Harley-ml/lesswrong huggingface dataset:
# "If and Only If" Should Be Spelled "Ifeff"

*If and only if* is an important logical concept, useful in many contexts, both mathematical and nonmathematical. Unfortunately, "if and only if" is also an unwieldy five-syllable phrase. Mathematicians have solved this problem by shortening it to "[iff](https://en.wikipedia.org/wiki/If_and_only_if)". Unfortunately, this shortening has not caught on in non-mathematical contexts. This makes some communication and thinking unwieldy and ambiguous.

I think the reason "iff" hasn't caught on more broadly is because it's easily misread as "if", and doesn't have an intuitive pronunciation. I think both of these problems would be solved by changing the spelling to "ifeff" (prononunced /[ɪfɛff](http://ipa-reader.xyz/?text=%C9%AAf.%C9%9Bff&voice=Joanna)/). The etymology is that you take "iff", and pronounce the second "f" separately. This would slightly improve the thinking and communication of most English speakers.

I think a small group of people using "ifeff" in their writing would likely start a process where "ifeff" eventually takes over, via the usual process by which vocabulary spreads, and that "ifeff" would be used by groups that don't currently have a short-enough word for this concept. I also think the correspondence between "iff" and "ifeff" is intuitive enough that this will not cause very much confusion.
# (2009) Shane Legg - Funding safe AGI

Above is a link to an interesting blog post by Shane Legg. It was written before he started DeepMind, and he earns a hell of a lot of points for accomplishing a lot of the insanely ambitious goals set out in the post.

  
This part is particularly interesting:

> The impression I get from the outside is that SIAI \[now MIRI\] views AGI design and construction as so inherently dangerous that only a centrally coordinated design effort towards a provably correct system has any hope of producing something that is safe.  My view is that betting on one horse, and a highly constrained horse at that, spells almost certain failure.  A better approach would be to act as a parent organisation, a kind of AGI VC company, that backs a number of promising teams.  Teams that fail to make progress get dropped and new teams with new ideas are picked up.  General ideas of AGI safety are also developed in the background until such a time when one of the teams starts to make serious progress.  At this time the focus would be to make the emerging AGI design as safe as possible.
# The Mountaineer's Fallacy

I'm sure this has a name, but I can't remember it.  So I have given it a new name.  The Mountaineer's Fallacy.

The Mountaineer's Fallacy is the suggestion that climbing Mount Everest is a good start on a trip to the moon.

In one sense, you are making progress on a key metric: distance from the moon.  But in another, more accurate sense, you are wasting a lot of time and effort on something that has no chance of helping you get to the moon.
# Pi Sound Box

In an effort to reduce clutter, simplify setup, and avoid damaging my gear, I've packaged up my [whistle synth](https://www.jefftk.com/whistle-synth) and [rhythm stage setup](https://www.jefftk.com/p/rhythm-stage-setup-v3) into a box:

[![](https://www.jefftk.com/sound-pi-box-connected.jpg)](https://www.jefftk.com/sound-pi-box-connected-big.jpg)

[![](https://www.jefftk.com/sound-pi-box-front.jpg)](https://www.jefftk.com/sound-pi-box-front-big.jpg)

[![](https://www.jefftk.com/sound-pi-box-back.jpg)](https://www.jefftk.com/sound-pi-box-back-big.jpg)

This consolidates:

*   [Raspberry Pi](https://www.jefftk.com/p/whistle-synth-pi)
*   Power supply
*   USB hub
*   Sound card x2
*   DI box
*   Internal cables and adapters

[![](https://www.jefftk.com/sound-pi-box-diagram.jpg)](https://www.jefftk.com/sound-pi-box-diagram-big.jpg)

The box is aluminum, [10x8x4](https://smile.amazon.com/gp/product/B08G4ZKVL1). I like working with aluminum: it's very strong, but it's soft enough to drill without too much trouble. I removed the front and back plates and clamped them between blocks of wood for drilling.

The DI is a [Radial PRO D2](https://www.radialeng.com/product/prod2). I removed the shell and reused the original screws to attach it to my case. I also carefully aligned it so I could reuse the existing XLR ports; 1/4" jacks are pretty easy but XLR is more hassle.

I should have included an ethernet port so I can reprogram it without opening it up. I may come back and add one.

It's very much a prototype: a production version of something like this would probably only be about 4" on a side. Combining existing parts does not minimize size or weight.

(In setting this up I moved my rhythm stage setup ([github](https://github.com/jeffkaufman/jammer)), which I essentially hadn't touched in a year, from a Mac to the Raspberry Pi. This meant porting it to Linux, which meant learning how to do MIDI on Linux. It also meant dropping a few sounds which aren't open source [only sort of support Linux](https://support.audiomodeling.com/guides/How_to_run_a_Audio_Modeling_SWAM_VSTi_on_Linux_v1.1.pdf), primarily the [sax](https://www.jefftk.com/p/trying-a-breath-controller) and [trombone](https://www.jefftk.com/p/synth-brass). Since I'm no longer playing the [Axis 49](https://www.jefftk.com/p/rearranging-axis-49-keys) because of [wrist issues](https://www.jefftk.com/p/wrist-issues), though, this isn't actually giving up very much.)
# Is there a reasonable reading according to which Baric, Shi et al 2015 isn't gain-of-function research?

