Astral Codex Ten

Miller

31 min read

Miller

Article

Miller is a recurring person in the Astral Codex Ten archive, appearing 3 times across 3 issues between July 08, 2022 and September 19, 2025. The archive places it in contexts such as “Miller, Zhang, and Azrael (2021) explores this question”; “Miller incorrectly claimed the N501Y mutation would result from passage in hACE2 mice”; “The major papers Miller relied on have been seriously challenged”. It most often appears alongside New York Times, Philadelphia, San Francisco.

Metadata

  • Category: People
  • Mention count: 3
  • Issue count: 3
  • First seen: July 08, 2022
  • Last seen: September 19, 2025

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

Highlights From The Comments On The 2020 Homicide Spike
July 08, 2022 · Original source
Guns are a much bigger factor in violent crime, which increased, then property crime, which decreased. Mass gun sales are a US phenomenon, with per-capita gun ownership in the US being the highest in the world, double the next contender and 5-10 times higher than Canada and Europe. If you're motivated to commit a murder, then whether you currently have a gun seems much more strongly and directly influential than whether you've briefly noticed a police car in the neighborhood in the past week or whether the police seem worried about being cancelled. [separated out unrelated paragraph here into a different section] If increased gun sales largely motivated by the 2020 riots were the most significant factor in the spike, that would be politically inconvenient for both the left and the right- I'd expect good reporting on that to be a bit slim. It would also be politically inconvenient for libertarians, though I hope you'll avoid the mistake of the journalists you criticize, and not allow politics to subconsciously shape how easily you reject hypotheses. I accept I should have put more work in the original post into ruling out gun sales as the cause. That having been said, I still don’t think gun sales were the cause, for four reasons. First, this argument confuses stocks and flows. The flow of guns went up by about 50% over 2020. The stock of guns went up much less. Wikipedia says there are about 400 million guns in the US. That means that in 2019, when people bought about 14 million guns, the total number of guns was going up about 3.5% (and murder was low). In 2020, when people instead bought about 22 million guns, the total number of guns went up 5.5%, so about 2 percentage points more than in a normal year. So this theory requires us to believe that number of guns increasing 3.5% every year from 2015 - 2020 had no effect on the murder rate, but that guns going up 5.5% in 2020 had a very strong effect on the murder rate. Specifically, an extra two percent increase in guns must lead to a 30% increase in murder rates. Why would we believe that? One reason might be if the people buying guns in 2020 were very different from the people buying guns in previous years. For example, if previous gun buyers were collectors who had 100 guns each, but 2020 gun owners were new buyers getting their first gun, then the share of people with at least one gun would go up by more than 2% over an average year. Miller, Zhang, and Azrael (2021) explores this question (thanks, darawk) and find the opposite: The people buying new guns are mostly (~80%) people who have guns already. This varies a bit by time period but other periods (the beginning of the pandemic and the 1/6 insurrection) were more disproportionately new gun owners than the June period when homicides started to spike. This also shows that the largest month-over-month increases in gun purchases, both new and total, were March 2020 and January 2021. There was no sudden homicide spike associated with either of these months, only May/June 2020. Finally, guns are usually more correlated with suicide deaths than with homicide deaths… State by state correlation between gun ownership and murder rates (left), and between gun ownership and suicide rates (right). Source here. …but there was no spike in suicides at the same time as the murder spike: Source This is what you’d expect given that the number of guns only increased by 2% over trend - a completely invisible effect on suicide. Unrelatedly, homicides rose by 30%. So the gun hypothesis requires that: Crime tracks the flow, rather than the stock, of guns.
