skybrian's recent activity
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Comment on Inside Google’s $200bn Wall Street finance machine for Anthropic in ~finance
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Comment on Inside Google’s $200bn Wall Street finance machine for Anthropic in ~finance
skybrian Linkhttps://archive.is/mC6hM From the article: [...] [...] [...] [...]From the article:
Google has assembled one of the largest infrastructure financing programmes in history to supply more than $150bn of artificial intelligence chips to Anthropic.
Surging demand from Anthropic, in which Google is an investor, has led the Big Tech company to orchestrate a sprawling operation to supply its chips to the start-up, according to people involved in the project and corporate filings reviewed by the FT.
The effort brings together Google, Broadcom, Apollo, Blackstone, Morgan Stanley and a slew of crypto miners in a web of transactions that stretches from chip manufacturing to data centre development.
At the centre of the project are Google’s tensor processing units, or TPUs — AI chips it has co-developed with Broadcom since 2016. Once used largely inside Google’s own data centres, the chips have begun to be sold externally, challenging Nvidia’s dominance of the AI processor market.
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To support the relentless surge in demand for the AI chips, Google, Broadcom and Wall Street investors have each taken on different pieces of the financial risk.
Google guarantees the data centres. Broadcom commits to buying the chips and helps finance them. Apollo and Blackstone provide much of the private-credit capital that purchases the hardware before leasing it to Anthropic.
“This is each of us putting our balance sheet to work,” said a Google executive involved in the effort. “We’re doing it on the data centre side, [Broadcom’s] doing it on the chip side.”The web of contracts underpinning these arrangements adds up to about $200bn, with roughly four-fifths tied to the chips themselves, making it one of the largest infrastructure financings ever assembled.
A programme of such a size posed a problem: none of the companies involved wanted to carry tens of billions of dollars of AI chips on their balance sheets.
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That challenge produced an unusual solution. Morgan Stanley helped arrange a private-credit vehicle, funded by outside investors, that buys the chips and leases them to Anthropic in an adaptation of the vendor-financing model Boeing and GE built to sell aircraft and engines.
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Financing the chips solved only half of Google’s problem. The company also needed enough powered data centres to house them. “We have a schedule and we’re looking for capacity that will fit the schedule,” the Google executive said. “Crypto miners with excess capacity were helpful.”
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People familiar with the matter said the Big Tech company had so far backstopped 10 developments with 2.4GW of power for TPUs. Google’s guarantees put it on the hook for as much as $44bn if all the leases go bad, though it marks the liability at $815mn on its balance sheet. It could also step into the leases itself.
The Google team is now racing to put together additional data centre projects with enough power to ultimately house all of the 4.5GW of TPU hardware they’ve agreed to sell. “We’re spending a lot of time on [power] right now — all of our time,” said the Google executive.
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Inside Google’s $200bn Wall Street finance machine for Anthropic
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Comment on How US states are streamlining college admissions in ~society
skybrian LinkFrom the article: [...] [...] [...]From the article:
More than 130,000 Georgia high school seniors will receive letters in October listing colleges and universities that are saving spots for them in their 2027 freshman classes—even though they never applied.
Georgia is one of 19 states that have developed some form of a direct-admissions system. Using data about academic performance through 11th grade, colleges essentially apply to students—a reverse of the traditional application process that can create logistical and financial barriers to enrollment.
“For a lot of high school seniors, maybe they aren’t sure if they are college material,” said Chris Green, the president of the Georgia Student Finance Commission, which helped launch the system, called Georgia Match, in 2023. “It’s a real eye-opening experience to say, ‘I’m already admitted to 45 schools.’”
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Organizers from multiple sectors of state government believe Georgia’s is the largest and most comprehensive direct-admissions program in the country. The first such program began in Idaho in 2015 and other states have followed suit.
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Organizers have found that eliminating friction from the admissions process can encourage students to give more consideration to in-state schools, helping states retain talent, said Melanie Heath, the strategy director for access at the Lumina Foundation, an organization that aims to expand postsecondary opportunities.
And including a wide array of institutions, including technical schools, may help students who weren’t previously considering college to credential programs in high-needs fields, like skilled trades, she said.
