trentmkelly/LessWrong-43k huggingface dataset:
Why is the war in Ukraine particularly dangerous for the world?
by mikbp — 2022-03-06T13:38:10.370Z

I have heard that since WW2 there have been ~140 armed conflicts in the world. Only few of them have been full-fledged wars, let alone big ones. However, as I don't know almost anything about wars and the politics around them, I cannot really formulate why this war is particularly dangerous and prone to start WW3. This one is specially frightening for me because it is very close by --I'm European--, but this does not make it more prone to e.g. start WW3.

I have thought of few factors (location, countries involved / potentially involved, possession of nuclear weapons...) but the war in Ukraine does not seem to be too special in any of them. Is it maybe the combination of factors what it makes it particularly dangerous? As many may, like me, not be too versed in geopolitics/geostrategy, I think it would be useful to compile a list of key factors setting this war aside from all the other wars the world has endured since WW2 and making it particularly dangerous for the whole world.
Accelerated [Honors] Calculus
by lsusr — 2022-03-06T10:34:46.133Z

The University of Washington offers the following introductory math classes:

MATH 111 Algebra with Applications is for people who dislike math.

MATH 124 Calculus with Analytic Geometry I is for people who like math.

MATH 134 Accelerated [Honors] Calculus is for people in an abusive relationship with math.

I took Accelerated [Honors] Calculus.

Accelerated [Honors] Calculus starts with the Peano axioms. The Peano axioms are a set of nine assertions like "0 is a natural number", "x=x" and "if x=y the y=x". It is possible to derive all of number theory using just the Peano axioms. Add the Cauchy Completeness Axiom and you can derive calculus too.[1]

Our assignment was to to derive calculus.

I tried out CSE 143: Computer Programming II too. CSE 143 used Java. The class was based around memorizing words like "polymorphism" and "postorderal traversal". My friend majoring in Human Centered Design and Engineering felt like CSE 143 was hard. I felt like I was watching a multi-level marketing campaign for Oracle development tools. I resolved to just teach myself how computers worked. That was the last computer science class I ever took.

Accelerated [Honors] Calculus lasts one year. By the end of the year, everyone with a shred of economic sense has quit to study Computer Science instead. The rest of us took Accelerated [Honors] Advanced Calculus in our second [sophomore] year of college.

My sophomore year of college was mostly "staying up after midnight in the library with my classmates doing calculus homework" and "working at the physics tutoring center where I helped other students with their calculus homework".

Was it worth it?

If college is about signaling to employers then "no". If college is about partying and finding a mate then "no, definitely not". If college is about learning things that make you smarter then "yes".

A physics student wrote an email to the tutors at my tutoring center. She had been getting bad scores on her exams and worried she wasn't smart enough for physics. I replied to her with an email that explained step-by-step what I did before each physics exam.

Her reply: "Oh. I guess I'm just not studying hard enough."

My memories of the class are hazy. Please correct me if I'm wrong about which axioms are necessary to prove what. ↩︎
Lower Risk of Nuclear war?
by arunto — 2022-03-06T06:59:10.565Z

The Russian invasion of Ukraine has led to some anxiety about possible escalation, especially given Putin's use of nuclear weapons as a threat. This shows in some topics here on lesswrong, too. And I find this anxiety in myself, as well, sometimes wondering what I would do, if there was suddenly an extremely bright flash of light.

And I think there is a real basis for this risk, given Putin's rationality is somewhat doubtful at the moment, and the fog of war can lead to all kinds of unexpected and unwanted outcomes.

But thinking about it for some days I believe there could be some negativity bias (in ourselves, and definitely in media reporting) about this topic. Because, I think, there are some factors in the current events that have reduced the risk of global nuclear war:

a) Baltic states

One way how a nuclear war between the US and Russia could develop is a Russian attack on a NATO country. The most likely scenario here is an attack on one or more Baltic states.

In the past, Russia has conducted very large military exercises there, iirc without much reaction from the NATO. I think this will change. NATO is in the process of increasing its permanent troop deployments there and I guess in the case of future massive Russian military exercises there NATO will step up its presence on its eastern flank (e.g. deploying additional airforce assets there on short notice).

At the same time, NATO's reaction to the Ukraine (help but no troops for the Ukraine, troops for the Baltic states) has reinforced its red line. I believe this could have made the Baltic states more secure compared to the time before the invasion (at the same time, of course, it has made the situation for non-NATO countries like Georgia or Moldova even more insecure).

b) Taiwan

I think China is watching very closely the reaction of the Western democracies to Russia's invasion. And if Bejing is a coldly calculating player (which currently is my impression), then they will have updated their prediction about the West's reaction to an invasion of Taiwan, increasing the estimated negative effects of such a move. And a war between mainland China and the US is one of the big risks for a global nuclear war.