Inline links: Wikipedia says, Miller, Zhang, and Azrael, darawk, https://substackcdn.com/image/fetch/$s_!alVC!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F3aee0f48-0747-4a30-80b3-297d79f4f7fc_710x504.png, https://substackcdn.com/image/fetch/$s_!TQUx!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5918467a-45dc-4e87-a2ab-230744fda597_1015x404.png, here, https://substackcdn.com/image/fetch/$s_!EJEG!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fbb830b21-3151-4e54-9310-c3c29a0436bb_325x235.png, Source
Highlights From The Comments On The Lab Leak Debate
April 09, 2024 · Original source
This alone isn’t fatal to lab leak. It’s perfectly possible for the lab to leak (let’s say) November 5th, the virus spreads a bit, and then a month later someone goes to the wet market, coughs on a vendor, and starts the officially recognized pandemic. But if that were true, you’d expect (let’s say) 30 cases by early December. Let’s say the wet market vendor was exactly Case # 30. She infected the other wet market vendors, starting a pandemic with an obvious center at the wet market and lots of infected wet market vendors and patrons. What about Case # 29? If they were (let’s say) a barista, how come they didn’t infect people at their coffee shop? How come there wasn’t a second obvious cluster radiating out from a coffee shop, lots of coffee-shop-linked cases, etc? How come there weren’t 30 equally-sized clusters? In order to avoid this, you either need to claim that the wet market was a perfect superspreader location, or that the pattern with lots of cases in the wet market and few-to-none anywhere else was a result of ascertainment bias. Saar made both those arguments during the debate, but I thought Peter rebutted them effectively. 1.4: COVID in Brazilian wastewater Nicholas Halden (blog) writes: What should we make of this study, which found the presence of covid in Brazilian wastewater in late 2019? Consider the doubling times. The study says that scientists working in late 2020 found COVID in samples of Brazilian wastewater from November 27, 2019. This was long before the first detected case of transmission in Brazil on March 13, 2020. Between November 27, 2019 and March 13, 2020 is about 16 weeks, so 32 COVID doubling times. 32 doubling times with no lockdown is enough time for COVID to infect every single person in Brazil. If COVID had infected everyone in Brazil before the first recognized case, we would have noticed. (again, COVID doubling time isn’t exactly invariably 3.5 days, but here we’re talking about numbers big enough that the exact details don’t matter very much) So if COVID was in Brazil on November 27, it must have fizzled out instead of going pandemic. How likely is that? If one person had COVID, it’s not too unlikely - not all COVID cases transmit it forward. If (let’s say) twenty people had COVID, it’s very unlikely - at that point, the law of large numbers takes over; in a freak coincidence, every single patient would have to fail to infect anyone else. So almost certainly fewer than 20 people in Brazil had COVID in November 27. So which is more likely - that somehow 20 people had COVID long before the virus was officially detected, and on a totally different continent, yet somehow a scientist looking through wastewater found the water from exactly those people and managed to detect the virus? Or that there was a sampling error, which happens all the time in these kinds of things? Peter wrote a blog post on some of these issues. He found that there were positive tests from wastewater samples as early as March 2019, which doesn’t fit anyone’s timeline, including lab leakers’. And most of these positives (including the Brazilian sample) contained later strains of the virus with mutations it picked up late in 2020. So these were almost certainly false positives from contamination. 1.5: Biorealism’s 16 arguments Biorealism has a list of sixteen arguments, which he liked so much that he posted it three times in the ACX comments, twice on Less Wrong, twice on Manifold, and about a dozen times on Twitter under multiple account names. Some posts were slightly different from others, but a typical version is: Importantly, Miller incorrectly claimed the N501Y mutation would result from passage in hACE2 mice (mixed them up with BALB/c mice). The major papers Miller relied on have been seriously challenged since the debate. See Stoyan and Chiu (2024), Weissman (2024), Bloom (2023) and Lv et al (2024). Overall the circumstantial evidence makes lab v plausible: Peter admitted getting this wrong during the debate. I think this very minor point about mice mutations was approximately his only mistake in 15 hours of debating, and he admitted it as soon as he noticed. Biorealism somehow heard about this (obviously not through watching the debate, as we’ll see in a moment), then left about 20-30 comments starting with it, under various accounts, on various platforms, as if it somehow discredited Peter. This is making me somewhat less charitable to him and his 16 arguments than I would be otherwise. 