skybrian's recent activity
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Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech
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Comment on How to buy cheap Claude tokens in China in ~tech
skybrian LinkFrom the article: [...] [...] [...] [...]From the article:
Regardless of whether Chinese labs rely on distillation to “catch up”, both documents misread the proxy economy they’re describing. Underneath the handful of labs sits a much larger market, one that has been operating in public on GitHub, Taobao, Twitter, and Telegram. It is a grey economy of API proxies (commonly called “transfer stations,” 中转站) that lets Chinese developers access Anthropic’s models at as low as 10% of the official price. The participants extend far beyond selective experienced AI researchers, and the motivations are much broader than building a frontier model to catch up. Everyone who wants to use more advanced AI models or tools, be they university professors and students, tech workers, individual developers, or hobbyists, uses API proxies. The logs they generate may have become a commodity, traded for purposes ranging from model training to targeted fraud.
Meanwhile, every layer of control frontier US AI companies have added (geoblocking, phone verification, credit card requirements, and now live biometric KYC checks) has produced a corresponding layer of evasion infrastructure. These new SMS farms and biometric harvesting operations have implications that extend beyond geopolitics into how frontier AI safety frameworks are designed.
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A transfer station (中转站) is what the Chinese developer ecosystem calls an API proxy–an overseas server that sits between a developer and Anthropic’s infrastructure. It accepts API requests, forwards them as if they originated from the transfer station’s location, and passes the response back. The user redirects their software to the proxy’s server instead of Anthropic’s, and pays the API proxy RMB via WeChat or Alipay. This sidesteps both the VPN and the overseas credit card needed for direct access. Prominent transfer stations are catalogued in community repositories and ranked by real-time price and uptime. Below them, a longer tail of small and individual projects comes and goes.
While this setup sounds functionally identical to legitimate Western API aggregators like OpenRouter, transfer stations operate in an entirely different universe of legality and trust. Legitimate aggregators exist to simplify developer workflows, charging standard rates based on transparent enterprise agreements. Transfer stations, conversely, are built explicitly for evasion, routing data through unaccountable middlemen.
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A transfer station is not a sole entity. It sits in the middle of a layered supply chain, with most participants never interacting with each other directly.
Upstream are the resource providers: account merchants who bulk-register or acquire Anthropic accounts at scale; SMS verification platforms that supply the foreign phone numbers needed to pass sign-up checks; and, at the more technical end, reverse engineers who analyze Anthropic’s client code to find authentication shortcuts or detect when detection logic has changed. The payment infrastructure with card merchants and proxy networks also enables overseas billing from inside China.
The upstream also tackles more sophisticated KYC regimes–either by AI or humans. AI services have demonstrated the ability to generate highly realistic fake IDs capable of bypassing identity verification on major platforms, and deepfake tools now allow criminals to create digital clones that successfully pass biometric verification remotely. Even if the defender can successfully detect AI faking humans, a more labour-intensive method exists to find real humans. Agents travel to lower-income countries in Africa or Latin America to recruit real individuals willing to complete in-person verification. The Worldcoin black market offered a documented precedent, with iris scans harvested from KYC merchants in Cambodia and Kenya, sold for under $30.
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Almost no one operates the full chain. Most participants own one or two links and monetise those well, resulting in a resilient, modular system. AI model providers can suspend individual operators, but the upstream account pools and downstream customer base remain intact. So long as there are developers who want access to Claude and identity black markets willing to supply the credentials, which are both durable features, a replacement can be stood up quickly.
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Meal 2: Swapping models and inflating tokens. Because users’ inputs and model outputs are mediated through a proxy, users cannot verify which model their request was actually routed to. A user selects Opus 4.7, but the proxy can silently route to Sonnet, Haiku, or, in the worst case, GLM or Qwen, and fraudulently relabel the output. In a recent paper from Germany’s CISPA Helmholtz Center for Information Security (which cited my article last year on grey market!), researchers audited 17 API proxies and found widespread model swapping–API proxy access to “Gemini-2.5” achieved only 37.00% on a medical benchmark, a staggering drop from the 83.82% performance of the official API. On the user end, the tell only comes on complex tasks, when the output feels off (often referred to as 降智, or “dumbed-down”), but there is no clean way to prove it. Numerous public records highlight concerns that certain API proxies have noticeably compromised model performance. These proxies are suspected of “diluting” (掺水) services by substituting premium frontier models with inferior tiers.
