trentmkelly/LessWrong-43k huggingface dataset:
Knowledge is not just digital abstraction layers
by Alex Flint — 2021-06-15T03:49:55.020Z

Knowledge is not just digital abstraction layers

Financial status: This is independent research. I welcome financial support to make further posts like this possible.

Epistemic status: This is in-progress thinking.

This post is part of a sequence on the accumulation of knowledge. Our goal is to articulate what it means for knowledge to accumulate within a physical system.

The challenge is this: given a closed physical system, if I point to a region and tell you that knowledge is accumulating in this region, how would you test my claim? What are the physical characteristics of the accumulation of knowledge? We do not take some agent as the fundamental starting point but instead take a mechanistic physical system as the starting point, and look for a definition of knowledge at the level of physics.

The previous post looked at mutual information between a region within a system and the remainder of the system as a definition of the accumulation of knowledge. This post will explore mutual information between the high- and low-level configurations of a digital abstraction layer.

A digital abstraction layer is a way of grouping the low-level configurations of a system together such that knowing which group the system’s current configuration is in allows you to predict which group the system’s next configuration will be in. A group of low-level configurations is called a high-level configuration. There are many ways to divide the low-level configurations of a system into groups, but most will not have this predictive property.

Here are three examples of digital abstraction layers:

Digital abstraction layers in computers

Information in contemporary computers is encoded as electrons in MOS memory cells. In these systems, the low-level configurations are all the ways that a set of electrons can be arranged within a memory cell. There are two high-level configurations corresponding to the "high" and "low" states of the memory cell. These high-level configurations correspond to groups of low-level configurations.

If we knew the high-level configuration of all the memory cells in a computer then we would know which instruction the computer would process next and could therefore predict what the next high-level configuration of the computer would be. We can make this prediction without knowing the specific low-level configuration of electrons in memory cells. Most other ways tha...
Anyone have experience with metabolic network modelling that would be willing to help me out?
by CraigMichael — 2021-06-14T22:40:33.647Z

In 2019 I had Megavitamin-B6 syndrome. I'm curious about the most common situation where people get it (chronic supplementation vs. acute overdose), and I have a hypothesis about how that may come about. Ideally, I'd like to see if it pans out in a model, and if it does maybe see if I can get some attention from interested biologists. But my background is in CS, not biology and I feel like I'd have a lot to learn. So anyone who would collaborate or just get me pointed in the right direction would be helpful.

In short it seems the chronic supplementation does factor in, but it also seems that plenty of people supplement for a very long time (more than 2 years) and never have an issue, sometimes at or above NOAEL or the even the LOAEL (100mg/day and 200mg/day in the US).

From many of the people I've talked to (and my own experience) it seems like something happens where someone takes a consistent dose of supplemental b6 for a year or more (at a reasonably high dose, say, 25mg/day or more) then at some point they take something else with b6 (or maybe are taking a poorly calibrated supplement that has more b6 than advertised) and then they start to develop toxicity, even if it the total dose is still below the "NOAEL."

So, my guess is that metabolic pathways adjust to receiving some daily dose of b6 and then become inflexible somehow (like a homeostatic thing) and can't ramp up the bandwidth/rate to process it in to 4-pyridoxic acid, the form where it's excreted.

Soo... I kind of want to see if that's plausible in a realistic model.
(Another) Using a Memory Palace to Memorize a Textbook
by Spencer_Green — 2021-06-14T22:12:26.697Z

Why do this? I was a year out of graduate school, but I could already feel my knowledge leaking away. This is a frustrating experience that will be familiar to any of you who've switched fields, if you are no longer working with your hard won knowledge/skills, they seem to vanish. The mind is a leaky sieve, without constant refilling it empties quickly.

Like, if you asked me to write down the Schrodinger equation (my PhD was in physics), right this instant, I'd have a 50/50 chance of getting it right (I just tried this, by the way, and I failed, now all I'm left with is a wrong equation and a slightly hollow feeling like what Scrooge McDuck might feel if he opened up his vault and all that was there were a few quarters. Canadian quarters.)

