trentmkelly/LessWrong-43k huggingface dataset:
Day Zero Antivirals for Future Pandemics
by Niko_McCarty — 2024-08-26T15:18:33.858Z
Link: https://www.asimov.press/p/antivirals

By Brian Wang

Ebola tore through Western Africa in 2014, killing an estimated 11,325 people in two years. After the outbreak ended, it took another three years for the first Ebola vaccine by Merck to be approved. When COVID-19 emerged in 2019, by contrast, mRNA vaccines developed by Pfizer and Moderna took just 326 days from the initial sequencing of the virus to gaining approval for emergency use.

Timelines for vaccine development are shrinking, but can it move even faster? The Coalition for Epidemic Preparedness Innovations (CEPI)—a nonprofit organization that funds vaccine research and development—thinks so. In 2022, they raised $2 billion from private investors, nonprofit organizations, and over a dozen national governments to advance their mission to deliver pandemic vaccines within 100 days.

Even this aggressive target of 100 days won’t always be fast enough to slow a pandemic, however. The Omicron variant of COVID-19 spread with alarming rapidity; after China ended its zero-COVID policy in 2022, estimates suggest Omicron infected upwards of 80 percent of its population—over a billion people—in about one month.

Fortunately, vaccines aren’t the only way to slow the spread of pathogens. We can also deploy broad-spectrum antiviral drugs, which treat infections caused by multiple viruses before vaccines are developed. These drugs would be ideal tools to bridge the wait for a vaccine against a quickly-spreading virus. And ideally, such broad-spectrum antivirals would be deployed at the earliest signs of an outbreak, thus enabling a pandemic response to begin on “day zero,” rather than day 100.

Broad-spectrum antivirals have been somewhat of a disappointment so far. Remdesivir, a decade-old broad-spectrum antiviral developed by Gilead and previously tested against Ebola, was quickly approved for emergency use against COVID-19 in May 2020, seven months earlier than the first mRNA vaccines. Lengthy manufacturing timelines slowed its deployment, though; it wasn’t until October—five months later—that drug manufacturers scaled up enough to meet national demand. Nor was remdesivir as effective as people hoped. One large-scale clinical trial found that it only reduces the relative risk of death by about ten percent in hospitalized patients.

We need to make more effective and rapidly deployable broad-spectrum antivirals. For guidance on how to do so, we can learn from the...
Molecular dynamics data will be essential for the next generation of ML protein models
by Abhishaike Mahajan — 2024-08-26T14:50:23.790Z
Link: https://www.owlposting.com/p/an-argument-for-integrating-molecular

Introduction

I’ve been pondering the thesis behind this post for a few months now, figuring out how to approach it. In my head, it feels plainly obvious, of course we should use molecular dynamics (MD) to help further train proteomics models. But it’s a good exercise to motivate the whole thing from a first-ish-principles place. Upon writing this, I realized a lot of my initial thoughts about the subject were misguided or misinterpreted. Hopefully this synthesis helps someone understand the role MD will play in the future of proteomics ML.

In this post, I’ll sketch out three reasons why I believe MD will be fundamental in the next generation of proteomics models, each one building off each other. We’ll then end with a brief thought on what will be necessary to produce this next generation of models. We’ll also quickly point out one recently released paper that I would bet is an early precursor of what’s to come.

Quick note: we won’t discuss things stuff like

neural-network potential

s in this essay, which are set up to change MD itself (and maybe discussed in a future essay). Instead, we’ll focus entirely on how even the current era of MD is sufficient to dramatically benefit proteomics models.

The arguments

Biology models don’t understand physics

Protein folding models, such as AlphaFold2 (and, recently, AlphaFold3) represent the clearest success of ML applied in the life sciences. In many ways, the single-chain protein structure prediction problem is largely solved, though a long tail of edge cases exists (and will likely continue to exist for a while).

