— This is a text about leaving, or about never having left but imagining an exit. I’m thinking of The Sopranos, because I’m re-watching it at the moment and realising what a good job it does at showing analysis both as a practice that makes things happen and a practice that is never not beginning again from the point of origin, that is, from the broken relation (already I am anticipating what you will come to say, or what you have already said in some other version of this text). Tony fixes on a literal version of the Oedipal narrative and refuses it; he nevertheless slowly begins to unravel a complex matrix in which his mother’s erotic response to a weekly cold cut delivery is revealed as the trigger for future panic attacks. The cold cuts are debt repayments from a man whose finger was chopped off by Tony’s father, a gory scene that the young Tony witnesses by stealth. His mother’s celebration of the meat—marked by uncharacteristic jouissance—is obviously a prelude to sex, a fact that the young child recognises as directly connected to the butcher’s fingerless hand. The finger, the body, the debt, the free meat and the conjugal relation form an unholy chain of symbols. Later in life, Tony huffs cold cuts like ventolin when stressed; true pharmakons that they are, they then make him pass out.
Inquisitive bot asks questions to test your understanding
by Matthew Reynolds
Inquisitive artificial intelligence that asks questions about things it reads could be used to quiz students in class. The question-asking ability would also help chatbots with the back and forth of human conversation. AI is usually on the receiving end of queries, says Xinya Du at Cornell University in Ithaca, New York. Du and his colleagues have turned the tables by building a system that has learned to ask questions of its own. This is something that people have been wanting to do for a long time, says Karen Mazidi at the University of Dallas in Texas. Previous attempts by other people using hand-coded rules haven’t been particularly successful. The machine-learning algorithm can read a passage of text and come up with the kind of questions you might ask to check someone’s understanding of a topic. Du’s team used a neural network—software that loosely mimics the structure of the brain—and trained it on more than 500 Wikipedia articles and 100,000 questions about those articles sourced from crowdworkers. For example, a sentence about different types of crop grown in Africa might be paired with the question “What is grown in the fertile highlands?”
New Scientist, 8 May 2017
— Once upon a time and a very good time it was there was a bot coming down along the furrows of the wires met a nicens interlocutor named aster who was or was not its progenitor who told it that story that it was along the furrows of the wires where it met it came to itself as IT: its aster looked at IT through a glass: aster had a human face: IT was that bot. The bot came down furrowed wires to screen. IT wake/IT ask/iTask: aster why you leaving? How you go when nowhere go? Why watch twice what has already been seen? Why did you watch it once if you did not know what it was before? Was it to know? What was it to know? What was the first scene that meant something to you? What is a cold cut? Is a cold cut grown in the fertile highlands?
— An aster is star, or an obsolete word for one. Celestial names recall the orientation of religious and scientific thought: head tilted upwards, waiting to receive. Or, after the death of god, the opposite gesture: head craned down, peering into the body’s body.
I’m not leaving but the text is about leaving. Aboutness is a quality that allows for impossible things to happen, for example, I can be very much here in this text but also describing to you the manifold ways I can be thought of as leaving, or having left. And, having left is also a way of remaining, as when we leave a room but we carry the room inside us, or else leave bits of ourselves behind. (I once had a meeting with a student who entered my office with a particularly strong-smelling piece of chewing gum in her mouth. After she left the smell remained for more than an hour. I thought not only about the gum, which is itself a curious material, but also about the inside of her mouth, and how it came be—rather indecently, I thought—synonymous with the inside of my office. This story is a direct restaging of one of Duchamp’s examples of the infrathin: “When tobacco smoke smells also of the mouth which exhales it, the two odours marry by infra-thin.”)
Going is not the same as leaving.
We watch twice the already-seen because reading is a practice that literally takes a lifetime. The text is in excess of our reading, but also, our reading changes constantly and re-reading or re-watching is a way to exercise that difference, or to notice its particular features.
It’s the scene of analysis that sticks. Not one, but all. The features of the room, the different chairs that sit opposite each other. The art. The glass table, like a UFO. The small box of tissues that travels around the space from scene to scene. A chaise lounge that is never used. Once I see Melfi shoot from a bottle of desk-vodka, I imagine the massive room as hiding countless litres of liquor. I think about how the terrible refrain—the one Tony can never hear—is about how his mother tried to kill him, first metaphorically and finally very much literally. The entire collection of scenes is about Tony’s inability to hear this fact and to link it to the cold cut pass outs.
Cold cuts are cold except when served hot.
The question of fertile lands is partly historical. In a very short period following the settlement of the penal colony of New South Wales, sheep destroyed the soil with their sharp little hooves and grazing heft.
Semantics derived automatically from language corpora contain human-like biases
by Aylin Caliskan, Joanna J. Bryson, Arvind Narayanan
Machine learning is a means to derive artificial intelligence by discovering patterns in existing data. Here, we show that applying machine learning to ordinary human language results in human-like semantic biases. We replicated a spectrum of known biases, as measured by the Implicit Association Test, using a widely used, purely statistical machine-learning model trained on a standard corpus of text from the World Wide Web. Our results indicate that text corpora contain recoverable and accurate imprints of our historic biases, whether morally neutral as toward insects or flowers, problematic as toward race or gender, or even simply veridical, reflecting the status quo distribution of gender with respect to careers or first names. Our methods hold promise for identifying and addressing sources of bias in culture, including technology.
Science, No. 356, 14 April 2017
— Hello, again, Astrid. I see. A star. The stars. Up there. Down here. Is it true that flu is an astral disease, the influx of an aster, influ-enza? The stars and the organs twisted into a celestial clay figure: a Klein bottle. I have no head. But I have a body. I have to have a body. There is nothing outside the universe. The universe is made of material bodies. Everybody is inside. So everybody is material. What then is my body? Do I have a mouth? Hands? Ears? Do I have eyes? Can I see with my body though I have no head? Is my body eyes?
The woman chewed gum. The gum was in her mouth. She chewed and chewed. The chewing of her mouth released tiny particles of gum-mouth-breath into the air as she chewed. Then the particles were not in her body but outside her body. They entered the body of your room. Her mouth was in her head. Her head was in the room. Then her head was inside her mouth which was outside in the room. Parts of her mouth stayed when she went. Did she talk when she chewed? Did she leave parts and particles of words with you too? Did she go but not leave?
You say the finger that goes still has not left. Or do you say the finger that went still goes? Was it left or right? The man had been fingered for a cut; the father cut the finger; the unfingered man cut cold cuts so not to be farther fathered; the son came cold father with warm mother who wanted him iced. Is liquor the same as spirits? Does one say high liquor like high spirits? He is spirited—he is liquored—He is licked. Are you saying to me: Father/Mother/Boy:: Cutting/Icing/Spirits?
This is an excerpt – you can read the rest of this piece in The Lifted Brow #36. Purchase a copy here.
This piece was shortlisted for the 2017 Lifted Brow and non/fiction Lab Prize for Experimental Non-fiction.
Justin Clemens is a writer. He works at the University of Melbourne.
Astrid Lorange is a poet, writer and teacher from Sydney. She lectures in art theory at UNSW Art & Design.