trentmkelly/LessWrong-43k huggingface dataset:
Russian x-risks newsletter March 2020 – coronavirus update
by avturchin — 2020-03-27T18:06:49.763Z

Russia recently attracted attention as it reported fewer CV cases than other countries. Probably the best explanation is under-reporting and under-testing. Other explanations are shorter life expectancy and higher home temperature.

Russia government is taking some measures against coronavirus, but they seem to be not radical or effective. Testing is not widespread, though some private companies are allowed to test now, as of March 26. Before it, only 3 consequent positive tests including the one in Novosibirsk Vector (the military bio lab where was an explosion in fall 2019 and which preserves a collection of deadly viruses) were needed to establish Сovid-19 officially. It created a backlog of testing. Also, mostly the people returned from abroad were tested, not locals, which created an illusion of no local transmission.

One may expect that Putin would act cruelly to stop the pandemic, maybe even put lions on the streets as in one meme, but he acted very mildly, not in Modi style.

From 28 of March national holiday is declared, which is not lockdown (lockdown requires to waive rents and the state may have to pay for it, which it doesn’t want). Many people are parting on warmer areas, and the spring is surprising early and warm. Cafe and parks will be closed from tomorrow. From my observations, only starting from today, I can see a significant number of people in masks on streets (like 10-20 per cent). People above 65 are not allowed to go out and some were fined, but many still out. Schools are online.

Several facts about CV in Russia:

As of 27 of March: Russia: 1036 cases, 703 in Moscow.
Age of recent CV deaths in Russia: 45m (abroad, in Cuba, diabetic), 70, 73, 79f (died from clot), 88, 56f (+cancer).
The reaction to the pandemic was delayed because they didn’t want to spoil important voting on new constitution April 22. Now it postponed.
The official number is growing, but not as a quick exponent like in NY. May grow more after testing will be expanded.
Male median life expectancy in Russia (not median age) is 67. vs 80 in Italy. May result in fewer deaths.
Russia typically has a warmer temperature in houses: 25 C is the norm. It may kill virus indoors. Italy doesn’t have heating in winter.

Russia decided to go in the oil war with Saudi and US shale which was an obvious mistake. Global demand failed 15 Mb because of CV, ...
When to assume neural networks can solve a problem
by George3d6 — 2020-03-27T17:52:45.208Z
Link: https://blog.cerebralab.com/When_to_assume_neural_networks_can_solve_a_problem

Note: the original article has been split into two since I think the two points were only vaguely related, I will leave it as is here, since I'd rather not re-post stuff and I think the audience on LW might see the "link" between the two separate ideas presented here.

A pragmatic guide

Let’s begin with a gentle introduction in to the field of AI risk - possibly unrelated to the broader topic, but it’s what motivated me to write about the matter; it’s also a worthwhile perspective to start the discussion from. I hope for this article to be part musing on what we should assume machine learning can do and why we’d make those assumptions, part reference guide for “when not to be amazed that a neural network can do something”.

The Various hues of AI risk

I’ve often had a bone to pick against “AI risk” or, as I’ve referred to it, “AI alarmism”. When evaluating AI risk, there are multiple views on the location of the threat and the perceived warning signs.

1. The Bostromian position

I would call one of these viewpoints the “Bostromian position”, which seems to be mainly promoted by MIRI, philosophers like Nick Bostrom and on forums such as AI Alignment.

It’s hard to summarize without apparently straw-man arguments, e.g. “AIX + Moore’s law means that all powerful superhuman intelligence is dangerous, inevitable and close.” That’s partly because I’ve never seen a consistent top-to-bottom reasoning for it. Its proponents always seem to start by assuming things which I wouldn’t hold as given about the ease of data collection, the cost of computing power, the usefulness of intelligence.

I’ve tried to argue against this position, the summary of my view can probably be found in “Artificial general intelligence is here, and it's useless”. Whilst - for the reasons mentioned there - I don’t see it as particularly stable, I think it’s not fundamentally flawed; I could see myself arguing pro or con.

