Plutonic Rainbows

The pool sat under a galvanised-steel pyramid. That was the detail that lodged in your head if you ever swam there. Faulkner Brown finished Bletchley Leisure Centre in 1974, a year when the British state still believed it could provide a tropical interior to a Buckinghamshire new town, and the answer it arrived at was a space-frame tetrahedron over a heated pool, glazed to the sightlines, surrounded by sub-tropical planting that the maintenance crew pruned during the night shift. The building came down in 2010, replaced by something with windows that did not need to keep the heat of the tropics inside an East Midlands winter.

There was a peculiar dread to those rooms even when they were new. The chlorine fog hit your sinuses in the entrance corridor and stayed with the rest of the day. The acoustics of tile and concrete turned a child's shout into a prolonged metallic ring that bounced off the roof and came back wrong, half a beat late, slightly higher in pitch. The fluorescent lighting was always too much for the eye and not quite enough for the camera, so every photograph from the period has the same washed-out yellow that makes the swimmers look as if they have been preserved rather than caught. You walked through a footbath of disinfectant before the water itself, and the smell of it was the smell of being small and slightly afraid.

Otto Saumarez Smith's Lost World of the British Leisure-centre Boom, published in 2019 in the Twentieth Century British History journal, makes the case that these buildings were the last serious municipal architecture this country produced. His phrase is "holiday atmosphere", lifted from the trade press of the period: pop imagery, fun, sun, the unashamed lowbrow populism of a council that thought a working-class family in Bletchley deserved to feel for an afternoon as if they were in Mallorca. Twenty-nine degrees centigrade, year-round, paid for out of the rates.

That model began to collapse the moment the funding mechanism behind it did. Coventry Sports Centre, the zinc-clad "Elephant" of 1976, closed in 2020. Swindon's Oasis, with its perspex dome, went the same year. Bradford's Richard Dunn Sports Centre, the Brutalist tent-roofed complex inspired by Kenzo Tange's Yoyogi gymnasium, shut in 2019 after a council decision driven by the cost of upkeep, and during the pandemic it served as a temporary morgue. The Twentieth Century Society's campaigns manager Oli Marshall told Dezeen in 2022 that every pool in the country was now at risk: the pandemic, the global chlorine shortage, the energy price shock, all of it falling on a building type designed in an era of cheap municipal gas.

What survives mostly survives by listing. The Oasis got Grade II status in 2021. Richard Dunn got it in 2022. The buildings themselves are mothballed, half-derelict, surrounded by hoardings, the tropical planting long dead. You can find drone footage on YouTube of the empty pools, the tile still gleaming, the ghost of a footbath at every threshold.

Five hundred leisure centres have shut since 2010, and the pyramid roof is a kind of period marker for the moment a place like Bletchley could still be promised the tropics by its own council. The dread of those rooms came from the gap between the promise and the building's own admission that the promise was provisional. The chlorine fog, the metallic echo, the yellow light, were the texture of an institution that knew, somewhere, it would not last.

David Silver came out of stealth this morning with $1.1 billion in seed money and a thesis that runs against the prevailing weather. Ineffable Intelligence, his new lab, plans to build models that learn from their own experience rather than from the internet's archive of human writing. The round, reported by CNBC, is the largest seed in European history. Sequoia and Lightspeed co-led it. Nvidia, Google, DST Global, Index, and the UK Sovereign AI Fund piled in. The post-money valuation is $5.1 billion before there is a product, a paper, or, as far as anyone outside the cap table can tell, a model.

Silver is not a celebrity outside the field, but inside it he is the person who designed AlphaGo and AlphaZero. The work that made DeepMind's name in 2016 was reinforcement learning, agents that played themselves until they were better than anyone alive. AlphaZero learned chess from scratch in nine hours and then beat Stockfish, which had spent two decades absorbing every game humans had ever recorded. The lesson Silver took from that, and which he is now raising a billion dollars on, is that human data is a ceiling. Anything an AI can only learn from us cannot, by definition, exceed us.