But models like Alphafold2 (AF2) do not work by simulating the physics of a protein. No ML-based folding model seems to, not

OmegaFold

, not

ESM2

, none of them. When AF2 first came out, it was likely hypothesized that it had somehow learned a fuzzy notion of physics from end-state structures alone. This was quickly called into suspicion by a 2022 paper titled ‘

Current structure predictors are not learning the physics of protein folding

’, which found that ‘folding trajectories’ produced by Alphafold2 (the details of which could be found in

section 1.14 here

) do not recapitulate real folding dynamics at all. This was reaffirmed in a 2023 paper titled ‘

Using AlphaFold to predict the impact of single mutations on protein stability and function

’, which studied whether Alphafold2 predicted confidence correlated with exper...
My lukewarm take on GLP-1 agonists
by George3d6 — 2024-08-26T12:34:27.929Z
Link: https://cerebralab.com/My_lukewarm_take_on_GLP-1_agonists

Motivation for posting:

I read Scott's recent article: https://www.astralcodexten.com/p/why-does-ozempic-cure-all-diseases

And it seems to me that scott isn't considering two points:

GLP-1s might fix a lot of things because people are metabolically compromised (e.g. literally to the point of having mitochondria that are unable to properly use all respiratory complexes due to an odd selection effect in always-high glucose environments) - Or they might be magic, but as of yet there's no conclusive evidence and a lot of incentives to say "magic"
You can always come up with alternative mechanisms for why GLP-1s might work, but we should wait for more studies to be done in basically healthy people before we recommend basically healthy people take them
If you are a basically healthy person, especially one that is looks-obsessed or hypochondriac, the risks might outweigh the benefits of GLP-1s... and while nobody is saying the reverse outright, there's a lot of hinting at benefits with no mention of side effects.
Interview with Robert Kralisch on Simulators
by WillPetillo — 2024-08-26T05:49:15.543Z

The following is a transcript of a

video interview

(edited for grammar and readability) with Robert Kralisch on simulator theory and its implications for AI safety.

Introduction by Will Petillo: In February 2023, Microsoft launched Bing chat, an AI-powered chatbot based on the same large language model technology that is used by ChatGPT and its competitors. Most of Bing's answers were what you might expect of a helpful assistant, but some were...weird. In one conversation, it threatened its user after learning his name and recognizing him as a red-team tester. In another, it stubbornly refused to admit that it made a simple mistake, attempted to gaslight the user, and insisted that it had been a “good Bing”. And in another, it claimed to have hacked its developers' personal webcams and taken pleasure in spying on them during intimate moments.

Microsoft's initial response was to hide the issue by limiting conversation lengths. Since then, AI companies have found less clumsy ways to train their AIs not to say weird and unsettling things—like spontaneously claiming to be conscious and having emotions—but the underlying technology has not changed, so the question remains: what's going on with these chatbots? And should we be concerned?

Robert Kralisch: I became interested in AI safety when the Superintelligence book from Bostrom came out late 2014, which was also right around the time where I was trying to orient towards what I want to do after my time in school, what I want to study, and so on. I started looking into the topic and deciding, okay, I want to contribute to that.

I was good at computer science and also the philosophical aspect. I had many open questions. What is intelligence? Can these systems recursively self improve and scale? Do we have the right mental frameworks for that? I was quite interested in the expert disagreement about the topic as well that I saw at the time.

I studied at the university, first computer science, dropped out, and then later did cognitive science. It took a while for me to figure out that I want to pursue the whole thing more autodidactically and that the university courses are not close enough in their relevance to the AI safety problems that I was reading about on LessWrong and also thinking about myself. I basically really tr...
One person's worth of mental energy for AI doom aversion jobs. What should I do?
by Lorec — 2024-08-26T01:29:01.700Z

Hi! I'm Lorec, AKA Mack. I made this post 3 years ago:

Wanted: Foom-scared alignment research partner

I met some great people, but we never got much of anywhere.

