trentmkelly/LessWrong-43k huggingface dataset:
A non-mystical explanation of insight meditation and the three characteristics of existence: introduction and preamble
by Kaj_Sotala — 2020-05-05T19:09:44.484Z

Introduction

Insight meditation, enlightenment, what’s that all about?

The sequence of posts starting from this one is my personal attempt at answering that question. It grew out of me being annoyed about so much of this material seeming to be straightforwardly explainable in non-mysterious terms, but me also being unable to find any book or article that would do this to my satisfaction. In particular, I wanted something that would:

Explain what kinds of implicit assumptions build up our default understanding of reality and how those assumptions are subtly flawed. It would then point out aspects from our experience whose repeated observation will update those assumptions, and explain how this may cause psychological change in someone who meditates.
It would also explain how the so-called “

three characteristics of existence

” of Buddhism - impermanence, no-self and unsatisfactoriness - are all interrelated and connected with each other in a way your average Western science-minded, allergic-to-mysticism reader can understand.

I failed to find a resource that would do this in the way I had in mind, so then I wrote one myself.

From the onset, I want to note that I am calling this a non-mystical take on the three characteristics, rather than the non-mystical take on the three characteristics. This is an attempt to explain what I personally think is going on, and to sketch out an explanation of how various experiences and Buddhist teachings could be understandable in straightforward terms. I don’t expect this to be anything like a complete or perfect explanation, but rather one particular model that might be useful.

The main intent of this series is summarized by a

comment written by Vanessa Kosoy

, justifiably skeptical of grandiose claims about enlightenment that are made without further elaboration on the actual mechanisms of it:

I think that the only coherent way to convince us that Enlightenment is real is to provide a model from a 3rd party perspective. [...] The model doesn't have to be fully mathematically rigorous: as always, it can be a little fuzzy and informal. However, it must be precise enough in order to (i) correctly capture the essentials and (ii) be interpretable more or less unambiguously by the sufficiently educated reader.

Now, having such a model doesn't mean you can actually reproduce Enlightenment itself. [...] However, producing such a model would

...
Competitive safety via gradated curricula
by Richard_Ngo — 2020-05-05T18:11:08.010Z

Epistemic status: brainstorming some speculative research directions. Not trying to thoroughly justify the claims I’m making.

One way to think about the AI safety problem: there’s a spectrum of methods which each represent a different tradeoff between safety and ease of training an AGI, and unfortunately the two are anticorrelated. In particular, consider four regimes in which the bulk of training might occur (perhaps with additional fine-tuning afterwards):

Training a language model to answer questions correctly.
Training a RL agent on a range of limited tasks (e.g. games).
Training a RL agent on general tasks in large-scale simulations for long time periods.
Training a RL agent in competitive multi-agent environments.

I claim (but won’t fully defend here) that these are in order from safest but most difficult, to easiest but most dangerous:

Regime 1 will produce a question-answering system which has no experience taking actions in the world, and which may not be goal-directed at all. But many researchers expect that it’ll be much easier to create an AGI which can answer difficult questions by training it to interact with a simulated world, so that its concepts are “

grounded

” by experience.
Regime 2 is likely to produce an agent whose goals are bounded, and whose concepts are grounded; but which might only do well on the specific tasks it had been trained on. If so, building AGI in this regime would require a very sophisticated curriculum, if it’s possible at all.
Regime 3 provides a rich environment for an agent to learn quite general skills and concepts. However, now the agent will also be rewarded for developing large-scale goals, which might make it dangerous.
Regime 4 additional provides an “

autocurriculum

” via competition, the training signal from which could accelerate the development of general intelligence (as it did in humans). However, the agent could learn harmful skills and motivations (such as deception, manipulation or aggression) from competing with other agents, which it might then apply to interactions with humans.

This is a problem - but it’s also an opportunity. If we accept the claims I’ve made about this spectrum, then it might be much easier to train a relatively safe and non-agentic AGI if we start training in less safe regimes, and then gradually transition the traini...
Writing Causal Models Like We Write Programs
by johnswentworth — 2020-05-05T18:05:38.339Z

Clunc

We’ll start with a made-up programming language called Clunc. The distinguishing feature of clunc is that it combines classes and functions into a single type, called a clunc. It looks like this:

quad = Clunc {
x = 4
constant = 3
linear = 2*x + constant
result = x*x + linear
}

We could then go to a terminal:

>>> quad.result
27
>>> quad.linear
11

In order to use this clunc like a function, we apply the do() operator. For instance,

>>> quad3 = do(quad, x=2)