Besides model swapping, overconsumption of tokens also makes the price per token cheaper, though at the expense of driving up the total cost. Some of it is structural, as proxies that rotate accounts frequently destroy cache continuity as a side effect, forcing users to burn full-price tokens on context that would otherwise be nearly free. Some of it may be deliberate as the proxy providers try to milk more usage. The line between the two is difficult to draw from the outside.
Meal 3: The logs are the product. This is perhaps the most important part as it intersects with data privacy and distillation. Every request that passes through a proxy — full prompt, full response, tool calls, iterations — is sitting on the proxy operator’s server. For AI coding agents, those logs contain long reasoning chains, real engineering decisions, repository context, and human-verified correct outputs. This makes them an ideal dataset for post-training: for supervised fine-tuning on real engineering tasks, and, where full reasoning traces are captured, for distilling Claude’s reasoning patterns into smaller models. Chinese developer communities assert this is happening in at least some cases, but whether proxy operators are systematically harvesting and selling these logs, and to whom, remains unverified. However, downstream distillation data does exist on the open web. Several datasets of Claude Opus 4.6 reasoning outputs circulate on HuggingFace with no clear source for the outputs. Theoretically, one can clean and sell similar distilled datasets to other model developers in China.
The first two meals are useful for providing cheaper tokens cheaper than Anthropic officially charges, but to really make prices ridiculously low — at 10%, or even 5%, of the original price — one needs to eat the third meal. And as a Chinese saying goes, there is no free lunch in the world (天下没有免费的午餐). Several Chinese developers have revealed that the markup business is just customer acquisition, and the log harvest is the actual margin. Users are simultaneously paying customers and unpaid data producers, selling their private data to proxy operators in exchange for a low price. Some also warn of potential promotion, fraud, and even blackmail based on leaked users’ data from the proxy. To avoid privacy risks, some Chinese developers have also constructed their own Claude Code API proxy and open-sourced the guidelines.
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How to buy cheap Claude tokens in China
24 votes -
Comment on Ending respiratory infections in ~health
skybrian LinkFrom the article: [...] [...] [...]From the article:
We believe that with enough focus and funding, these problems are tractable. Intercept is a $500 million philanthropic initiative that will take advantage of these new tools to catalyze the development of two types of products: broad-spectrum preventatives and air cleaning technologies. Together, these technologies can radically reduce the burden of respiratory infections, and can eventually help eliminate them altogether.
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These are products—a shot, a nasal spray, a pill—that defend individuals against rhinoviruses, influenza, coronaviruses, and other respiratory viruses simultaneously. Our goal is to catalyze the development of safe and tolerable preventatives that will prevent more than 75% of symptomatic respiratory infections in as few doses as possible, via easy-to-administer modalities, and that have a credible path to ~60% uptake. We will prioritize approaches that are convenient with minimal side effects to support the goals of widespread adoption and uptake. This will be the core technical challenge some of these drug candidates face: they need to find the sweet spot between being too narrow (targeting only one viral strain like most vaccines today) and being too broad (causing unwanted side effects, e.g., via excessive stimulation of the immune system or unwanted off target effects on the host).
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Still, even with sufficient funding, developing a truly broad-spectrum preventative is technically very challenging: respiratory viruses include several different virus families and some have many variants that mutate constantly. Further, the safety bar for developing preventative medicines is appropriately extremely high. If these drugs are to be given to millions of otherwise healthy people, the likelihood they cause harm needs to be extremely low. This means very large and long-lasting clinical trials, which can increase costs and timelines.
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Air cleaning technologies improve indoor air quality by removing or inactivating airborne viruses, just like municipal water infrastructure removes and inactivates pathogens from our drinking water supply. Our goal is to catalyze the uptake of air cleaning technologies that safely reduce infectious aerosols by >75% and have a path to >50% uptake in transmission-relevant indoor spaces at low cost.