The pitch deck almost writes itself. The frontier labs are spending the GDP of small countries on training runs that cannot continue at this clip, because the supply of high-quality human text is genuinely close to exhausted. The fix the industry has settled on is to pay forty labelers to write rubrics and hope the model generalises. Silver's bet is that the whole labelling layer is a distraction, that the actual gradient runs the other way, that a system which generates its own curriculum from interaction with an environment will skip the human bottleneck entirely. "Our mission is to make first contact with superintelligence," is how he put it in the press release. I flinched a little at the phrasing, but the technical claim underneath is real and not new. He has been making it for years.

What is new is that Sequoia is now writing a nine-figure cheque to fund the experiment in public. The talent flight from the big labs has been gathering for eighteen months. Mira Murati's Thinking Machines, Ilya Sutskever's Safe Superintelligence, and now Silver. Each one walks out of a hyperscaler with a plausible technical story, a Rolodex full of researchers, and a venture market willing to fund a five-billion-dollar valuation on day zero. The implicit critique is the same in every case: whatever the labs are doing inside, it isn't ambitious enough.

I am not sure the experience-based path scales the way the self-play games did. Chess and Go are closed worlds with crisp reward signals. The physical world is messy, slow, and expensive to simulate at fidelity. Reward hacking is the default outcome, not the edge case. The companies that have tried to do open-ended RL at the scale of, say, robotics, or science, or software engineering, have spent years learning how hard the reward-design problem actually is. None of that is solved by money, although money buys time to keep trying.

Still, a billion dollars is a real signal, and the people writing the cheques are not naive. The bet, as I read it, is not that Silver will reach superintelligence. The bet is that he will produce one or two genuinely novel results within three years that the existing labs cannot replicate without rebuilding their training stacks from the ground up. That is enough to clear the seed. Whether it is enough to clear the next round, when the science gets specific and the costs go vertical, is a question for 2028.

Six months after the last restructuring, OpenAI and Microsoft have rewritten the deal again. The new agreement, announced this morning on OpenAI's blog and almost immediately on every business desk in New York, ends the exclusive licensing relationship that has been the load-bearing wall of the partnership since 2019. Microsoft keeps its rights through 2032, but those rights are now non-exclusive. OpenAI can ship its models on Google Cloud, on AWS, on whatever infrastructure a customer happens to prefer.

That last clause is the one that matters. The Financial Times reported in March that Microsoft was considering legal action to block a $50 billion enterprise deal between OpenAI and Amazon, on the grounds that the original exclusivity language covered exactly that scenario. The new terms quietly retire the threat. Azure remains the first port of call. OpenAI ships there first, "unless Microsoft cannot and chooses not to support the necessary capabilities," at which point everything else is fair game. In practice, that escape hatch is wide enough to drive a fleet of TPU pods through.

The financial side has been turned around. Microsoft has paid a revenue share to OpenAI for years; that stops now. OpenAI continues to pay 20% back to Microsoft, but the obligation is capped and runs only through 2030, not indefinitely. So Microsoft trades open-ended upside on a runaway customer for a fixed ceiling and a clean exit window. That is not the move of a company that thinks the next two years will be the most valuable two years.

I am trying to read the body language and finding it hard. The official framing is mutual, friendly, "next chapter." The market read is more guarded; Microsoft shares dropped about 1% on the announcement, and Wedbush put out a note calling the deal a net positive because it ends a year of "limbo." Limbo is a generous word for it. Denise Dresser, OpenAI's revenue chief, sent an internal memo earlier this month complaining that the partnership had "limited our ability to meet enterprises where they are." Enterprises, in that sentence, means customers who already buy Bedrock from AWS and Vertex from Google and would quite like to add ChatGPT-class inference without having to re-architect their procurement.

There is a longer arc here that the press release does not mention. OpenAI's restructuring last October turned the nonprofit-owning-a-for-profit into something closer to a conventional company. Microsoft's stake, depending on whose valuation you trust, sits somewhere between $135 billion (NYT) and $225 billion (Forbes), or roughly 27% of OpenAI on paper. Wedbush thinks today's renegotiation clears a runway for an IPO, and that part feels right. Public-market filings work better when your distribution rights are not contingent on a single counterparty's willingness to keep the relationship warm.