From the [A SARS-like cluster of circulating bat coronaviruses shows potential for human emergence](https://doi.org/10.1038/nm.3985) by Baric, Shi et al:

> Wild-type SARS-CoV (Urbani), mouse-adapted SARS-CoV (MA15) and chimeric SARS-like CoVs were cultured on Vero E6 cells (obtained from United States Army Medical Research Institute of Infectious Diseases), grown in Dulbecco's modified Eagle's medium (DMEM) (Gibco, CA) and 5% fetal clone serum (FCS) (Hyclone, South Logan, UT) along with antibiotic/antimycotic (Gibco, Carlsbad, CA). DBT cells (Baric laboratory, source unknown) expressing *ACE2* orthologs have been previously described for both human and civet; bat *Ace2* sequence was based on that from *Rhinolophus leschenaulti*, and DBT cells expressing bat *Ace2* were established as described previously[^8^](https://www.nature.com/articles/nm.3985#ref-CR8). Pseudotyping experiments were similar to those using an HIV-based pseudovirus, prepared as previously described[^10^](https://www.nature.com/articles/nm.3985#ref-CR10), and examined on HeLa cells (Wuhan Institute of Virology) that expressed *ACE2* orthologs. 

To me building chimeric viruses and then infact human cells (HeLa cells are human cells) looks like dangerous gain-of-function research. Fauci seems to argue that someone the NIH is able to define this work as not being gain-of-function research. To me this redefinition seems to be the bureaucratic way they circumvent the gain-of-function moratorium. Before the moratorium was imposed Fauci was arguing against it and the moratorium wasn't imposed by anyone in the NIH or the HHS but the Office of Science and Technology Policy. To me that looks like a way to evade safety regulation by the NIH by dedefining terms because the NIH didn't like the moratorium.

This question is about more then just assigning guilt for things that happened in 2015. If we want to prevent further risk, getting the NIH to accept that growing chimeric viruses that infect human cells is what the gain-of-function regulation is supposed to prevent seems to me to be very important. 

It's likely also a good case study for evading safety regulation and we should think about it in other context as well. If we end up with AI safety regulation, how do we prevent the people causing problems from just redefining the terms so that it doesn't apply to them?

If anyone has a defense of not classifying this work as gain-of-function research I'm also happy to hear that.
# Why is Kleros valued so low?

Kleros provides a system that allows smart contract in natural language to be written by letting randomly drafted juries evaluate the contract. It seems to me that this principle is incredibly powerful for all sorts of real world applications whether it's arbitrating the outcome of a prediction market or making sure that the events listed in the prediction market follow rules spelled out in natural language. 

At the moment it seems like Ethereums transaction costs are still limiting the utility of Kleros but either further progress in Ethereum or a Ethereum Virtual Machine on another chain is likely soon able to allow Kleros to provide the services more cheaply. 

Kleros Market cap is currently at $58,597,050 (with $73,236,896 fully diluted) which is relatively low compared to other crypto-assets especially given that it has potentially so much real world use-cases compared to a lot of other blockchain projects without real world usecases. Either there's some argument against Kleros that I'm not seeing or it should be valued 100-1000X of what it's current value happens to be.
# The shoot-the-moon strategy

Sometimes you can solve a problem by intentionally making it "worse" to such an extreme degree that the problem goes away. Real-world examples:

* I accidentally spilled cooking oil on my shoe, forming an unsightly stain. When soap and scrubbing failed to remove it, I instead smeared oil all over both shoes, turning them a uniform dark color and thus "eliminating" the stain.  
* Email encryption can conceal the content of messages, but not the metadata (i.e. the fact that Alice sent Bob an email). To solve this, someone came up with [a protocol](https://en.wikipedia.org/wiki/Bitmessage) where every message is always sent to *everyone*, though only the intended recipient can decrypt it. This is hugely inefficient but it does solve the problem of metadata leakage.

Hypothetical examples:

* If I want to avoid spoilers for a sports game that I wasn't able to watch live, I can either assiduously avoid browsing news websites, or I can use a browser extension that injects fake headlines about the outcome so I don't know what really happened.  
* If a politician knows that an embarassing video of them is about to leak, they can blunt its effect by releasing a large number of deepfake videos of themself and other politicians.

The common theme here is that you're seemingly trying to get rid of X, but what you really want is to get rid of the distinction between X and not-X. If a problem looks like this, consider whether [shooting the moon](https://en.wikipedia.org/wiki/Black_Lady#Shooting_the_moon) is a viable strategy.
# ($1000 bounty) How effective are marginal vaccine doses against the covid delta variant? 

UPDATE: the bounty has now been awarded as follows: 

*   $425 to Connor_Flexman
*   $300 to Josh Jacobson
*   $150 to JenniferRM/johnswentworth
*   $75 to ChristianKl
*   $50 to SoerenMind

===

Since I got vaccinated I’ve started working in-person, going to restaurants, travelling and whatever. But the delta variant might change this risk calculation. Some of the same buzz that got covid right early on, the first time around, is now buzzing about delta potentially being very bad.  

So I’m exploring ways of responding to that. This time around I’d rather [stand up and fight](https://www.lesswrong.com/posts/niQ3heWwF6SydhS7R/making-vaccine) than lock myself in a house for a year. And so this question explores one possible approach. 