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In Georgia, students’ college options are hosted on the same state data platform they use to discuss career paths as early as middle school. Students can click “claim my spot” next to a college on their offer letter to finish the application process, and schools waive application fees in November every year to eliminate another hurdle.
As it works to refine its program in bigger ways, the state has also made small tweaks to ensure students understand how it works, Green said. For example, organizers beefed up the envelope size for offer letters when they realized families had mistaken the business-sized envelopes they originally used as junk mail.
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How US states are streamlining college admissions
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Comment on California goat grazing faces crisis after wage change in ~enviro
skybrian Link ParentOn the one hand, when a business shuts down because they can't make it work, sure, that's capitalism. There will be other businesses. But on the other hand: when a factory lays everyone off and...On the one hand, when a business shuts down because they can't make it work, sure, that's capitalism. There will be other businesses.
But on the other hand: when a factory lays everyone off and shuts down, that is not good news for the people who are out of a job and it seems rather heartless to cheer about it. It seems like the same thing here?
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Comment on Building luxury homes is good for the poor in ~society
skybrian LinkWe previously discussed the same Financial Times article here.We previously discussed the same Financial Times article here.
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Comment on California goat grazing faces crisis after wage change in ~enviro
skybrian Link ParentAs the employers tell it, they provide everything to their foreign workers and the they don't interact with the community at all. They claim that the cost of living is nothing while they're...As the employers tell it, they provide everything to their foreign workers and the they don't interact with the community at all. They claim that the cost of living is nothing while they're working, and then they go home.
This reminds me of someone getting a job on a fishing boat in Alaska.
Maybe it doesn't really work that way, though? It would be nice to hear from the goatherds themselves.
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Comment on California goat grazing faces crisis after wage change in ~enviro
skybrian Link ParentOne thing that strikes me is that the article doesn't include any interviews with the goatherds. I wonder what they think? It's a traditional occupation. Have goatherds been abused for centuries?One thing that strikes me is that the article doesn't include any interviews with the goatherds. I wonder what they think?
It's a traditional occupation. Have goatherds been abused for centuries?
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Comment on Boarding China’s last bus in ~society
skybrian LinkFrom the article: [...] [...] [...] [...]From the article:
China’s tech giants — Alibaba, Tencent, and Baidu — were all founded between 1998 and 2000. By the end of 2000, the number of internet users in China had jumped from 3000 in early 1995 to 22.5 million. In 2001, China joined the WTO. Urbanization accelerated, and the growth of the middle class fueled demand for luxury goods, tourism, and better nutrition. The number of private cars in China went up from 1 million in 1992 to almost 10 million by 2002. Many people envisioned a hopeful future in which they could acquire new clothes, new luxuries, and new technology in the new millennium.
But the “many” did not include the 100 million people residing in the Northeast — roughly 8.5% of China’s total population as of 2000. By the 1990s, urban shrinkage, which is measured by sustained population loss, had already taken hold across 52 cities in the Northeast. And of the 68 cities across China whose populations diminished continuously into the 2010s, half were in this region. The regional birth rate has been trending lower than the national average for more than three decades, and net outmigration has become an increasing problem since 2000. In 1990, the Northeast represented 8.66% of the country’s population; by 2016, that proportion had dropped to 7.9%. The one-time cradle of China's industrial development has become a place that many would rather not raise kids or live in, given the choice.
In the span of a decade, Chinese society simultaneously experienced rapid economic growth and extreme economic precarity. Individuals were offered transformative opportunities and faced catastrophic crises, all due to the same factors put in place by a select elite who generated the incredible promise and acute challenges modern China still faces. To many Americans watching AI reshape their economy, this narrative may sound familiar, though calls to regulate, pause, or stop the technology reflect a belief that the transformation can still be steered or stopped. That option did not exist for Chinese workers in the 1990s.
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For China’s policymakers, slowing development was never an option. A 1931 quote from Joseph Stalin — “落后就要挨打 (luohou jiu yao aida) or “those who fall behind get beaten” — that adapted by Mao Zedong in 1956 permeated society, serving as a cornerstone of high-level policy narratives. In China’s mnemonic practices, this phrase, linked to the idea that only development can sustain a nation’s independence, is the most significant lesson from the past, necessary to remember from China’s 20th-century history of war and colonization. “The reform is painful but rewarding,” wrote the state in 2012 in reference to the previous century.
