Posts Tagged ‘AI’
“Where grows?–where grows it not? If vain our toil, / We ought to blame the culture, not the soil.”*…
Even as agricultural land is becoming a coveted investment (as manifest in the purchases of billionaires like Stan Kroenke, Bill Gates, and Jeff Bezos, and by institutions like Nuveen and the Canadian Pension Investment Board and by publicly-traded REITs like Farmland Partners and Gladstone Land Corp), there’s another class of investor– with a very different use case– on the hunt. Joy Shin and Ryan Duffy report…
Last year, a datacenter developer started working the phones along Green Hill Road in Silver Spring Township, PA, outside Harrisburg. Mervin Raudabaugh got the call: a mystery buyer wanted to buy his 261 acres of farmland. The developer offered him $60,000 an acre for the land the 86-year-old had farmed for six decades. Mervin turned it down, selling to Lancaster Farmland Trust for <$2M instead, thereby locking the soil into agricultural use. “I was not interested in destroying my farms,” he told a local Fox affiliate.
Two things about this story might have been unthinkable a generation ago: that anyone would offer a farmer nearly $16M for that land, and that it’d be worth more dead (paved over) than alive (producing food).
The Supermarket of the World
For the better part of a century, that’s what America was. From 1959 through 2018, the country ran an agricultural trade surplus every single year, peaking near $27B in 1981, when soybeans, corn, wheat, and rice flowed out of the heartland in volumes that functioned as soft power and hard trade leverage. (When the Soviet harvest failed in 1963, Khrushchev had to buy American wheat through private US grain companies: at market rate, without credit, shipped on American vessels, which was a humiliation leveraged by his enemies to oust him the following year.)
Then, in 2019, the curves crossed. The U.S. has since run a deficit in four of the last six fiscal years. Last year, we imported $43.7B more in agricultural products than we sold.
Washington has started saying the right words. Last month, the USDA and Department of War signed a memorandum designating agriculture as a national security priority. Multiple bills linking food security to national security percolated through the last Congress. If you talk to the right folks in Washington, you’ll hear agriculture now being discussed the way semiconductors were in 2021 — as a sovereign capacity that a serious country cannot offshore.
All of which sounds right, none of which changes what is happening on the ground. Because the ground is the problem.
In real estate, you think in square feet, in proximity, in comps. Farmland trades in acreage, water tables, growing seasons, and soil composition. And right now, profitably farming that acre is just about the hardest it’s ever been.
Since 2020, seed costs have climbed 18%, fertilizer 37%, fuel 32%, and interest on operating loans 73%. Labor is up 50%. These costs never came back down after the 2021-22 supply chain shock, but crop prices did, creating a double squeeze on farmers. Farmland has appreciated nearly four-fold from ~$1,090/acre in 2000 to $4,170 in 2024.
Some 40% of U.S. farmers are over 65. The American Farmland Trust estimates nearly 300M acres will change hands through inheritance in the next two decades. When it does, the math facing each heir will look a lot like Mervin’s. What would you do: keep farming a business with collapsing margins, or if one was offered, take the check?
A Collision of Old & New Economies
Datacenters, chip fabs, and other megaprojects need what farms need: flat land, abundant water, reliable power, and access to transport.
In Loudoun County, VA, ground zero of America’s datacenter buildout, farmland already lists at $55,000–$79,000/acre, a significant premium over the statewide average because markets are pricing in the possibility the land will convert from farmland to computerland.
Conversions are large and getting larger. Meta’s $10B compute cluster in Richland Parish, Louisiana, sits on 2,250 acres of former soybean fields. Samsung’s new $17B fab occupies 1,200 acres outside Taylor, Texas, a town that once called itself the largest inland cotton market in the world. Micron’s $100B megafab is going up on 1,400 acres of former agricultural land and wetlands in Clay, New York. These are some of the largest private investments in American history, and among the most economically and strategically consequential bets we’re making as a country. You can’t help but notice the symbolism of it all: each is being built on rural land that was growing something one or two generations ago.
Datacenter developers, who already need some PR help, have seen local opposition to these projects emerge as a real planning risk, with farming families showing up at county meetings to argue that once the land converts, it will never come back.
Nobody should pretend this is irrational. A fab generates more economic value per acre than any soybean field ever will, the jobs pay better, and the strategic logic of onshoring chips is sound. But the math that makes each individual conversion obvious is the same math that, in the aggregate, leaves you structurally short on food. The country is losing about 2,000 acres a day, with 18M more projected to convert by 2040.