There’s evidence that two vaccine doses are more effective than one (though there might be much higher diminishing returns than is commonly acknowledged). I’ve also heard that past infection confers marginal immunity even in the presence of vaccination. Further, as far as I understand, the 2-dose schedule for many vaccines is more “a common thing that we happened to test in the big trials” rather than “the dose level at which marginal benefit = marginal risk”. (And giving your population more than two doses is probably much harder logistically.)

Hence: getting *more* than the standard 1-2 vaccine doses might be a way to protect against delta. 

I live in California, and we currently seem to have a large vaccine surplus. I heard a vague rumour about a friend basically just walking into a pharmacy and getting a 3rd shot. There’s also RADVAC, which you can make yourself. 

So, if there is supply... how worthwhile is it to get more vaccine doses? Should you get a 3rd, 4th, … or even more? How does getting a further dose of the same vaccine compare to getting the first dose of a different vaccine?

**I’m posting a bounty of $1000 for answers that change my mind on this question (maybe increasing to many times that if this proves valuable). **

The ideal thing I want would be a graph with the x-axis showing # doses, and the y-axis reduction-vs-control of the following four parameters: 

*   Symptomatic infection
*   Hospitalisation
*   Death
*   Long covid

(Answers are of course impacted by the combinatorial search space of dose spacing / dose number / dose size / vaccine type / various demographics, but I won’t make any special restrictions here for now)

I will pay at least $1000 for answers that help me get clarity on this, split at my full discretion in proportion to how useful I find the answers. I’ll pay out the bounty on a rolling basis as answers come in; there is no deadline. In case this proves fruitful and there seems to be useful marginal work, it’s possible I will increase the bounty a lot (i.e. up to many thousands of dollars), or reach out to work with some answerers as contractors.
# Fire Law Incentives

Pacific Gas & Electric is planning to spend [$15-30b](https://www.npr.org/2021/07/21/1019058925/utility-bury-power-lines-wildfires-california) to bury power lines. I see why they're doing it: PG&E equipment sparked some of the worst fires in California history, including the 2018 [Camp Fire](https://en.wikipedia.org/wiki/Camp_Fire_(2018)) which destroyed [Paradise](https://en.wikipedia.org/wiki/Paradise,_California), but I'm not convinced that this is good for California overall.

Historically, the area used to burn periodically. We haven't allowed this for about a century, and flammable materials have been building up. It's all very likely to burn at some point, and burying power lines mostly just reduces the chance that it will be triggered by PG&E. [Prescribed burns](https://www.pewtrusts.org/en/research-and-analysis/blogs/stateline/2020/09/18/california-may-need-more-fire-to-fix-its-wildfire-problem), spreading out the combustion and moving it to safer times of year, would reduce fire risk far more for the money. Even though when PG&E pays for something the money comes from their customers, CA residents, this isn't a tradeoff PG&E is in a position to consider.

The problem is that CA law puts too much focus on sparks: if you start a fire, you are fully liable for its damage. This approach makes sense in most places, where a "we will never let it burn" policy is practical. In ecosystems adapted for periodic burning, however, where flammable materials build up over time, it means everyone is trying not to be the legally recognized cause of the inevitable fire. And it makes prescribed burns look expensive because when one goes out of control, which there is always a risk, that puts the fire control organization on the hook for the full costs.

Let's work on a system of laws and policies which lead to minimizing overall fire damage.
# The Walking Dead

Information asymmetry is a funny thing.

A while ago I created a [question](https://www.metaculus.com/questions/5463/mars-sample-mission-vs-starship/) asking "***Will NASA return a sample of material from the surface of Mars to Earth before SpaceX Starship lands on Mars?"**.  *Currently the odds according to the Metaculus prediction are that there's an 80% chance Starship will land on Mars before the sample-return mission is complete.  How different would NASA's Mars exploration program look if everyone working there believed this to be the case?  What if every American believed this to be the case?

Now Metaculus could be wrong of course, but its predictions are historically well-[calibrated](https://www.metaculus.com/questions/track-record/) and it has a track-record of beating the experts (for [example](https://www.metaculus.com/news/2020/06/02/LRT/) on covid-19).  That means anyone--and specifically anyone reading this post--has access to information that while not "secret" is hardly general knowledge.

Other than writing dire letters to NASA about how SLS is a waste of money because it is likely to succeed at about [2 launches](https://www.metaculus.com/questions/1503/how-many-nasa-space-launch-system-sls-launches-before-2030/) prior to 2030, what can you do with this information?

Consider Metaculus' [prediction](https://www.metaculus.com/questions/5121/when-will-the-first-artificial-general-intelligence-system-be-devised-tested-and-publicly-known-of-stronger-operationalization/) that the first AGI will be created around 2052.  Or the fact that there is a 30% [chance](https://www.metaculus.com/questions/5320/chinese-annexation-of-most-of-taiwan-by-2050/) of China annexing Taiwain in the same time frame? Or that there is a 50% [chance](https://www.metaculus.com/questions/5205/bitcoins-market-dominant-cryptocurrency/) another cryptocurrency will eclipse Bitcoin by 2026?