At the turn of the century, then, the policy question was therefore not whether to reform; instead, it was how to make the transformation less painful. The government attempted to address the pain. In 1998, the state established re-employment Service Centers, which provided laid-off workers with living allowances, basic social security, and job training. The state taxation administration introduced tax incentives for businesses that hired displaced workers. Xiagang workers were entitled to tax exemptions, fee waivers, and preferential access to microloans when starting small businesses or seeking new employment. The Minimum Living Security System was established in 1999 to guarantee basic income for urban residents and expanded to rural areas in the 2000s. Higher education grew in 1999 and university attendance increased 600% in less than 10 years. This expansion was partially aimed at delaying China’s youth from entering the job market, thus leaving spaces for the re-employment of laid-off workers.
For some workers, these policies provided a bridge. But the scale of the problem overwhelmed the response. Funds were too small or simply did not arrive. When funds did arrive, they rarely reached the people they were meant for. In one case, one former deputy director of the city-level Development and Reform Commission — an institution responsible for implementing national economic policies — embezzled the subsidies of 556 xiagang workers.
Even as market reform and industrial upgrades brought new job opportunities, there were simply not enough: In 2004-2005, 24 million people entered the workforce, but only 9 million new roles were created. Even within these new jobs, there was a mismatch between supply and demand. The workers who had been laid off were predominantly in their forties and fifties with industrial skills, while the foreign companies entering China wanted fresh university graduates or young rural migrants who were willing to work for less. And though the expansion of higher education benefited many, it eventually produced young workers who were overqualified for many jobs, resulting in high youth unemployment that persists in China today. And much of the suffering was silently buried under cold numbers and grand policies.
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If economic restructuring was an unstoppable force of nature, then the only possible response was to move with it before it moved without you. Xiang Biao diagnosed this as a "last bus" mentality: a collective fear that missing the opportunity to seize a piece of post-socialist accumulation meant missing everything. You either catch this bus towards success or be left out forever. It was a frenzy born not of greed or enthusiasm, but of the desperate realization that the old world was gone and the new one had no reserved seats. What began as a northeastern industrial experience has, amid decades of social change and competition, became a prevalent psychological structure spanning different socioeconomic classes and regions.
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In the late 1990s and early 2000s, learning English was the last bus. Globalization was the irreversible trend; only by learning English could Chinese people interact with the greater world. The state mandated English education as a core Gaokao subject and pushed it into primary schools in 2001, giving rise to cultural phenomena like "Crazy English" (疯狂英语; fengkuang yingyu), wherein tens of thousands of people gathered in public stadiums to scream English phrases at the top of their lungs in a desperate collective bid for fluency. In the late 2010s, the mobile internet boom was the last bus. As tech giants like Alibaba and Tencent offered unmatched salaries in other industries, millions rushed to learn coding and enroll in computer science degrees in universities that were aggressively expanding computer science programs, only to find themselves facing a constantly decreasing employment rate.
In 2023, understanding AI was the last bus, and over 250 thousand people paid for rudimentary AI crash courses, terrified of being rendered obsolete overnight. In 2026, OpenClaw was the last bus, with thousands of people — retirees, white-collar workers, housewives — lining up outside tech company offices for engineers to install the agent directly onto their phones.
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When polled only three decades later, perhaps every respondent genuinely believes that AI is good for both society and for themselves. Or perhaps they see AI as another surgery necessary to survival, knowing full well that flesh will be cut away and discarded, but convinced that the pain borne by individuals — however devastating to them — is small against the benefits at large. The polls, as they are written, cannot distinguish between these narratives. .
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Boarding China’s last bus
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Comment on California goat grazing faces crisis after wage change in ~enviro
skybrian Link ParentIt seems like it's bigger than any single business. If they double their prices will they still get customers, or will their customers decide that, at that price, they can do without the goats?...It seems like it's bigger than any single business. If they double their prices will they still get customers, or will their customers decide that, at that price, they can do without the goats?
They seem to believe they won't have a business anymore. Maybe they're wrong, but...