There are several ACTs we’ll focus on initially, each of which layers on top of building ventilation systems that dilute and recycle air. These technologies can often (but not always) be used in combination, and each has unique characteristics that make it more or less well-suited for different types of indoor spaces and use cases.
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Air filtration: Products that remove particulate matter and pathogens from the air. Filters can either be placed in the ducts of mechanical ventilation systems to act on recirculated air, or in separate devices placed or mounted in a single room.
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Antimicrobial light: A specific wavelength of ultraviolet light (“far-UVC”) that can inactivate pathogens in the air and on surfaces, but does not penetrate human skin or eyes enough to harm dividing cells.
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Antimicrobial vapors: Compounds such as triethylene glycol and propylene glycol that can inactivate pathogens in the air and on surfaces, by being drawn into respiratory droplets and inactivating them.
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Ending respiratory infections
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Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech
skybrian Link ParentDo they normally run GPU's this hot in data centers? Nvidia seems to have decided it's okay.Do they normally run GPU's this hot in data centers? Nvidia seems to have decided it's okay.
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Comment on Nobody clicks your share buttons in ~tech
skybrian Link ParentIt's not transformative if you just copy a meme. I mean, nobody worries about whether it's copyright infringement (although it might be), but from an artistic standpoint, it's still pretty...It's not transformative if you just copy a meme. I mean, nobody worries about whether it's copyright infringement (although it might be), but from an artistic standpoint, it's still pretty thoughtless.
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Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech
skybrian LinkFrom the article: [...]From the article:
AI GPU maker Nvidia just announced a “hotter than a hot tub” liquid cooling system that it says will cut water and electricity use. According to the company, this new solution will run coolant — composed of 75% water and 25% propylene glycol — at 113 degrees F (45 deg C). By comparison, the water in hot tubs hovers at 100 to 104 degrees F (38 to 40 deg C). This feels counterintuitive, but the company says that the “cool” water is enough to handle the heat generated by Nvidia’s Rubin chips and exit the system at 131 degrees F (55 deg C).
Traditional water-cooling methods, especially those that use chillers, often account for nearly 40% of a data center’s power consumption. Aside from that, these systems must often deal with water loss through evaporation. On the other hand, air-cooled facilities also use a considerable amount of electricity, plus they also generate noise pollution. On the other hand, Nvidia says that this new solution uses a lot fewer resources because of its higher base temperature.
Since 113 degrees F is often higher than ambient temperature, data centers can simply rely on outdoor dry coolers to expel the heat to the environment. This is also a closed-loop system; Nvidia claims an up to 100% reduction in water consumption — it’s “filled once and runs closed for the life of the facility.” This solution is most effective in regions with cooler climates, but it should still be effective in warmer areas as long as the ambient temperature is below 113 degrees F.
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This solution addresses several of the issues that many local governments raised that led to the delay of more than 75 data centers earlier this year. However, it will likely take time for this cooling system to roll out to new and existing projects, so we expect the delays and resistance to continue until Nvidia’s liquid cooling system gains wider adoption. Furthermore, this only addresses the water use of the data center itself — the GPU servers themselves still require massive amounts of electricity.
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Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100%
25 votes -
Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~society
skybrian LinkFrom the article: [...]From the article:
AI GPU maker Nvidia just announced a “hotter than a hot tub” liquid cooling system that it says will cut water and electricity use. According to the company, this new solution will run coolant — composed of 75% water and 25% propylene glycol — at 113 degrees F (45 deg C). By comparison, the water in hot tubs hovers at 100 to 104 degrees F (38 to 40 deg C). This feels counterintuitive, but the company says that the “cool” water is enough to handle the heat generated by Nvidia’s Rubin chips and exit the system at 131 degrees F (55 deg C).
Traditional water-cooling methods, especially those that use chillers, often account for nearly 40% of a data center’s power consumption. Aside from that, these systems must often deal with water loss through evaporation. On the other hand, air-cooled facilities also use a considerable amount of electricity, plus they also generate noise pollution. On the other hand, Nvidia says that this new solution uses a lot fewer resources because of its higher base temperature.
