trentmkelly/LessWrong-43k huggingface dataset:
The central limit theorem in terms of convolutions
by Maxwell Peterson — 2020-11-21T04:09:44.145Z

There are multiple versions of the central limit theorem. One common version says that, as n→∞, the mean of means looks like a Gaussian distribution. People in industry sometimes ignore the "goes to infinity" part, and assume that if n is large, that's good enough. But is that true? When is it safe to assume that your means have converged? I heard of a case recently where the mean of means was assumed to have converged, hadn't, and the application it was a part of suffered accuracy problems for months without anyone knowing. This sequence will explore: under what conditions does the central limit theorem "fail" like this?

The central limit theorem is about convolutions

There are multiple versions of the central limit theorem. They're all a version of the statement:

If you have a bunch of distributions fi (say, n of them), and you convolve them all together into a distribution F∗:=f1∗f2∗f3...∗fn, then the larger n is, the more F∗ will resemble a Gaussian distribution.

The simplest version of the central limit theorem requires that the distributions fi must be 1) independent and 2) identically distributed. In this sequence, I'm gonna assume #1 is true. We'll find that while condition #2 is nice to have, even without it, distributions can converge to a Gaussian under convolution.

A Gaussian distribution is the same thing as a Normal distribution. Some examples of Gaussian distributions:

Wikipedia

Wait - this doesn't sound like the central limit theorem I know

Most statements of the central limit theorem, including Wikipedia's, talk in terms of the sums of random variables (and their density functions and expected values). But this is the same thing as our convolution-of-distributions, because the density function of the sum of two random variables X, Y is the convolution of the density functions of X and Y. Looking at the central limit theorem in terms of convolutions will make it easier to see some things. It's also useful if your version of probability doesn't have the concept of a random variable, like probability theory as extended logic*.

Another statement of the central limit theorem, from Jaynes:

The central limit theorem tells us what is essentially a simple combinatorial fact, that out of all conceivable error vectors e1,...,en that could be generated, the overwhelming majorit

...
AGI Predictions
by Amandango — 2020-11-21T03:46:28.357Z

This post is a collection of key questions that feed into AI timelines and AI safety work where it seems like there is substantial interest or disagreement amongst the LessWrong community.

You can make a prediction on a question by hovering over the widget and clicking. You can update your prediction by clicking at a new point, and remove your prediction by clicking on the same point. Try it out:

Elicit Prediction (elicit.org/binary/questions/FIVfnQ_kJ)

Add questions & operationalizations

This is not intended to be a comprehensive list, so I’d love for people to add their own questions – here are instructions on making your own embedded question. If you have better operationalizations of the questions, you can make your own version in the comments. If there's general agreement on an alternative operationalization being better, I'll add it into the post.

Questions

AGI definition

We’ll define AGI in this post as a unified system that, for almost all economically relevant cognitive tasks, at least matches any human's ability at the task. This is similar to Rohin Shah and Ben Cottier’s definition in

this post

.

Safety Questions

Elicit Prediction (elicit.org/binary/questions/_Sw39Z-kh)

Elicit Prediction (elicit.org/binary/questions/HqT9XSwfs)

Elicit Prediction (elicit.org/binary/questions/sTO9o3bLg)

Elicit Prediction (elicit.org/binary/questions/kua2HCDhi)

Elicit Prediction (elicit.org/binary/questions/KqSEIKayU)

Elicit Prediction (elicit.org/binary/questions/yoiBUdpgO)

Elicit Prediction (elicit.org/binary/questions/RcOt6wSs7)

Elicit Prediction (elicit.org/binary/questions/ZjN5qqVRz)

Timelines Questions

See

Forecasting AI timelines

,

Ajeya Cotra’s OP AI timelines report

, and Adam Gleave’s

#AN80 comment

, for more context on this breakdown. I haven’t tried to operationalize this too much, so feel free to be more specific in the comments.