1. Chinese researchers Botao & Lei Xiao observed lab origin was likely given the nearest known relatives to SARS-CoV-2 were far from Wuhan. Wuhan Institute of Virology (WIV) sampled SARS-related bat coronaviruses where the nearest relatives are found in Yunnan, Laos and Vietnam ~1500km away. They refuse to share their records. The ancestral viruses of SARS were found equally far from where SARS spilled over into humans, so we know it’s possible (and likely) for viruses to travel that far. 2. Patrick Berche, DG at Institut Pasteur in Lille 2014-18, notes you would expect secondary outbreaks if it arose via the live animal trade. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234839/ There are constant outbreaks of weird coronaviruses in animal handlers. See eg this paper, which estimates about 60,000 of these per year. None of these ever go anywhere, because the farmers are in rural areas that aren’t dense enough to sustain a high R0, and the epidemic fizzles out after a single digit number of cases. Any early outbreaks of COVID would have vanished into this long and mostly unnoticed list. 3. Molecular data: Only sarbecovirus with a furin cleavage site. Well adapted to human ACE2 cells. Low genetic diversity indicating a lack of prior circulation (Berche 2023). Restriction site SARS-CoV-2 BsaI/BsmBI restriction map falls neatly within the ideal range for a reverse genetics system and used previously at WIV and UNC. Ngram analysis of the codon usage per Professor Louis Nemzer https://twitter.com/BiophysicsFL/status/1667232580255490053?t=IJgitS5cw364ioclzVWxaA&s=19 The SARS2 backbone is very low in CG and CpG. While the 12-nt insert that gives it the FCS is extremely high in both. Almost as if it was some kind of chimera of a consensus sequence and a codon-optimized polybasic cleavage site? https://twitter.com/BiophysicsFL/status/1752800486837678377?t=EpIRgyybJVaPgeMP5xdstA&s=19 https://www.biorxiv.org/content/10.1101/2022.10.18.512756v1 https://link.springer.com/article/10.1007/s10311-021-01211-0?fbclid=IwAR1HMUMtLIAFOFppVasQDeoIAYrVhP8j4YoPO4wnaTOUiKLsllZl_oKryOw Most of this was discussed extensively in the second session of the debate, which I recommend. The CGG-CGG arginine codon usage is particularly unusual but used in synthetic biology. I asked a synthetic biologist about this. He said: » “Nope. I would literally never do this if I was designing a small insert (maybe I wouldn't notice if it happened by chance with ~1 in 25 odds in a naive codon optimization algorithm as part of a larger sequence). High GC% is bad. Tandem repeat is worse. Several other perfectly fine arginine codons. And I wouldn't engineer a viral genome using human codon usage. An engineer would not do it.” 4. DEFUSE full proposal: virus 20% different from SARS1, consensus seq assembled with 6 segments, without disrupting coding seq, BsmBI order, FCS. SARS2: 20% different than SARS1, 6 evenly spaced fragments w BsmBI and BsaI restriction sites, FCS. Jesse Bloom, Jack Nunberg, Robert Townley, Alexandre Hassanin have observed this workflow could have lead to SARS-CoV-2. Work often begins before funding sought or goes ahead anyway. Re: 4 - Also scattered across second section of debate, also not going to retread 5. Market cases were all lineage B. Lv et al (2024) indicates there was a single point of emergence and A came before B. So market cases not the primary cases. See also Bloom (2021), Kumar et al (2022). Peter Ben Embarek said there were likely already thousands of cases in Wuhan in December 2019.https://t.co/50kFV9zSb6 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/34398234/ https://academic.oup.com/bioinformatics/article/38/10/2719/6553661 There was a Lineage A sample in the market, lab leak proponents just try to ignore/dismiss/conspiracize it away. The first two known Lineage A cases were very close to the market. Lv (is this even a real name? It sounds like Roman numeral? But I guess that’s what you expect in a country ruled by someone named Xi) found some weird COVID variants in Shanghai that might or might not mean anything; you can see some discussion of the implications here, but I don’t think they’re strong evidence either way. If A was first, it means some really weird stuff coincidences have to happen to give us the spread rates and genetic clock data we get, but they’re not necessarily weirder in the zoonosis hypothesis than the lab leak one. The claim that there were “thousands of cases in Wuhan in December 2019” is very easy to disprove by doubling rate arguments like the one above, by the blood bank study mentioned above, by the WHO’s failed case search, and by many other lines of argument. 