Conclusion

I am not claiming, that overall Russia's invasion has reduced the risk of nuclear war - there is a short term hightened risk. But I do claim that the increase of risk is less than i...
2022 ACX predictions: market prices
by Sam Marks — 2022-03-06T06:24:42.908Z

As part of the 2022 ACX prediction contest, which I am co-running with Eric Neyman, I wanted to get market prices for all of the predictions.[1] These market prices will be included with the contest data, which should be released soon.

This ended up being harder than I expected, and I can't guarantee this data is error-free. So in the interest of transparency, I'm making this post to explain where all the numbers came from.

Before I get into it, some notes:

These are supposed to be market prices as of February 14, 2022, which was the last day for contest submissions.

In some cases (like when backing a probability out of a Metaculus probability distribution) I didn't know how to get historical data. If it didn't look to me like the market had moved much since 2/14, I instead used the predictions as of today, March 5.

When aggregating predictions from different markets, I'm weighting them according to how many stars they get from Metaforecast, when available. When not available, I'm using my judgement.

Many of the Manifold markets were very lightly traded, some having only 1 or 2 bets. I tried to note this below when I noticed it.

There was some personal judgement involved in e.g. deciding whether a market asked close enough to the right thing to be relevant, adding or subtracting a few percentage points to PredictIt markets which don't sum to 100%, etc. If it seems like I misjudged anything here, it's possibly because I did.
I also expect that there's at least one outright error from something silly like copying the wrong number.
So: if you see anything wrong please let me know! Also please let me know if there's a relevant market which I missed or if you see a way to back predictions out of financial markets which I didn't think of (I've noted such cases below).

Anyway, here we go:

Scott predictions

Biden approval rating (as per 538) is greater than fifty percent: 14
(12 from Manifold; also this market from Kalshi saying 20% for having approval >45% on election day in November)
At least $250 million in damage from a single round of mass protests in US: 36 (Manifold)
PredictIt thinks Joe Biden is most likely 2024 Dem nominee: 73 (Manifold)
PredictIt thinks Donald Trump is most likely 2024 GOP nominee: 60 (Manifold)
Major flare-up (worse than past 5 years) in Russia/Ukraine conflict: 76 (88 from Manifold; 60% chance of invasion from Metaculus)
Major fl

...
Don't Let Personal Domains Expire
by jefftk — 2022-03-06T02:50:04.343Z

It's common to see advice along these lines:

Don't build your stuff in someone else's sandbox. Get
your own domain and point it to whatever service you choose to use.
Your email address should be @yourdomain, where you have full control
and no one can lock you out. Don't fall into the trap of digital
sharecropping.

There are complicated tradeoffs here and different choices will make
sense for different people, but it's close to what I do personally.
My writing and projects are hosted on my own domain [1] and my email is

jeff@jefftk.com.

On the other hand, I don't think this is something to do lightly.

Say you register you.example and start going by
you@you.example. A few years later you decide this is
too much hassle, switch to using you@fastmail.com or
you@gmail.com, and let you.example expire.
Someone else can register it, send email legitimately as
you@you.example, and Angular
gets compromised. If there is anywhere you forgot to remove your
former email from your profile, now you are open to being
impersonated.

This problem isn't unique to personal domains, but it's much more
likely: the major email services don't make abandoned email addresses
open to reregistration, to avoid exactly this issue.

If you're considering registering a domain to use as your online
identity, make sure you're willing to take on the cost and hassle of
keeping the domain registered indefinitely.

[1] I do cross-post to Facebook, LessWrong, and occasionally other
places. I also rely on them to host discussions on my posts, though I
attempt to archive those discussions back on my site.
What we know about machine learning's replication crisis
by Younes Kamel — 2022-03-05T23:55:35.138Z
Link: https://youneskamel.substack.com/p/what-we-know-about-machine-learnings?s=w

The replication crisis is a a phenomenon that plagues modern day scientific research. And contrary to popular belief, it has being going on for a long time. The incentive structure within academia seems to reward quantity of publications over quality. This leads to questionable research practices which in turn lead to scientific journals containing false positive results.

This crisis is particularly strong in the social sciences where according to some estimates as much as 50% of published research is not replicable. The crisis is so prevalent in psychology that some psycholgists such as

Daniel Lakens

or

Ulrich Schimmack

made replication their main research interest.