Since then, technical alignment research in general also has not gotten much of anywhere [ counterexample; other strongish counterexamples I know of include the Visible Thoughts idea and Pliny's approach, Anthropic's approach doesn't seem to have panned out ] and AI doom aversion policy has become a thing.

I made a Discord a while ago for discussion of doom aversion methods. We were some of the first people [to my knowledge] talking positively about SB-1047. I consider it a failure: we were early and correct, but because we were not plugged into any network, nothing came of it.

I am indifferent to technical versus policy work except to the extent of [ the effectiveness factor over the risk factor of [technical work in general] ], versus [ the effectiveness factor over the risk factor of [policy work in general] ].

Factors I'm coming in considering important contributors to the technical versus policy weigh-in:

Pro Technical

- Can potentially have low safety risks if the researcher knows exactly what they are doing and does not use their employer's money to contribute to capabilities

- Can potentially have high safety upsides if the researcher knows exactly what they are doing and is a paranoid saint and can work without ever posting their exciting intermediate results on social media [difficulty level: impossible]

- Technical experience lends [any] policy credibility, while policy experience does not lend technical credibility

Pro Policy

- Fairly safe, for people who have a reasonable level of knowing what they are doing

- Policy jobs [from my faraway position; this might be wrong] seem likely to be more fungible [with each other] than technical jobs - resulting in less risk of being locked in to one employer whose mission I find myself disagreeing with

- I expect to have an easier time getting one of these kinds of jobs; while I consider myself decent enough at programming to be qualified for such technical alignment research as is hiring in principle, in practice I have no degree, job history, or portfolio, and am done wasting my time trying to acquire them, like, no, really, done. End of story.

Who should I talk to? What movements or orgs should I look into? Where are Things Happening the most? As stated in tit...
Secular interpretations of core perennialist claims
by zhukeepa — 2024-08-25T23:41:02.683Z

After the release of Ben Pace's extended interview with me about my views on religion, I felt inspired to publish more of my thinking about religion in a format that's more detailed, compact, and organized. This post is the second publication in my series of intended posts about religion.

Thanks to Ben Pace, Chris Lakin, Richard Ngo, Damon Pourtahmaseb-Sasi, Marcello Herreshoff, Renshin Lauren Lee, Mark Miller, Roger Thisdell, and Imam Ammar Amonette for their feedback on this post, and thanks to Kaj Sotala, Tomáš Gavenčiak, Paul Colognese, and David Spivak for reviewing earlier versions of this post. Thanks especially to Renshin Lauren Lee, Roger Thisdell, and Imam Ammar Amonette for their input on my claims about perennialism, and Mark Miller for vetting my claims about predictive processing.

In my previous post, I introduced the idea that there are broad convergences among the mystical traditions of the major world religions, corresponding to a shared underlying essence, called the perennial philosophy, that gave rise to each of these mystical traditions.

I think there’s nothing fundamentally mysterious, incomprehensible, or supernatural about the claims in the perennial philosophy. My intention in this post is to articulate my interpretations of some central claims of the perennial philosophy, and present them as legible hypotheses about possible ways the world could be.

It is not my intention in this post to justify why I believe these claims can be found in the mystical traditions of the major world religions, or why I believe the mystical traditions are centered around claims like these. I also don’t expect these hypotheses to seem plausible in and of themselves – these hypotheses only started seeming plausible to me as I went deeper into my own journey of inner work, and started noticing general patterns about my psychology consistent with these claims.

I will warn in advance that in many cases, the strongest versions of these claims might not be compatible with the standard scientific worldview, and may require nonstandard metaphysical assumptions to fully make sense of.[1] (No bearded interventionist sky fathers, though!) I intend to explore the metaphysical foundations of the perennialist worldview in a future post; for now, I will simply note where I think nonstandard metaphysical assumptions may be necessary.