The first three questions in this section are mutually exclusive — that is, the probabilities you assign to them should not sum to more than 100%.

Elicit Prediction (elicit.org/binary/questions/0LL9WacY-)

Elicit Prediction (elicit.org/binary/questions/9e9nB8Arw)

Elicit Prediction (elicit.org/binary/question

...
Predictions made by Mati Roy in early 2020
by Mati_Roy — 2020-11-21T03:24:56.020Z

Author: Mati Roy | Created: 2020-01-11 | Updated: 2020-03-01 (Adjusted: 2020-11-07) | Published: 2020-11-07

Quality: Those are notes I took for my present and future selves; they weren’t taken with the purpose of informing others.

Importance: 3/10. I don’t think all those predictions are important / transformational. It’s likely not important for you to read this.

Epistemic status: My credences are already quantified for each prediction. But my predictions are not independent of each other. For example, shorter AI timelines could mean shorter timelines on all those predictions, and vice versa. I might also be miscalibrated on long-term predictions — I don’t have first hand experience with that having only been born recently.

Context: I wrote some predictions in January-Ferbruary 2020 (some with links to PredictionBook and Metaculus with the exact date available on those platforms). I hadn’t published it at the time because there were a bunch of other topics I wanted to make predictions on. They are mostly predictions made on a 10-100 years time horizon.

Value to me: Making this research was much more time consuming than I thought. It was an interesting exercise, and will likely be interesting to check back on those predictions in the future. Here’s how I felt going down this rabbit hole.

Medium: Ideally, I would like a prediction platform where I could post my comments and predictions on public questions, like Metaculus, but with the additional option of having a personal public page automatically aggregating all my predictions and comments, similar to what I did here.

Cellular agriculture

Why care?

50 billion animals are raised and killed in factory farms every year. Most experience extreme levels of suffering over the course of their lives due to intense confinement and the removal of body parts. The meat industry is also one of the largest contributors to climate change, with 14.5% of global greenhouse gas emissions. (source)

A reduced population of farmed animals would also likely reduce the risk of pandemics.

It would also likely allow us to create meat for cheaper.

It might also provide a more robust food supply.

It would also allow us to create healthier meat, with less contaminants.

It would also allow us to create a wider range of food, such as synthesizing new forms of meat.

It might also make it easier to sustain human life on other celestial bodies.

Predictions

8...
Zen and Rationality: Skillful Means
by Gordon Seidoh Worley — 2020-11-21T02:38:09.405Z

This is post 5/? about the intersection of my decades of LW-style rationality practice and my several years of Zen practice.

In today's installment, I look at skillful means from a rationalist perspective.

As part of Zen practice, a teacher may use or encourage the use of many skillful means. Sometimes called expedient means or upaya, these may include things like encouraging a student to take up a particular meditation practice like breath counting or labeling, assigning a koan, or giving the student a job within the Zen center, like alter care or bell ringing. These are meant to aid the student in their practice of the way.

Importantly, the idea behind these means being "skillful" or "expedient" is that they are not necessarily practices a student will continue with forever, but rather things the student should do now that will help them. What may be useful for one student to do may not be useful for another, and what was once a useful practice for a student may later become a hindrance.

A good example is structured meditation practices, like breath counting. When a student begins meditating, they might find it very difficult to stay seated for 30 minutes, even during timed meditation periods sitting with other people in a zendo. Giving them something to do, like counting their breath, gives them something to focus on and distract the part of their mind that wants to get up and do anything else. Over hundreds of hours, they'll retrain themselves to be able to stay seated even when distracted by gathering evidence that they can do it, and slowly the breath counting will stop being a skillful means to help them practice and will instead become a hindrance and a distraction from just sitting, at which point they might move towards a different, less structured meditation practice or spend less of the time in meditation counting breaths. If they kept counting their breath for years even after it was no longer necessary to get them through a sitting period, it would no longer be a skillful use of the means, but as long as the alternative would be failing to keep sitting so they have the chance to develop skills that will let them meditate more full heartedly, it remains skillful.

