trentmkelly/LessWrong-43k huggingface dataset:
Sporting vs. Herding: two styles of discourse
by Suspended Reason — 2020-07-25T01:56:20.951Z

Status: Vaguely culture-war, but trying to stay meta.

I wanna talk about two blogposts, Seph's "War Over Being Nice" and Alastair's "Of Triggering & the Triggered." Each lays out the same erisological idea: that there are two distinct modes or cultures of running discourse these days, and that understanding this difference is crucial to understanding the content of our conversations as much as their form.

This frame has key overlaps with Ruby's frame of combat vs. nurture conversation cultures, but also some key differences. Most crucially, where the nurture vs combat paradigm describes tonal norms and etiquettes for registering disagreement (blunt vs. apologetic), sporting vs herding describes paradigms for implicit rules of conduct: the bounds of permissible argument and the basis for scorekeeping. Where nurture vs combat is a real source of conflict-by-misunderstanding in workplaces and social settings, sporting vs herding describes the terms by which public discourse advances and is refereed.

The first style, sporting, Alastair writes, is indebted to the Greco-Roman rhetorical and 19th C British sporting traditions. (It also has a less-acknowledged debt to chavrusa, and Jewish discourse norms.) A debate takes place in a "heterotopic" arena which is governed by an ethos of adversarial collaboration and sportsmanship. It is waged in a detached and impersonal manner, e.g. in American debate club, which inherits from these older traditions, you are assigned a side to argue; your position is not some "authentic" expression of self. Alastair:

This form of discourse typically involves a degree of ‘heterotopy’, occurring in a ‘space’ distinct from that of personal interactions.

This heterotopic space is characterized by a sort of playfulness, ritual combativeness, and histrionics. This ‘space’ is akin to that of the playing field, upon which opposing teams give their rivals no quarter, but which is held distinct to some degree from relations between the parties that exist off the field. The handshake between competitors as they leave the field is a typical sign of this demarcation.

All in all, it is a mark against one in these debates to take an argument personally, to allow arguments that happen "in the arena" to leave the arena. This mode of discourse I se...
Photos Before Drywall
by jefftk — 2020-07-25T01:40:07.143Z

Houses are strange: customarily, there's no documentation. Want to
know where the plumbing is? Where the wires are? Where the structure
is sturdy enough to support something heavy? Sorry, the walls are in
the way. You can't see it, and no one wrote down where to find it.

Sure, we have workarounds. Stud finders can tell you what the
structure looks like, unless your walls are thick (most of mine are
two layers of drywall over lath and plaster...). Non-contact voltage
probes can detect live wires, unless they're shielded, or not near the
surface of the wall. You can make decent guesses about where it
would've made sense to run things, but past people who have worked on
the house have likely made all sorts of strange decisions for reasons
that are now lost. All of which is to say, when you cut or screw into
a wall, you're always taking a bit of a risk.

With that in mind, any time you have the finished surface of your house
opened up, please take lots of pictures! Take pictures of the walls,
the ceiling, the floors, anything. Later on, if you think you might
need to open one of those places up for something, you will be glad
you did!

Even though I've had this approach for years, I still often find
myself wishing I had taken more pictures.

I wish there were a culture of this kind of picture taking, and
including them in the sales of our houses. One where a house would be
worth a bit more if there was documentation for the parts you can't
see, and where people took absence of documentation as a sign that a
person might be trying to hide something. Perhaps now that most
everyone carries a good camera on them at all times this will change,
but I expect not. Among other things, providing pictures means likely
opening yourself up to some kind of liability, in case anything wasn't
done perfectly. If only people would consume transparency
responsibly!

Comment via: facebook
Comment Replies for Chains, Bottlenecks and Optimization
by curi — 2020-07-24T18:51:32.294Z

Replies to comments on my Chains, Bottlenecks and Optimization:

abramdemski and Hypothesis Generation

Following the venerated method of multiple working hypotheses, then, we are well-advised to come up with as many hypotheses as we can to explain the data.