2. The Standard Position

Advocated by people ranging from my friends, to politicians, to respectable academics, to CEOs of large tech companies. It is perhaps best summarized in Stuart Russell’s book Human Compatible: Artificial Intelligence and the Problem of Control...
Explanatory power of C elegans neural models
by sjonany — 2020-03-27T17:30:58.372Z

Background

@jkaufman wrote a nice post on the progress of C elegans modeling effort in 2011, with a followup post in 2014. Here we are, almost a decade later, and I still have the same question that I would have asked even in 2011 if I had dived into the project.

Question

Considering that we do not know the signs of the connectome weights, what do you think about the strength of explanations that try to explain biological phenomenon (E.g. locomotion) in terms of neural dynamics (e.g. from this model, we propose that there's push-pull circuitry because we see that our model shows these fluctuating membrane potentials)?

My preliminary take: Weak and highly uncertain.

Cook et al., 2019 said "modelling the functions of the nervous system at the abstracted level of the connectivity network cannot be seriously undertaken if a considerable number of nodes or edges (for example, edges that represent electrical couplings) are missing." I would think that misdirected edges might just be as harmful as missing edges.

Why doubt the preliminary take?

I have seen commentaries in papers like Kunert et al., 2014 and Kim et al., 2019 that analyze neuronal dynamics from the model (E.g. oscillatory dynamics were observed in membrane potentials of neuron set A if neuron set B are stimulated). I don't doubt the methodological contributions of the paper, but I wonder if it's worthwhile to produce a study that is purely an analysis of the dynamics of such a model, given the uncertainties in the connectome.
Overhead of MessageChannel
by jefftk — 2020-03-27T17:10:02.352Z

The

Channel
Messaging API gives you a way to pass information asynchronously
between different origins on the web, such as cross-origin iframes.
Traditionally you would use

window.postMessage(), but the
a

MessageChannel has the advantage of being clearer, only
requiring validating origins on setup, and

handling
delegation better. Reading

this
2016 post, however, I was worried that it might have enough
overhead that

postMessage made more sense in
performance-sensitive contexts. Benchmark time!

I made a test page which alternates
between loading trycontra.com/test/messageChannelResponse.html
and trycontra.com/test/postMessageResponse.html.
I'm using two different domains so that I can test cross-origin
performance. First it loads messageChannelResponse in an
iframe, waits for it to load, and then times how long it
takes to pass in a MessagePort and receive a response on
it. Then it does the same basic operation
postMessageResponse with plain postMessage.
This is a worst-case for MessageChannel, since I stand up
the while channel only to use it a single time.

I ran 1,000 iterations, interleaved, on Chrome (80.0), Firefox (74.0),
and Safari (13.1). All of these were on my 2017 MacBook Pro. Here
are all the runs, sorted from fastest to slowest [1]:

In Chrome, MessageChannel is a bit faster, while in
Firefox and especially Safari it's slower. Additionally, Firefox runs
it faster than Safari, which runs it faster than Chrome. Safari also
has more consistent performance than Chrome, with a flatter
distribution. Firefox is in between, with a flat distribution for
postMessage but a few slow calls in the tail for
MessageChannel. If you're writing something where ~7ms/call
in Safari is an issue then it might be worth sticking to
postMessage, otherwise MessageChannel seems
fine.

[1] I find this kind of "sideways CDF" a really useful visualization
tool, and possibly the chart I make most often.
March 25: Daily Coronavirus Updates
by habryka — 2020-03-27T04:32:18.530Z

Aggregators

Clusters C19 literature for easier filtering and digestion

Given a target article, identifies similar articles

Economics

Balancing the cost in lives of C19 and shutdown

Plea to consider both the cost in lives of doing nothing and of gutting the economy, and spend more money to get things fixed faster

Spread & Prevention

Disinfection and reuse of N95 masks (guidelines and data)

A report on disinfecting N95 disposable respirators. The second half of the document is a paper with fresh results: 70C air for 30 min (good), UV 254nm@8W for 30 min (good, but light must reach all surfaces), hot steam for 10 min (significant degradation after 5-10 cycles), bleach or alcohol (destroys filtration, do not use).