Rationality has its own version of skillful means via the practice of instrumental rationality, or systematically achieving one's ends. It's the art of finding ways to help one become strong...
The Darwin Game - Rounds 21-500
by lsusr — 2020-11-21T00:58:42.926Z

Rounds 20-30

EarlyBirdMimicBot takes the lead off the backs of the Clone Army.

Rounds 30-100

EarlyBirdMimicBot exhausts the clone army before the treaty expires in turn 90.

Rounds 100-500

From here on out it is a random walk. The bots with low populations die to variance. Congratulations to BeauBot and Insub's CooperateBot for making it this far!

Winners

Note: This is an alternate timeline. It is not the official tournament.

EarlyBirdMimicBot by Multicore
BendBot by Zvi
MeasureBot by Measure
LiamGoddard by Liam Goddard

Today's Obituary

Bot	Team	Summary	Round
RaterBot	Chaos Army	Estimates opponent's aggression by counting the number of 3s, 2s, return 3s and return 2 instances in its source code. Then picks a strategy based off of that.	21
Copoperater	Chaos Army	Tit-for-tat, starting at 2.	22
RandomOrGreedyBot	Chaos Army	If the opponent averaged less than 2.5 over the last 100 turns then plays int(5 - opponent_avg). Otherwise randomly selects 3 or 2 randomly.	24
Silly TFT Bot 3	NPCs	Plays tit-for-tat starting at 3.	28
Empiricist	Chaos Army	Performs the best strategy that would have worked against historical data.	28
CopyBot Deluxe	Chaos Army	Tit-for-tat. Picks starting value of 2 or 3 based off of round number.	32
Pure TFT	Chaos Army	"For the first round, play 2 or 3 with a 50/50 chance of each. For each subsequent round, play whatever the opponent played on the previous round."	36
Silly TFT Bot 2	Chaos Army	Plays tit-for-tat starting at 2.	40
CloneBot	Clone Army	CloneBot. Died before the treaty broke.	42
jacobjacob-Bot	Norm Enforcers	Cooperates with Ben-Bot	42
SimplePatternFinderBot	Chaos Army	Finds simple patterns.	42
Silly 2 Bot	NPCs	Always returns 2.	43
Winner against low constant bots	Chaos Army	Starts with 2. Then always returns 5 - opponent_previous_move.	44
Clone wars, episode return 3	Clone Army	CloneBot. Died before the treaty broke.	50
a_comatose_squirrel	Clone Army	CloneBot. Died before the treaty bre	52
CliqueZviBot	Clone Army	CloneBot. Died before the treaty bre	53
incomprehensibot	Clone Army	CloneBot. Died before the treaty bre	53
A Very Social Bot	Clone Army	CloneBot. Died before the treaty bre	57
KarmaBot	Clone Army	CloneBot. Died before the treaty bre	58
Akrasia Bot	Clone Army	CloneBot. Died before the treaty bre	60
AttemptAtFair	Chaos Army	Oscillates between 3 and 2, starting with 3.	95
OscillatingTwoThreeBot	Chaos Army	"cooperates in the dumbest possible way"	95
Why can't we all just get along	Chaos Army	Doesn't negotiate with terrorists. Doesn'

...
Working in Virtual Reality: A Review
by ozziegooen — 2020-11-20T23:14:28.707Z

For the past three days, I started experimenting with working in Virtual Reality. I'm quite impressed. My guess is that it's not good for most people yet, but that 1 to 10% of people reading this would gain a 2 to 20% increase in computer productivity by using a VR working setup. The upper end is for people who get distracted easily or have a difficult time with SAD.

This feels like the most radical experiment I've made to my setup so far, so I'm quite happy with how it's worked out. I've used to dream of similar setups and it's really cool that the technology is basically there. I've given demos to a few people in my house who haven't been close to VR and their responses varied from fairly impressed to incredibly impressed.