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Comment on No data centers in my backyard in ~society
skybrian LinkFrom the article: [...] [...] [...]From the article:
The only solution seemed to be hitting the road, going to the towns where data center fights were happening, and talking to as many people as I could: activists, yes, but also workers, planners, politicians, and residents. I wanted to learn: Do most people actually care about data centers, or just a passionate few? What’s motivating these revolts—is it about AI, or energy costs, or good old NIMBYism? How did local opposition become a national issue? And how is AI moving elections?
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My conversations make me wonder if the technical content of data center deals is mostly beside the point. Closed-loop cooling systems? “I don’t believe them.” Paying millions in taxes? “I don’t believe them.” Creating a thousand jobs? “I don’t believe them.” I hear a reflexive skepticism of every claim.
Rather, the way that AI companies engage with communities—forcing NDAs, dangling billion-dollar promises, pushing environmental externalities far away from AI’s wealthy user base—resembles a classic story about dark money in politics. Your politicians are being bought by billionaires and gigantic corporations to screw you over. It’s not Skynet: it’s the oligarchy.
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So: what is driving the data center fights erupting across America, from rural farmers to feminist academics, from conservative NIMBYs to Bernie bros?
First, the material impacts: AI data centers are big, ugly, noisy, and very energy-hungry. Construction processes are long and locally disruptive. Water consumption and air pollution is generally minimal, but there are exceptions. In a vacuum, most people would choose to live by a flower field over a data center. But these costs are not so different from other industrial developments like manufacturing or solar farms. Those don’t go up without dissent, but have not commanded the shared hatred that data centers have.
Second, process failure. Many people living near data center sites don’t feel that they got a choice. In San Francisco we see how desperate the industry is for compute—atoms still do not scale as seamlessly as bits. That tremendous financial pressure is materializing as fast tracks, fat checks, and limited time for public input. It looks like Big Tech cheating the system, engaging in cronyism and bribery, throwing money bags at politicians and hoping the dollar signs substitute for a positive case.
Third, weak benefits. There is no compelling pro-data-center, pro-AI faction. Charles Franklin, who runs the Marquette Law Poll, emphasized that you only get sentiment this skewed when one side fails to make a case. The AI and utility companies are unsympathetic, permanent workers are not numerous, and most consumers do not feel that AI products are essential to their lives. At least nuclear power and public housing has its advocates (especially among those who live far away). Data centers are hated whether you live near one or not.
Moreover, tax contributions can be delayed, and many in deindustrialized areas aren’t sure if they’ll ever pan out. In the era of the K-shaped economy, being “pro-growth” in the generic has lost its sheen. Several activists assured me they were not anti-technology—I didn’t hear much about specific AI harms—but that an email-writing widget was not worth a data center in their backyard. And more crucially, they did not want their town to be the collateral damage in a few tech billionaires’ pointless ego race. If AI is a bubble, they didn’t want to be part of the pop.
Finally, grievance is amplified by a national environment of historically low trust in corporations and the government. Americans of all parties feel the economy is “rigged” against them; “corruption” and “affordability” regularly rank as top concerns. News articles and viral TikToks teach people to link their local complaints to these bigger political messages: data centers are enriching politicians and billionaires while raising your electric bills. Facebook groups convert solo concerns into social movements. Everywhere in my interviews, people suspected their opponents of being paid off.
You cannot detach the data center backlash from these broader trends in American political culture. “AI populism” is more about populism than about AI.
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Back in San Francisco, it is striking how little the AI industry understands its own unpopularity—the reasons that people resist. They ask if it’s a problem of benefits not being generous enough, or else a big misinformation campaign. (By the end of the trip, my friends and I felt slightly ashamed of the caricatures we originally believed in. In general, one should be cautious about assuming your opponents are just reading fake news.)
In Wisconsin and Michigan, sometimes bigger numbers made observers more suspicious. People saw them and thought: I’m being bribed. There must be a catch. It turns out that politics is more than an optimization game; voter interests are neither stable nor reducible to dollar amounts. It is also about thymos: the desire to be “recognized as a human being… with a certain worth or dignity,” who can sacrifice material survival in service of higher ideals. Through Fukuyama’s lens, elections and town halls and social media debates matter not because they are maximally efficient preference aggregators, but because they are “a stage for the expression of thymos”—a place where people make their values heard.