The Goodness of Reali

...
Darwinian Traps and Existential Risks 
by KristianRonn — 2024-08-25T22:37:14.142Z

This part 1 in a 3-part sequence summarizes my book, The Darwinian Trap (see part 2 here and part 3 here). The book aims to popularize the concept of multipolar traps and establish them as a broader cause area. If you find this series intriguing contact me at kristian@kristianronn.com if you have any input or ideas.

Global coordination stands as arguably the most critical challenge facing humanity today, functioning both as a necessary component for solving existential risks and as a significant barrier to effective mitigation. From nuclear proliferation to artificial intelligence development and climate change, our inability to collaborate effectively on a global scale not only exacerbates these threats but also perpetuates the emergence of new systemic vulnerabilities if left unaddressed.

In this sequence, I will argue that the root of this coordination problem lies in the very mechanisms that shaped our species: natural selection. This evolutionary process, operating as a trial-and-error optimization algorithm, prioritizes immediate survival and reproduction over long-term, global outcomes. As a result, our innate tendencies often favor short-term gains and localized benefits, even when they conflict with the greater good of our species and planet.

The inherent limitations of natural selection in predicting future optimal states have left us ill-equipped to handle global-scale challenges. In a world of finite resources, competition rather than cooperation has often been the more adaptive trait, leading to the emergence of self-interested behaviors that arguably dominate modern societies. This evolutionary legacy manifests in the form of nationalistic tendencies, economic rivalries, dangerous arms races and a general reluctance to sacrifice immediate benefits for long-term collective gains.

This three-part series summarizes my book: The Darwinian Trap: The Hidden Evolutionary Forces That Explain Our World (and Threaten Our Future).

Part 1 (the part you are reading): This part explores how evolutionary selection pressures contribute to existential risks, particularly through global resource, power, and intelligence arms races.
Part 2: This part delves into the evolution of cooperation and discusses how survivorship bias might mislead us into thinking cooperation is easier to achieve than it actually is. It suggests that li

...
DIY LessWrong Jewelry
by Fluffnutt — 2024-08-25T21:33:56.173Z

[There are no affiliate links in this post and I haven't been paid by anyone; I just happened to have bought the charms from Shein. You can probably get similar things on Temu, Aliexpress or Amazon]

I made a cute LessWrong themed necklace/earring set for cheap, here's how.

For the necklace, buy a pair of these earrings from Shein:

US: https://us.shein.com/1pair-Fashionable-Rhinestone-Star-Decor-Drop-Earrings-For-Women-For-Daily-Decoration-p-15276285.html

CAN: https://ca.shein.com/1pair-Fashionable-Rhinestone-Star-Decor-Drop-Earrings-For-Women-For-Daily-Decoration-p-15276285.html.

Then remove the dangly charm and use a wire to attach it to a necklace chain.

(I bought a cheap necklace from Shein to use as the chain but it tarnished within days. Amazon seems to sell decent chains/necklaces for ~20$, but I haven't bought any so can't personally recommend them (I used an old chain from my grandmother instead). If you're buying a necklace make sure any pre-existing charms can be removed.

You can either get two pairs of the above earrings to make a set, or get these ones if you prefer studs:

US: https://us.shein.com/1pair-S999-Sterling-Silver-Cubic-Zirconia-Eight-pointed-Star-Design-Symmetric-Earrings-For-Women-p-23036383.html

CAN: https://ca.shein.com/1pair-S999-Sterling-Silver-Cubic-Zirconia-Eight-pointed-Star-Design-Symmetric-Earrings-For-Women-p-23036383.html

Here they all are together:

Note the stud is quite small. Here is what it looks like on my ear, in comparison with the hoop earrings:
Meta: On viewing the latest LW posts
by quiet_NaN — 2024-08-25T19:31:39.008Z

To view all the latest posts on LW without the use of bookmarks or cookies, here are the steps I take:

Go to lesswrong.com
Switch from Enriched to Latest
Click on Advanced Sorting/Filtering
Click on Sorted by Magic (New & Upvoted)
Click on New in the column Sorted by

This will then allow me to browse through all posts[1] in chronological order, including bad AI takes modded to -7 like "How to easily solve AI alignment using Maxwell's equations" or whatever.