What hasn't changed: the money still goes in circles. Microsoft funds OpenAI, OpenAI buys Azure, Microsoft books the cloud revenue, and the headline number gets bigger every quarter. The new agreement loosens the loop without breaking it. OpenAI gets to court Bezos and Pichai while still paying its toll to Redmond. Microsoft gets locked-in cloud spend without the political cost of being the only adult in the room.

It is the kind of deal you sign when both sides have grown up and noticed the other one is now their main competitor's landlord.

Pick up a rental cassette from a bin at a car-boot sale and the first thing you read is not the cover. You read the stickers. A yellow neon "£1 OVERNIGHT" pasted across the actor's face. A red genre flag, HORROR, half-curling at the corners. A barcode sticker on top of an older barcode sticker. A "BE KIND, REWIND" in a typeface designed by someone who had three hours and a Letraset catalogue. Then, underneath all of it, the original sleeve art the distributor paid an illustrator £400 for in 1986.

These layers were not meant to be a record of anything. The shop manager wanted to flag the new releases on Tuesday and the late returners on Friday, so he peeled the old sticker off, or didn't, and slapped a new one over the top. Twelve years later, when the shop closed and the stock went to a wholesaler and from there into a cardboard box at a market in Wolverhampton, the sleeve carried the entire commercial autobiography of one rental counter. Price changes. Genre reshelvings. The week the BBFC sticker for an 18 was added because a parent had complained. The fortnight in 1992 when the shop ran a promotion on tapes that had not been hired in six months.

This is what Jacky Lawrence and Josh Schafer's Stuck on VHS: A Visual History of Video Store Stickers, published by Birth.Movies.Death. and sold through Mondo, has the patience to take seriously. A hundred and sixty pages of it, plus three pages of stickers bound in. The book treats the rental cassette the way a museum treats a Roman ostracon, as a thing that accidentally preserved the conditions of its own use, because nobody at the time thought the conditions were worth preserving.

What the layered stickers carry is not nostalgia. Or not only nostalgia. They carry the economics of the late video shop, the way a small business managed shelf-space without a database, the margin of error in a manual stock system. You can read a price war on a single sleeve, the £3.50 of 1989 crossed out, the £2.50 of 1991 crossed out, the 99p of 1996 underneath the "CLOSING DOWN" flash. The rental shop was a kind of analogue spreadsheet, and the spine of every tape was a row in it.

Academic paratextual work has caught up to this only recently. The 2023 Accidental Archivism volume, written for cinema archivists trying to figure out what to do with the rogue archives of fan sites and zine collections, mentions VHS sleeves in the same breath as performance scripts and photocopied pamphlets. The implication is that the sleeve is a document, which means the stickers are an annotation layer on the document, which means the rental shop, without intending to, ran a forty-year participatory archive on the high street.

It died, of course, on the back of a worse archive. Streaming keeps no sticker. There is no overdue flag on a Netflix browse page, no genre tag in fluorescent yellow that the manager hand- applied because the official one had peeled off. The metadata is clean, complete, and impossible to read against itself. You can't see, on Prime Video, that someone in 1994 thought Predator 2 should be reshelved from action to sci-fi, or that the Friday sticker fell off in the rain. There is no record of the disagreements.

The sleeves at the car-boot sale still hold theirs. Take one home and peel a corner. There will be another sticker underneath. Then another.

The most consequential sketch in 1980s luxury was drawn on an airplane sick bag. The flight was Air France, Paris to London, sometime in 1983. Jane Birkin had been seated next to a polite older man in first class, her wicker basket had tipped, and the contents of her life as a thirty-six-year-old mother of two had spilled into the aisle. She apologised, complained about the absence of a leather bag big enough to hold a script, a baby bottle, and the rest, and her seatmate suggested she try Hermès. She replied, more or less, that the day Hermès made one with pockets she would buy it.

He smiled and said, in the line that has been repeated in every retelling since: I am Hermès.