The Flow of Capital
As Washington works to subsidize the farming, to the tune of $10–$15B in federal support each year, Wall Street is betting on the land underneath it leaving farming.
Nuveen Natural Capital, a subsidiary of TIAA, manages $13.1B in farmland across 3M acres globally and recently launched a REIT targeting $3B in new capital. Those holdings have appreciated far beyond what crop income would justify, because it follows the pattern of a conversion optionality play: buy well-located agricultural land at agricultural tax rates and wait for rezoning.
Nearly 95% of American farms are still family-run, but most are modest operations. The 6% of farms generating $1M+ in sales produce 78% of everything, up from 69% just five years ago. Farming has developed the power-law distribution of a winner-take-most industry, except the winners don’t get to set their own prices. The family farm persists in name, but the economics (and economies of scale) increasingly push it to operate like a corporation or exit.
And institutional investors have some strange bedfellows on their side of the orderbook. Foreign investors held an interest in nearly 46M acres as of 2023 – 3.6% of all privately held farmland – up 85% since 2010. Canada alone holds 15M acres. China, which cannot feed its population from its own soil, built COFCO International into a state-backed grain trader that does $38.5B a year and accumulated millions of acres globally. Saudi Arabia was pumping Arizona’s groundwater through Fondomonte, a state-linked operation growing alfalfa for export, until Arizona killed the leases in 2023. Those countries treat productive soil as something worth a sovereign premium, and something you want to physically control…
[The authors recount the history of “Agro-Doomerism” and consider the (largely technological) potential solutions to the conundrum: “This is a hard problem, but it is a solvable one, as shown by the long history of technological revolutions in agriculture. Today, a set of technologies that were each too expensive or immature a decade ago have converged to the point where the raw inputs for a farm, ex land, can get radically cheaper, all at once.” They enumerate some of those potential saviors, and conclude…}
… The long arc of agro-doomerism and technological revolutions say there’s reasons for optimism. Many times before, the “math” said we’d run out of food; many times before, new science, systems, and processes came along that changed the denominator and proved the doomers wrong. Hoping and praying for AGI or another Norman Borlaug [the father of the Green Revolution] to save our bacon is not a strategy, but abundance-oriented technology stacks that don’t force a zero-sum choice between preservation and productivity might be. We should look at systems that help unfallow and uplift acres, making farmland competitive enough that we don’t pave over too much and one day realize we want the topsoil back – or our ag trade deficit erased.
The bet worth making is 1) to never bet against America, of course, and 2) that something similar will happen here: that productivity, not preservation alone, will close the gap. This is a generational opportunity, a category deeply in the national interest, and a sector wanting more capital, technology, engineers, and founders to show up. Those who get there first will be serving a gigantic market, and attacking a problem that Washington has acknowledged is existential but has no idea how to productively solve.
The supermarket of the world was built on cheap land and cheap water. Neither are cheap anymore, and both are being bid up by us – via population growth – as well as the industrial renaissance that we care so deeply about. But that doesn’t mean we can forget foundational inputs – literally – to our way of life…
Farming vs. fabs (and data centers)… American agriculture is caught in a collision between old and new economies: “The Supermarket of the World.”
* Alexander Pope
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As we contemplate cultivation, we might note that this, the third week in March, is National Agriculture Week.
“Beauty is the first test: there is no permanent place in this world for ugly mathematics”*…
Is mathematical beauty real? Or is it just a subjective, human ‘wow’ that is becoming redundant in an AI age? Rita Ahmadi explores…
It is a hot July day in London and I take the bus to Bloomsbury. I often come here for the British Library, the British Museum or the London Review Bookshop. More than a location, Bloomsbury feels like stepping into a work of art – maybe one of Virginia Woolf’s stories, or Duncan Grant’s paintings.
This time, I am here for mathematics: the Hardy Lecture at the London Mathematical Society (LMS), named after G H Hardy, a professor of mathematics at the University of Cambridge, a member of the Bloomsbury Group, and a president of the LMS. You may know him from the film The Man Who Knew Infinity (2015), in which he’s played by Jeremy Irons.
The 2025 lecture is by Emily Riehl of Johns Hopkins University in Baltimore, who is talking about a complex mathematical ‘language’ known as infinity category theory: could we teach it to computers so that they could understand it? If successful, computer programs could verify proofs and construct complex structures in this area.
