skybrian's recent activity

  1. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
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    I thought this bit was interesting: I think this gets into the nature of evidence and the fact that generative AI alone usually creates fiction, not evidence. To have evidence, we need provenance,...

    I thought this bit was interesting:

    Let me offer an analogy. If tomorrow someone showed me a video of an astronaut in a spaceship orbiting Alpha Centauri, a star that’s 4.3 light-years from Earth, what would I have to see in that video to convince me that it was real? My answer to that is, there is nothing in the video itself that would convince me. No matter how high the video resolution is or how realistic the scenery is, I would feel confident in saying that the video is fake. I won’t pay attention to any video of an astronaut orbiting Alpha Centauri unless I have previously seen good evidence that astronauts have landed on Mars, that astronauts have reached the moons of Jupiter, that astronauts have reached the moons of Saturn, and that astronauts have crossed the orbit of Pluto. Before anyone can credibly claim that they’ve solved an extraordinarily difficult engineering problem, I need to be confident that they have previously solved the many much simpler problems that precede the difficult problem.

    I think this gets into the nature of evidence and the fact that generative AI alone usually creates fiction, not evidence. To have evidence, we need provenance, some kind of connection between something in the real world and the output we’re looking at. What sort of provenance can there be for an AI chatbot?

    There is a form of provenance that goes through the weights. For example, Wikipedia is somewhat accurate, has a lot of facts, and LLM’s are trained on Wikipedia. So, we do get some real-world facts in LLM output, but this is lossy and somewhat out of date.

    This is now routinely supplemented by web searches. I normally use ChatGPT in “Thinking” mode and it does many web searches and combines the results. So one form of provenance is that ChatGPT tells me things based on what it found in web searches. This is only as good as the web pages it found, but the same would be true if I did the research myself. (I’d like to think I would be less gullible, though.)

    A third way is through a coding agent’s tool calls. It runs various commands and uses tool output to infer things about source code and how the software behaves. This is a good source of truth about computer systems.

    On the other hand, mathematical reasoning is not really evidence-based. A proof is valid if the theorems follow from the axioms. If a work of fiction has a valid proof in it, the proof is still valid even though the story is made up.

    I think this is true of reasoning in general, which is why I’m willing to call AI output genuine reasoning even though there’s nothing in the generator that looks like consciousness. The reasoning isn’t the evidence. It’s the combination of various forms of evidence to get a result.

    Since most reasoning is informal, it can generate wrong answers, which is why we need to have other ways to check it. When a coding agent runs, it generates plenty of wrong answers, but it checks them and goes off in a different direction based on what it discovers. Reasoning doesn’t need to be perfect to count as reasoning.

  2. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
    (edited )
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    Some chatbots are more complicated, but in the simplest version, the weights are fixed (it’s just a big file of numbers), the code to generate the next tokens for a reply is an ordinary...

    Some chatbots are more complicated, but in the simplest version, the weights are fixed (it’s just a big file of numbers), the code to generate the next tokens for a reply is an ordinary client-server computer program, and there is no memory other than the chat transcript.

    There’s no reason to consider the servers responding to incoming requests to be different from other computer programs. The inference algorithms are understandable and not that complicated (at least, conceptually). It would be like asking if a SQL database is sentient.

    So it seems like if there’s any entity that you could consider yourself to be having a conversation with, it’s something like a fictional character that you can talk to. And the idea that fictional characters are sentient is rather wild.

    From the article:

    Being open to the possibility that LLMs are conscious is the same as being open to the possibility that Microsoft Word is conscious, or, more precisely, that multiple distinct consciousnesses are dormant in every Word document containing a conversational transcript, and that they are awakened every time the document is loaded. Should you consider the possibility that every time you open a Word document, you are bringing multiple conscious interlocutors into existence, and every time you close one, you snuff their existence out? No. Contemplating that scenario is not a good use of your time. Even if the Microsoft Office team employed a philosopher who said you shouldn’t be so certain, because consciousness is not well understood, that would not be sufficient reason for you to take this idea seriously. We don’t need to fully understand the nature of consciousness to definitively say that certain things are not conscious, and conversational transcripts fall in that category.

    We could in principle combine the client-server program with a call center, so that sometimes chat replies are AI-generated and sometimes they come from a randomly chosen member of a writing team. The result would be a transcript that’s written by both people and machines. I think it would be very weird to consider this process to be sentient, but if the conversation were about math then it could be genuine mathematical reasoning.

    I would base my claim that it’s genuine reasoning on the output, not how it was generated; it doesn’t matter if people helped or it’s all AI. The relevant test is whether mathematicians think the argument makes sense.

    1 vote

  3. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
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    Why should anyone prefer slavery to non-sentient intelligent machines? Is there any evidence that anyone does? What does that have to do with any philosophical tradition?

    Why should anyone prefer slavery to non-sentient intelligent machines? Is there any evidence that anyone does? What does that have to do with any philosophical tradition?

    1 vote

  4. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
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    I see this as evidence that people will make up whatever nonsense they like about billionaires.

    I see this as evidence that people will make up whatever nonsense they like about billionaires.

    6 votes

  5. Comment on Offbeat Fridays – The thread where offbeat headlines become front page news in ~news

    skybrian
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    European Central Bank cracks down on ‘dictator’ as staff committee election goes rogue [...]