Jean-Louis Dumas was four years into running the house his great-great-grandfather had founded. He listened to her specification, which boiled down to a single phrase, a Kelly, four times the size, with pockets, and started drawing. The sketch went onto the only paper available in the cabin. He took her name and address. About a month later a cardboard mockup was waiting for her at Hermès' Faubourg Saint-Honoré flagship.

The bag launched in 1984.

It is worth pausing on what Dumas actually did, because the plane-and-sick-bag story has flattened into pure mythology and the design decisions tend to disappear inside it. He went back to the Haut à Courroies, the equestrian travel bag Hermès had been making since around 1900 to carry a saddle and boots between stables. He kept its proportions, kept the saddle stitching the house had perfected in the carriage-trade nineteenth century, kept the flap closure with a turn lock and clochette and the four protective metal feet underneath. Then he softened the leather, fitted two rolled top handles, and shortened the body so a woman could carry it in the crook of an arm.

The first model was supple black leather, sizes 35 and 40 centimetres, and retailed for around $2,000. Each one took a single craftsman fifteen to twenty hours to assemble. Jane herself was given a prototype in 1985, with brass hardware and a shoulder strap she added herself. She covered it in stickers, beads, and a Médecins du Monde sticker, and developed shoulder tendinitis from carrying it.

The interesting thing, looking at this from forty years on, is how unfashionable the choice was at the time. The early 1980s was the era of the European designer logo, the gilded LV monogram and the Gucci horsebit, and Hermès' nearest cousin was Loewe, not Vuitton. The decision to launch a leather tote in 1984 without a visible logo, named after a singer rather than a royal, priced like a piece of furniture, and built to be carried hard, looks now like a refusal to compete with the trend at all. By the time the supermodel-era runway made the labelled handbag a screaming part of the silhouette, Hermès had positioned the Birkin in the opposite register, quiet, non-shouting, identifiable only by people who could already identify it.

This was the trick. The Kelly had carried Hermès through the postwar decades on the back of Grace's photograph; the Birkin carried it through the nineties on the back of word-of-mouth. You did not see the Birkin in a magazine ad. You saw it on Carolyn Bessette-Kennedy on a Manhattan sidewalk and on the fictional handful of Sex and the City viewers a decade later. The waiting list became, by the late nineties, the marketing campaign.

Birkin sold her own prototype in 2011 for $162,000 to fund earthquake relief in Japan, and Sotheby's sold it again in July 2025 for $10.1 million, the highest price ever paid for a handbag. The arc from sick-bag sketch to ten-million-dollar auction lot took forty-two years and almost no advertising. The old house at 24 Faubourg Saint-Honoré had spent a century learning how to make a saddle. It used the last twenty years of the twentieth century turning that knowledge into the most coveted object in luxury, by listening to a woman complain on a plane.

The plan was not to repel the invasion. The plan was to slow it down. A Southern Command memo dated 22 June 1940 set the intention plainly: divide England into small fields surrounded by a hedge of anti-tank obstacles, close the gates behind the German armour, and let the mobile columns round up the cattle. The cattle, in this metaphor, were the Wehrmacht. The hedge was concrete.

General Edmund Ironside had three weeks. By the end of June 1940 the Home Defence Executive was passing plans for thousands of pillboxes and tank-traps along beaches and at nodal points, and work began everywhere at once. Around 28,000 hardened field defences went up between June 1940 and February 1941, when the order came down to stop building. Ironside was already gone by then, replaced in late July by Sir Alan Brooke, who disliked fixed lines and preferred mobile reserves. The pillboxes remained. They had cost too much to demolish.

About a quarter of them are still here.

Roughly 7,000 concrete pillboxes survive across Britain, most of them along the GHQ Line, the 400-kilometre stop-line running from Somerset to the Medway, designed as the last fallback before London and the industrial Midlands fell. In Surrey it follows the Wey from Farnham to Shalford, then the Tillingbourne to Wotton, the Pippbrook to Dorking, the Mole to Horley. The pillboxes sit at roughly 500- metre intervals, sighted to cover the river or the road, often half-buried in undergrowth now. In Essex, between Great Chesterford and Canvey Island, over a hundred FW3 boxes still exist; about forty of them are highly visible from the A130, hexagonal concrete drums sitting in field corners as if they had grown there.

