A drawing for a fellow Dwarf Fortress player, Kontako. To survive the dreadful necromancer queen, he used the forgotten secret technique of the spinning wild strawberry.
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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 youโve been online today, youโve probably interacted with a machine learning algorithm.
But it doesnโt always work well. Sometimes the programmer will think the algorithm is doing really well, only to look closer and discover itโs 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, andย 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, thatย in 2018 a group of researchers wrote a fascinating paperย that collected dozens of anecdotes that โelicited surprise and wonder from the researchers studying themโ.ย The paperย is well worth reading, as are the original references, but here are several of my favorite examples.
Bending the rules to win
First, thereโs 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?ย 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?ย 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.ย

[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.ย 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:ย 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:ย 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 werenโt 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:ย 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:ย 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.ย
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 algorithmโs hallucinated dream-version of Doom.ย Delightfully, you can play the dream-versionย here

[Image: Q*bert player is accumulating a suspicious number of points, considering that itโs not doing much of anything]
Shooting the moon:ย 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 programโs 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, itโs notย unsorted:ย 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 theย Kobayashi Maruย test:ย 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:ย 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 algorithmโs strategy, let it evolve its own approach. Surprisingly, the algorithm suddenly began winning all its games. It turned out that the algorithmโs strategy was to place its move very, very far away, so that when its opponentโs 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.ย
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 weโre 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 thereโs another, easier route toward solving a given problem, machine learning will likely find it.ย
Fortunately for us, โkill all humansโ is really really hard. If โbake an unbelievably delicious cakeโ also solves the problem and is easier than โkill all humansโ, then machine learning will go with cake.
Mailing list plug
If you enter your email,ย there will be cake!
The Boltzmann Lament
No greater love, some chemists say,
than that of Boltzmann and his k.
The constant made him quite afflicted
and to an early grave (he self-inflicted).
How can we live with this duplicity
in a world of endless multiplicities?
I once tried to clean my room, you see,
But the universe increased its entropy.
Could anyone ever truly follow
such a sad lifetime full of sorrow?
For we’re all alone with these notations,
even with Maxwell’s relations.
And oh, what would good old NIST
possibly begin to think about of all this?
But alas, there was nowhere to start
for questions put forth by the heart.
We’re star-crossed lovers, pchem and I,
And I understand why Boltzmann cried.
When asked if I would marry, would I say yes?
I could only yell my reply: VdP plus TdS!
I couldn’t stop, I couldn’t end it,
What’s the use, I cannot mend it!
I am feeling warm, I need a refresher.
What was constant, temperature or pressure?
Oh, the probability density may disappoint,
But I get faint at the thought of the triple point.
And energies, like jewels, they sing to me.
Especially in exponent, divided by kT.
They said, are you hungry? You look faint ‘round the eyes.
I looked up from my work, full of surprise.
I could not eat in all my frustration
when calculating the partition for vibration.
“Electronic, translation, rotation!” I gasped.
Each was more beautiful than the last.
And with gases ideal, I knew what to do.
The free energy was minus kT ln of Q.
I think the spirit of Boltzmann has me possessed
For I spent two weeks deciding which I liked best,
those energies, potential or kinetic.
I think these problems are genetic.
Boltzmann, soon we shall meet,
Hand in hand, Einstein we shall greet.
In the meantime, though, I’ve got just the ticket:
Let’s apply Arrhenius to those hyper crickets.
By: Maria Moutsoglou, entangled For Dr. Hirko’s spring 2012 graduate statistical mechanics/thermodynamics course.
So fitting for my thermodynamics exam today !
I’m very happy to announce the start of my first comic : one eyed cat ! Each day a new drawing. I’ve been keeping that up for 20 days, so I guess it will go on like this. Follow on insta, facebook or tumblr : @oneeyedcatcomic and on the website : www.lm6d.com/oneeyedcatcomic.
Also, keep in mind that it is an interactive comic ! Eventually you’ll be able to explore the fate of each and every occurrence of the one eyed cat by taping its head (website feature only), and if everything goes on as planned, I’ll also develop a mobile app.
Thanks for your interest and support !
Trump “Golfing”
I just read an interesting story about the way Trump likes to golf. At first, I thought it was an inconsequential puff piece, but it turned out quite revealing. Trump loves golf. He plays it constantly. Even when he probably shouldn’t. Many of his golf buddies have been interviewed about his skills on the course and they all had basically the same thing to say.
He cheats.
Not a little bit.
He cheats A LOT.