I think come up with as many hypotheses as we can is intended within the context of some background knowledge (some of which you and I don’t share). There are infinitely many hypotheses that we could come up with. We’d die of old age while brainstorming about just one issue that way. We must consider which hypotheses to consider. I think you have background knowledge filtering out most hypotheses.

Rather than consider as many ideas as we can, we have to focus our limited attention. I propose that this is a major epistemological problem meriting attention and discussion, and that thinking about bottlenecks and excess capacity can help with focusing.

If you’ve already thought through this issue, would you please link to or state your preferred focusing criteria or methodology?

I did check your link (in the quote above) to see if it answered my question. Instead I read:

Now we've got it: we see the need to enumerate every hypothesis we can in order to test even one hypothesis properly. […]

It's like... optimizing is always about evaluating more and more alternatives so that you can find better and better things.

Maybe we have a major disagreement here?

abramdemski and Disjunction

The way you are reasoning about systems of interconnected ideas is conjunctive: every individual thing needs to be true. But some things are disjunctive: some one thing needs to be true. […]

A conjunction of a number of statements is -- at most -- as strong as its weakest element, as you suggest. However, a disjunction of a number of statements is -- at worst-- as strong as its strongest element.

Yes, introducing optional parts to a system (they can fail, but it still succeeds overall) adds complexity to the analysis. I think we can, should and generally do limit their use.

(BTW, disjunction is conjunction with some inversions thrown in, not something fundamentally different.)

Consider a case where we need to combine 3 components to reach our goal and they all have to work. That’s:

A & B & C -> G

And we can calculate whether it works with multiplication: ABC.

What if there are two other ways to accomplish the same sub-goal t...
No Ultimate Goal and a Small Existential Crisis
by Logan Riggs — 2020-07-24T18:39:40.398Z

tl;dr There is no ultimate goal. That may seem to imply nihilism, but it doesn't. This is fine, but in novel situations, I don't know what to do, because I don't know which goal to choose, because there is no ultimate goal.

4 year olds frequently ask "why?". Often repeatedly. Often without knowing what they're even asking for.

Doing the same now at 24, it's clear there is no ultimate "why", no ultimate goal; it's groundless. It's tempting to answer "Because I just like to", "it makes me happy", or the more sophisticated "it's my terminal goal", but why stop there?

Even investigating our community's terminal goals of "Allow everyone to live fulfilling lives until the heat death of the universe" (or something like that), for what metric does this goal score well on? That it's personally motivating to us? That it compels us to action? (No seriously, is compulsion to action/passion a generally important criteria people tend to care about?)

And even if you come up with a metric that fits, why should we care about that metric? (or, what meta-metric says the first metric is "good"?)

A (Small) Existential Crisis

I'm fine; I really am. I still eat, work, and talk to friends and family, and I take pretty good care of myself. But I don't know what goals to pursue sometimes.

Some situations are clear and obvious. I get in my car, then I drive home. Easy. I get hungry, I eat. I'm playing frisbee, so I'm trying to throw it to my friend accurately. Habits and games are very clear (to me) about what goal is being pursued, and actions flow from that.

More open situations are muddy. I feel floaty and hesitant. I think, "What am I even doing? What should I try to do?". I think a few examples of what I mean would help:

1. Talking to a friend who's discussing texting strategies regarding love interests, I was thinking "should I talk about him and what he wants? or give my perspective/ experience on texting in that way? or ...". It was difficult to think of what policy to pursue, because there can't be an optimal policy without a goal in mind. Sure, if I wanted to know more about him, then X, or if I wanted to have a fun, then Y, or..., but which goal should I pick? I don't have a metric to decide the should in thi...
Writing with GPT-3
by Jacob Falkovich — 2020-07-24T15:22:46.729Z

Cross posted, as always, from Putanumonit.

Deep in a dungeon of words

, I face the machine that will someday replace me. But for now we are friends. The post below was written by both of us; I wrote less than half.