… creates a new clunc which is just like quad, except that x is 2 rather than 4:

>>> quad3
Clunc {
x = 2
constant = 3
linear = 2*x + constant
result = x*x + linear
}

When we query fields of quad3, they reflect the new x-value:

>>> quad3.result
11
>>> quad3.linear
7

There’s no designated “input” or “output”; we can use the do() operator to override any values we please. For instance

>>> quad_zero_linear = do(quad, linear=0)
>>> quad_zero_linear
Clunc {
x = 4
constant = 3
linear = 0
result = x*x + linear
}
>>> quad_zero_linear.result
16

A few quick notes:

Clunc is purely clunctional: everything is immutable, and each variable can only be written once within a clunc. No in-place updates.
Clunc is lazy.
Variables can be set randomly, e.g. “x = random.normal(0, 1)”.
The do() operator creates a new clunc instance with the changes applied. If there are any random variables, they are re-sampled within the new clunc. If we want multiple independent samples of a randomized clunc M, then we can call do(M) (without any changes applied) multiple times.

To make this whole thing Turing complete, we need one more piece: recursion. Cluncs can “call” other cluncs, including themselves:

factorial = Clunc {
n = 4
base_result = 1
recurse_result = do(factorial, n=n-1).result
result = (n == 0) ? base_result : n * recurse_result
}

… and that’s where things get interesting.

Causal Models

Hopefully the mapping from clunc to probabilistic causal models is obvious: any clunc with random variables in it is a typical

Pearl-style causal DAG

, and the do() operator works exactly like it does for causal models. The “clunc” is really a model, given by structural equations. The one big change is the possibility of recursion: causal models &#x...
"AI and Efficiency", OA (44✕ improvement in CNNs since 2012)
by gwern — 2020-05-05T16:32:20.335Z
Link: https://openai.com/blog/ai-and-efficiency/

Abstract:

We’re releasing an analysis showing that since 2012 the amount of compute needed to train a neural net to the same performance on ImageNet1 classification has been decreasing by a factor of 2 every 16 months. Compared to 2012, it now takes 44 times less compute to train a neural network to the level of AlexNet2 (by contrast, Moore’s Law3 would yield an 11x cost improvement over this period). Our results suggest that for AI tasks with high levels of recent investment, algorithmic progress has yielded more gains than classical hardware efficiency.
I'd Like To Maximizing Profit and Happiness but My Happiness conflicts a lot with making profit...
by Master MintZ — 2020-05-05T05:54:11.091Z

I have a history of changing and trying different things. I can learn things relatively quickly than the average person however there comes a point where I reassess what I am doing and most of the time change my course of action. A huge goal of my life is to be extremely wealthy. However, many of the businesses I chose or that was choosen for me "up for debate" has been slow growth businesses. The business don't have much rooms to scale very quickly because I prefer the own and rent model. As it doesn't take up much time so I can spend learning new things. The two businesses are real estate and car rentals. I finally realized that the majority of the value in the business is from the capital built up and management. So I decided to go into the arts and businesses that I create value for business. My most recent Art business is music. I tried painting and not that interested or also its not really scalable. I also worked on fashion design however I ended up outsourcing the entire design process and without sufficient knowledge of the design process my value to the business was pretty much zero. Anyways I feel like I have gaps in my knowledge and understanding to get to the next level of personal development and financial success. Any suggestions to help speed up this process?

Thank you
Direct work vs. earn-to-give?
by warrenjordan — 2020-05-05T05:52:09.562Z

I've been working in healthcare technology for 5+ years and am hitting a crossroads in terms of where I want to go in my career. Ever since discovering EA, I've been questioning whether I want to prioritize direct work vs. earn-to-give.

The core reason why I work in health tech is to make a difference by improving or saving people's lives. I used to believe that my direct work was the only way to make that difference. Now that I know there is other options, I'm conflicted.

For example, should I take a higher-earning role at a Facebook or Google-like company to donate more to effective charities or take a lower-pay role at a health tech company which will lessen my donations?

Of course there's other factors that would have to weigh in my decision - culture, work-life balance, rate of growth of career capital, remote flexibility, etc.

However, the path of earn-to-give is making me seriously consider other industries. If there's a company out there that is a great fit to my values and is higher-earning, but doesn't provide much impact as a health tech company would - I'll probably take it.

Now, that's not to say I will work at a company that does harm. I'd still want my company to be neutral or do some amount of good, but doesn't necessarily have to provide as much impact as a health tech company. Whereas before EA, impact mattered the most to me so I solely applied to health tech companies.