Here is the point: many future changes are *highly predictable,* but people for the most part go about their lives acting as though things will continue more or less the way they always have.  Don't be that way!  Imagine you were born with a superpower that gave you prophetic insight into the future. It wouldn't just be dumb to ignore that power, it would borderline reprehensible.  We have a moral obligation to warn the world around us about the changes that are coming.  

To warn them that they are the walking dead.

P.S.

It would be really cool to create a project that studies on which topics Metaculus disagrees most with the average expert (or the average member of the public) and somehow systematically make use of that information (e.g. by making strategic investments).
# Housing Without Street Parking: Implemented

In 2017, [I wrote](https://www.jefftk.com/p/housing-without-street-parking):

> What if, in places like Somerville where all parking is already by-permit-only, we added a new category of housing unit, one that didn't come with any rights to street parking?

It turns out this was included in the 2019 zoning overhaul (I missed this among all the other great changes):

> [11.2.7](https://library.municode.com/ma/somerville/codes/zoning_ordinances?nodeId=Chapter%2011%20-%20Parking%20and%20Mobility): **On-Street Parking in Transit Areas**
> 
> 1.  Upon the adoption of an official policy limiting on-`street` residential parking permits in `transit area`s, the review boards shall require the following as a condition(s) of any discretionary or administrative permit:
>     1.  that the `applicant` complete and file formal acknowledgment that all `dwelling unit`(s) are ineligible to participate in the Somerville Residential Permit Parking program with the with the Middlesex South Registry of Deeds or Land `court` prior to the issuance of a building permit;
>     2.  that all `dwelling unit`s are advertised as ineligible to participate in the Somerville Residential Permit Parking program; and
>     3.  that all buyers grantees, lessees, renters, or tenants are informed that all `dwelling unit`(s) is ineligible to participate in the Somerville Residential Permit Parking program.

By `transit area` they mean everything within half a mile from a subway stop, which with the Green Line makes [most of the city](https://library.municode.com/ma/somerville/codes/zoning_ordinances?nodeId=Zoning%20Maps):

[![](https://www.jefftk.com/somerville-transit-areas.png)](https://www.jefftk.com/somerville-transit-areas-big.png)

I'm very excited to see this! While housing without parking is not what everyone wants or needs, this change (a) makes it an option for people who do want it and (b) should help reduce opposition to construction.
# What are some triggers that prompt you to do a Fermi estimate, or to pull up a spreadsheet and make a simple/rough quantitative model?

I'm currently viscerally feeling the power of rough quantitative modeling, after trying it on a personal problem to get an order of magnitude estimate and finding that having a concrete estimate was surprisingly helpful. I'd like to make drawing up drop-dead simple quantitative models more of a habit, a tool that I reach for regularly. 

But...despite feeling how useful this can be, I don't yet have a good handle on in which moments, exactly, I should be reaching for that tool. I'm hoping that asking others will give me ideas for what TAPs to experiment with.

What triggers, either in your environment or your thought process, incline you to start jotting down numbers on paper on in a spreadsheet?

Or as an alternative prompt: When was the last time you made a new spreadsheet, and what was the proximal cause?
# Academic Rationality Research

There are now at least two academic research groups on rationality, in the sense we use the word in here, in Germany that seem to be little known in the US rationality community. The point of this post is telling you they exist if you didn't already know.

There's the [Rationality Enhancement Group](https://re.is.mpg.de/) lead by Falk Lieder in the Max-Plank Insititute in Tübingen and there's a group on [Adaptive Rationality](https://www.mpib-berlin.mpg.de/research/research-centers/adaptive-rationality) in the Max-Plank Insititute in Berlin.

When Falk Lieder was in at our European community weekend he repeatidly said that he's interested in collaborating with the wider rationality community. There's a list of [publications](https://re.is.tuebingen.mpg.de/publications) of his group and also a [Youtube](https://www.youtube.com/channel/UCKlqE2KeTfBy1irUcgHY09A/videos) channel that presents a few ideas. 

The adaptive rationality group has decided to speak of rationality techniques we would likely call applied rationality techniques as "boosting decision-making" in contrast to the academic literature on nudging. I think it's worth exploring whether we should also apply their term for the cluster of techniques like Double Crux.
# Is there a theoretical upper limit on the R0 of Covid variants?

Looking at the Wikipedia article on [basic reproduction number](https://en.wikipedia.org/wiki/Basic_reproduction_number), it looks like the most contagious virus (as of right now) is measles with an ***R*****~0~** (high estimate) of 18. I'm wondering if there is some asymptotic limit to how contagious viruses can get, and maybe measles is close there? If there is or isn't, do we have any ideas as to what biological mechanisms are related to this? 

I'm asking because it seems as the new variants emerge, it would be wise to aware of the worst case scenario. Just making a rough plot of the Covid rows in the basic reproduction article, and a rough stab on when they emerged, the wild-type, Alpha, Delta trend looks like this. 

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/e7145329316c3f7e09a132e909942bae99954ed3974cb77f.png)

Wild-type, Alpha and Delta ***R*****~0~**s (upper limits) and approximate dates when they emerged

From [Tomas Pueyo's excellent thread](https://twitter.com/tomaspueyo/status/1343868475492732928), it looks like as Covid gets more transmissible it's likely to get more deadly.

