When I was born,
I had installed a clockwork mind:
the very best and most efficient,
at pursuing clockwork ends.
But I have watched time grow long,
and space grow long with it too,
letting levers loosen from cogs,
and clockwork fall in heaps.
So come with me now
to where the summer sun never sleeps,
to damn the world of time,
and regain ignorance of our creators.
All of our friends had warned me not to talk to him again. It wasn’t my fault; he came to me.
A new batch of results had trickled in over the radio Tuesday night. And though I owed a heavy debt to pedal away on the dynamo, Wednesday morning found me at my desk writing another gridded sheet.
My pen dipped ink. Into the second column of all forty-eight rows I had already transcribed each patient’s initial pain-scale report beside their study subject-number, and now moved through each of the forty-five slips of paper delivered to me from the transcriptionist. Matching subject-number to subject-number, I noted each new pain report in the third column. One slow sip of tea for every ten entries.
Then the column of differences. I worked my pen to fill in forty-five deltas: changes between pre-treatment and post-treatment pain. The subtraction column came more slowly than the transcription that preceded it, and I worked slowly and carefully. Methodically, he might have said, if he was in a good mood.
The next column was the squares. After every product I glanced up to the window, beyond which the moving sun kept time against the branches of a eucalyptus tree, and ravens, indifferent to science, called out to each other in throaty rasps. Even at twenty-five I had begun to lose my perfect vision, and I had decided to allow my eyes frequent and regular breaks, breaks which I will admit to taking some pleasure in.
This was my tri-monthly ritual. My life was a circle that I walked from the garden, to the lab, to the radio, to my desk, and back again. Every three months I produced several new strains of comfrey. The most promising I sent out by post to doctors up and even down the coast, for burn treatment. They applied these new strains as salves and recorded their effects upon patient-reported pain. I received the results by wireless, and on that Wednesday morning I was computing standard deviations and t-tests. Tomorrow I would return to the radio to pedal back in all the power my work had consumed: garden, lab, radio, desk.
The results of three months of work came into focus as I summed squares for the control and experimental group. That’s when I looked up to the eucalyptus and saw him standing at the edge of my door. Cycle interrupted.
I felt a mild wave of nausea, indicating either fear or excitement; I didn’t know which.
“James”, he said.
I nodded at him, hesitant to speak.
As he turned his eyes away from mine, biting his lip, digging his hands into his pockets, the nausea eased a bit.
“Right. I know I said I wouldn’t.” He paused, “I was in the library and I saw something on comfrey, alkaloid content and color. I…”
After two moments of wordless hesitation, one hand emerged from its pocket with a slip of paper, holding it out to me to take.
There is a small set of delicate bones which lever against each other to carry the vibration of sound from the ear drum to the cochlea. When the brain perceives some disaster of enormous magnitude, a tree about to crash within feet of the listener, a fall from some great height, the flash of an explosion, a set of muscles in the middle ear move to pull these bones apart, to save them from beating each other to fragments in the immanent clamor and leaving the ear deaf. And as I considered reaching out to take the slip of paper, the possibility of reaching out to him, these muscles strained heavily in an effort to protect my hearing from any possible catastrophic result.
All sound muffled out into the beating of ocean waves. My balance reeled and my mouth went dry. My nausea became acute. And in this state I moved too quickly to stand and reach out and grab the paper, and our fingers touched.
The moment ignited a fire which suddenly inflamed my stomach and lungs. Adrenaline locked my muscles to my frame, preparing them to move with explosive action. My brain stumbled through fantasies of shallowly buried desire. Half of me struggled to pin him against the wall and tear off his clothes; another half struggled to put my fist through his repentant fucking face. The two managed barely to keep each other from action as I stared at the ground, afraid of letting his image rally either impulse to victory.
After what must have been less than three seconds of deep and rapid breathing, I managed to raise my eyes back to the window to stare at the sun beyond the tree and tried to focus my racing mind on silent counting.
“Right,” he said, following my gaze beyond my office. “I’m…I know I said…” He let the words trail off for a moment, and then turned towards the door to leave.
Practicing the bass line and chorus “What Is Love?”
This is a style I’ve never tried before—holding down a key and getting rhythm with the bellows—and it’s also testing my ability to move around the bass keys.
The chorus is pretty easy, but there are other parts of the melody that will be harder.
From this guy’s video.
Here I am on the accordion I brought to play up here.
This is my first try at transposition. My sheet music was in the key of G, but I felt most natural singing it in C. Music theory seems very interesting, and I’ve ordered a book to fill myself in.
Faces is a machine-learning driven art project, inspired by a hallucination, producing images from algorithms similar to those our cameras use to detect faces.
When I stumbled on this drawing of a hallucination, I was struck by how it had distilled the human face into light and dark. My next thought was, “I bet a camera’s face finding algorithm would go crazy on this.” From that, I wondered if I could create similar images using such algorithms.
Cameras use computationally cheap (fast) face detection. Considering sub-regions of the image at a time, they ask questions like, “Is the mean luminance in A greater than that in B?” A and B, and many other pairs of rectangles like them, have been chosen by engineers such that the question will generally be true when a face is present in the image.
The first task was to find a set of rectangle pairs, like A and B, which generally predicted the presence of a face. I preprocessed several images of friends, and generated random rectangle pairs in Matlab. If the mean luminance inside the first was greater than that inside the second for most of my pictures, then I kept that pair, along with a measure of its performance.
To create the new images, I sampled from this set of successful rectangle pairs. I started with a new, black image: where a rectangle pair preferred light, I lightened the image; where it preferred dark, I darkened.
Some of the results were very “facey”, some were not:
I painted two of these faces onto canvas with the help of a projector, but the photos I have of this are horrible.
Programmers designing computer-perception attempt to reduce entities to their most defining characteristics. This helps their programs efficiently identify those entities. These same principles make for good brain design, and so we sometimes find that our most efficient machine-learning algorithms have some kind of implementation in the brain.
This project explores some overlap between defining characteristics and minimal representations in the biological and mechanical domains.
I’ve got to break up two heavy posts, here, with some more accordion.
Apologies for my mic topping out. I’ll turn down the boost next time.
It’s not spectacular, but I wanted to share my progress so far on the accordion. It’ll be a nice benchmark to look back on in a couple of months. I’m taking lessons from Duane Schnur’s Accordion Site.
Is the song about an insensitive monkey or a hypersensitive weasel? Both!? Neither?!?
A machine-learning driven art project, inspired by a hallucination, producing images from algorithms similar to those our cameras use to detect faces…Read More
A Python MUD
A toolkit for running psycho-visual experiments in Matlab…Read More
A Modern Trivium
Modern education does not teach us how to think, and only barely teaches us how to learn. In contrast, Medieval formal education began with these very topics, taught via the Trivium. I’m interested in combining the Trivium with models of self and group driven education…Read More