But this is a blog about AI and machine learning, so what we’re interested in is knowing how robust the machine learning academic literature is. Does it suffer from this crisis ? Yes, it does. And

according to computer science researcher Genevera Allen

machine learning is also contributing to the replication crisis in other disciplines. She adds that she knows of the crisis from anecdotal evidence but does not have any number estimate of the proportion of reproducible (

replicable and reproducible don’t mean the same thing

but they are tightly linked and are part of the same problem) machine learning papers. In this article, we will review the existing literature and gather several strands of evidence of the replication crisis in machine learning and see if it is possible to get a number estimate.

Peer review in machine learning

Peer review is an integral part of the scientific process and it is important to understand it to understand the replication crisis. The gold standard of scientific research is to publish in peer-reviewed publications which vary in their level of prestige. The more publications in prestigious journals the more one rises trough the ranks of academia and receives more funding.

The issue is that peer reviewed journals are privately owned, even though they contain research paid for by the taxpayer, and thus require their publications to be marketable and sellable. They thus have a strong incentive to publish novel, positive results that will get people talking. This creates an incentive for researchers to produce only positive findings and over-hype their results to get published, which results in scientific journals containing a lot of false positives.

Moreover, peer review seems ...
Forecasting Newsletter: February 2022
by NunoSempere — 2022-03-05T19:30:11.094Z

Highlights

The FTX foundation will potentially give out millions in forecasting
Insight Predictions and Futuur have real-money prediction markets on the invasion of Ukraine
At least $444k paid out in over the counter bets on the invasion of Ukraine

Index

Thoughts on The FTX Foundation Funneling Funds to Forecasting
Prediction Markets & Forecasting Platforms
Forecasting Job Board
Odds and Ends
Long Content

You can sign up for this newsletter on

substack

, or browse past newsletters

here

. If you have a content suggestion or want to reach out, you can leave a comment or find me on

Twitter

.

Thoughts on the FTX Foundation Funneling Funds to Forecasting

The FTX Foundation announced a massive $100M to $1B/year (a) Future Fund. Amongst their areas of interest (a) and project ideas (a) are:

More forecasting. We’re huge fans of prediction markets and forecasting tournaments. We’d love to see these widely adopted and used to inform political decision-making. We’re particularly excited about long-term forecasting (10+ years out), and methods that might make long-term forecasting more feasible.

Prediction markets. We’re excited about new prediction market platforms that can acquire regulatory approval and widespread usage. We’re especially keen if these platforms include key questions relevant to our priority areas, such as questions about the future trajectory of AI development.

Forecasting Our World in Data. We’d love to see a project that takes one hundred of the most important charts in Our World in Data (we think the Technological Progress charts would be especially interesting) and employs superforecasters to plot out how the charts will go over the next one, three, ten, thirty and one hundred years. Ideally, the output would be well-presented and easily understandable, and display probability distributions for each year.

Forecasting that will affect important decisions. We think a key challenge for making forecasting organizations better is ensuring that the questions asked are interesting and important. We’d be especially excited about forecasting projects that have a great plan for ensuring that the questions asked are of significant interest to influential and altruistic actors, potentially including thoughtful government officials and large funders in the EA ecosystem.

More generally, we’re interested in a “superforecasting institute.” Few jobs are more important than rigor

...
Retrospective: Quantified Self Assessment
by The Guild of the Rose — 2022-03-05T15:11:26.040Z
Link: https://guildoftherose.org/articles/retrospective-quantified-self-assessment?utm_campaign=lw-retro-qsa

Quantified Self Assessment was the second Guild of the Rose course. Taught by Consul Alex Hedtke, the course was an evolution of the Alpha's Character Sheet and helped users discover bugs in their life.
[Letter] Russians are Welcome in America
by lsusr — 2022-03-05T10:15:44.883Z

Edit [to clarify]: American immigration policy is unwelcoming to immigrants. Often, the only ways to enter the US legally are to marry someone in the US or to get the sponsorship of a powerful tech company. It takes several months even under the best of circumstances. I just wanted clarify that Russians living in the US face no prejudice.

Dear [redacted],

I'm sorry. I had notifications turned off and didn't see your message until right now.

Get out of Russia before the borders close! If your in-group is LW-adjacent techies then you're probably smart enough to find a great job in the USA that pays way more than you could ever earn in Russia (even before the war and the sanctions).

I ask you for advice on how to help them find safe place in the foreign social fabric? Is there anyone left who can offer them student\IT positions w/t being ostracised?

Lol.

Ostracism is a complete non-issue for Russians in the United States. (And, presumably, other Western nations.) I have never met a single person in real life with hatred towards Russians. Nobody hates Russians here. Russians fit right in. All you need is good English (and, judging by your message, your English is fine (even if it's not, English isn't too hard for Russian-speakers to learn)).

Don't get me wrong. The United States has problems with racism, prejudice and xenophobia. But it's not directed towards Russians living in America. Getting a visa is hard. But that's it. Once you're in, you're in. (Don't worry about obtaining an American visa right now. Just get out of the country immediately. Worry about obtaining an American visa later.)