It starts with the initial drive. He will often take several mulligans until scoring his first stroke. Meaning he keeps hitting the ball until he is satisfied with where it lands. However, if he does hit it into the woods, the ball will somehow magically appear back on the fairway by the time he reaches it. Due to his caddie rooting around in the tall grass and tossing the ball back to civilization.
Then Trump gets into his cart and since the rules don’t apply to him, he drives it straight onto the carefully manicured green. No one is supposed to drive on this delicate grass. There is video of Trump doing this. And he drives with gusto too. I was surprised he didn’t do a few donuts.
And to finish the hole off, Trump never actually takes his final putt. He calls this a “gimmie.” If the ball is close to the hole, that’s good enough for him. I guess he just assumes he would have hit the ball in.
Some of the people who have golfed with Trump say he often brags about winning championships and setting course records. After seeing him play, all of these people say that is most likely bullshit.
Pretty much everything about Trump’s golfing experience is a lie. Not only that, he doesn’t even try to be sneaky about it. He cheats in plain sight for everyone to see. It’s like a card hustler pointing to the cards hidden in his sleeves before a hand. I’m not even sure why he plays. I mean, technically he doesn’t really play. He just goes through the motions to make it seem like he is playing. The whole point of sport is to challenge yourself. That’s what makes it fun. I don’t understand what Trump gets out of the experience.
I remember back when the original Doom came out for the PC. I loved that game and played it nonstop for weeks. One day I found cheat codes on the internet and at first it was very exciting. I had unlimited ammo and turned on God Mode. Nothing could touch me. Initially, it was kind of awesome. I was plowing through demons like they were paper people. I was getting to levels I couldn’t reach before. But that excitement quickly faded as I played. I discovered that I was getting very, very bored. Overcoming the odds, fear of dying, progressing through the game using my skills, reflexes, and wits… that’s what made the game fun. These cheat codes had turned this once exciting game into a total yawnfest. After years and years of playing in God Mode, how is Trump not totally bored with golf?
I guess this article struck a chord with me because it showed that Trump doesn’t even take the things he claims to love seriously. Even in a game where the outcome means basically nothing, he cannot stand to do poorly. He must lie to himself and others while playing. Nothing is more important than maintaining his ego. It seems like there is nothing too small that he will not lie about. There is nothing so inconsequential that he will not try to cheat. In every aspect of his life, that’s who he is. A liar and a cheater. Nothing is sacred.
And it just makes me think, if he is willing to lie about pointless golf outings… if he is willing to perform these lies blatantly in front of others with absolutely no shame… what items of actual importance is he willing to lie and cheat about?
I don’t think I have ever witnessed anyone as hollow, needy, and pathetic as Trump. Someone so empty of anything save a clawing, desperate need not merely for validation, but veneration… and even the thinnest, most ethereal kind will do.
See, Trump isn’t using golf as a game. He’s using it as a system to test participants in his circle.
First up, he’s brazen. So brazen, people call their own world view into doubt before being willing to accept how brazen, blatant and obvious the cheating was, to the point, some will refuse to process that it happened.
This is the first buy in for the con. He can test if you’re willing to exert consequences for his actions, or willing to give him the benefit of the doubt. If you were to inform Trump that you’ll not be having this bullshit from an biped Cheezles packet, you’ll find yourself in a circumstance of either being escorted from the scene, or having those people who have bought into the previous bullshit make an excuse for the Orange-a-Tan.
Alternatively, he may offer you some deal or reward, to buy into the bullshit, or threaten you to comply.
That’s phase 2.
Once you’ve drunk the Tang, being waterboarded by the Kool-Aid or pocketed the benefit,, you’re going to have to either live with consistency to avoid cognitive dissonance, or you have to face being complicit when you try to break rank.
And then we get to round 3 - Trump has consistently worked to create circumstances where there is no consequence for his actions that cannot be mitigated by lies, fraud, or other means. He’s not playing a round of golf, he’s working out and training his primary core system - brazen bullshit buy-in, and every one of his recurring golfing buddies are recurring enablers of this bullshit because they value what they think they can gain over forcing consequences, even tiny little consequences like golf scores. So when they let Trump slide that little thing, and then another little thing, he’s setting them into the patterns needed to accept bigger and bigger things until they’re either full invested in backing their man, or they’re in so deep, they’ll have to face themselves if they try to back out.
Which is why he does what he does - the benefits to Trump outweigh any consequences, because very few people have ever made the man experience a negative repercussion for his actions. It’s economic rationalism cost-benefit calculation take to a moral free logical conclusion - does this benefit me? Yes, then do it.