Since 113 degrees F is often higher than ambient temperature, data centers can simply rely on outdoor dry coolers to expel the heat to the environment. This is also a closed-loop system; Nvidia claims an up to 100% reduction in water consumption — it’s “filled once and runs closed for the life of the facility.” This solution is most effective in regions with cooler climates, but it should still be effective in warmer areas as long as the ambient temperature is below 113 degrees F.
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This solution addresses several of the issues that many local governments raised that led to the delay of more than 75 data centers earlier this year. However, it will likely take time for this cooling system to roll out to new and existing projects, so we expect the delays and resistance to continue until Nvidia’s liquid cooling system gains wider adoption. Furthermore, this only addresses the water use of the data center itself — the GPU servers themselves still require massive amounts of electricity.
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Comment on Micah Lasher wins New York primary to succeed his political mentor in star-studded contest in ~society
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Comment on Taiwanese go deep into debt to amp 100% stock rally in ~finance
skybrian LinkFrom the article: [...] [...] [...]From the article:
AI mania has gripped any number of stock markets across the globe in recent months — South Korea, China, the U.S. — but perhaps nowhere is it as frenzied as in Taiwan, the No. 1 producer of the chips that power the technology.
Teenagers are rushing to open brokerage accounts; spikes in trading volumes are crashing firms’ websites; and the Taiwanese market, up over 100% in the past year, is rallying so fast that in a matter of weeks it overtook the U.K., Canada and India to become the world’s fifth largest.
Much of this boom is, like in Cheng’s case, fueled by heaps of money borrowed at rock-bottom interest rates. So much so that many of the island’s brokerages have hit their internal limits on certain types of loans, forcing them to demand more collateral and bump up their rates, according to people familiar with the matter. Those investors who are rebuffed by their brokers often just turn to their banks for leverage instead, taking out new loans or canceling financial products to free up cash.
The borrowing binge is so intense, and has spread so deeply across the financial system, that it even disrupted a recent central bank debt auction. Not enough buyers showed up to buy all the debt on sale on June 3, the first time that’s ever happened.
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Moreover, the speculative mania sweeping Taiwan today is rapidly approaching the fevered pitch it reached during the dotcom days. Over the past 12 months, the amount of money investors borrowed from brokerages to finance stock purchases swelled 160%, leaving it near an all-time high set just before the 2000 crash. That surge in margin debt, as it is called, dwarfs the 50% increase recorded in the final 12 months of the bubble back then. It even tops the 94% rise posted recently in Asia’s other AI powerhouse, South Korea, a country where the government has worked relentlessly to fan stock-investing fever and drive the market higher.
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Investor demand for loans has been so torrid that Taiwanese brokers have themselves embarked on a borrowing spree to shore up working capital. They’ve issued nearly $1.2 billion in bonds this year, more than seven times the amount raised in all of 2025.
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Some firms have instructed sales staff to push their most aggressive clients to rein in risk. Others have started stress-testing their loan portfolios against a sudden plunge in the market of, say, 20% or 30%.
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Taiwanese go deep into debt to amp 100% stock rally
14 votes -
Comment on Clarence Thomas gives US border agents terrifying new power in ~society
skybrian LinkFrom the article: [...] [...]From the article:
On Tuesday, the Supreme Court blessed this Kafkaesque nightmare by a 6–3 vote along the usual partisan lines. Justice Clarence Thomas’ majority opinion in Blanche v. Lau declared that officers do not need “clear and convincing evidence” that a green-card holder committed “a crime of moral turpitude” before treating them as an “applicant for admission” who may be denied entry, detained, or (at best) conditionally allowed back in on parole. Indeed, Thomas expressly declined to say what, if any, burden the government bears at the border—an ambiguity that the Trump administration will surely exploit to throw green-card holders into deportation limbo. As Justice Ketanji Brown Jackson explained in dissent, “the court has now handed the government a massive blank check” to hollow out “the benefits and security that come with having a green card.”