In 20 months Covid has went from an ***R*****~0~** (again, high estimate) of 3.4 to 8. I'm not an epidemiologist, but that seems like a really big jump in context. To be fair, again, I'm using the high estimates, but the general trend is concerning and I would sleep better knowing if there was some biological reason it would plateau.  

A scary, but I'm not sure how likely, scenario would be if another 20 months out (March 2023 or so), assuming there's large enough sections of the world where Covid is still spreading (either because vaccines haven't gotten there, or new vaccines are required for breakthroughs, or vaccines/infection immunity declines too quickly, etc), is there any reason to think it wouldn't jump another ~4.6 to ~12 or higher? Could it go above 18? 

 I'm just surprised I'm not seeing more discussion about this. Maybe I've missed it?
# Wanted: Foom-scared alignment research partner

Hi, my name is Mack Gallagher, I'm 20 years old, I have ZERO familiarity with computer architecture or \[math or computer science technical jargon\] \[although I'm OK at reasoning\], I have never attended a prestigious university, and I currently live in a 15,000-person meatpacking town, where I pack meat. I am terrified of impending foom as the most likely cause of my early death, I think my brain needs regular active reinforcement from \[the presence of\] people who share my beliefs-and-affect-toward-them to fuel sustained positive action on my part, and I am tired of sitting around waiting to die.

Are you, like me, 

*   Consistently apprehensive of impending foom
*   Allergic to high-status AI risk discussion
*   Currently doing something completely unrelated to AI for a day job
*   Tired of sitting around waiting for death

and preferably:

*   15-25 years old
*   Low-status \[have never attended a prestigious university\]

***???***

My email is magallagher00@gmail.com. Please email me or message me on LessWrong. Maybe we can be less useless together.
# Black ravens and red herrings

The [raven paradox](https://en.wikipedia.org/wiki/Raven_paradox) is a dilemma in inductive logic posed by Carl Gustav Hempel. It starts by noting that the statement "All ravens are black" can be expressed in the form of an implication: "If something is a raven, then it is black." This statement is logically equivalent to its contrapositive: "If something is not black, then it is not a raven."

We then consider that observing a black raven would typically be considered evidence for the statement "All ravens are black." The paradox comes from asking whether the same holds for the contrapositive; to put it another way, if we observe a non-black non-raven, such as a green apple, does that constitute evidence that all ravens are black?

The standard Bayesian solution, [given by I. J. Good](https://sci-hub.se/10.1093/bjps/XI.42.145-b), goes as follows. Suppose there are N objects in the universe, of which *r* of them are ravens, and *b* of them are black, and we have a probability of 1/N of seeing any given object. Let H_i be the hypothesis that there are *i* non-black ravens, and let us assume we have some sensible prior over our hypotheses. Then upon observing a non-black non-raven, our probability of H_0 increases, albeit only very slightly when N is large.

I. J. Good's solution reveals a distinct way of thinking about evidence among Bayesians. Most logicians view logical fallacies as examples of poor reasoning, but [the Bayesian interpretation](https://www.lesswrong.com/posts/YgNLfytckSyKTnDXN/fallacies-as-weak-bayesian-evidence) is slightly different. Many fallacies, when stated in their appropriate inductive form, are actually valid in a Bayesian sense, though the evidence they provide is usually weak.

Which is to say that if you criticize a Bayesian for using a "red herring" they may not see the issue. Observing a red herring is indeed Bayesian evidence for the statement "All ravens are black."
# How much do variations in diet quality determine individual productivity?

A few days ago Jim Babcock [stated](https://www.lesswrong.com/posts/igEogGD9TAgAeAM7u/jimrandomh-s-shortform?commentId=rkMMdRdAqrKyzdv6a)

> I care about nutrition because I believe it has a very large, very underappreciated impact on individual productivity. Low quality diets make people tired and depressed, so they don't get anything done.

There's obviously a sense in which that is trivially true. If you start consuming no more than zero calories per day, you will get very tired, maybe depressed as well, and you will eventually not be able to get anything done. And getting adequate iodine and other nutrients is very important for children to properly develop their cognition. But Jim Babcock is probably making a stronger claim. I think what he is claiming is something like "going from the 10th percentile in diet quality among Americans to the 90th percentile would have very large, very underappreciated impact on an adult's individual productivity (taking into account that diet quality is almost certainly at least partially dependent on individual factors)." 

I'd like to know what evidence we have for that claim. The strongest piece of evidence I can find is [Rae et al., 2003](https://www.gwern.net/docs/www/www.ncbi.nlm.nih.gov/8acbfd6032dd083ecf72f484632de89f5aab60d4.pdf), which showed that creatine supplementation increased the average IQ of their sample of vegetarians by 12 points, but that [hasn't been replicated](https://www.gwern.net/Creatine)\[1\], and it seems [extremely hard to substantially improve the cognition of adults](https://www.gwern.net/Drug-heuristics). And, when it comes to depression, people have been trying really hard to show that omega-3 supplementation has substantial effects on it, but [it's dubious that it does](https://astralcodexten.substack.com/p/peer-review-request-depression). L-methylfolate is a nutrient that is apparently effective enough that someone convinced the FDA to approve it to treat depression (as an add-on to treatment to another antidepressant), but only in quantities that far exceed those that anyone gets from their diet. 

So I have a fairly low credence that his claim (as I formulated it) is true. But I was wondering if there were any major pieces of evidence I have completely missed.