6. Evidence for lineage A in the market is based on a low quality sample according to Liu et. al. (2023). I really think lab leakers need to decide whether they think China is a sinister actor trying to cover up the truth, or whether they should trust every offhand comment by Chinese government officials as gospel. Dr. Liu doesn’t explain in what sense he thinks the Lineage A sample is “low-quality”, and the Western scientists who I asked about this said they didn’t understand this complaint and that the sample was fine. A Western team re-analyzing the same sample describes it as “conclusively contain[ing] Lineage A.” I think most lab leakers have switched from trying to deny the genetics to claiming that this was “contamination”, which also doesn’t make sense (the sample is genetically very early). Note that aside from this sample, the first two Lineage A cases discovered were both very close to the wet market. 7. Bloom (2023) shows market samples do not support market origin. There is also no evidence of transmission in the claimed susceptible animals elsewhere. https://academic.oup.com/ve/advance-article/doi/10.1093/ve/vead089/7504441 Discussed extensively in my article as well as the first section of the debate. 8. Lineage A and B only two mutations apart. François Ballox, Bloom and Virginie Courtier-Orgogozo note this is unlikely to reflect two separate animal spillovers as opposed to incomplete case ascertainment of human to human transmission (Bloom 2021). Discussed extensively in my article as well as the first section of the debate. 9. Sampling bias. George Gao, Chinese CDC head at the time, acknowledged to the BBC stating they may have focused too much on and around the market and missed cases on the other side of the city. David Bahry outlines the documented bias. Michael Weissman has shown this mathematically. https://journals.asm.org/doi/10.1128/mbio.00313-23 https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnae021/7632556 Re: Dr. Gao, see above comment about Chinese officials. See the section Ascertainment Bias below for why I disagree with this specific claim, which also addresses the Michael Weissman argument. 10. Spatial statistics experts show the Worobey claim the market was the early epicentre was flawed. https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnad139/7557954 Re: 10 - See Confirmation Of The Centrality Of The Huanan Market Among Early COVID-19 Cases, a response to the paper you cite: The centrality of Wuhan's Huanan market in maps of December 2019 COVID-19 case residential locations, established by Worobey et al. (2022a), has recently been challenged by Stoyan and Chiu (2024, SC2024). SC2024 proposed a statistical test based on the premise that the measure of central tendency (hereafter, "centre") of a sample of case locations must coincide with the exact point from which local transmission began. Here we show that this premise is erroneous. SC2024 put forward two alternative centres (centroid and mode) to the centre-point which was used by Worobey et al. for some analyses, and proposed a bootstrapping method, based on their premise, to test whether a particular location is consistent with it being the point source of transmission. We show that SC2024's concerns about the use of centre-points are inconsequential, and that use of centroids for these data is inadvisable. The mode is an appropriate, even optimal, choice as centre; however, contrary to SC2024's results, we demonstrate that with proper implementation of their methods, the mode falls at the entrance of a parking lot at the market itself, and the 95% confidence region around the mode includes the market. Thus, the market cannot be rejected as central even by SC2024's overly stringent statistical test. I think this response is pretty strong. In one analysis, they show that even though the other paper’s methodology is worse than theirs, if you apply it correctly (instead of inappropriately excluding various cases like the paper’s authors did), the center of all early cases in Hubei province lands on the wet market parking lot. In another analysis, they show that the other paper’s recommended tests wouldn’t have correctly pointed to the offending water pump in the famous John Snow cholera outbreak, but theirs would have. Still, I think it’s useful to supplement fancy statistics with normal common sense, so I recommend just looking at the map of early cases: …and deciding whether you think the assumptions behind a specific statistical test are likely to debunk the idea that cases are centered around the wet market. 11. Wuhan used as a control for a 2015 serological study on SARS-related bat coronaviruses due to its urban location. