by Dan Cohen
(Noah Kalina, Lumberland / 20180716)
Noah Kalina is a gifted photographer who has a commercial practice and also works as an artist. He is probably best known for his Everyday project, in which he has been taking a photograph of himself each day for the last two decades. I am more interested in his nature photography, which is uniformly gorgeous. Noah lives in Lumberland, in upstate New York, and his photos across the seasons — of a single tree or river bend — are evocative and engrossing.
I want to buy a print of one of these photographs, but I can't, for reasons you can probably imagine, since it is 2021: these remarkable images are only available as NFTs. Thus far, as I write this newsletter, Noah has sold 16 Lumberland NFTs, for a total of 13 ETH (Ether cryptocurrency), which is about $55,000.
Good for him! I want to see Noah's art supported, and if I can't throw old-timey U.S. dollars at him in exchange for physical media, I'm glad that he is auctioning off certified links to JPEGs for something equally ethereal. May he convert his ETH to USD ASAP.
But this feeling is bittersweet. Is this how we are going to support the arts and culture in the future? Are books, for instance, going to have associated NFTs? (Seriously, don't look now.)
Noah's extraordinary photography is not even in same ballpark as most NFTs, which tend toward disposable doodles and garish digital art. And yet...they are now in the same cinematic universe, with the same cartoonish twists and turns. One of the Lumberland NFTs, which Noah sold just last week for 0.408 ETH ($1,729), was put back on the market for a quick flip. First, it was listed by its owner for the juvenile price of 420.69 ETH (a cool $1,778,845), before it was lowered to 10 ETH ($42,284).
Regardless of artistic merit, because the underlying technology of NFTs is so aggressively decentralized and opposed to traditional forms of institutional, legal, and social forms of trust and value, to succeed they must rely instead on the cohesion that comes from an imagined community (of Bored Apes or VeeFriends), but since such communities often have weak ties — weakened further by online anonymity — they are currently only viable when supercharged by a speculative financial mania.
Noah Kalina may take beautiful photographs, but this is not a pretty picture.
[Further reading: Robin Sloan's recently published jeremiad, "Notes on Web3," provides a fuller humanistic rebuke to this creeping financialization of everything, and the creepy notion that all transactions will live on forever in a consumption ledger.]
The world without us: a map of the world with just green spaces and water, by Jonty Wareing:
(The map defaults to London, but you can go anywhere. Above, of course, is Boston.)
Last week in our library, Charlotte Wiman, a Northeastern grad student in paleohydrology, presented some fascinating research about the future of the Mississippi River on a quickly warming planet. She projected forward by looking backward, specifically by finding detailed descriptions of the river and its morphology in old books.
(Plate from Harold Fisk, Geological Investigation of the Alluvial Valley of the Lower Mississippi River, 1944.)
Taking measurements from the maps, cross sections, and diagrams within these books, Wiman and three colleagues were able to generate a hydrological model going back centuries, to a time in the middle ages when last there was a warming trend in the Americas. They then reversed the timeline of this model to see what the Mississippi will look like centuries in the future. Their unsettling conclusion: The mighty Mississippi will be much less mighty, with vastly increased evaporation along its entire pathway.
[Charlotte Wiman, Brynnydd Hamilton, Sylvia G. Dee, Samuel E. Muñoz, “Reduced Lower Mississippi River Discharge During the Medieval Era,” Geophysical Research Letters, 19 January 2021.]
Previously covered in Humane Ingenuity: the potent combination of human expertise and AI processing. A lingering question: how much “human” is needed? In a new paper on the identification of galaxy types, “Practical Galaxy Morphology Tools from Deep Supervised Representation Learning,” Mike Walmsley, Anna M. M. Scaife, et al. find that you don’t need much. Given a relatively small number of human-categorized shapes — just around 10 examples — machine learning tools can extract similarly shaped clusters from nearly a million examples with near 100% accuracy.
They have even built a little interface so you can find galaxy shapes yourself.
Meanwhile, back here on Earth: “For legible pages from World War I handwritten diaries held at the State Library of Victoria, AI services are able to correctly transcribe them at a level between 10% to 49% accuracy.” Not great! Understanding century-old cursive handwriting may end up being one of the hardest problems in AI/ML.
(Sofia Karim, Lita’s House – Gallows (ফাঁসির মঞ্চ) / I (detail), 2020, photographic drawing, from the new Infinitude exhibit at Northeastern University.)