Quick takes

The Current Landscape: The current State-of-the-Art (SOTA) in function-based screening relies heavily on sophisticated machine learning models, such as Transformers and Sparse Autoencoders (SAEs), trained on massive genomic databases. These tools excel at analyzing sequence text to identify familiar structural homologies or dangerous functional motifs. By screening digital intent at the order stage, these models provide a highly effective defense against known biological threats and their immediate variants. The Frontier Challenge: However, as synthesis capabilities advance, the frontier of biosecurity faces a deeper challenge: predicting entirely novel, engineered mutations that do not exist in any historical training data. When an amino acid sequence is heavily modified, its digital text changes drastically, often allowing it to clear traditional pattern-matching filters as unclassified noise. Yet, if the altered sequence retains the ability to fold into the same functional three-dimensional shape, the underlying threat remains identical. To a purely computational framework, mapping these potential evolutionary trajectories feels like an intractable problem because the theoretical mutational space is nearly infinite. A Physics-Based Complement: A highly promising frontier lies in integrating these machine learning screens with principles of statistical mechanics to radically bound this problem space. In the physical world, an amino acid chain cannot simply adopt any arbitrary configuration; its survival and function are strictly governed by its thermodynamic energy landscape. Out of billions of theoretical sequence combinations, the vast majority are physically non-viable—they will naturally misfold, aggregate, or degrade due to energetic constraints. While calculating these landscapes from scratch remains a monumentally difficult computational challenge, leveraging thermodynamic stability models allows us to systematically filter out the non-physical noise. By

So... what's the general take on the hantavirus outbreak?

Gavi's investment opportunity for 2026-2030 says they expect to save 8 to 9 million lives, for which they would require a budget of at least $11.9 billion[1]. Unfortunately, Gavi only raised $9 billion, so they have to make some cuts to their plans[2]. And you really can't reduce spending by $3 billion without making some life-or-death decisions. Gavi's CEO has said that "for every $1.5 billion less, your ability to save 1.1 million lives is compromised"[3]. This would equal a marginal cost of $1,607 $1,363 per life saved, which seems a bit low to me. But I think there is a good chance Gavi's marginal cost per life saved is still cheap enough to clear GiveWell's cost-effectiveness bar. GiveWell hasn't made grants to Gavi, though. Why? ---------------------------------------- 1. https://www.gavi.org/sites/default/files/investing/funding/resource-mobilisation/Gavi-Investment-Opportunity-2026-2030.pdf, pp. 20 & 43 ↩︎ 2. https://www.devex.com/news/gavi-s-board-tasked-with-strategy-shift-in-light-of-3b-funding-gap-110595 ↩︎ 3. https://www.nature.com/articles/d41586-025-02270-x ↩︎

According to someone I chatted to at a party (not normally the optimal way to identify top new cause areas!) fungi might be a worrying new source of pandemics because of climate change. Apparently this is because thermal barriers prevented fungi from infecting humans, but because fungi are adapting to higher temperatures, they are now better able to overcome those barriers. This article has a bit more on this: https://theecologist.org/2026/jan/06/age-fungi Purportedly, this is even more scary than a pathogen you can catch from people, because you can catch this from the soil. I suspect that if this were, in fact, the case, I would have heard about it sooner. Interested to hear comments from people who know more about it than me, or have more capacity than me to read up about it a bit.

EU opportunities for early-career EAs: quick overview from someone who applied broadly I applied to several EU entry programmes to test the waters, and I wanted to share what worked, what didn’t, and what I'm still uncertain about, hoping to get some insights. Quick note: I'm a nurse, currently finishing a Master of Public Health, and trying to contribute as best I can to reducing biological risks. My specialisation is in Governance and Leadership in European Public Health, which explains my interest in EU career paths. I don’t necessarily think the EU is the best option for everyone. I just happen to be exploring it seriously at the moment and wanted to share what I’ve learned in case it’s useful to others. ⌨️ What I applied to & how it went * Blue Book traineeship – got it (starting October at HERA.04, Emergency Office of DG HERA) * European Committee of the Regions traineeship – rejected in pre-selection * European Economic & Social Committee traineeship – same * Eurofound traineeship – no response * EMA traineeship (2 applications: Training Content and Vaccine Outreach) – no response * Center for Democracy & Technology internship – no response * Schuman traineeship (Parliament) – no response * EFSA traineeship – interview but no feedback (I indicated HERA preference, so not surprised) If anyone needed a reminder: rejection is normal and to be expected, not a sign of your inadequacy. It only takes one “yes.” 📄 Key EA Forum posts that informed and inspired me * “EAs interested in EU policy: Consider applying for the European Commission’s Blue Book Traineeship” * “What I learned from a week in the EU policy bubble” – excellent perspective on the EU policymaking environment 🔍 Where to find EU traineeships All together here: 🔗 https://eu-careers.europa.eu/en/job-opportunities/traineeships?institution=All Includes Blue Book, Schuman, and agency-specific roles (EMA, EFSA, ECDC...). Traineeships are just traineeships: don’t underestimate what