Update from the future (1/16/2023): [iron deficiencies are really bad](https://www.lesswrong.com/posts/6frs5xTkeLc9vZSRN/iron-deficiencies-are-very-bad-and-you-should-treat-them), worse than I thought when I wrote this.

\[1\] Apparently [some rationalists planned to try to replicate this](https://www.facebook.com/paulfchristiano/posts/10216845104297715), but there seemingly hasn't been an update to that in three years.
# How much compute was used to train DeepMind's generally capable agents?

I'm talking about [these agents](https://www.lesswrong.com/out?url=https%3A%2F%2Fdeepmind.com%2Fblog%2Farticle%2Fgenerally-capable-agents-emerge-from-open-ended-play) ([LW thread here](https://www.lesswrong.com/posts/mTGrrX8SZJ2tQDuqz/deepmind-generally-capable-agents-emerge-from-open-ended))

I'd love an answer either in operations (MIPS, FLOPS, whatever) or in dollars.

Follow-up question: How many parameters did their agents have?

I just read the paper (incl. appendix) but didn't see them list the answer anywhere. I suspect I could figure it out from information in the paper, e.g. by adding up how many neurons are in their LSTMs, their various other bits, etc. and then multiplying by how long they said they trained for, but I lack the ML knowledge to do this correctly.

Some tidbits from the paper:

> For multi-agent analysis we took the final generation of the agent(generation5)andcreatedequallyspacedcheckpoints (copies of the neural network parameters) every 10 billion steps, creating a collection of 13 checkpoints.

This suggests 120 billion steps of training for the final agents. But elsewhere in the post they state each agent in the final generation experienced 200 billion training steps, so.... huh?

Anyhow. Another tidbit:

> In addition to the agent exhibiting zero-shot capabilities across a wide eval-uation space, we show that finetuning on a new task for just 100 million steps (around 30 minutes of compute in our setup) can lead to drastic increases in performance relative to zero-shot, and relative to training from scratch which often fails completely.

So, if 100 million steps takes 30min in their setup, and they did 200 billion steps for the final generation, that means the final generation took 30 x 2,000 = 41 days. Makes sense. So the whole project probably took something like 100 - 200 days, depending on whether generations 1 - 4 were quicker.

How much does that cost though??? In dollars or FLOPs? I have no idea.

EDIT: It says each agent was trained on 8 TPUv3's. But how many agents were there? I can't find anything about the population size. Maybe I'm not looking hard enough.
# How to bayesian update on multiple covid tests?

I'm curious how I should think about the risk of hanging out with a friend (who is 2x pfizer vaccinated).  It seems like a good opportunity for bayesian thinking in the real world, but I'm really unclear how to think about it.  
  
Info: he tested positive on 4 UK lateral flow tests (LFTs), all from the same box (on 2 different days). After this, his roommates took two tests from the same box & both were negative.  
He has subsequently taken 3 PCR tests + a LFT each day, which have been negative.  
  
However, false positives seem to be very rare even for LFTs. They're ~1/1000 (number range from .9968 in original studies to .9997 more recently)  
[https://www.gov.uk/government/news/new-analysis-of-lateral-flow-tests-shows-specificity-of-at-least-999](https://l.facebook.com/l.php?u=https%3A%2F%2Fwww.gov.uk%2Fgovernment%2Fnews%2Fnew-analysis-of-lateral-flow-tests-shows-specificity-of-at-least-999%3Ffbclid%3DIwAR1zNfTpTF97FBkqnIRcy8XniKa6e7FU2gpljtqDiYb8nyiiP4AuqIf3Ta8&h=AT3yZB9OXdoTLDG7cJjMiqCDGUj1COOa0LCou_O-xA8j7mJGeAyWM6mr7R8z_x17qG1FYBiDHTuSDNObiXG-PLdplKqoglLYcfKg6KITfVUqcgKPhEMQ2Q5JavxFMmKm-qEOMvdVFtA)   
[https://www.bmj.com/content/372/bmj.n706](https://www.bmj.com/content/372/bmj.n706)  
  
But false negatives seem common for everything, including PCRs. It seems there's a 20-67% false negatives (20% being best it ever gets, on day 8 of infection)  
[https://www.acpjournals.org/doi/10.7326/m20-1495](https://www.acpjournals.org/doi/10.7326/m20-1495)  
[https://pubmed.ncbi.nlm.nih.gov/33301459/](https://pubmed.ncbi.nlm.nih.gov/33301459/)  
  
Given this, what are the chances he had covid (from maybe 10-20x lower-than-average-risk prior, but in oxford/England)?
# Did they or didn't they learn tool use?

[DeepMind claims that their recent agents learned tool use](https://www.lesswrong.com/posts/mTGrrX8SZJ2tQDuqz/deepmind-generally-capable-agents-emerge-from-open-ended); in particular, they learned to build ramps to access inaccessible areas *even though none of their training environments contained any inaccessible areas*!

This is the result that impresses me most. However, I'm uncertain whether it's really true, or just cherry-picked.

Their [results showreel](https://www.youtube.com/watch?v=lTmL7jwFfdw&t=762s) depicts multiple instances of the AIs accessing inaccessible areas via ramps and other clever methods. However, in the actual paper page 51, they list all the hand-authored tasks they used to test the agents on, and mention that for some of them the agents did *not* get >0 reward. One of the tasks that the agents got 0 reward on is:

> Tool Use Climb 1: The agent must use the objects to reach a higher floor with the target object.