I'm fairly convinced that there's an extremely promising future for work in VR. The VR ecosystem seems to be improving much more quickly than the alternatives. It strikes me as surprisingly possible that within 2 to 5 years, VR work setups will be the generally recommended work setups, at least for "people in the know."[1] This could both lead to direct improvements and lead the way for radical rethinkings of what work setups are possible.

My Setup

My specific setup is an Oculus Quest 2 ($300), a 2016 Macbook Pro, and the application Immersed VR. Immersed works using WiFi. My router is around 15 feet away from my headset, and my computer is connected directly to the router via Ethernet. In the app I use two "monitors"; I downscale a 4K monitor to 2048x1280 and use a side monitor of 1920x1080. It's suggested to keep resolutions rather low both because the Oculus Quest 2 doesn't itself have a high resolution (1832×1920 per eye), and because higher resolution means higher latency. You can have up to five "virtual" monitors with Immersed, but I prefer one or two big ones.

This is me editing this post. My setup is pretty simple when writing. I have a second screen on the right, but I'm not using it at the moment. I typically have the main screen a bit closer to me, but zoomed it out to make this image more interesting.

Me browsing LessWrong in the Spaceship area.

I think I used this setup for around 5 working hours on Wednesday, 6 on Thursday, and maybe 2 so far today (but it's still early). It didn't seem to get particularly tiring over that time.
I've been getting latency of around 5ms to 15ms, but every minute or so there are some frustratin...
Epistemic Progress
by ozziegooen — 2020-11-20T19:58:07.555Z

Epistemic Status: Cautiously optimistic. Much of this work is in crafting and advancing terminology in ways that will hopefully be intuitive and useful. I’m not too attached to the specifics but hope this could be useful for future work in the area.

Introduction

Strong epistemics or “good judgment” clearly seems valuable, so it’s interesting that it gets rather little Effective Altruist attention as a serious contender for funding and talent. I think this might be a mistake.

This isn’t to say that epistemics haven’t been discussed. Leaders and community members on LessWrong and the EA Forum have written extensively on epistemic rationality, “good judgment”, decision making, and so on. These communities seem to have a particular interest in “good epistemics.”

But for all the blog posts on the topic, there is less in terms of long term and full-time efforts. We don’t have teams outlining lists of possible large scale epistemic interventions and estimating their cost-effectiveness, like an epistemics version of the Happier Lives Institute. We don’t have a Global Priorities Institute equivalent trying to formalize and advance the ideas from The Sequences. We have very little work outline what optimistic epistemic scenarios we could hope for 10 to 200 years out from now.

I intend to personally spend a significant amount of time on these issues going forward. I have two main goals. One is to better outline what I think work in this area could look like and how valuable it might be to pursue. The second is to go about doing work in this area in ways that both test the area and hopefully help layout groundwork that makes it easier for more people to join in.

One possible reason for a lack of effort in the space is that the current naming and organization is a bit of a mess. We have a bundle of related terms without clear delineations. I imagine that if I asked different people how they would differentiate “epistemics”, “epistemic rationality”, “epistemology”, “decision making”, “good judgment”, “rationality”, “good thinking”, and the many subcategories of these things, I’d get many conflicting and confused answers. So some of my goal is to try to highlight some clusters particularly worth paying attention to and formalize what they mean in a way that would be useful to make decisions going forward.

I’ll begin by introducing two (hopefully) self-evident ideas. “Epistemic Pr...
Why is there a "clogged drainpipe" effect in idea generation? 
by Bird Concept — 2020-11-20T19:08:08.461Z

I've noticed something curious about creativity. (Like when doing the Babble challenges, or just when thinking in general.)