Any thoughts from those who have experienced this dichotomy throughout their career? Most ideal would be to have both, but I'm sure those positions are extremely competitive.
Constructive Definitions
by Chris_Leong — 2020-05-04T23:50:17.251Z

For some concepts, the most natural way for them to be defined is for the definition to first apply to a paradigmatic or natural domain which is then extended for reasons of convenience. We will call these constructive definitions.

Defining Numbers

Consider the example of numbers. The most natural or paradigmatic case are the counting numbers 1, 2, 3... In many cases, you don't even need a number for zero, you can just say "There were no cats" instead of using the word zero.

Fractions allow us to represent divisible objects like pies or shares of a hunt.

The number zero becomes important as soon as you have a decimal system, but beyond this adding it in allows the sum operation to handle columns with zero items without it being a special case.

Once we allow borrowing negative numbers become convenient, especially if an account can be positive or negative.

Eventually we might reach the point where we find it useful to define complex numbers or even quaternians so as to produce neater proofs in some cases.

Reflections

Notice how the definition of numbers was constructed incrementally.

There wasn't a single definition all the way through. As we progressed, we wanted numbers to be able to serve different functions, so we produced different formalisations or tools.

In other words, there is a sense in which they are an answer and not a question. If someone asks, "What are numbers?" and they haven't specified which kind of numbers they are referring to, then the question is essentially meaningless until clarified. It is only once a particular purpose has been chosen that we can answer with the appropriate kind of numbers for the task at hand. I suppose they could be looking for the paradigmatic case of numbers, but then they could have asked directly about that.

These kinds of definitions have a few properties. Firstly, while it is common to have a unique paradigmatic definition, this isn't always the case or undisputed. Some people might have included zero in the paradigmatic definition of numbers. Secondly, certain extensions might be controversial with people either rejecting an extension or proposing an alternative. However, instead of becoming enmeshed in disputes like, "Are complex numbers even a number?" we instead end up in more productive conversations like, "Is this extension practically useful enough to be wor...
Welcome to Less Wrong Spb [Edit With Your Details]
by игорь тимофеев — 2020-05-04T23:30:35.302Z

(The following are our suggestions for what kind of information is best to include in the welcome post of your group, feel free to replace them with whatever you think is best)

What kind of events does your group usually run? What does it usually do?

How frequently does your group organize events or meet?

Who would be a good fit for you group?

Should they have any particular skills or have done some specific background reading?
Individual Rationality Needn't Generalize to Rational Consensus
by Akshat Mahajan — 2020-05-04T22:53:15.442Z

tl;dr

Organizations that enforce rationality at the collective level can get very different voting outcomes than organizations that enforce rationality at the individual level, per known results in social choice theory. This has implications for real-world expert panels.

Here, "rationality" is logical consistency - it is possible for the majority of members to vote to reject a conclusion while also believing the necessary conditions to accept it hold, and vice-versa, even if they all independently evaluated the precepts and arrived at the conclusion logically. This arises because of how majority votes work.

This post summarizes Philip Pettit's 2002 paper outlining the issue and its implication for any deliberative democracy. It additionally summarizes Pettit and List's impossibility result on judgement aggregation rules from the Stanford Encyclopedia of Philosophy.

Introduction to the Discursive Dilemma

The Doctrinal Paradox

Three judges have to decide by majority whether a defendant broke a contract.

Legal doctrine dictates that if the following two premises are true:

(a) the defendant was contractually obliged not to do action X, and

(b) the defendant did action X,

then the conclusion is that the defendant broke his contract. Let's call this conclusion (c).

The judges get to decide which of the premises, (a) and (b), are true.

This is the simple conjunctive formula a∧b⟹c , and, taking one possible way the judges vote, we can construct a truth table for the same.

A
B
A∧B

Judge 1
True
True
True

Judge 2
True
False
False

Judge 3
False
True
False

Majority
True
True
False

In this permutation of votes, because the majority voted false for (c), the judges vote to pardon the defendant.

But here's the paradox: if the majority of the judges thought (a) was true and (b) was true, then it should have implied that the majority thought (c) was true.

You now have the unfortunate case where the majority voted true for all the precepts, but also rejected the conclusion.

This demonstrates collective inconsistency arising from individual consistency.

Generalizations

A similar paradox can be constructed for disjunctive propositions A∨B⟹C . It scales to arbitrary groups of people.

In fact, Pettit identifies the following minimal conditions:

a. there is a conclusion to be decided among a group of people
by reference to a conjunction (or disjunction) of independent or sepa

...
COVID-19 from a different angle
by jmh — 2020-05-04T17:58:02.100Z

Just trying to put things into a larger context for my own thinking here. Not much (if anything) new here. Purely USA centered.