You know that Russian rocket scientist friend I was advertising? I have already gotten contacts from three companies that want to help him acquire employment and a visa. And not just three ordinary companies. Three of the best places to work in the entire United States of America. I can't promise you the same, but I hope my words help reassure you. We literally have a giant statue in New York symbolizing how welcoming this country is to immigrants.

Your priorities should be.

Get the hell out of Russia before the borders close.

Secure your short-term finances.

Start figuring out how to get a tech job.

Sincerely,

Lsusr
Ukraine Situation Report 2022/03/04
by lsusr — 2022-03-05T06:44:15.068Z

TL;DR: Shortages in Russia are so bad the Russian people are reusing Soviet jokes.

These posts are read by Ukrainians, Russians and veterans. Here is a gem by former American paratrooper ryan_b.

I feel like the biggest item here is the peacekeeping mission charade.

The Russians in this video are acting like they actually believe themselves to be on a peacekeeping operation.

Though clearly implied, I want to make it explicit for emphasis: peacekeeping operations and offensive operations are maximally different. Let us put aside the question of night vision or optics, since the Ukrainians don't have them either, and consider this problem instead: how the hell do you get your people to do what you need them to do when you won't tell them what they need to do?

―comment by ryan_b

American ryan_b's compassion for his Russian comrades is exactly the kind of universal love we need right now.

Scorched Earth

Ukraine is putting up fierce resistance. The Ukraine-Russia War already looks like a repeat of the disasterous War in Afghanistan. I'm not talking about the 2001–2021 War in Afghanistan between the US and the Taliban. I'm talking about the Soviet–Afghan War of 1979–1989. The Soviets lost, but it took ten years and the death of between 6.5% and 11.5% of the Afghani population.

The Russian Armed Forces outnumber the Ukrainian military. The Russians have more soldiers, more tanks, more vehicles, more artillery, more fighter jets and the second-most-powerful[1] nuclear arsenal in the world. The Ukrainian's advantages are morale, allies, the terrain advantages of fighting a defensive war and desperation. The Ukrainian population is as united as it is possible for a population to to be. The Russian military's morale is "meh", at best. I predict Russian troops' morale will monotonically decrease the longer Russian forces remain in Ukraine (excluding the Donbas region).

Urban warfare is harsh on invading forces. Insurgents can strike at you in three dimensions and then instantly flee back into the buildings.

将不胜其忿而蚁附之，杀士三分之一而城不拔者，此攻之灾也。

A general who grows impatient, angers and storms a city will kill one third of the attacking force and fail to take the city.

―Chapter 3 of Sunzi

Russia is attempting to surround major cities. Once they do, you should expect a siege. Food and utilities will be cut off. Your priorities are.

Don't get shot.

Warmth. Don't freeze. Clothes a

...
Deterministic Strategies Can Be Suboptimal
by Robert Kennedy — 2022-03-04T21:09:01.964Z

Yesterday I posted the following problem

You are playing a game against ROB, the robber. In this game, ROB will choose two arbitrary (real/computable) numbers, A and B. ROB will send both numbers to TABI the arbiter, who will secretly flip a fair coin and then hand you either A or B depending on the outcome of the flip. Your task is to come up with an algorithm which does better than 50% accuracy to determine if you have the larger number.

I will now insert line breaks, then some hints, then more line breaks, then the solution. Edit: This sentence is meant to remind you that you can only discover the answer once, and it is sweet victory to solve puzzles.

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Note that ROB is obviously not uniformly choosing any two arbitrary real numbers - that is incoherent! Much worse, ROB is stealing your algorithm and choosing his numbers from a probability distribution which minimizes your changes of winning.

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You can probably solve this if you restrict ROB to only picking two of {0,1,2} with different probability distributions, and then extrapolate.

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The solution is to choose any strictly increasing function P whose range is (a subset of) (0,1), and guess that your number X is the larger number with probability P(X). For any given pair A<B selected by ROB, you will guess "larger" correctly with probability P(B)2, and you will guess "larger" incorrectly with probability P(A)2; since P is increasing, it is clear you will guess "larger" correctly more often than you guess "larger" incorrectly. I hope the remaining details are clear.

Shout-out to jacob.wood who posted a solution first, and dxu who posted the entire solution first.

This is naively surprising to those who know that strategies should often not be probabilistic, even when the games you are playing are. Yudkowsky's newest novel demonstrates other areas where probabilistic strategies dominate. I will cover an example in my next post, as well as illustrate real world use cases where I have immediately applied the lesson.

The link to Yudkowsky's newest novel is here: https://www.glowfic.com/posts/4582