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No data centers in my backyard
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Comment on New Zealand has a new official language — English in ~society
skybrian Link ParentNot really, no. The way I'd expect it to work for something symbolic and uncontroversial, like legislation declaring national peach tree day or something like that, is that if nobody wants it,...Not really, no. The way I'd expect it to work for something symbolic and uncontroversial, like legislation declaring national peach tree day or something like that, is that if nobody wants it, there's no reason to do it, but given that some people do want it, there's no reason to oppose it.
This is obviously a controversial issue, but I don't really see why it should be. It's hard to imagine any compelling arguments either way for something that doesn't seem to matter much. The ones briefly summarized so far don't seem compelling.
But since that's just a first impression, I'm leaving the door open to there being more to it.
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Comment on New Zealand has a new official language — English in ~society
skybrian Link ParentOkay, clearly many sympathetic people have argued against it. But this brief summary doesn't tell us how good the arguments are. For example, I'm wondering how expensive this measure could be when...Okay, clearly many sympathetic people have argued against it. But this brief summary doesn't tell us how good the arguments are. For example, I'm wondering how expensive this measure could be when it seemingly doesn't do anything substantial? And how exactly does it undermine the official status of other languages?
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Comment on A thread about the history of streetcars in the US in ~transport
skybrian LinkFrom the Bluesky thread: [...] [...] [...] [...] [...] [...]From the Bluesky thread:
in general, public transport before world war II was generally privately owned. it was a business, like railroads had been since the start of the industrial age. nobody liked the privately owned monopolies that owned public transit. 2/
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basically, these monopolies dominated metro areas, because they weren't just the transport monopoly. in la, oakland and miami, the train company was the biggest real estate developer. in atlanta, new jersey and new orleans, they were the power company. 3/
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these monopolies were hilariously corrupt as well, and they had few friends. henry huntington (of LA's red cars), or charles yerkes (of the chicago eleveated) were as detested as bezos and zuckerberg were today. 4/
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the trains got a serious challenge from cars in the early 20th century. and by the end of world war II, the train systems were worn out and needed massive government investment to survive. but because the transit companies were shitty monopolies, nobody wanted to help them out! 5/
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On top of that, the new, shiny buses often had A/C, and the streetcars only had fans. The first air-conditioned bus was introduced in 1946. The first air-conditioned streetcars weren't introduced until 1976. 8/
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All of this is to say, GM was picking the bones of the dying streetcar companies. Think vultures, not eagles. And when we talk about the GM conspiracy charges... GM-affiliated National City Lines actually kept streetcars running longer than peer systems. 10/
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There was, however, one exception to this: Minneapolis-St Paul. There, a finance bro, the mob, and a crooked lawyer really did buy the trains and sell them for scrap - but that was the exception, not the rule. 12/12
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A thread about the history of streetcars in the US
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Comment on New Zealand has a new official language — English in ~society
skybrian Link ParentTo put it another way, "the other side wants it" is a heuristic that might understandably make one suspicious, but it's only convincing to committed partisans. If there are other, better arguments...To put it another way, "the other side wants it" is a heuristic that might understandably make one suspicious, but it's only convincing to committed partisans. If there are other, better arguments then they should stand on their own.
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Comment on New Zealand has a new official language — English in ~society
skybrian Link ParentI think this controversy is stupid, but if you reflexively oppose harmless changes then it makes your own side look stupid, too. And that's what they want.I think this controversy is stupid, but if you reflexively oppose harmless changes then it makes your own side look stupid, too. And that's what they want.
You might be underestimating how deeply AI is being embedded into some companies. For example, here’s what Cloudflare is doing.
The AI labs have poor uptimes, but that means they will switch to a different LLM provider rather than do without.
I imagine it’s going to be an expected utility like email and Internet access and cell phone service. Some banking services will degrade or stop working altogether if their AI goes down and they have to revert to manual procedures.
But I don’t expect bailouts anytime soon because switching is pretty easy. It will be a temporary disruption like an airline going bankrupt. Think of a data center like an airplane that some other airline could lease.
Also, the government doesn’t particularly like any AI companies and neither do the people. It’s not like the auto industry where factory workers have a lot of clout.