Needless to say SARS-CoV-2 is THE event of 2020 and may well prove to be the event of the century (but a lot can happen in 100 years). At least that is probably what everyone would think at this point.

Probably a lot of wide CI bands here but we'll learn going forward.

What I wanted to look at was some guess at what we might see looking back on 2020 regarding mortality.

Currently the USA seems to have a mortality rate of about 8.34 per 1000.

Statista provide a graphic show daily deaths (7,969.7/day) for 2019 and a few days for COVID-19. I very crude calculation (basically Feb, Mar, Apr + 10 days) gets us about 690 COVID-19 deaths per day -- likely an under estimate as we're probably not peak death now.

So what happens to the expect mortality rate if we assume all COVID-19 deaths would not have occurred in the absence of the virus -- in other words, the person with a cause of death identified as COVIV-19 would have lived rather they having died during the year from some other cause.

Well, using the 690/day guess mortality would increase about 7.9%. Using the number for April 29 provided by Statista that goes up to about 12.6%. These mean the (very crude) expected mortality rate for 2020 would be between 9 and 9.3.

In one sense that doesn't seem like a lot. However, it would also represent the rates for the USA in the early 1970s; basically a 45 year set back. That does seem rather significant.

However, that is the worst case scenario as it assumed non of those COVID-19 deaths would have occurred due to some other cause. This seems a highly questionable assumption given the most at risk population.

I'm not sure how to really assess that question. I do think that some insights here are probably very useful in the context of reopening/relaxing the existing restrictions on social and economic activity.

Has anyone seen studies on funeral data that might offer some insight to allow calculation of the net new deaths resulting from the virus? I would be surprised the data is not there but suspect it is not in any consolidated DB.

So a prediction option for those who perhaps want to offer their thought. How much will the current mortality rate, 8.34 is what I've found but not sure if that is 2018 or 2019, increase due to SARS-C...
Insights from Euclid's 'Elements'
by TurnTrout — 2020-05-04T15:45:30.711Z

Presumably, I was taught geometry as a child. I do not remember.

Recently, I'd made my way halfway through a complex analysis textbook, only to find another which seemed more suitable and engaging. Unfortunately, the exposition was geometric. I knew something was wrong – I knew something had to change – when, asked to prove the similarity of two triangles, I got stuck on page 7.

I'd been reluctant to tackle geometry, and when authors reasoned geometrically, I'd find another way to understand. Can you blame me, when most geometric proofs look like this?

Distasteful. In a graph with n vertices, you'd need to commit O(n3) things to memory (e.g. triangles, angles) in order to read the proof without continually glancing at the illustration. In a normal equation with n variables, it's O(n).

Sometimes, we just need a little beauty to fall in love.

Welcome to Oliver Byrne's rendition of Euclid's Elements, digitized and freely available online.

Elements

Propoſitions are placed before a ſtudent, who though having a ſufficient underſtanding, is told juſt as much about them on entering at the very threſhold of the ſcience, as gives him a prepoſſeſſion moſt unfavourable to his future ſtudy of this delightful ſubject; or “the formalities and paraphernalia of rigour are ſo oſtentatiouſly put forward, as almoſt to hide the reality. Endleſs and perplexing repetitions, which do not confer greater exactitude on the reaſoning, render the demonſtrations involved and obſcure, and conceal from the view of the ſtudent the conſecution of evidence.”

Thus an averſion is created in the mind of the pupil, and a ſubject fo calculated to improve the reaſoning powers, and give the habit of cloſe thinking, is degraded by a dry and rigid courſe of inſtruction into an unintereſting exerciſe of the memory.

~ Oliver Byrne

Equality and Similarity

Old mathematical writing lacks modern precision. Euclid says that two triangles are "equal", without specifying what that means. It means that one triangle can be turned into another via an isometric transformation. That is, if you rotate, translate, and/or reflect triangle A, it turns into triangle B.

Similarity is a bit more lenient, because you can rescale as well:

My favorite characterization of similarities is:

As a map f:Rn→Rn, a similarity of ratio r takes the form f(x):=rAx+t, where A∈On(R)

...
What information on (or relevant to) modal immortality do you recommend?
by Mati_Roy — 2020-05-04T11:30:47.869Z

Which information should I consume if I want to better understand the implications (or whether there are any implications) of modal immortality?

Modal immortality combines two premises:

we live in a Big World: your brain configuration is instantiated many times in the multiverse

functionalist view of mind: you are your function, not a specific instantiation