Work & Donate

Empathetic listening for frontline medics

Connects front line medics and carers with volunteer listeners

Full Database Link
Charity to help people get US stimulus payments?
by skybrian — 2020-03-27T03:16:38.130Z

It seems like once the big coronavirus bill passes, the stimulus payments might result in an interesting one-time opportunity for effective altruism. Apparently, anyone who didn't file a tax return last year would need to file a return to get the money. A charity that helps people file might be a highly leveraged opportunity for financial help? For example, if you can spend $60 to help someone get a $1200 check then that's pretty good leverage.

This seems similar to what mRelief does, but probably a better fit for tax preparers. Does anyone know anything?

(On the other hand, I suppose any tax preparer could do this for profit? Hmm.)
Coronavirus: the four levels of social distancing, and when and why we might transition between them
by VipulNaik — 2020-03-27T03:07:27.943Z

In this post, I describe four increasingly strict levels of social
distancing that have been considered in response to the coronavirus
situation. I then talk about how likely each is to succeed, how
sustainable it is, and the relative economic and social cost. I then
talk about the likely time periods that we'll transition between these
levels. The purpose here is to simply help think systematically about
trade-offs and transitions and identify points of agreement. I've
tried to indicate confidence levels for various claims, but am
probably overconfident about many specific things.

The four level of social distancing

The levels

What exactly falls in a given level is subject to debate, but is not
the focus here.

Level 1 (avoid large gatherings) Avoid sporting events, large
lectures, conferences, political rallies, demonstrations, rave
parties, cinema halls, cruise ships, prisons, and other
environments that involve close contact with large numbers of
people.

Level 2 (do all work and recreation remotely where feasible, and
avoid crowding when meeting in person): Run schools,
universities, and workplaces remotely, except those that need
in-person interaction (for instance, retail storefronts and
restaurants). Postpone recreational travel and substitute virtual
entertainment for physical entertainment where feasible. Go to
restaurants and cinema halls sparingly and when they are less
crowded.

Level 3 (flexible lockdown, "stay home except for essential
needs"): Whatever workplaces can be run remotely, run
remotely. For others, shut them down unless they serve "essential
needs". For instance, shut down nail salons, spas, gyms, etc. Only
things like grocery stores, convenience stores, hardware stores,
and takeout food are allowed. Restrict travel, both regional and
across cities, to essential needs. Go out only for exercise and
buying essentials.

Level 4 (strict curfew-style lockdown, with police
enforcement): Similar to Level 3, but with stricter
restrictions. Mass transit, both intra-city and inter-city, may be
stopped for everybody except essential workers. Even takeout food
may not be allowed. If you leave the house, you may be stopped by
lockdown enforcers and may have to submit documentation or show an
identity card to justify yourself.

Chart 15 in the hammer and the
dance
is somewhat similar in that it lays out various levels of social
distancing.

...
Alternative mask materials
by Dmitry Vaintrob — 2020-03-27T01:22:11.435Z

Posting for the first time -- please LMK if this is the wrong format for a question.

I like Elizabeth's idea that we are still in the "throw things against the wall and see what sticks" phase of coronavirus response, so even very messy and non-expert questions can be helpful.

So here's a question. Tl:dr version: what are possible mask alternatives that are more easily scalable than standard N95 masks and have better coronavirus protection than surgical masks? If promising materials do exist, what are good ways to test promising materials without endangering doctors? Long version below.

I have been reading about the shortage of PPE (personal protective equipment) for doctors: hospitals are planning for re-using masks, substituting the more effective N95 masks for much less effective surgical masks (SSC compares effectiveness here https://slatestarcodex.com/2020/03/23/face-masks-much-more-than-you-wanted-to-know/). I have friends who are doctors or work with doctors and are absolutely miserable about this, and this strikes me as one of the biggest short-term problems we'll be facing.