01010101010101010111-deactivate asked:
mylordshesacactus answered:
Carpathia received Titanic’s distress signal at 12:20am, April 15th, 1912. She was 58 miles away, a distance that absolutely could not be covered in less than four hours.
(Californian’s exact position at the time is…controversial. She was close enough to have helped. By all accounts she was close enough to see Titanic’s distress rockets. It’s uncertain to this day why her crew did not respond, or how many might not have been lost if she had been there. This is not the place for what-ifs. This is about what was done.)
Carpathia’s Captain Rostron had, yes, rolled out of bed instantly when woken by his radio operator, ordered his ship to Titanic’s aid and confirmed the signal before he was fully dressed. The man had never in his life responded to an emergency call. His goal tonight was to make sure nobody who heard that fact would ever believe it.
All of Carpathia’s lifeboats were swung out ready for deployment. Oil was set up to be poured off the side of the ship in case the sea turned choppy; oil would coat and calm the water near Carpathia if that happened, making it safer for lifeboats to draw up alongside her. He ordered lights to be rigged along the side of the ship so survivors could see it better, and had nets and ladders rigged along her sides ready to be dropped when they arrived, in order to let as many survivors as possible climb aboard at once.
I don’t know if his making provisions for there still being survivors in the water was optimism or not. I think he knew they were never going to get there in time for that. I think he did it anyway because, god, you have to hope.
Carpathia had three dining rooms, which were immediately converted into triage and first aid stations. Each had a doctor assigned to it. Hot soup, coffee, and tea were prepared in bulk in each dining room, and blankets and warm clothes were collected to be ready to hand out. By this time, many of the passengers were awake–prepping a ship for disaster relief isn’t quiet–and all of them stepped up to help, many donating their own clothes and blankets.
And then he did something I tend to refer to as diverting all power from life support.
Here’s the thing about steamships: They run on steam. Shocking, I know; but that steam powers everything on the ship, and right now, Carpathia needed power. So Rostron turned off hot water and central heating, which bled valuable steam power, to everywhere but the dining rooms–which, of course, were being used to make hot drinks and receive survivors. He woke up all the engineers, all the stokers and firemen, diverted all that steam back into the engines, and asked his ship to go as fast as she possibly could. And when she’d done that, he asked her to go faster.
I need you to understand that you simply can’t push a ship very far past its top speed. Pushing that much sheer tonnage through the water becomes harder with each extra knot past the speed it was designed for. Pushing a ship past its rated speed is not only reckless–it’s difficult to maneuver–but it puts an incredible amount of strain on the engines. Ships are not designed to exceed their top speed by even one knot. They can’t do it. It can’t be done.
Carpathia’s absolute do-or-die, the-engines-can’t-take-this-forever top speed was fourteen knots. Dodging icebergs, in the dark and the cold, surrounded by mist, she sustained a speed of almost seventeen and a half.
No one would have asked this of them. It wasn’t expected. They were almost sixty miles away, with icebergs in their path. They had a respondibility to respond; they did not have a responsibility to do the impossible and do it well. No one would have faulted them for taking more time to confirm the severity of the issue. No one would have blamed them for a slow and cautious approach. No one but themselves.
They damn near broke the laws of physics, galloping north headlong into the dark in the desperate hope that if they could shave an hour, half an hour, five minutes off their arrival time, maybe for one more person those five minutes would make the difference. I say: three people had died by the time they were lifted from the lifeboats. For all we know, in another hour it might have been more. I say they made all the difference in the world.
This ship and her crew received a message from a location they could not hope to reach in under four hours. Just barely over three hours later, they arrived at Titanic’s last known coordinates. Half an hour after that, at 4am, they would finally find the first of the lifeboats. it would take until 8:30 in the morning for the last survivor to be brought onboard. Passengers from Carpathia universally gave up their berths, staterooms, and clothing to the survivors, assisting the crew at every turn and sitting with the sobbing rescuees to offer whatever comfort they could.
In total, 705 people of Titanic’s original 2208 were brought onto Carpathia alive. No other ship would find survivors.
At 12:20am April 15th, 1912, there was a miracle on the North Atlantic. And it happened because a group of humans, some of them strangers, many of them only passengers on a small and unimpressive steam liner, looked at each other and decided: I cannot live with myself if I do anything less.
I think the least we can do is remember them for it.
I HAVE WAITED FOR THIS GIFSET FOR MY ENTIRE LIFE
THIS IS WHY GIFSETS WERE CREATED
LOL ah, I remember my years of going to the live RHPS shows. So fucking fun.