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/ I don’t know why this point is supposed to matter. If you mean that Wuhan isn’t directly exposed to bats, nobody ever said it was. The zoonotic theory is that wildlife carted in from other areas of China started the pandemic in the wet market. 12. Superspreader events also seen at wet markets in Beijing and Singapore (Xinfadi and Jurong). This was discussed very extensively in the debates, both in section 1 and section 3. Wet markets weren’t “superspreader locations” - in fact, the disease spread no more quickly there than anywhere else. They were the first place in those cities that the pandemic started, due to contaminated animal products. If anything, this supports zoonosis. See also my discussion with Saar on this point below. 13. WIV refuse to share their records with NIH who terminated subaward in 2022. Wider suspension over biosafety concerns. https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling Although WIV has not been especially forthcoming, some of their databases were leaked in various ways and showed that they did not have any viruses capable of transforming into COVID. 14. PLA involvement at WIV and MERS research prior to SARS-COV-2. MERS features several similarities with SARS-CoV-2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/ I can’t even tell what conspiracy theory you’re trying to propose with this one; if you spell it out I can try to explain why it might be false. 15. SARS1 leaked several times and SARS-COV-2 has leaked from a BSL-3 lab in Taiwan. Agreed that SARS leaked several times. It also spilled over from animals several times. During the debate, a lab leak rate of once per lab per 500 years was proposed (everyone agreed to steelman this by 10x for WIV numbers); I would be interested to know whether anything about the study of SARS challenges that number. 16. Unpublished infectious clone identified from Wuhan contradicting arguments such reverse genetics systems would be published. https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full I asked some scientists about this paper and here’s what they told me. Wuhan University sequenced some rice. In the middle of the sequence, there’s an unexpected sequence from a common coronavirus, HKU4. The most likely explanation is that someone else in Wuhan was working on the coronavirus and there was cross-contamination. Plausibly this is Wuhan Institute of Virology, who is known to work with coronaviruses. This is cool detective work, but it’s not clear what it’s supposed to prove. I think some lab leakers are using it to prove that WIV can do reverse genetics, but they admitted this already in a published paper so that’s not too helpful. I think others are using it to prove WIV had “secret viruses” in their catalogue, but the rice virus wasn’t secret, it was HKU4, which is common and which WIV has already published papers about. 1.6: DrJayChou’s 7 Arguments Once again, I cannot stress enough how much better a take you might have on this debate if you watch it. “The first known case predates the market outbreak by a month” - this is not the consensus position. I cannot say for sure what Dr. Chou means by this, but I suspect he’s referring to one of the many claims to this effect that Peter effectively debunked during the debate (Connor Reed, Mr. Chen, the 92 cases, Brazil, etc).
Inline links: blog, writes, this study, wrote a blog post on some of these issues, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10234839/, this paper, https://twitter.com/BiophysicsFL/status/1667232580255490053?t=IJgitS5cw364ioclzVWxaA&s=19, https://twitter.com/BiophysicsFL/status/1752800486837678377?t=EpIRgyybJVaPgeMP5xdstA&s=19, https://www.biorxiv.org/content/10.1101/2022.10.18.512756v1, https://link.springer.com/article/10.1007/s10311-021-01211-0?fbclid=IwAR1HMUMtLIAFOFppVasQDeoIAYrVhP8j4YoPO4wnaTOUiKLsllZl_oKryOw, https://t.co/50kFV9zSb6, https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/34398234/, https://academic.oup.com/bioinformatics/article/38/10/2719/6553661, here, describes it as, https://academic.oup.com/ve/advance-article/doi/10.1093/ve/vead089/7504441, https://journals.asm.org/doi/10.1128/mbio.00313-23, https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnae021/7632556, https://academic.oup.com/jrsssa/advance-article-abstract/doi/10.1093/jrsssa/qnad139/7557954, Confirmation Of The Centrality Of The Huanan Market Among Early COVID-19 Cases, https://substackcdn.com/image/fetch/$s_!BNAm!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fffd4cddb-6e3e-41f5-8ef6-ec0b27bec600_626x426.webp, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6178078/, https://www.bloomberg.com/news/articles/2023-07-18/us-suspends-wuhan-institute-funds-over-covid-stonewalling, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022351/, https://www.biorxiv.org/content/10.1101/2023.02.12.528210v1.full, a published paper, has already published papers about, https://substackcdn.com/image/fetch/$s_!yA9U!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F467dd304-190a-4437-8920-d498c433dffb_1600x960.jpeg