Many companies and individuals have donated their stock of N95 masks, but there simply doesn't seem to be enough to go around. To be safe a medical professional needs to put on a fresh N95 mask for each shift that might involve coronavirus exposure. For most doctors and nurses in affected wards, this corresponds to (bare minimum) two masks per day, which will most likely mean 2-4 million masks per day for the US alone in the coming months.

From what I understand, this kind of production is nigh-impossible in the short term, because of the shortage of melt-blown fabric. From this NPR source

making a single machine line takes at least five to six months.

(Though the same source discusses Chinese factories that have gotten around this time limit.)

So a reasonable next question is to ask whether there are alternative materials/designs for masks that do not use melt-blown fabric or other difficult-to-scale materials and offer better protection against n-CoV exposure than flimsy fabric or surgical masks. A cursory literature search shows a bit of promise:

This nature article claims that adding a layer to a mask which is coated in dried salt significantly improves H1N1 flu virus filtration. The article has problems, and its *in vivo* mouse section strikes me as

...
TikTok Recommendation Algorithm Optimizations
by Xodarap — 2020-03-27T01:03:58.721Z

Update 2020-06-07: I have done more in-depth investigations into TikTok, whose results can be found at tiktokodds.com.

Summary

The communities I am part of rely heavily on longform text for communication. The world seems to be moving away from text (and especially longform text).

One clear example is TikTok, which is the

most downloaded

social media application. It centers around sharing short videos. I’m interested in whether important concepts can be communicated via this medium.

As part of that, I researched more about the recommendation algorithm. This has led me to some success (e.g. a coronavirus video with 400,000+ views). Because I found it very hard to get useful information about TikTok when I was doing this research, and because I want the sort of person who would read this post to get wider visibility for their ideas, I am writing this summary.

Background

Most TikTok videos are viewed through the “for you page”, roughly analogous to the Twitter feed. The TikTok algorithm recommends videos for you to view on this page. Note that, unlike with Twitter or Instagram, a large fraction of the content comes from creators that the user does not follow.

The TikTok recommendation algorithm is proprietary and mostly confidential. We know only a few things through information that employees have leaked to the press.

The TikTok recommendation algorithm consists of two components: an automated component and a manual component.

Automated

When a user creates a video, TikTok analyzes the video to identify the target audience for the video. They claim to use a combination of discrete fields (namely the hashtags used by the author and the sound chosen), natural language processing (presumably analyzing any text which is overlaid in the video), and computer vision. For example, they might analyze your video to find that contains images of a cat, has text like “meow” and the hashtag “#catsoftiktok”. They will use this information to identify an audience of people who like cat videos.

They then create a small sample audience of cat-video-lovers who get shown this video. If this audience likes the video, it will be shown to a larger audience. If that audience likes it, it will be shown to a still larger audience, etc.

Whether the audience likes the video is some function of how they engage with it: do they watch it the whole way thr...
LW Team Updates: Pandemic Edition (March 2020)
by Ruby — 2020-03-26T23:55:02.238Z

TL; DR

The LessWrong team has been throwing our combined might behind coronavirus efforts. As I see it, coronavirus is both of a problem immense proportion that we might be able to help with as well as a domain well suited to the development and application of rationality + rationality tools

Our efforts include:

A Coronavirus Research Agenda for the community to contribute research efforts towards.
A Link Database of Coronavirus Resources which have been vetted, rated, and briefly summarized.

Plus daily updates of the best additions to the database.

New tagging features which allow for:

A dedicated coronavirus tag page.
Filtering for coronavirus content (exclude or include).

A thread of Justified Practical Advice.

plus summary.