The origins of Tuesday’s case illustrate its stakes. In 2012, a green-card holder named Muk Choi Lau returned to the United States after a trip to China. At that time, he faced criminal charges for selling designer-style shorts with a counterfeit trademark. As a lawful permanent resident, or LPR, Lau would typically be let into the country without hassle, deemed “already admitted” rather than “seeking admission.” But a border officer noticed the pending criminal charges and refused to formally admit him. Instead—playing prosecutor, judge, and jury—the officer deemed Lau to have committed “a crime involving moral turpitude.” And federal law permits the government to treat a lawful permanent resident who has committed such a crime as an “alien seeking admission” rather than someone already admitted to the country. The officer invoked this exception against Lau, snatching his green card and “paroling” him into the country. That move made Lau far more vulnerable to detention and deportation than if he had been admitted as an LPR.
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Now consider Thomas’ distortion of the congressional scheme. In his telling, the government may simply accuse an LPR of committing a crime, strip them of the protections that ordinarily come with permanent residency, and then spend years gathering the evidence needed to retroactively justify that decision. It need only prove its accusation to an immigration judge much later, and that proof somehow backfills the evidence the officer lacked at the border. Thomas would not even say that border officers bear any burden of proof before consigning LPRs to this legal purgatory, and he left open the possibility that they have no such burden at all. That would mean that an officer could simply invent an accusation of criminality, leaving the green-card holder trapped in a bureaucratic twilight zone for years before they have a chance to rebut the accusation at a hearing.
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And that twilight zone has serious costs—a fact that Thomas ignores but Jackson rightly highlights. Without a permanent green card, it is harder for legal permanent residents “to work, open bank accounts, secure housing, obtain health insurance, and enroll in school,” Jackson noted. It is also easier for the government to deport them. A typical green-card holder may not be removed unless the government proves they’re deportable. An LPR in Lau’s situation, by contrast, bears the burden of proving in immigration court that they are entitled to remain. Moreover, a single conviction for a crime of moral turpitude can be enough to expel an LPR in Lau’s position, even when that same conviction would not be enough to deport a green-card holder who had been formally admitted. They may even be detained for months or years while their case grinds through immigration court.
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Clarence Thomas gives US border agents terrifying new power
15 votes -
Comment on US Congress clears housing bill, cementing a rare bipartisan feat in ~society
skybrian LinkFrom the article: [...] [...] [...] [...]From the article:
The House on Tuesday overwhelmingly passed a landmark housing bill, notching a rare bipartisan accomplishment ahead of the midterm elections and clearing the way for President Trump to sign the most significant piece of housing legislation in 36 years.
The bill’s passage, by a lopsided 358-to-32 vote, ended months of sparring between the House and the Senate over a sprawling measure that aims to tackle the housing crisis by boosting supply in a country facing an acute shortage of new homes. The Senate passed its version of the same bill Monday, by a vote of 85 to 5.
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With dozens of provisions, the 21st Century Road to Housing Act aims to touch communities across the country, addressing rural and urban needs as part of a strategy to eventually bring down housing costs. It loosens federal regulations, making it easier, faster and cheaper to build; eases lending rules; rewards communities that build; delivers aid to communities reeling from disasters; and, in a policy that proved to be one of the biggest flash points but was favored by Mr. Trump, sets new limits on the role institutional investors can play in the market.
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Chief among the sticking points was a provision to check institutional investors, which had been crafted in negotiations among White House officials, Senator Tim Scott, the South Carolina Republican who leads the Banking Committee, and Ms. Warren.
The measure prohibits corporate entities from owning more than 350 existing single-family homes, although it does not require them to sell homes purchased before the measure became law. A stricter proposal that would have required investors to sell single-family homes built explicitly as rentals after seven years was dropped; it had prompted a backlash by home builders and affordable housing advocates, who feared it would discourage new home construction.
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The bill tackles the crisis from different angles. For example, manufactured homes, which are built in a factory and arrive at a site on a truck, will no longer have to be built on a steel chassis to meet federal standards, a change that could shave thousands of dollars of the cost of these homes, and expand the types of designs factories can build. The bill also loosens lending rules for these homes and provides grants to communities to repair existing ones, which are often cheaper and faster to build than stick-built homes.
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The bill also makes new construction of affordable housing eligible for certain federal grants; cuts requirements around environmental reviews to make it easier for communities to build faster; and offers funding for communities that are building housing to improve infrastructure.
And it loosens regulations overseeing community banks and makes it easier to get small mortgages of less than $100,000, an issue important in rural communities where housing costs are lower.