I’ve seen a few people in the LessWrong community congratulate the community on predicting or preparing for covid-19 earlier than others, but I haven’t actually seen the evidence that the LessWrong community was particularly early on covid or gave particularly wise advice on what to do about it. I looked into this, and as far as I can tell, this self-congratulatory narrative is a complete myth. Many people were worried about and preparing for covid in early 2020 before everything finally snowballed in the second week of March 2020. I remember it personally. In January 2020, some stores sold out of face masks in several different cities in North America. (One example of many.) The oldest post on LessWrong tagged with "covid-19" is from well after this started happening. (I also searched the forum for posts containing "covid" or "coronavirus" and sorted by oldest. I couldn’t find an older post that was relevant.) The LessWrong post is written by a self-described "prepper" who strikes a cautious tone and, oddly, advises buying vitamins to boost the immune system. (This seems dubious, possibly pseudoscientific.) To me, that first post strikes a similarly ambivalent, cautious tone as many mainstream news articles published before that post. If you look at the covid-19 tag on LessWrong, the next post after that first one, the prepper one, is on February 5, 2020. The posts don't start to get really worried about covid until mid-to-late February. How is the rest of the world reacting at that time? Here's a New York Times article from February 2, 2020, entitled "Wuhan Coronavirus Looks Increasingly Like a Pandemic, Experts Say", well before any of the worried posts on LessWrong: The tone of the article is fairly alarmed, noting that in China the streets are deserted due to the outbreak, it compares the novel coronavirus to the 1918-1920 Spanish flu, and it gives expert quotes like this one: The worried posts on LessWrong don't start until weeks after this article was p

Striking paper by Anant Sudarshan and Eyal Frank (via Dylan Matthews at Vox Future Perfect) on the importance of vultures as a keystone species.  To quote the paper and newsletter — the basic story is that vultures are extraordinarily efficient scavengers, eating nearly all of a carcass less than an hour after finding it, and farmers in India historically relied on them to quickly remove livestock carcasses, so they functioned as a natural sanitation system in helping to control diseases that could otherwise be spread through the carcasses they consume. In 1994, farmers began using diclofenac to treat their livestock, due to the expiry of a patent long held by Novartis leading to the entry of cheap generic brands made by Indian companies. Diclofenac is a common painkiller, harmless to humans, but vultures develop kidney failure and die within weeks of digesting carrion with even small residues of it. Unfortunately this only came to light via research published a decade later in 2004, by which time the number of Indian vultures in the wild had tragically plummeted from tens of millions to just a few thousands today, the fastest for a bird species in recorded history and the largest in magnitude since the extinction of the passenger pigeon.  When the vultures died out, far more dead animals lay around rotting, transmitting pathogens to other scavengers like dogs and rats and entering the water supply. Dogs and rats are less efficient than vultures at fully eliminating flesh from carcasses, leading to a higher incidence of human contact with infected remains, and they're also more likely to transmit diseases like anthrax and rabies to people. Sudarshan and Frank estimate that this led to ~100,000(!) additional deaths each year from 2000-05 due to a +4.2%(!) increase in all-cause mortality among the 430 million people living in districts that once had a lot of vultures, which is staggering; this is e.g. more than the death toll in 2001 from HIV/AIDS (92,000), malaria

Ajeya Cotra writes: Like Ajeya, I haven't thought about this a ton. But I do feel quite confident in recommending that generalist EAs — especially the "get shit done" kind —  at least strongly consider working on biosecurity if they're looking for their next thing.