I lost the blog post that I was reading by Some Guy about Some Thing, but I would like to digest it a bit here regardless. The Guy I will definitely not be able to remember, but The Thing I can flesh out still. I think. The good thing about losing source material is that I don't have to worry about getting facts right: I can worry more about what feels true than what is real.
But digression!
The article I was reading was about machine learning and backpropagation, which is (and don't murder me on technicalities here) a way to tweak a neural net's weights based on a dataset to best solve for new inputs. Basically think of a bunch of strings attaching a network of bells, and we're trying to make it that when we yank on a starting string the bells produce a meaningful response. Backpropagation is the act of "strengthening" sections of the string so that they impact the final result in a way that better matches a set of data. This is probably a terrible analogy, but it's the best I got right now. The MORE IMPORTANT thing about this how we go about adjusting the strings in the first place, which is usually done with a gradient descent algorithm. This is just a fancy way to say that we adjust things in set pattern of steps to have the whole bell apparatus settle into a solution that works for what we have observed.
But this solution can be a solution that isn't optimized to the most broad view. Depending on the steps taken, we can settle into a localized solution versus something more global. Imagine if I told you to find the lowest point in a city, but required you to close your eyes and then run 20km between your observations. Each step in this case, 20km, would set you in a new place of the city where you could observe which way is downhill and then run 20km in that direction (eyes closed, remember). In this fashion you probably will run over the lowest point again and again, never reaching a minimum of any kind. On the other side of things, if you were to take a step size of a foot, you'd end up in a slight sinkhole somewhere in the city. Standing in the sinkhole, walking a foot out of it, noticing downhill is back into the sinkhole and concluding the sinkhole is the lowest point in the city.
There's ways data scientists get around this by adjusting step sizes as they go along. BUT my train of thought is more around this idea of finding solutions to my surroundings in a more general sense. Solutions can be things like "Where can I find a good Taco?" or "What's the best place to take someone named Gillian on a romantic date?". To find a solution to this involves my own experience and then my ability to find and integrate new information. And how I receive information, the mechanism that transfers this information, is a type of step size. If there's a good friend of mine that only eats a certain type of food, that aren't tacos, she probably won't be a good person to ask about tacos. The step sizes she would afford me to find good tacos would have me bouncing all over a taco landscape with little hope for finding global values. BUT, maybe she's a romantic at heart and the step size she would give me for finding a place to woo Gillian, would be the perfect amount of petite.
People are a bit harder to think about as having step sizes, because people change the way they present information depending on topic. An easier step size disseminator to think about is social media.
I often think about the reasons I never have liked being on social media. I think one of the main reasons is I have a hard time representing myself in a way that feels authentic when on a platform that requires specific types of content to be created. Square photos. Short bursts of text. Whatever. I've realized also that social media creates a very small step size for me that makes me feel that I have gotten stuck repeatedly in a local minimum (or maximum) while being led to believe I'm in a global minimum (or maximum). I guess this is a reframing of the echo chamber everyone always talks about, but I don't think that that captures very well what I'm speaking of since I know of people that can make social media perform with amazing step sizes for them. These people I think of a bit like someone that can put a perfect bullnose on a piece of wood with a chisel: I wouldn't think it possible, but god damnit they can do it.
In some ways these people are finding the diagonals when the rest of us are just bouncing up, down, left, right on a grid. They're cutting corners and finding shorter paths and better solutions (https://en.wikipedia.org/wiki/Power_series). Good tools ("tool" being used in this case as some apparatus that distills and organizes an environment... which I think social media can be) should always be finding the square root of 2 instead of just 2. But maybe that also requires WHERE you want a tool to take you.
I guess the big point that I've been thinking: we get information through tools, and these tools have step sizes: chunks they break the world into (Conversation is a tool! And conversation in non-adjustable step sizes is rhetoric: a tool used to achieve a sense of local stability without hope of continued growth.) These chunks can have default sizes that don't suit us: they lead us to only local solutions when we could be reaching for something more encapsulating. If we are thoughtful we can put a tool into a different context to better find local maximums and minimums. But it requires intent.
I have a story of small step sizes that involves high heel shoes. I was at a dinner party and a woman announced that she had always wanted to walk on someone while wearing high heel shoes. I offered myself up as a test subject and can report that being walked on by someone wearing high heel shoes is extremely uncomfortable. However, in such small step sizes I do believe I was shown a global maximum of someone's thought process. So as a step sizes go, those couple inches at a time seemed like miles.
