves: Computer game-playing algorithms are really good at discovering the kind of Matrix glitches that humans usually learn to exploit for speed-running. An algorithm playing the old Atari game Q*bert discovered a previously-unknown bug where it could perform a very specific series of moves at the end of one level and instead of moving to the next level, all the platforms would begin blinking rapidly and the player would start accumulating huge numbers of points. 

A Doom-playing algorithm also figured out a special combination of movements that would stop enemies from firing fireballs - but it only works in the algorithm’s hallucinated dream-version of Doom. Delightfully, you can play the dream-version here

[Image: Q*bert player is accumulating a suspicious number of points, considering that it’s not doing much of anything]

Shooting the moon: In one of the more chilling examples, there was an algorithm that was supposed to figure out how to apply a minimum force to a plane landing on an aircraft carrier. Instead, it discovered that if it applied a *huge* force, it would overflow the program’s memory and would register instead as a very *small* force. The pilot would die but, hey, perfect score.

Destructive problem-solving

Something as apparently benign as a list-sorting algorithm could also solve problems in rather innocently sinister ways.

Well, it’s not unsorted: For example, there was an algorithm that was supposed to sort a list of numbers. Instead, it learned to delete the list, so that it was no longer technically unsorted.

Solving the Kobayashi Maru test: Another algorithm was supposed to minimize the difference between its own answers and the correct answers. It found where the answers were stored and deleted them, so it would get a perfect score.

How to win at tic-tac-toe: In another beautiful example, in 1997 some programmers built algorithms that could play tic-tac-toe remotely against each other on an infinitely large board. One programmer, rather than designing their algorithm’s strategy, let it evolve its own approach. Surprisingly, the algorithm suddenly began winning all its games. It turned out that the algorithm’s strategy was to place its move very, very far away, so that when its opponent’s computer tried to simulate the new greatly-expanded board, the huge gameboard would cause it to run out of memory and crash, forfeiting the game.

In conclusion

When machine learning solves problems, it can come up with solutions that range from clever to downright uncanny. 

Biological evolution works this way, too - as any biologist will tell you, living organisms find the strangest solutions to problems, and the strangest energy sources to exploit. Sometimes I think the surest sign that we’re not living in a computer simulation is that if we were, some microbe would have learned to exploit its flaws.

So as programmers we have to be very very careful that our algorithms are solving the problems that we meant for them to solve, not exploiting shortcuts. If there’s another, easier route toward solving a given problem, machine learning will likely find it. 

Fortunately for us, “kill all humans” is really really hard. If “bake an unbelievably delicious cake” also solves the problem and is easier than “kill all humans”, then machine learning will go with cake.

Mailing list plug

If you enter your email, there will be cake!

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flipping from page 1 to page 2 on an exam

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fun story I first became obsessed with the harry potter series and hermione in particular in yr 3 of primary school and I decided I wanted to be like hermione in every way so I started reading *lots* and working super hard in school, got a reputation for bookishness and being the smart kid that I kept up into high school and lol here I am graduating in a few weeks from Cambridge all bc I adored this clever bookworm in a children’s book series and absorbed her into my personality as a child like ???

basically long story short female role models in kids media are EVERYTHING

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so this guy at school has a 3d printer and he’s been secretly selling these

kirbies with legs

and i got mine today

here’s the handmade package

i open it and

oh

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Vintage LGBT Badges

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I unno what meme this is, but I’m here for this.

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sometimes a family can just be you, a six-pack of diet coke, and soft cell’s 1981 hit ‘tainted love’