What strikes you about the surviving boxes is how indifferent the landscape has been to their purpose. A Type 22 hexagonal pillbox in a Suffolk field is now a shelter for sheep. A Type 24 on the Stroudwater Canal is a fishing platform. The loopholes have been blocked up with breeze-block, or left open, or filled with empty cider cans. Iron hooks for camouflage netting still poke from the roofs. The Kent Archaeological Society's Victor, surveying a pillbox in Tonbridge, noted with quiet pride that it was bubble-level and vertical, showed no sign of having been dislodged, and was only superficially damaged at the firing apertures. They built them to last a week of bombardment. They are lasting forever.

This is what makes them hauntological in a way that, say, an abandoned Victorian railway viaduct is not. A viaduct is a thing that worked, then stopped working. A pillbox is a thing built for a future that never arrived. The men who poured the concrete in the wet summer of 1940 believed, with reasonable confidence, that German armour would shortly come along that road. Most of those men did not live to know how precisely they had been wrong, and how completely. The boxes are a frozen anticipation, a fortified flinch. The country built itself a defensive crouch and then quietly forgot it was crouching.

There is also the matter of category drift. Henry Wills published his survey Pillboxes: A Study of UK Defences in 1985, and the Pillbox Study Group has been recording sites since the 1990s. In 2003 Historic England (then English Heritage) issued Power of Place, the document that finally reframed the boxes from eyesores to be cleared into part of the historic landscape worth keeping. The bureaucratic sentence had taken sixty years. By then, half of the originally-surveyed boxes had already been lost, mostly to motorway construction, gravel extraction, and the steady incremental tidiness of farmers who wanted their fields back. Listing came late, as listing usually does in Britain.

What the surviving boxes carry, more than military history, is a kind of bureaucratic embarrassment. Nobody quite knew what to do with them in 1946, and nobody quite knew in 1976, and the default position of the British state when it doesn't know what to do is to leave the thing alone and let weather and ivy do the work. This is also how we treat asbestos garages, redundant village telephone exchanges, and the sort of public information films that arrived in primary schools without anyone deciding they should. The pillbox is the same gesture in concrete: an institutional shrug that lasts seventy years.

You can still walk a stop-line. Bring an Ordnance Survey map and the Pillbox Study Group's locations, and follow the Wey or the Stroudwater or the upper Thames. The boxes appear roughly where they should. Some have plaques. Most do not. Sheep wander in and out of them. Children climb on them. The country has metabolised them so completely that the question of what they are for has stopped being asked, which is, I think, the only honest answer it could have arrived at.

The standard origin story for backpropagation gives the year as 1986 and three names on the byline: David Rumelhart, Geoffrey Hinton, Ronald Williams. The paper ran in Nature on October 9, volume 323, four pages, a tidy little letter about training networks of neuron-like units by adjusting weights to minimise a measure of error. Hidden units, the paper says, would come to represent useful features of the task domain. That sentence is the one that mattered. It promised that a network could learn its own internal vocabulary, instead of being hand-fed one by a human.

The paper is rightly famous. It is also not the first time backpropagation existed.

Twelve years earlier, in November 1974, a Harvard graduate student called Paul Werbos submitted a thesis in applied mathematics that worked the same algorithm out from the direction of optimal control theory. Werbos called it reverse-mode gradient computation, framed it as a way to steer complex dynamic systems toward a goal, and showed how the chain rule, applied backwards through a sequence of differentiable operations, gave you exact derivatives at a cost roughly equal to running the system forward once. Different vocabulary, same mathematics. He had the insight before the field he eventually joined was ready to receive it.

The thesis sat. Symbolic AI was the fashionable thing in the 1970s, expert systems were eating the funding, and neural networks were still under the cloud Marvin Minsky and Seymour Papert had thrown over them in 1969 with Perceptrons. A man with a method for training multilayer networks had nowhere useful to publish it, because nobody serious wanted multilayer networks. Werbos worked at the National Science Foundation for most of the next decade. The thesis was cited a handful of times.