If there are other claims about Pekar and Worobey being “debunked”, I don’t know them. In general, I find claims about “debunking” annoying even when they’re made by Important People who theoretically have the authority to make pronouncements. I think they’re even more annoying when they’re made by self-styled rebels who admittedly disagree with the scientific consensus. 1.9: Was there ascertainment bias in early cases? observeralt writes: The judges put huge weight on early cases being near the market. Michael Weissman's recent paper showing ascertainment bias in early case data is also significant as Miller relies on the sampling being random. Chinese CDC head at the time George Gao acknowledged this to the BBC last too. They focused too much on and around the market and missed cases on the other side of the city. Here’s the Worobey map everyone is debating: Before going further, I recommend reading page 8 of the supplementary text of Worobey’s paper, titled “Robustness Of Statistical Test Results To Ascertainment Bias”, or pages 14-17, “Additional Data Related To Case Ascertainment Biases”, which explain all the reasons he thinks this isn’t true. I promise you aren’t the first person to think that maybe Worobey could be contaminated by ascertainment bias. If that still doesn’t help, Worobey talks more about his strategy for avoiding ascertainment bias here. Most important, he counted only cases from December; the market connection was discovered December 30 and added to diagnostic criteria January 3. This doesn’t mean bias is impossible - some of these points are people who caught COVID on December 31, but only got diagnosed January 4 after the new diagnostic criteria were added. But most cases are pre-criteria. And Worobey looked at various subsets of pre-criteria cases and found they were all at least as market-focused as the overall set. For example, he looked at the earliest COVID records in one Wuhan hospital system: 10 of these hospitals’ 19 earliest COVID-19 cases were linked to Huanan Market (∼53%), comparable both to Jinyintan’s 66% (of 41 cases) (4) and to the WHO-China report’s 33% of 168 retrospectively identified cases within Wuhan across December 2019 (1). Regarding cases at the Wuhan Central Hospital and HPHICWM, patients with a history of exposure at Huanan Market could not have been “cherry picked” before anyone had identified the market as an epidemiologic risk factor. Hence, there was a genuine preponderance of early COVID-19 cases associated with Huanan Market. Likewise, a study conducted January 2 (so not impacted at all by the January 3 criteria) found that 27 of 41 known patients had market links. Likewise, the first five cases were all detected in the market, and it doesn’t even make sense to talk about ascertainment bias for these. What is the Weissman paper that observeralt is talking about? It argues: if the pandemic started at the market, each seemingly non-market-linked case must ultimately derive from a market-linked case. Therefore, we should expect non-market-linked cases to require more steps than market-linked cases. Therefore, they should be further away. But if we look at the map above, we see that not-market-linked cases are closer to the market than market-linked cases. So something must be wrong, and that something might be ascertainment bias. (at least this is my interpretation of Weissman’s argument, which is more mathematical; read the paper to make sure I’m getting it right). This is a weirdly spherical-cow view of an epidemic, worthy of a physicist. It’s easy to think of reasons the linked-cases-should-be-closer rule might not hold. For example, suppose that on their lunch break, market vendors go have lunch at restaurants surrounding the market. They infect people in these restaurants, who then infect their friends and family. But these people never went to the market themselves. Now there are a bunch of non-market-linked cases immediately surrounding the wet market. But also - of all markets in Wuhan, Huanan sold the most weird wildlife. Suppose someone in the boonies gets a craving for raccoon-dog one day, their local convenience store doesn’t have it, so they hop on a bus and go downtown to the city’s main wet market. Then they get infected with COVID. Now there’s a wet-market-linked case in the boonies. In other words, we should expect two modes of spread: general geographic diffusion from the epicenter, and people from far away who made