A Coronavirus Open Thread for coronavirus thoughts that don't warrant their own post.
A Template Spreadsheet for Houses to coordinate their coronavirus quarantine and health statuses within and between themselves.
Various direct research contributions [1, 2, 3].
Online Events & Meetups

The first event, this Sunday 3/29, will be a livestream debate + meetup with Robin Hanson and Zvi Mowshowitz on whether we should intentionally expose parts of the population to the coronavirus in a controlled way.
When: Sunday, March 29 at 12:00 PDT (West Coast Time)
Full Details Here

Full Update

2020 is turning out to be quite the year. I apologize that the LessWrong team hasn’t yet put out any updates so far: we’d lined up some great Q1 plans and then things got...messy.

The team’s attention is now fully focused on COVID-19. Habryka has some elaboration on why this is a top priority

here

.

Before I go any further, serious respect to the LessWrong community which has done a fantastic job addressing the coronavirus situation ahead of the curve. Really, the response has been very proportionate to the situation.

A Note on Additional Help

For the last several weeks, the LessWrong team has been contracting with Elizabeth to help lead coronavirus efforts, hence her name being attached to several of the below projects. Elizabeth has been a member of the extended LessWrong moderator team since possibly the rise of LW2.0 and may be recognized for her work on

epistemic spotchecks

and

other research

.

Current Projects

[This Sunday!! March 29] Online Events & Meetups

The LessWrong team is beginning to organise various online meetups and events. The plan is to experiment and explore

...
Hanson vs Mowshowitz LiveStream Debate: "Should we expose the youth to coronavirus?" (Mar 29th)
by Ben Pace — 2020-03-26T23:46:08.932Z

I'm running the first LessWrong LiveStream Debate and Meetup, an experiment in online events.

This Sunday (3/29) at noon PDT, Robin Hanson and Zvi Mowshowitz will debate Robin's policy proposal of deliberate infection of certain parts of the population. This will be on a YouTube LiveStream. After the debate, there will be several chat rooms in Mozilla Hub for a general LW meetup, where you can talk to other LessWrong users and with the two debaters.

Link to Youtube Stream

After that, there'll be lots of online meetups in Mozilla Hub chatrooms like this one:

Please RSVP for the event here, so we know how many people are coming.

Summary

Time and Date: March 29 at 12:00 PM PDT (US West Coast Time)
On Feb 17th, Robin wrote the post Consider Controlled Infection, and has since followed up with six more posts on the policy proposal of deliberate exposure of certain parts of the population. Robin and Zvi will be debating that proposal and its alternatives.
They will have a 90 min debate followed by a 30 min Q&A that I'll moderate.
For the Q&A, if you are selected you will be given an invite link and will join the Zoom call to ask your question.
The online meetup will start just after 2pm. (If there's problems with Mozilla Hubs, we have a Discord server prepared as backup.)

I'll update this page with a link to the live stream and further info on how the Q&A and meetup will happen. I look forward to chatting with people! Check back for updates.

Update: the Mozilla Hub meetup rooms are listed here.

Updated 2: for the Q&A, please leave a comment on this post with a question or PM jacobjacob with your question. He will select the questions he likes and invite you onto the zoom call to ask the question.
What are the most plausible "AI Safety warning shot" scenarios?
by Daniel Kokotajlo — 2020-03-26T20:59:58.491Z

A "AI safety warning shot" is some event that causes a substantial fraction of the relevant human actors (governments, AI researchers, etc.) to become substantially more supportive of AI research and worried about existential risks posed by AI.

For example, suppose we build an unaligned AI system which is "only" about as smart as a very smart human politician, and it escapes and tries to take over the world, but only succeeds in taking over North Korea before it is stopped. This would presumably have the "warning shot" effect.

I currently think that scenarios like this are not very plausible, because there is a very narrow range of AI capability between "too stupid to do significant damage of the sort that would scare people" and "too smart to fail at takeover if it tried." Moreover, within that narrow range, systems would probably realize that they are in that range, and thus bide their time rather than attempt something risky.

EDIT: To make more precise what I mean by "substantial:" I'm looking for events that cause >50% of the relevant people who are at the time skeptical or dismissive of existential risk from AI to change their minds.