What changed in 1986 was not the algorithm. It was the surrounding cast. Rumelhart, working at UC San Diego, had been trying to build a connectionist alternative to symbolic cognition since around 1979 and had spent years convinced that multilayer perceptrons with learned hidden representations were the missing piece. Hinton was at Carnegie Mellon, having shifted from Boltzmann machines back to gradient methods because Boltzmann was punishingly slow. Williams handled much of the implementation work. The three of them rediscovered the procedure independently, ran it on toy problems that produced results an outsider could see and admire, and packaged it inside the much larger Parallel Distributed Processing volumes published the same year. The Nature letter was the four-page advert. The two PDP books were the argument.

Werbos did get credit, eventually. By the late 1980s he was publishing his own extensions, including backpropagation through time for recurrent networks, and the textbooks gradually started naming him in the lineage. There is a small genre of backpropagation-history essays now, and they all reach the same verdict: the algorithm was rediscovered at least three times before 1986 (Werbos, then David Parker at MIT in 1985, then Yann LeCun in a French conference paper the same year), but it was the Rumelhart-Hinton-Williams presentation that broke through.

The instructive part is not who deserves the credit. The instructive part is what the discrepancy tells you about how ideas actually land. Werbos had the maths in 1974 and almost nobody noticed. Rumelhart, Hinton and Williams had the same maths in 1986 and the field reorganised around it inside a decade. The difference was an ecosystem: a community of researchers ready to use the result, a crisp pair of papers that made the result legible, hardware that was finally fast enough to make small networks do interesting things, and worked examples (the Nature letter itself trains a small network on a family-tree relationship task) where the network learned something a person could feel.

Twenty-six years after the Nature paper, two GPUs in Krizhevsky's bedroom took the same algorithm and embarrassed two decades of hand-engineered computer vision in a single afternoon. The maths in those CUDA kernels is still the maths in Werbos's thesis. Compute caught up. Data caught up. The story of backpropagation is not a story about who invented something. It is a story about how long good ideas can sit on a shelf before the rest of the world is ready for them.

Meta is cutting 8,000 jobs starting May 20, roughly ten percent of its workforce, and not filling another 6,000 open roles. Microsoft is offering early retirement and voluntary buyouts to about 8,750 US employees, near seven percent of its US headcount. Both announcements landed inside the same 48-hour window. Both companies report earnings on Wednesday. And both are on track to spend a combined sum on AI infrastructure this year that makes those payroll numbers look like rounding.

The framing the companies are using is interesting because it has finally stopped pretending. Janelle Gale, Meta's chief people officer, told staff the cuts are needed to "offset the other investments we're making." She did not say which investments. She did not have to. Zuckerberg has said the quiet part out loud several times this year already: 2026 is the year of "major AI acceleration," with planned spend north of $115 billion on data centres, custom silicon, and the people who can build them. Microsoft's number is comparable. Across Meta, Microsoft, Alphabet, and Amazon the collective AI infrastructure outlay this year clears $700 billion.

The arithmetic, then, is plain. You move money from one column to another. You stop paying a recruiter and start paying for a GB200 rack. You stop paying a layer of middle management at Reality Labs and start paying TSMC for a wafer allocation. The headcount line shrinks because the capex line is eating it. There is no hidden mystery about where the money is going.

What's new is that the labour story is no longer being told through the language of a downturn. There is no recession to blame. Hyperscaler revenue is up. The cuts are not because business is bad. They are because the business has decided that a particular shape of human labour is now optional. Coding, recruiting, ops, mid-tier programme management. The kinds of work where an agent does eighty percent of the task and a smaller team does the cleanup.