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US Congress clears housing bill, cementing a rare bipartisan feat
25 votes -
Comment on Micah Lasher wins New York primary to succeed his political mentor in star-studded contest in ~society
skybrian LinkFrom the article: [...] [...] [...]From the article:
New York Assembly member Micah Lasher won the Democratic primary Tuesday to succeed his political mentor Rep. Jerrold Nadler in the House, following a bitter primary that started as a celebrity contest and evolved into a proxy war between AI giants.
The district is a solidly blue seat, meaning Lasher is likely to win the general election in November. The New York City-based district is one of the richest and most highly educated and has sent liberal icons to Congress. Lasher was endorsed by Nadler and favored by many of New York’s top Democrats.
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In the final weeks of the race, Lasher was in a close contest with Bores as the primary evolved into a spendathon between AI firms OpenAI and Anthropic, which each poured millions into super PACs to influence the race.
The race wound up among the most expensive House primaries in New York history, with more than $26 million spent on TV ads alone, according to the political tracking firm AdImpact.
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Bores became a target of groups funded by investors behind OpenAI after shepherding a high-profile AI regulatory bill through the state assembly last year. His RAISE Act created new safety standards for AI developers including multimillion dollar penalties in New York state. Gov. Kathy Hochul (D) signed the bill into law in December, and Bores vowed to advance similar legislation federally if elected to Congress.
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Bores said the multi-million dollar effort against him was a warning from the AI industry to other Democrats not to pass robust AI regulation. During his concession speech Tuesday night, he urged Democrats “to look at this campaign, not as a cautionary tale, but as a blueprint to take into the future.”
Still, Bores also had deep-pocketed super PACs in his corner, including AI interests — something the OpenAI allies gleefully pointed out. A super PAC funded heavily by Anthropic, Open AI’s most prominent rival, spent more than $4 million in television ads supporting Bores, according to AdImpact. Total spending from Anthropic’s allies for Bores exceeded $10 million. Crypto tycoon Chris Larsen also committed more than $3 million to support Bores.
Anthropic and OpenAI have engaged in a bitter rivalry that has included competing political funding throughout the midterms. OpenAI has supported federal regulations for AI, while Anthropic has backed state-level legislation akin to Bores’s.
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Micah Lasher wins New York primary to succeed his political mentor in star-studded contest
7 votes -
Comment on UNC-Chapel Hill researchers developing the world’s largest sky-survey telescope in ~space
skybrian LinkFrom the article: [...] [...] [...]From the article:
The University of North Carolina at Chapel Hill is embarking on a bold new era of astronomical discovery with the construction of the Argus Array, a revolutionary telescope system that will be the first large telescope capable of observing the entire Northern nighttime sky at once and identifying rare cosmic events in real time.
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Rather than a single telescope, Argus is composed of an array of 1,200 small telescopes, each observing a different patch of sky. Together, they cover the entire sky in every exposure, ensuring that no transient event — from exploding stars to planetary microlensing events — goes unnoticed. The telescopes are arranged in a unique “pseudofocal” concept — an inverted bowl structure in which large groups of telescopes point inward through a single window. This configuration allows the entire array to operate inside a sealed, laboratory-like environment, protecting the sensitive optical equipment for a decade-long survey and dramatically lowering operating costs.
The Argus Array’s telescopes form a vast 122,000-megapixel camera — the world’s largest digital camera, by a factor of 30. Argus will take millions of 122-gigapixel images to build the first deep, high-speed movie of the Northern sky, discovering and following cosmic events as they happen.
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Argus will generate data at a rate of 2,000 gigabits per second, making it one of the largest producers of scientific data in the world. To deal with this vast data rate, the system will rely on high-speed computing and machine-learning algorithms to analyze data as it is collected, selecting the most interesting events and sky locations for long-term storage.
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In addition to its scientific impact, Argus will serve as a cornerstone for open data in astronomy. The project will conduct the deepest and fastest survey of the entire Northern sky to date, and the full dataset will be made publicly available — rapidly and completely.
I doubt it’s in reaction to protests. The companies that run data centers are always going to be interested in ways to improve efficiency.