A few seats to my left, I recognise Kevin Buzzard, wearing the multi-coloured, patterned trousers he’s known for among mathematicians. Based at Imperial College London, Buzzard is working on a computer proof assistant called Lean. His interest is personal: after long disputes with a colleague over a flawed proof, he lost trust, as he often puts it, in ‘human mathematicians’. His mission now is to convince all mathematicians to write their proofs in Lean. In the Q&A after one of his talks, he said of the debate between truth and beauty in mathematics: ‘I reject beauty, I want rigour’ – though his vibrant sense of fashion suggests otherwise.
Interest in an AI-driven approach to mathematics has been exponential, and many mathematicians have left traditional academic research to explore its potential. Recently, one group of distinguished mathematicians designed 10 active, research-level questions for AI to tackle. At the time of writing, various AI companies and researchers had claimed to find solutions, which were under evaluation by the community.
Sitting in the room in Bloomsbury, I stared at the Hardy plaque and wondered: would Hardy find proofs generated by AI beautiful? I wasn’t sure. He believed there should be a strong aesthetic judgment in mathematics, drawing parallels with poetry, and argued that beauty is the first test of good mathematics. He went as far as to say that there is no permanent place in the world for ugly mathematics.
If asked, many mathematicians today still talk about the aesthetic appeal of one approach over another.
Yet we live in a different century to Hardy and his Bloomsbury peers, with different technologies and techniques, so perhaps we need a clearer definition of what mathematical beauty actually is. Over the history of mathematics, we can find examples where both rigour and the pursuit of beauty have shaped mathematics itself. So, if we’re completely replacing this with a computer-assisted quest for truth and rigour, we ought to know what we’d be abandoning, if anything. Is mathematical beauty like the beauty in literature and art – or is it something else?…
[Ahmadi explores the idea of “beauty,” generally and in mathematics; traces the rise of AI as a tool, and concludes…]
… my own definition of beauty in mathematics would be as follows:
“Asimplemathematical structure that surprises even the most experienced mathematicians and transfers a sense of vitality.”
But is an AI-assisted proof simple or surprising? How do we define vitality in a machine? On these questions, the jury is out. Myself, I am torn. Maybe models just need more training to match our creativity. But I also wonder whether our limbic system is required. Can we write proofs without emotional kicks? I am also unsure if perfectly efficient brains can come up with novel revolutionary ideas.
Ultimately, this debate is about more than aesthetics; it is closely tied to the development of AI-assisted mathematics. If AI models can produce novel mathematical structures, how should we direct them? Is it a search for beautiful or truthful structures? A question that possibly guides the years to come.
Some mathematicians say they prefer the ‘truth’ and only the ‘truth’. However, my recent discussions with mathematicians showed me that most immediately recognise, enjoy, and even wholeheartedly smile at a beautiful piece of maths. In fact, they spend their whole lives in search of one…
Fascinating: “The eye of the mathematician,” from @ritaahmadi.bsky.social in @aeon.co.
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As we embrace elegance, we might send garcefully-calculated birthday greetings to Eduard Heine; he was born on this date in 1821. A mathematician, he is best remembered for his introduction of the concept of uniform continuity, for the Mehler–Heine formula, and for the Heine–Cantor theorem… all of them, quite beautiful.
“The economic system is, in effect, a mere function of social organization”*…

The AI race is, of course, afoot. But while most headlines focus on the new capabilities and benchmarks achieved by competing developers, Jeremy Shapiro reminds us that the winners in this race won’t necessarily be the most objectively capable, but rather the players who most effectively integrate the technology into their organizations, economies, and societies…
Artificial intelligence has rapidly become a central arena of geopolitical competition. The United States government frames AI as a strategic asset on par with energy or defense and seeks to press its apparent lead in developing the technology. The European Union lags in platform power but seeks influence over AI through regulation, labor protections, and rule-setting. China is racing to catch up and to deploy AI at scale, combining heavy state investment with administrative control and surveillance.
Each of these rivals fears falling behind. Losing the AI race is widely understood to mean slower growth, military disadvantage, technological dependence, and diminished global influence. As a result, governments are pouring money into chips, data centers, and national AI champions, while tightening export controls and treating compute capacity as a strategic resource. But this familiar race narrative obscures a deeper danger. AI is not just another general-purpose technology. It is a force capable of reshaping the very meaning of work, income, and social status. The states that lose control of these social effects may find that technological leadership offers little geopolitical advantage.