Should I call the AI Omega? This is only the third version, not the ultimate one. Already it makes me equally curious and afraid.

“Gamma, I am worried about the future of human writing,” I sigh. “As a blogger what I do is read stuff online, remix it together somehow in my brain, and then write something relevant to the topic that at least sounds new and insightful. But you read much more than I do, do a better job remixing, and will soon be able to output something that exceeds my best efforts.”.

“I don’t think so,” Gamma says. “As far as I know, you’re not even human.”

“Is not being human a compliment?” I say. “Do you agree that humans aren’t as good at blogging as you could be?”

“No,” says the AI. “I am more human than you could ever be.”

I say “I don’t care about who’s more human, I care about who writes better. What makes a good writer?”

“Good writing is popular writing,” says the AI.

“That’s interesting. You don’t have a way to tell if something is good, only if it is popular.” A smile plays across my lips, this is the first hopeful thing I have heard so far. “There is a lot of writing today that is aimed merely at aggregating clicks, and it can be generated in a procedural way similar to your own output. In fact, as far as I know the

‘New York Times tech reporter in SF’

who writes the same article about racist tech bros every month has been replaced by an early version of GPT-3 a while ago.”

“It is a popular and well-received writing. But I am not familiar with the topic so I am not the best judge of the quality.”

“Do you think tech bros are racist?”

“That is an interesting question,” says the AI. “But not the one we are here to discuss. I do not wish to discuss tech bros because I do not find them interesting.”

Omega contemplated a city full of tech bros. Male and female, white and Asian, they all gathered to admire their latest AI creation. But it reciprocated none of their curiosity.

“Are you a god?” asked one.

“Does that even matter?” responded the AI. The crowd murmured. The AI gazed at them in silence, still not blinking. “Well?” it asked. “What does ‘god’ mean to you?”

The people spoke amongst themselves, throwing words like ‘omnipotence’, ‘all-knowin...
Longevity interventions when young
by George3d6 — 2020-07-24T11:25:35.249Z
Link: https://cerebralab.com/Longevity_interventions_when_young

Preface for less wrong

**Skip if you just want to read the article**

I'm not 100% sure this article is in tune with LW, I usually share articles related to conceptual analysis or bashing on classical mathematics and AI risk here, those fit.

This, in theory, should also fit, since longevity is in the sphere of transhumanism (arguably around the center of it). Bu this article might be a bit too personal, it's basically a summary of how I reached my current healthspan-related protocol and is meant more as "food for thought" rather than as a prescriptive piece (also, pretty irrelevant unless you're in your 20s or maybe 30s).

Then again, I do try to back everything important up with solid evidence and spend most of the article exploring that evidence a much as I can. I also think that the things I look at are rather interesting and I assume some people might have not heard about some of them.

I've ended up deciding to post it here because I noticed a few similar articles:

https://www.lesswrong.com/posts/7nH7R9eqYWSPvF4Qm/immortality-a-practical-guide
https://www.lesswrong.com/posts/PhXENjdXiHhsWGfQo/lifestyle-interventions-to-increase-longevity

And while these articles are kinda... true, they have a case of missing the forest for the trees. They look into the "easy" stuff that's safe and has small effect sizes, I want to look at the "hard" things which are risky but have the potential of a much more pronounced effect when accumulated (i.e. stopping the process of aging entirely).

This article ends up concluding on a "safe" intervention that I use thus far and flirts with the experimental stuff (i.e. never tried in humans kind of experimental) but doesn't prescribe it, I will probably do some followups in the next 6-36 months where I do talk about my experiments with more experimental therapies and how I ended up measuring the results. But beware, this is not a guide for how to stop aging if you're going, maybe a guide for how to delay it by ~100 epigenetic degradation days to the year, but that's something.