I am not sure the agents are quite there yet. The shootouts between GPT-5.5 and Opus 4.7 are still close enough that nobody outside the labs can confidently call a winner on a given task, and the public benchmarks have a known habit of flattering the model that wrote them. But the executives are not waiting for proof. They are pricing the bet now, against this year's salary budget, on the assumption that the gap closes before the next fiscal year begins. If it does, the cuts look prescient. If it does not, the cuts still happened, and the people are still gone, and the inference bill arrives anyway.

There is an honesty to it that I almost respect. For most of the last decade, "efficiency" was the euphemism that companies reached for when they wanted to fire people without saying why. The word still gets used. But the underlying bookkeeping has shifted. Efficiency now means a specific trade: a payroll line exchanged for a compute line, a headcount slot exchanged for a token bill that the CFO can model with a straight face.

Wednesday's earnings will be the test. If the analysts ask about the labour impact in the same breath as they ask about Azure growth, the equation has been accepted. If they ask only about capex, it already has been.

Pick up any phone made in the last forty years and look at the keypad. The 2 has ABC under it. The 6 has MNO. The 9 has WXYZ. The 1 has nothing, and neither does the 0. Nobody dials letters anymore, not really, and yet the layout is fixed. It survives every redesign of every handset. It survives the move from metal to plastic to glass. It survives the death of the keypad itself, persisting as a virtual grid on a touchscreen that could just as easily render any other arrangement and chooses not to.

The reason is a naming convention that died sixty years ago. Until the early 1960s, telephone numbers were not numbers, they were words attached to numbers. You did not call 685-9975, you called MUrray Hill 5-9975, and the operator routed you on the strength of the first two letters of the exchange name. The Ricardos on I Love Lucy had MU 5-9975 because Murray Hill was the east side of Manhattan. The whole city was a quiet atlas of these prefixes: PEnnsylvania, TRafalgar, YUkon, BUtterfield. London had WHItehall and KENsington and SLOane. San Francisco had KLondike on 55x because there were almost no other words you could build out of the letters available on those digits.

The exchange names existed because the manual-to-automatic transition of the 1920s and 1930s needed a way to make seven-digit numbers memorable in a country where most people had not yet memorised any. AT&T issued a recommended list of exchange names around 1955 in its Notes on Nationwide Dialing, including a short catalogue of neutral words (LIberty, LIncoln, KLondike) for small communities. You looked your number up in the directory and the first two letters were printed in bold. The bold told you which buttons your finger had to find on the rotary dial.

By 1960 the New York Telephone Company had started issuing all-numeric exchanges, and a small, articulate, very furious group of San Franciscans formed the Anti-Digit Dialing League to fight it. They lost. The Committee of Ten Million To Oppose All-Number Calling lost too. By the late 1970s the letter exchanges had been pushed out of the white pages even in New York, where they had clung on longest. The names were gone. The letters stayed.

Once the system did not need them, marketers found them. The toll-free 1-800-FLOWERS line went live in the mid-1980s. 1-800-COLLECT followed. Vanity phonewords became a small industry, supported entirely by a mapping that the phone company had stopped caring about decades earlier. Then T9 predictive text arrived in the late 1990s and, on a generation of feature phones, the 2-9 letter groups became the only way most teenagers wrote anything for about a decade. SMS culture was built on a keypad that had been laid out for a vanished switching system. Tap 7777 to get S, wait, tap 4 to get G. The cadence of an entire pre-iPhone adolescence was metered to a 1920s alphabet.

What I find strange is the degree of the persistence. There is no reason a smartphone keypad needs ABC on the 2. The keypad is software. Apple, Google, and every Android OEM could ship a numeric-only dialler tomorrow and almost nobody would notice for a fortnight. They never will. The letters are vestigial but load-bearing: every business with a vanity number (1-800-FLOWERS still answers, still ships), every emergency line that asks you to remember a word, every accessibility feature that lets a blind user dial by letter instead of digit, depends on a mapping that the system that produced it has not used since the Anti-Digit Dialing League gave up.

Hauntology is supposed to be about the future that did not arrive. The keypad is the opposite case. It is a past that refuses to leave because the cost of evicting it is, every year, slightly higher than the cost of letting it stay. Murray Hill is not coming back. The letters that pointed to it are not going anywhere.