History suggests that societies unable to absorb disruptive economic change become politically volatile, strategically erratic, and ultimately weaker competitors. The central question, then, is not only who builds the most powerful AI systems, but who can integrate them into society without triggering a societal backlash or an institutional breakdown.
Karl Polanyi’s The Great Transformation, published in 1944, explains why the capacity to “socially embed” new market forces determines national strength. By “embeddedness,” Polanyi meant that markets have historically been subordinate to social and political institutions, rather than governing them. The nineteenthcentury idea of what he called a “self-regulating market” was historically novel precisely because it sought to “disembed” the economy from society and organize social life around price and competition rather than social obligation. As Polanyi put it in his most succinct formulation, “instead of economy being embedded in social relations, social relations are embedded in the economic system.”
Writing in the shadow of the Great Depression, Polanyi argued that the attempt in the nineteenth century to create a self-regulating market society that treated labor, land, and money as commodities generated social dislocation so severe that it provoked authoritarian backlash and geopolitical collapse. Stable orders, he insisted, required markets to be re-embedded in social and political institutions. Where they were not, societies sought protection by other means, which often translated into support for fascist or communist regimes that promised to tame the market. Today, it often means electing populist leaders who promise to break the entire existing order, both domestic and international.
Polanyi insisted that the idea of a “self-adjusting market implied a stark utopia” because such a system could not exist “for any length of time without annihilating the human and natural substance of society.” The interwar gold standard, for example, disciplined states in the name of efficiency, but it did so by transmitting economic shocks directly into social life. When democratic governments proved unable to shield their populations, they either abandoned the liberal economic order or turned authoritarian (or both)…
[Shapiro considers the history of the 20th century, in particular the rise of Nazi Gernmany, sketches the state of play in the AI arena, considers the challenge of embedding the changes that AI will bring in The U.S., Europe, and China, then teases out the ways in which the “industrial revolution” is different from it predecessors (in particular, the mobility of capital, the services (as opposed to manufacturing)-heavy character of employment today, and the accelerating pace of tech deelopment. He concludes…]
… Geopolitical competition in the AI age will not take place solely in clean rooms or data centers. It will also involve the less visible realm of social institutions: labor markets, communities, social protections, and political legitimacy. Polanyi teaches us that markets are powerful only when societies can bear them. When they cannot, markets provoke their own undoing and often in rather spectacular fashion.
The West’s success in the Cold War owed much to its ability to reconcile capitalism with social protection. If the AI age is another “great transformation,” the same lesson applies. Chips matter. Data matters. But the ultimate source of power may be the capacity to re-embed technological change in society without sacrificing cohesion.
That is not a liberal-progressive distraction from geopolitical competition. It is its hidden core.
“The Next Great Transformation,” from @jyshapiro.bsky.social and @open-society.bsky.social.
For a complementary perspective (with special focus on the interaction between labor and the supply side of the economy) pair with: “Brave New World- a third industrial divide?” from @thunen.bsky.social in @phenomenalworld.bsky.social.
And see also: “AI and the Futures of Work,” from Johannes Kleske (@jkleske.bsky.social). A response to dramatic predictions of AI’s impact– most recently, Matt Shumer‘s viral “Something Big Is Happening“: it’s a possible future, Kleske suggests. but only one possibe future– and one that, while plausible, isn’t likely (at least outside the rarified atmsphere of coding, in which Shumer operates). In a way that echoes Shapiro’s piece above, Kleske suggests that individuals need to better understand the technology in order to retain/regain some agency, and societies need the same kind of rekindled resistance to act clearly and with purpose in re-embedding AI, and markets, in society. Not the other way around… Resonant with the thinking of Tim O’Reilly and Mike Loukides featured here before: “The best way to predict the future is to invent it“; and with Ted Chiang‘s “ChatGPT Is a Blurry JPEG of the Web” and “Will A.I. Become the New McKinsey?” And then there’s the ever-illuminating Rusty Foster (riffing on Gideon Lewis-Kraus‘ recent New Yorker piece): “A. I. Isn’t People.”
For a look at a high-value, trust-based use case for AI that seems to avoid the objections to AGI (and speak to Shapiro’s points), see “The Middle Game: Routers at the Edge,” from Byrne Hobart.