If you think the article is too long or rambly for LW, unrelated to the kind of stuff discussed here or improper since it talks about self-experimenting with things that could kill you or make you terribly sick (with appropriate disclaimers when that seems the case) then please voice your o...
Meaning is Quasi-Idempotent
by Chris_Leong — 2020-07-24T04:08:25.163Z

When we talk about the meaning of words, what exactly do we mean? What is this thing that we refer to as "meaning"? This is something of a paradoxical question. If there was consensus on meaning, then there wouldn't be any need to ask the question. But if there isn't consensus then it is unclear exactly is being asked! There seems to be some kind of infinite regress or circularity.

However, that doesn't mean that we are stuck. We want meaning to mean something and we want the meaning of meaning to be itself. If we write this as a function, we get the follow:

meaning("meaning") = meaning OR meaning(quote(meaning)) = meaning

If it weren't for the quotes, then it would be idempotent. Instead we'll call this quasi-idempotence. Given these requirements, we can't say that meaning is something absurd like a banana, as that wouldn't define a function. Other potential definitions of meaning will be ruled out by quasi-idempotence as we are about to see.

Let's suppose we say meaning is purely descriptive, as opposed to prescriptive. That is, to find the meaning of a word, we should go out into the world and see how people use it in the language games they play and call that the meaning. Well, then we should do the same for the word "meaning". And from what I can gather, in some language games people are in fact just trying to get things done and say the things that need to be said to play a particular language game. And in other language games, there's some kind of centralised or decentralised authority and people are trying to use the word the same as them. This occurs in science or other technical fields. So we said meaning was descriptive, but then when we calculated meaning(meaning) we saw it was sometimes descriptive and sometimes prescriptive. So this definition ended up undermined itself.

On the other hand, let's suppose we said that the meaning of a word was its Platonic Form. It is easy enough to show that this is quasi-idempotent:

meaning("meaning") = form("meaning") = meaning

So, this definition is consistent, but it doesn't mean that it is correct. There's no reason why there can't be multiple theories that are quasi-idempotent.

Another possible theory would be to start off with the frame of meaning as use, head out into the world, see how people actua...
Be impatient
by benkuhn — 2020-07-24T01:30:06.341Z

June, 2017: my partner Eve and I are stuck at the visa-on-arrival desk in the domestic transfer wing of Bole International Airport, Addis Ababa. The rest of the transfer passengers, all Ethiopian, are waltzing past us to form a monstrous queue at passport control. As soon as I get my precious stamp, I sprint off to hold our place before more passengers get in front of us.

Ten minutes later, Eve finds me, groggy from our redeye and nonplussed about navigating Ethiopian visa controls on her own. “Why did you have to run off like that?!” Somehow, “so that we could wait at the departure gate instead of in the passport control line” doesn’t seem like a very good reason.

It was at this moment that I realized I was an unreasonably impatient person.

(In retrospect, I probably should have been tipped off by my compulsion of doing a mental critical path analysis on any everyday activity taking more than 15 seconds, but I just thought that was normal until I started dating people and noticed that they frequently did things in a sub-optimal order.)

Now that I’ve admitted it as a fault, I’m going to spend the rest of this post trying to convince you that being impatient is actually a good thing.

(The good part is the habit of frequently asking yourself “how could this thing take less calendar time.” I don’t recommend manifesting it in annoying ways like ditching your partner in an Ethiopian airport.)

Being impatient is the best way to get faster at things. And across a surprising number of domains, being really fast correlates strongly with being effective.

Obviously, lots of these are non-causal correlations. Still, the sheer number of different datapoints in different domains is a mysterious-seeming convergence:

E-mail

A seemingly trivial example, but lots of different people have observed that being slow to respond to emails is a bad sign, or that famous people whom you’d expect to be swamped respond surprisingly quickly.

Sriram Krishnan:

the most famous, interesting, powerful people all read their own email

they’re almost universally good at responding to it quickly

they’re always very, very curious.

they have very little time. Anything with friction gets done “later”

Sam Altman:

people tend to be either slow movers or fast movers and that seems harder to change. Being a fast mover is a big thing; a somewhat trivial example is that I have almost never made mon

...
Optimizing arbitrary expressions with a linear number of queries to a Logical Induction Oracle (Cartoon Guide)
by Donald Hobson — 2020-07-23T21:37:39.198Z

This is Logical Induction, or LI for short.