There was a young brown whippet that seemed to be the leader and she would sprint up and down the pack acting as hardened steel tracks placing the group on what seemed a crash course with destiny; one large freight train of quivering muscle below thin skin. Whippet's vascular systems are a bit too prominent, visible to the naked eye in a way that makes me uncomfortable like spouses discussing each other publicly in ways they think are clever in their cutting nature, but are far from hidden. The whippets were both chaotic and ordered and how I assume one would feel inside of a balloon, atop a helium atom that has just slipped from a child's grip at the apex of a ferris wheel sitting in the center of a carnival; face smashing off latex and other atoms like the first bondage party of the universe.
The whippets drifted around in a quick flurry of cottonwood blossoms on pavement, then were gone.
The following day I would be peeing along a fence and have a german shepard run at me snarling while I was mid stream, and I thought of that scene in The World According to Garp (the book, not the movie, which I don't say in snobbery, but more that I don't know if/how this scene was portrayed in the movie as I did not see it), where the guy is accidentally castrated when the wife's car gets rear ended during the infidelitous blowjob, and I worried that if I lashed out at the dog with a fist or hand, I would inadvertently cause my own castration, so instead I just continued standing and peeing. Unusually, the tip of "ignore it and it will go away" worked in this situation.
I guess the two events seem connected not just because of their canine base notes, but because one had such a sense of the eternal and one had a sense of immediacy. Two sides of the same coin, sort of thing.
The picture has nothing to do with any of this, but is from a similar moment of time. Or maybe there is something to be said about a horse head in a window and a window that is empty. Dreams of racetracks next to a bright abyss.
This will loop back, I swear, but what popped into my head while thinking about Didon and Wallace was Eminem as featured on a Big Sean track; stick with me even if you don't like Eminem at all. This was a few years ago and I was running on an elliptical in a gym in Budapest called something like Kisslife Fitness or Chilli's Fitness... I can't remember which. But as I ran in jean shorts next to an arrangement of people that seemed sculpted from the internet's idea of what made the perfect body (porn), I remember hearing the gravely machine gun delivery of what seemed like a familiar voice on a Spotify radio station meant to make me run (trap music and pop), referencing things that felt familiar but in the offered lyrical relationship sounded like a police line up of items a bot shopping on an Amazon Prime account purchased:
I'm not trying to beef with Eminem, but I really don't get what that's supposed to mean. I don't think it really means anything, but his delivery SOUNDED like the pinnacle of what he has made his craft to be: voice a snare drum firing away on all syllables. His voice as remembered circa the 90s was lost in what sounded like a smokers haze, but the rhythm was buttoned up tight on its way to prom and easy to identify as coming from the Mather's home. Honing a part of craft, especially the part of one's craft that they are most well known for, can result in the illusion of the entirety of that craft being good while actually being sort of garbage. I could run like hell to that track until I googled what was being said, and then it became more of a slow trot as I pondered what to make of the whole thing.They blame me for murdering Jamie Lee CurtisSaid I put her face in the furnace, beat her with a space heaterA piece furniture, egg beater, thermos
And THIS is what I was thinking of as I realized David Foster Wallace was sort of like an overly honed Joan Didion. I say this with the utmost love for the things he has written and really only taking into account his essays (I don't have the attention span for Infinite Jest), but it made me realize that the way Wallace can craft his essays makes the structure feel like the same dish served over and over again. The nuance and playfulness is only there after forgetting you already once consumed the dish you are about to eat.
Snowflakes form when cold water freezes onto pollen or dust in the sky. There needs to be some turbulence of pollen and dust in the general climate of "cold" and "wet" in order to get the whole snow thing started. Good art is a balance of turbulence with environment. Didion is so good at bringing a current event in line with history, current context, and tangential supportive information. She builds sparse houses that hold incredible spatial value. And while using such bare building materials each house she makes comes across with a subtlety that doesn't bombard the environment with a pollen or dust storm, turning a possible snowfall instead into a desert storm (non militaristic, but still overwhelming). Each work is a light snowfall pattering around the world and allowing one to revel in the fact that snowflakes are all different, they change the notion of an environment, and in the end things pass after a moment in order to be held anew in a future context. Didion's work seems to wrap itself in a base layer that prepares for the possibility of being seen in a new light at some future junction.
Good art I fall in love with. It's because with good art I'm not bombarded and forced into an environment but shown a path forward that doesn't promise anything but a perspective. I've recently made a promise to someone that I'm deeply in love with. And thinking on it in the light of how it relates to art, it is quite similar. We have agreed on our environment and look to create the right type of turbulence for perfect snow storms. Maybe sometimes this means a storm that seems like it will destroy all (I don't actually think we'll get these... but you never know), but more often a storm that lays blankets of soft-focus light across pines and hidden cabins, where fires stay lit as long as we both can still hold the other in our mind.
So to recap: new Eminem is possibly like David Foster Wallace. Reading Joan Didion is a lot like love. And I am hopelessly IN love.