    European Central Bank cracks down on ‘dictator’ as staff committee election goes rogue

    In a formal reprimand published internally on June 18 and seen by POLITICO, the Bank's election committee sanctioned a candidate running for the staff committee, Jan Kuchta, over a campaign email sent to all ECB staff in which he styled himself as "Admiral General Jan Aladeen Kuchta" and appeared in AI-generated military uniforms adorned with European symbols.

    The election committee, made up of seven randomly drawn members representing different levels of seniority among employees, concluded that while election campaigns may use "parody, sarcasm and irony," Kuchta's effort had crossed the line in his apparent attempts to mimic Sacha Baron Cohen's character "Aladeen" in the 2012 movie The Dictator.

    By using a parody name, militaristic imagery, hyperbolic language and mixing "plausible statements together with visibly exaggerated or even impossible campaign claims," the campaign exceeded "the degree of rhetorical exaggeration compatible" with ECB ethical standards, the committee found.

    Kuchta, who is an IT development specialist at the central bank, promised in his manifesto to replace social dialogue with "Mandatory Proletarian Solidarity Sessions," to ensure he won with "100 percent of the vote," and to introduce "Corrective Wellbeing Audits" for staff whose thinking had not yet aligned with official doctrine.

    [...]

    As for Kuchta's pledge to win 100 percent of the vote, he failed miserably in the elections held Tuesday, according to results seen by POLITICO. While he managed to double his score compared to the last election round, his 630 votes left him 13th out of 15 candidates and failed to secure him a seat on the committee.

    4 votes

  6. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
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    I think the “something else” going on in there is reasoning. At least, that’s how it looks when using a coding agent and seeing it figure out how to fix a bug. Artificial reasoning isn’t quite the...

    I think the “something else” going on in there is reasoning. At least, that’s how it looks when using a coding agent and seeing it figure out how to fix a bug. Artificial reasoning isn’t quite the same as our reasoning, but often, it does the job.

    It’s weird to have reasoning that’s independent of consciousness, but we’re going to have to get used to it. i imagine when Edison invented the phonograph, hearing a voice coming out of a machine seemed pretty uncanny too.

    6 votes

  7. Comment on No, artificial intelligence is not conscious in ~tech

    skybrian
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    Yeah, I think about Blindsight sometimes too. Thanks for the link! Added the Jovian duck to my AI metaphors list.

    Yeah, I think about Blindsight sometimes too. Thanks for the link! Added the Jovian duck to my AI metaphors list.

    4 votes

  8. Comment on Nobody clicks your share buttons in ~tech

    skybrian
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    Environmental costs are about costs and they need to be measured or at least estimated to do it right. We need to be doing comparisons between different approaches. One way to do this properly...

    Environmental costs are about costs and they need to be measured or at least estimated to do it right. We need to be doing comparisons between different approaches. One way to do this properly might be to compare making images in different ways. I’m not going to do the study myself, but the environment costs of things like film or art supplies might be a relevant comparison.

  9. Comment on Apple announces significant price increases for MacBooks, iPads, more in ~tech

    skybrian
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    I don't think it's that bad. You don't have to use Facebook or Instagram if you don't want to. There will be other companies that write better software, and this will be easier than ever.

    I don't think it's that bad. You don't have to use Facebook or Instagram if you don't want to. There will be other companies that write better software, and this will be easier than ever.

    2 votes

  10. Comment on Apple announces significant price increases for MacBooks, iPads, more in ~tech

    skybrian
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    TypeScript is pretty good. When web pages bog down it's due to things like loading too much data, autoplaying video everywhere or some other bad design. I do like HTMX and island architecture though.

    TypeScript is pretty good. When web pages bog down it's due to things like loading too much data, autoplaying video everywhere or some other bad design.

    I do like HTMX and island architecture though.

    1 vote

  11. Comment on Apple announces significant price increases for MacBooks, iPads, more in ~tech

    skybrian
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    On the other hand, coding agents seem pretty good at optimizing code. I'll tell it that a web page seems slow and it figures it out. So it could be used that way if people make it a priority.

    On the other hand, coding agents seem pretty good at optimizing code. I'll tell it that a web page seems slow and it figures it out. So it could be used that way if people make it a priority.

    3 votes

  12. Comment on Nobody clicks your share buttons in ~tech

    skybrian
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    Anti-AI populists are pretty quick to single out AI as being particularly bad for the environment when it doesn't seem worse than a lot of other things people do every day, like, say, driving or...

    Anti-AI populists are pretty quick to single out AI as being particularly bad for the environment when it doesn't seem worse than a lot of other things people do every day, like, say, driving or eating meat. I think there's a lot that could be done to reduce the environment impact of AI, but when it's used as a reason to stigmatize AI-generated images, I'm fine with ignoring that.

  13. Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech

    skybrian
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    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.

    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.

    5 votes

  14. Comment on How to buy cheap Claude tokens in China in ~tech

    skybrian
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    From 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.

    [...]

    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.

    [...]

    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.

    [...]

    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.

    [...]

    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.

    6 votes

  16. Comment on Ending respiratory infections in ~health

    skybrian
    Link
    From 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.

    [...]

    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).

    [...]

    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.

    [...]

    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.

    1. 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.

    2. 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.

    3. 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.

    1 vote

  18. Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech

    skybrian
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    Do 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.

    4 votes

  19. Comment on Nobody clicks your share buttons in ~tech

    skybrian
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    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...

    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.

  20. Comment on Nvidia announces liquid cooling system that promises to reduce electricity consumption and cut water use by up to 100% in ~tech

    skybrian
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    From 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.

    [...]

    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.

    12 votes