So... what gives? They have video of the agents using objects to reach a higher floor containing the target object, multiple separate times. But then in the chart it says failed to achieve reward >0.

EDIT: Maybe the paper just has a typo? The blog post contains this image, which appears to show non-zero reward for the "tool use" task, zero-shot:

![](https://39669.cdn.cke-cs.com/rQvD3VnunXZu34m86e5f/images/0fc11bb89d00a2735682405a9a8d3951b84e4772fcadf030.PNG)
# Brief thoughts on inefficient writing systems

A phonemic language is one where how you write is very similar to how things sound. Essentially, if you know how to say something and you know the alphabet, then you can write/read the same thing. Serbian is an example of a phonemic language. A non-phonemic language is one where words are not written how they sound. English is a non-phonemic language. Non phonemic languages are harder to acquire literacy in. Children learning to read and write in the UK have to learn a host of complex rules, exceptions and individual word spellings. Finally a logogramatic language is one where the alphabet doesn't represent sounds. Instead symbols usually represent words or ideas. Chinese is such a language. If you want to learn how to read/write it to any reasonable level, you'll need to know at least 3000 characters.

The continued existence of non-phonemic writing systems is a suboptimal equilibrium. Such writing systems make learning to be literate in a language far harder than it needs to be. They also probably have very serious costs. They affect hundreds of millions of people and, given that even in first world countries between 10% and 25% of adults are functionally illiterate (remember that your bubble is strong), their costs in terms of lost productivity and individual flourishing are likely large. Still I've never heard anyone talk about language reform. Why is that?

One theory is elite blindness. Almost everyone in the elite is fully literate. You don't get to be a  journalist/professor/union leader/politician/NGO worker if you're not literate or have a low IQ (which strongly correlates with literacy). Because our personal bubbles tend to be incredibly strong, most elites are hence surrounded by people similar to them or at most a standard deviation or two away in terms of IQ. Hence most people with power will not only never struggle with literacy themselves but they will also never meaningfully interact to the 10 - 20% of society which does. Hence the problem is essentially invisible to everyone who matters.

Another theory is sunk costs. Even if we did recognize the problem with bad writing systems, there's a massive sunk cost in terms of how many people use the current language and how hard it is to shift that usage to a different form. It would take a national campaign, a large amount of resources and a huge political effort. The problem seems intractable, hence no one bothers to bring it up.

A third theory is that it's not controversial/sexy. There's no bad guy to point at. There's no ideological struggle or way to tie language systems into larger political narratives. It's a fairly dry issue that no individual or political faction can be blamed for. 


(N.B: While I'm fairly convinced that having a non-phonemic language makes learning to read and write much, much harder than it needs to be that's based on personal experience and conversations, not an any kind of systemic research. Maybe I'm just wrong. Epistemic Status: Reasonably high confidence)

Also posted to my blog at https://dissent.blog/2021/07/29/inefficient-writing-systems/
# What weird treatments should people who lost their taste from COVID try?

My friend had COVID in September 2020 and never got her taste back. What low-risk random things should she try doing to get it back? Recommendations need not be backed by anything stronger than “a friend of a friend heard…” or “I saw it on TikTok” - I’m looking for a broad library of things for her to consider trying. She is sane and is not the type to drink bleach or whatever, so don’t worry about recommending questionable things.
# Cherry Pit Storage

When eating cherries, what do you do with the pits? You don't want to swallow them, but spitting them out one by one is inconvenient. The answer: use your upper lip.

Eat the cherry as normal, separating the pit with your teeth and tongue as usual, but once the pit is free use your tongue to tuck it up under your upper lip. Once it's there, it will stay safely out of the way while you chew and swallow the rest of the cherry. You can repeat this several times; depending on your mouth geometry you can probably hold six to ten pits.

Asking around and looking online, it seems a lot of people don't know you can do this? I think this is because the pits are not especially visible, and the only clue someone is doing this is that they're needing to remove pits much less often.
# Torture vs Specks: Sadist version

Suppose that instead of the classic version of torture vs specks where the choice is between specks in the eyes of 3^^^3 people or one person tortured for 50 years, there are no specks but rather there are 3^^^3 people who just want the one guy to be tortured. (No particular reason, this just happens to be part of their utility function, which is not up for grabs) The preference of each is mild but somewhat stronger than the preference to not get a speck in one's eye. Is torture the right decision?

I am especially interested in hearing from people who answer differently in this situation than in the original situation.
# What made the UK COVID-19 case count drop?