But back to AGI… as Nicholas Carr observes, we might understand Bosrtrom’s “paperclip maximizer” “not as a thought experiment but as a fable. It’s not really about AIs making paperclips. It’s about people making AIs. Look around. Are we not madly harvesting the world’s resources in a monomaniacal attempt to optimize artificial intelligence? Are we not trapped in an “AI maximizer” scenario?”
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As we digest development, we might recall that it was on this date in 1962 that an early precondition for the revolution underway was first achieved: telephone and television signals were first relayed in space via the communications satellite Echo 1– basically a big metallic balloon that simply bounced radio signals off its surface. Simple, but effective.
Forty thousand pounds (18,144 kg) of air was required to inflate the sphere on the ground; so it was inflated in space. While in orbit it only required several pounds of gas to keep it inflated.
Fun fact: the Echo 1 was built for NASA by Gilmore Schjeldahl, a Minnesota inventor probably better remembered as the creator of the plastic-lined airsickness bag.

“To-day I think / Only with scents”*…

We’ve considered before smell, the unsung hero of the senses. Today, Kaja Šeruga explains how scientists using chemistry, archival records, and AI are reviving the aromas of old libraries, mummies and battlefields…
We often learn about the past visually — through oil paintings and sepia photographs, books and buildings, artifacts displayed behind glass. And sometimes we get to touch historical objects or listen to recordings. But rarely do we use our sense of smell — our oldest, most primal way of learning about the environment — to experience the distant past.
Without access to odor, “you lose that intimacy that smell brings to the interaction between us and objects,” saysanalytical chemist Matija Strlič. As lead scientist of the Heritage Science Laboratory at the University of Ljubljana in Slovenia and previously deputy director of the Institute for Sustainable Heritage at University College London, Strlič has devoted his career to interdisciplinary research in the field of heritage science. Much of his work focused on the preservation and reconstruction of culturally significant scents.
Reconstructed scents can enhance museum and gallery exhibits, says Inger Leemans, a cultural historian at the Royal Netherlands Academy of Arts and Sciences. Smell can provide a more inviting entry point, especially for uninitiated visitors, because there’s far less formalized language for describing smell than for interpreting visual art or displays. Since there’s no “right way” of talking about scent, she says, “your own knowledge is as good as the others’.”
Despite their potential to enrich our understanding of history and art, smells are rarely conserved with the same care as buildings or archaeological artifacts. But a small group of researchers, including Strlič and Leemans, is trying to change that — combining chemistry, ethnography, history and other disciplines to document and preserve olfactory heritage…
Read on for the fascinating details: “Recreating the smells of history,” from @knowablemag.bsky.social.
* Edward Thomas, “Digging“
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As we take a whiff, we might recall that it was on this date in 1924 that Coco Chanel agreed with the Wertheimer brothers Pierre and Paul, directors of the perfume house Bourjois, to create a new corporate entity, Parfums Chanel, Its signature product was Chanel No. 5. She had been selling small quanitites of the scent in her boutique since 1921.
Traditionally, fragrances worn by women had fallen into two basic categories. Respectable women favored the essence of a single garden flower while sexually provocative indolic perfumes heavy with animal musk or jasmine were associated with women of the demi-monde. Chanel sought a new scent that would appeal to the flapper and celebrate the seemingly liberated feminine spirit of the 1920s. Her scent was formulated by chemist and perfumer Ernest Beaux, who designed an unprecedented olfactory architecture, a bouquet of 80 scents whose precious notes were blended with high proportions of aldehydes, organic compounds that carry a crisp, soapy, and floral citrusy scent. In late 1920, when presented with small glass vials containing sample scents numbered 1 to 5 and 20 to 24 for her assessment, she chose the fifth vial. Chanel told Beaux, “I present my dress collections on the fifth of May, the fifth month of the year and so we will let this sample number five keep the name it has already, it will bring good luck.”
The first promotion for Chanel No. 5 appeared in The New York Times on December 16, 1924– a small ad for Parfums Chanel announcing the Chanel line of fragrances available at Bonwit Teller, an upscale department store. The fragrance, of course, become a fave. An Andy Warhol subject and worn by everyone from Marilyn Monroe and Catherine Deneuve to Mad Men’s Peggy Olson, the perfume, is a foundational part of fragrance history… and still sells a bottle every 30 seconds.







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