specific trips. If this still doesn’t seem obvious to you, consider - usually when COVID first arrived in America or Brazil or wherever, they were able to trace it back to a specific person from Wuhan who visited the country. If I was the first person in America to get COVID, I could usually say “Oh, it must have been my business meeting with Mr. Chin from Wuhan”. At the same time, if someone from the next town over from Wuhan got COVID, they probably couldn’t trace it back to a specific Wuhanite - everyone from Wuhan is coming and going so often that my town is just full of COVID in general. So I don’t think Weissman’s paper proves anything, and I think the general pattern of blue and orange dots suggests ascertainment bias wasn’t playing a role. So why does George Gao say that there was ascertainment bias? I looked for the direct source of the Gao quote and couldn’t find it; if someone else is able to, please let me know, since I’d be interested in exactly what he thinks about this. 1.10: Connor Reed / Gwern on cats Gwern wrote: Yes, I don't understand this (paraphrased) claim by Peter: > He also told the Mail that his cat got the coronavirus too, which is impossible. 'Impossible', thus implying the man was lying? I was under the impression that, quite aside from cats having tons of coronaviruses in general (FCoV being a particularly serious threat to young cats, which also seems to be a remarkable case study of the harms of the FDA), that it was not just not 'impossible' for domestic pet cats to get the coronavirus too, it was routine for them to get COVID-19, and even other cat species in *zoos* have tested positive and this was true very early in the COVID-19 pandemic and quite well publicized and well known (eg April 2020 https://www.nationalgeographic.com/animals/article/tiger-coronavirus-covid19-positive-test-bronx-zoo ). This was a topic of interest to me at the time because I like cats and have a cat and was wondering what the implications of me being inevitably infected might be for my cat, and so I remember this quite well despite my general attempt to remain ignorant of as many COVID-19 matters as possible... And double-checking now to see if all of these reports were somehow false positives or faked, I continue to see everyone like the CDC stating that it is still totally possible and routine for cats in close contact with infected humans (you know, like a *pet* cat) to be infected with COVID-19: https://www.cdc.gov/healthypets/covid-19/pets.html Given that Peter has supposedly spent years autistically researching every last detail and this detail in particular in order to discredit that British dude, I'm experiencing sudden Gell-Man Amnesia here about the rest of his claims, as well as the supposed experts evaluating Peter's claims if they didn't flag that (I have not checked). This is in the context of Connor Reed, a British man who claimed to have gotten COVID on November 25 - which, if true, would be surprisingly (though not impossibly) early according to the zoonosis narrative. Peter argued his story didn’t hold up, and one of his points centered around his claim that his cat might have caught COVID from him and died. Unfortunately, I mis-quoted Peter. I said Peter argued it was impossible for his cat to get COVID-19 (false). His actual statement was that it’s extremely rare for a cat to die of COVID-19. Peter, Gwern, and I then proceeded to get very confused about the exact claims and timeline, which I think is because Connor said totally different things in different interviews: In an interview with Wales Online on 2/4/2020, he said that "my kitten caught the feline coronavirus and developed pneumonia and died, but I don't think I caught it from her. I think that was just coincidence.”
Inline links: claims about “debunking”, writes, https://substackcdn.com/image/fetch/$s_!9CBx!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1356d8dc-92cd-4f35-abd3-9b5706c1ed32_720x656.webp, here, 4, 1, a study, the Weissman paper, https://www.nationalgeographic.com/animals/article/tiger-coronavirus-covid19-positive-test-bronx-zoo, https://www.cdc.gov/healthypets/covid-19/pets.html, an interview with Wales Online
Your Review: Project Xanadu - The Internet That Might Have Been
September 19, 2025 · Original source
Mark Miller, a mathematical wunderkind who’d read Computer Lib and grokked it so hard that Nelson invited him to give a lecture to his UIC class when Miller was just 19, and a sophomore at Yale. The students all thought Nelson was crazy, and so they thought Miller was crazy too. Nelson thought him a genius.
Stuart Greene was a UIC student who thought Nelson and Miller might not be so crazy. He was invited to Pennsylvania too. Nelson, in his autobiography, describes Greene as “the mystic who’d taught holography at 14.”