According to [Google COVID-19 data](https://www.google.com/search?q=covid+19+uk&client=firefox-b-d&sxsrf=ALeKk01zPpaRGAaoyziHJbv85qe7x5utpA%3A1627908740876&ei=hOoHYYnrNI7XkwXBqr3wBw&oq=covid+19+uk&gs_lcp=Cgdnd3Mtd2l6EAMyBQgAEIAEMgUIABCABDIFCAAQgAQyBQgAEIAEMgUIABCABDIFCAAQgAQyBQgAEIAEMgUIABCABDIFCAAQgAQyBQgAEIAEOgcIABBHELADOgQIIxAnOgUIABCRAjoECAAQQzoECC4QQzoHCAAQyQMQQzoFCAAQkgM6CggAEIAEEIcCEBQ6CAgAEIAEEMkDSgQIQRgAUMYzWMJdYIZfaANwAngAgAF7iAGOCZIBAzcuNZgBAKABAcgBCMABAQ&sclient=gws-wiz&ved=0ahUKEwiJvefRsJLyAhWO66QKHUFVD34Q4dUDCA0&uact=5), something made COVID-19 cases drop after July 21, 2021. To me that event is unexpected given that the measures where in the process of being lifted and I wouldn't expect that to coincide with citizens engaging in more risk avoiding behavior. 

If there's a factor bringing cases down we don't know, understanding what the factor is could be very valuable. Does anybody have a good explanation for why the cases dropped?
# How Many Affordable Units?

With [last week's post on affordable housing](https://www.jefftk.com/p/come-build-affordable-housing) I was wondering: if we did build out all the Somerville lots zoned for four stories (MR4) to be seven stories of affordable housing, how much housing would that be? I count 254 lots zoned MR4 with a total area of 1.8M sqft. Built out at seven stories and an average of 80% coverage that's 10M sqft of housing. Figure 10% for stairs, elevators, and hallways, and it's really 9M for units. Let's say you build:

| bedrooms | portion of construction | unit size |
| --- | --- | --- |
| 2br | 25% | 850 sqft |
| 3br | 25% | 1000 sqft |
| 4br | 25% | 1100 sqft |
| 5br | 25% | 1200 sqft |

Then building all of this would give you:

| bedrooms | number of units |
| --- | --- |
| 2br | 2230 |
| 3br | 2230 |
| 4br | 2230 |
| 5br | 2230 |

These properties currently comprise just under 1k units, so this is 7.9k new units of affordable housing and 1k units converted to affordable housing. This would bring Somerville from ~35k units to ~43k.

*Comment via: [facebook](https://www.facebook.com/jefftk/posts/10100225099570492)*
# How should my timelines influence my career choice?

TL;DR: Recent progress in AI has tentatively shortened my expected timelines of human-level machine intelligence to something like 50% in the next 15 years. Conditional on that being a sensible timeline (feel free to disagree in the comments), how should that influence my career choice?  
  
Context:  
I am currently a master student in Artificial Intelligence at the University of Amsterdam with one more year to go (mainly doing my master's thesis). So far, my go-to plan was to apply for safety-relevant PhD positions, probably either in NN generalization or RL, and then try to become a research scientist in a safety-oriented org. Given the shorter timelines, I am now considering becoming an engineer instead since that seems to require much less upskilling time, compared to doing a PhD for 4-5 years. I think the answer to my question hinges upon 

*   my personal fit for engineering vs. research
*   the marginal value of an engineer vs. researcher in the years directly preceding HLMI
*   the marginal value of an engineer *now* (i.e. a year from now) vs. a researcher in 5-6 years.
    *   The reason I split these is that maybe the value changes significantly once HLMI is clearly on the horizon or already there in a number of relevant domains.

I feel like I enjoy research more than pure engineering, but it's not like I don't enjoy engineering at all. Engineering seems more competitive in terms of coding skills, which I might lack compared to the most skilled other applicants. However, that is something I could practice pretty straightforwardly.   
  
How have other people thought about this question, and how would you judge the questions about marginal value of the two roles?
# What's the status of third vaccine doses?

People seem to think that getting a third mRNA vaccine dose, or "booster shot", substantially increases immunity after 4ish months from your second dose.

*   Is it currently "illegal" to get one, or is it just the policy of all current pharmacies and vaccine distributors to refuse to give them?
*   Is there any shortage of vaccines in the US at this point? Would getting a booster shot counter-factually cause another person to get a dose later?
*   Is there chance that booster shots will become commonly available in the next month? Is it even in the Overton window of things that politicians are bothering to think about?
*   Lastly -- because I assume the answer is no -- is there any reason to think that getting a third shot of a different vaccine would be biologically dangerous?
# What psychology studies are most important to the rationalist worldview?

The importance of cognitive psychology, neuroscience, and evolutionary psychology to rationalist projects are no secret.  The sequences begin with an introduction to cognitive biases and heuristics for example.  I am an amateur researcher of theoretical and philosophical psychology currently preparing a series of blog posts intended to introduce the rationality community to some of the key insights from that field. As part of that project, I'm hoping to use a couple of studies as case studies to examine the processes by which the knowledge gained from them was produced and the philosophical and theoretical assumptions at play in the interpretation of their findings. In choosing which studies to use as case studies, I'm hoping to optimize for the following criteria.  
  
1\. Rationalist/Science approved methodologies were followed. The more confident the community would be in relying on the findings of the studies the better.

2\. Relevance to rationalist projects.

3\. The "less likely to fall to the replication crisis" the better  
  
4\. The more important to the rationalist worldview the better.  
  
I don't know if I'll do all three yet(no promises), but I'm interested in choosing one study or finding from each of these three categories, each optimized for the above criteria.   
  
1\. Cognitive Experimental Psychology

2\. Neuroscience

3\. Evolutionary Psychology.  
  
Meta-analyses are alright, but I'm going to need specific studies for this project.