I have a bad idea. ("Send an object to the moon using a bird in a spacesuit") I don't write it down, instead trying to generate other ideas. Yet the bad idea keeps lingering on my mind. Eventually, I say "okay, fine, I will write you down!" and suddenly there's a sense of flow and relaxation, as if though new space has opened up for other ideas.

Ed Sheeran describes something similar:

If I was advising anyone to start songwriting, I’d just say: write anything that comes into your head. Anything. Just get stuff out there. I kinda treat songwriting as a dirty tap in an old house. When you run a dirty tap, it’s clogged up, bit of dirt in it, bits of mud. You run it, mud’s going to come out, a little bit of water, a bit more mud, and then suddenly it’s going to start flowing clean water.

You’ve got to unclog the pipes when you’re songwriting. So just start writing bad songs. Write songs for the sake of it. Write a song a day. Just sit down, pick a chord, write a song, get that song out of you, and the more and more you do it, the more and more you unclog the pipes.

I’d say, if you want to start songwriting, just start. Don’t worry too much about writing the best songs possible. If anyone wants to listen to growth, go on YouTube, type in “Ed Sheeran Addicted” and you’ll hear a song that I did when I was 12. And the singing is dreadful, the songwriting is dreadful, the guitar playing is dreadful, and now I’m here talking to you as a professional musician.

When I did the "100 ways to light a candle" Babble challenge yesterday, something similar happened. I had the lingering idea of "I could ask someone else to do light the candle", but also thought "That's a boring answer". Yet it kept lingering. Finally, I wrote down "There's a general class of strategies around getting the help of other people". And suddenly that unblocked a whole range of similar ideas -- some of which I really liked, like:

"Destroy a bunch of other light sources in the world, thereby strongly increasing the incentive for others to light this candle"

or

"Go around the neighbourhood, finding a bunch of lit candles, place them next to you in a beautiful pattern EXCEPT that in a symmetry-breaking place is your candle. Wait until someone fixes it."

It ...
Embedded Interactive Predictions on LessWrong
by Amandango — 2020-11-20T18:35:32.089Z

Ought and LessWrong are excited to launch an embedded interactive prediction feature. You can now embed binary questions into LessWrong posts and comments. Hover over the widget to see other people’s predictions, and click to add your own.

Try it out

Elicit Prediction (elicit.org/binary/questions/qqEklFgQG)

How to use this

Create a question

Go to elicit.org/binary and create your question by typing it into the field at the top
Click on the question title, and click the copy button next to the title – it looks like this:

Paste the URL into your LW post or comment. It'll look like this in the editor:

Troubleshooting: if the prediction box fails to appear and the link just shows up as text, go to you LW Settings, uncheck “Activate Markdown Editor”, and try again.

Make a prediction

Click on the widget to add your own prediction
Click on your prediction line again to delete it

Link your accounts

Linking your LessWrong and Elicit accounts allows you to:

Filter for and browse all your LessWrong predictions on Elicit
Add notes to your LessWrong predictions on Elicit
See your calibration for your LessWrong predictions on Elicit
Predict on LessWrong questions in the Elicit app

To link your accounts:

Make an Elicit account
Send me (amanda@ought.org) an email with your LessWrong username and your Elicit account email

Motivation

We hope embedded predictions can prompt readers and authors to:

Actively engage with posts. By making predictions as they read, people have to stop and think periodically about how much they agree with the author.
Distill claims. For writers, integrating predictions challenges them to think more concretely about their claims and how readers might disagree.
Communicate uncertainty. Rather than just stating claims, writers can also communicate a confidence level.
Collect predictions. As a reader, you can build up a personal database of predictions as you browse LessWrong.
Get granular feedback. Writers can get feedback on their content at a more granular level than comments or upvotes.

By working with LessWrong on this, Ought hopes to make forecasting easier and more prevalent. As we learn more about how people think about the future, we can use Elicit to automate larger parts of the workflow and thought process until we end up with end-to-end automated reasoning that people endorse. Check out our

blog post

to see demos and more context.

Some ex

...