Eric Hill, a 15-year-old hacker and indicted felon, who “had been dismissed by the judge with admiration.” In Swarthmore, Nelson hoped his decades-old dream of Xanadu would finally materialize. 5. Developing Xanadu Ted Nelson had built Project Xanadu into, for lack of better terminology, a cult.8 He writes: We all were deeply concerned about the Bad Guys, who we saw as a combination of IBM and the government. (The others were all Libertarians, I still called myself a Cynical Socialist.) The Bad Guys would spy on people, withhold and block information, and give us inferior hypertext. We had to Do It Right, to help prevent this. This meant using the standard business defenses—especially non-disclosure agreements (I made all of them sign) and secret proprietary algorithms. The Xanadians had a messiah—Ted Nelson—a gospel—Computer Lib—a persecution complex, a fearful dystopia—“inferior hypertext”—a hopeful utopia—Xanadu—and utter secrecy. Just six dudes in a rented house near Philly, building the internet, hiding from the Feds, signing NDAs, and saving the world. Nelson spent a summer explaining the project to his team in its entirety. By the end, Gregory, Miller, and Greene were the only ones left. They told Nelson, “We’ll do it,” and moved to another suburb, where they finally began to work on an implementation of Xanadu. The three quickly figured out a new system that would allow users to reference and link to specific parts of a file—they called these links tumblers, and made them work with transfinite numbers. Suddenly, transclusions were really possible. But after only a few early successes, the team’s progress stalled completely. Greene and Miller were young and left for jobs elsewhere, and so Gregory was left working on Xanadu alone. Nelson, meanwhile, ran a magazine called Creative Computing for a while, then tried again to build his JOT word processor—this time for the Apple II—then spent a year in San Antonio pitching a watered-down version of Xanadu (rebranded as “Vortext”) to a tech company called Datapoint. Datapoint wasn’t buying, but kept Nelson on in some sort of fake, primitive email job anyway. Gregory kept working on Xanadu in Philadelphia, slowly running out of money. Ted Nelson held an “Ecstasy party” in San Antonio: “A number of us floated down the river on inner tubes. It was quite lovely.” In 1987, like he did every year, Roger Gregory went to The Hackers Conference in Saratoga to show off the latest unimpressive version of Xanadu. There, he met a man named John Walker—founder of the wildly successful Autodesk—and pitched the project to him. Incredibly, Walker was interested, and after tense negotiations with Nelson, agreed to fund Xanadu in earnest. Beginning in 1988, Autodesk poured millions of dollars into the project, and a programming team led by Gregory finally started to make real progress. Walker said of Xanadu: “In 1980, it was the shared goal of a small group of brilliant technologists. By 1989, it will be a product. And by 1995, it will begin to change the world.” Sweeping rhetoric—clear deadlines. The team came nowhere close to meeting them. Infighting broke out between two factions—while Gregory simply wanted to patch together his old C code, insisting his product “was within six months of shipping,” the whiz-kid Mark Miller came back from his new job at Xerox PARC, alongside a half-dozen of his closest friends, and insisted on a perfectionistic rewrite in a more flexible language, Smalltalk. The PARC faction began to drive Gregory up the wall. According to Nelson, it got to the point that he “was throwing things and acting crazy.” So Nelson called John Walker, the two “summoned Roger to meet [them] at John’s house at Muir Beach, and Walker told Roger he was no longer in charge.” Miller took over and began the rewrite in Smalltalk. Walker’s deadline came and went, and the team delivered nothing. Xanadu’s offices descended into chaos—Miller anointed two PARC programmers to be “co-architects,” and the three of them increasingly left the rest of the team out of the loop. For four years, Miller dawdled about, adding features, giving them clever names (files were “berts,” after Bertrand Russell, and so, for symmetry’s sake, royalty-generating transclusions became “ernies”), and never building them.9 Meanwhile, Ted Nelson was living on a houseboat, attending sex retreats and Keristan orgies, and giving talks in Singapore. He recorded a new soundtrack for his student film, the one from 1959. In 1992, Autodesk’s stock cratered, and they divested entirely from Xanadu. Miller lamented that his program was just six months from completion. Ted Nelson started a film studio to make a movie with Doug Engelbart, then left for Japan to get a PhD. Xanadu’s code was open-sourced in the late 90s. 6. The World Wide Web In March 1989, a British computer scientist named Tim Berners-Lee, working at CERN, wrote a proposal for a system unifying hypertext and the internet. It was ignored. In 1990, Berners-Lee resubmitted his proposal, it was accepted, and he began to work on the World Wide Web. The WWW had a number of advantages over Xanadu: It was much simpler—Ted Nelson wrote of it disparagingly: “Where were annotation and marginal notes? Where was version management? Where was rights management? Where were multi-ended links? Where were third-party links? Where were transclusions? This ‘World Wide Web’ was just a lame text format and a lot of connected directories.” As it turns out, it’s much easier to build a lame text format and a lot of connected directories!
Inline links: 8, 9, Keristan