Now, I get the idea that a new person visiting LW for the first time should probably not be subjected to a list of terrible AI posts right away, but I would also wager that most people ending up on the LW start page are causal readers like myself.

Personally, I have subscribed to the curated posts, so I will get the highly upvoted posts in my inbox -- once their discussion is long over. My main motivation to visit LW is thus to see if there are current posts where I can participate in the ongoing discussion.

For that, the so-called Latest sorting is virtually useless. Per the mouse-over text, it uses an "algorithm that combines karma with time discounting". Perhaps some exponential decay of the effective karma score with a half-life of a month or so? No, that fits for the months range posts, but there also seems to be a huge penalty for posts which are a week old as opposed to posts which are three days old. In any case, most of the posts shown there are from at least a week ago, by which time discussion is mostly over.

Now, if this preference for fresh posts is exclusive to me, I should probably bookmark https://www.lesswrong.com/allPosts?sortedBy=new&filter=all&karmaThreshold=-1000 and get on with my life. On the other hand, if more people here feel the same, we might try to lobby for a Fresh button next to the Latest button which just displays posts in chronological order (for all I care sans the downvoted ones, if 'new readers (or LLM scrappers?) should not be exposed to bad AI takes' is a concern).

^

Technically, posts by low karma users might still be filtered unless I spend an extra click, I think.
you should probably eat oatmeal sometimes
by bhauth — 2024-08-25T14:50:37.570Z
Link: https://bhauth.com/blog/food/oatmeal.html

Inspired by all the blog posts I've seen promoting unusual diets, nootropic drugs, unusual sleep cycles, and so on, I've decided to make my own post suggesting some radical lifestyle choice.

My suggestion here is, as the title says: you should probably eat oatmeal sometimes. Yes, I know, oats are <2% of global grain production, so this is a pretty crazy-sounding idea, but bear with me. Eating oatmeal sometimes will literally change your life.*

*slightly

oatmeal vs rice

White rice is one of the most popular foods in the world.

Compared to white rice:

oats have ~2x the protein and much more fiber

their amino acid composition is somewhat more balanced

their arsenic levels are generally lower

oatmeal is slightly more expensive, but still cheap

oatmeal is generally faster to cook

about whole-wheat flour

Whole-grain wheat flour goes rancid much faster than white flour.

Wikipedia, quoting a 2004 book, says:

The germ is rich in polyunsaturated fats (which have a tendency to oxidize and become rancid on storage) and so germ removal improves the storage qualities of flour.

(The "germ" is the part of the seed that actually grows into a new plant. As you'd expect, it's the part with the most protein and vitamins.)

Hmm. If that's the problem, why do (unground) wheat berries last for 10+ years, longer than white flour? Does the bran protect stuff from oxygen? I don't think so, it's not metal foil, it has some gas permeability.

Maybe there's a correction of Wikipedia from some reliable source, like Wikipedia. Here's a post from a food testing company that says:

The lipolytic enzyme lipase reacts with triglycerides to form free fatty acids in a degradation process known as hydrolytic rancidity; lipase enzymes cleave fatty acids from triglycerides.

...

Oats also contain a powerful lipoxygenase that adds oxygen to the double bonds of unsaturated fat to form peroxides, as discussed above. The other enzyme present, peroxidase, reduces peroxides producing mono-, di-, and tri-hydroxy acids, which are extremely bitter. These compounds cause the bitter flavor of rancid wheat germ.

...

In most biological systems, peroxidase requires much more heat to destroy than lipases, lipoxygenases or any of the other enzymes that may be present.

Ah yes, enzymes. When wheat berries are ground to flour, the enzymes start doing things and the flour goes rancid, but if you remove stuff to ma...