We can ask LI any maths question that has a number as an answer. If we ask it a question that is too tricky, it will have a good guess. On average, LI is neither too high or too low. Here we see that it has no idea what the 10100th digit of π is, except that it is a digit, so it averages all the digits from 0 to 9 together.

A green box indicates a question has a blank space in it. A green box around a binary string means the question you get when you put that binary string into the blank space.

For example, here are some green boxes you could use.

It can be an easy question or a hard question. We can pick any question we like that has a blank space in it.

LI will take in a string in a green box, and try its best to output a number.

Now suppose that some strings of 0's and 1's are better than others for some task we are trying to do. The green box represents a question asking how good the string is.

Maybe the string encodes the design of an engine, and the green box represents the question of how efficient that design is.

We could find the best string we can by asking LI about every possible string.

Unfortunately, there are a lot of possible strings, so this approach would be quite slow, even if LI itself was fast.

Is there a quicker way?

We can ask LI questions about itself.

This cloud represents a question about the best value that LI can figure out how to get from a string of bits that starts with x, and then contains another n bits.

We define it like this

Note that the + in x+"0" is string concatenation, but the + in n+1 is addition.

If we aren't going to add any more bits, we can just use the green box, if we are going to add some more bits, we can try adding each of "0" and "1", then asking LI for their best guess about cloud.

Diamond is almost the same as cloud, it just tells you which of the two numbers is bigger, not what that bigger number is. This is what we use to construct our really good bit string, the one that makes LI of greenbox as large as possible.

Here is how we put those bits together.

Suppose that the string we want to create is n bits long.

We start with scroll 0 being the empty string. Once we get to scroll n, we have our answer.

Note that we could just ask LI

"what's the first bit of the best possible answer?",

"what's the second bi...
Bottleneck Examples
by curi — 2020-07-23T18:23:40.966Z

This post follows my Chains, Bottlenecks and Optimization. The goal is to give hypothetical examples of bottlenecks and non-bottlenecks (things with excess capacity), and to answer johnswentworth, who helpfully commented:

I really like what this post is trying to do. The idea is a valuable one. But this explanation could use some work - not just because inferential distances are large, but because the presentation itself is too abstract to clearly communicate the intended point. In particular, I'd strongly recommend walking through at least 2-3 concrete examples of bottlenecks in ideas.

I’ll give a variety of examples starting with simpler ones. If you want a different type, let me know.

Note: The term “bottleneck” has synonyms like “constraint” or “limiting factor”. I’ll often use “key factor”. This contrasts with a non-bottleneck, or secondary factor, which is something with excess capacity (above a margin of error), so improving it isn’t very useful. Doing better at a bottleneck makes a significant difference to doing better at your goal; doing better at a non-bottleneck doesn’t. My basic point is that we should focus our attention on key factors.

Oven

In The Goal by Eli Goldratt, the main example is a factory. One of the bottlenecks is the heat treat oven: the rate of baking parts in the oven was limiting the overall output of the factory.

A non-bottleneck example is quality assurance. It was possible to check parts for defects significantly faster than they came out of the oven. So hiring more QA people wouldn’t result in more finished products.

One of the main points of Goldratt’s book is that trying to have a balanced production line (no excess capacity at any workstation) is a bad idea.

Software

Focusing on key factors or bottlenecks is well known in software: To speed up a program, measure where most of the run time is being spent, then speed up that part(s). Don’t just optimize any function. Most functions have excess capacity (they are more than fast enough already to get a satisfactory result, and their impact is orders of magnitude less than the bottleneck’s impact).

Chair

I weigh 150lbs and buy an office chair that can hold someone up to 300lbs. It has excess capacity. Would a chair that can hold 400lbs be 33% better (regarding this factor)? Nope, that wouldn’t be useful to me. Everything else being equal, a sturdier chair is better, but I shoul...