My experience with memory palaces were that:

They are a bitch to get right, you need to put in significant practice to get proficient, but...

They give more permanence to memories

This permanence was exactly what I wanted: I wanted to be able to remember things like the Schrodinger equation, even if I hadn't thought about it in years.

So, instead of memorizing the entire textbook, I narrowed my vision-- could I memorize the important equations and figures in a chapter. The goal would be to be able to deliver a lecture on the chapter without looking at written notes-- being able to move from important equation to important equation, and being sure of your derivations.

The usual format of a palace is: you take a place you are familiar with, and you mentally 'place' objects there, and then you walk through the palace in order, visiting the objects that help encode memories.

Approach 1: Picture-in-the-mind

I first tried just taking a 'snapshot' of an equation, and placing it on pedestals around my palace (which was just my dingy basement suite apartment). Unfortunately, this was an abject failure. My powers of visualization were not enough to create permanent 'mental' snapshots, they disappeared to dust when I wasn't focusing on them. I needed something more memorable...

Approach 2: Story-in-the-mind

For every equation, I tried creating a little visual 'story' for it. This was fairly free-form. Say I wanted to memorize y = x/2 +1, I might picture an "x" sliding down a divisor "/" into the waiting arms of a "2". This was easier for me to recall than a static picture of the equation, the visual story allowed me to 'move' through t...
Avoid News, Part 2: What the Stock Market Taught Me about News
by PeterMcCluskey — 2021-06-14T20:54:05.386Z
Link: http://www.bayesianinvestor.com/blog/index.php/2021/06/13/avoid-news-part-2-what-the-stock-market-taught-me-about-news/

It's been a decade since I blogged about the benefits of avoiding
news.

In that time I mostly followed the advice I gave. I kicked my addiction
to The Daily Show in late 2016 after it switched from ridiculing Trump
to portraying him as scary (probably part of a general trend for the
show to be less funny). I got more free time, and only missed the news a
little bit.

Then the pandemic hit.

I suddenly needed lots of new information. Corporate earnings releases
were too slow.

Wikipedia, Our World in Data, Metaculus, and some newly created
COVID-specific web sites partly filled that gap. But I still needed
more, and I mostly didn't manage to find anything that was faster or
more informative than the news media storyteller industry.

That at least correlated with higher than normal stress. I suspect that
paying attention to the storytellers partly caused the stress.

Distorted Salience

Do you want to focus your attention on problems that are most likely to
hurt you? If so, the storyteller industry is likely to distract you:

It's hard for a daily news source to avoid that effect. It has to focus
on recent, unusual events. When coal plants emit radioactive
smoke,
there's little occasion to write about it, because it's very routine,
and not at all a sign that someone did something wrong when people
initially adopted coal. Yet when a nuclear plant emits a similar amount
of radioactive material, that's a rare sign of an avoidable mistake.
It's unclear how the storyteller industry could avoid causing readers
to pay undue attention to the nuclear mistakes. But the natural
consequence is that readers will, at least subconsciously, treat that
attention as implying more harm.

Storytellers could reduce the biases from that distorted salience, by
sounding more worried in proportion to harm implied by their stories.
But that conflicts with the goal of making their stories entertaining,
and with the goal of maximizing the number of stories that readers
believe to be important. Alas, few readers are willing to give the
storytellers incentives to prioritize that kind of balance.

Preparing for the Pandemic

One of the bigger mistakes that I made in 2020 came from recalling that
Ebola, SARS, the 1976 swine flu outbreak, and various bird flu's all
generated a modest amount of news, but little harm in the US. Even the
older pandemics that did kill many Americans had little apparent effect
on...
Are there any existing open source human evolution models?
by ChristianKl — 2021-06-14T17:28:49.731Z

It's famously said that "nothing in biology makes sense except in the light of evolution". This suggest that evolutionary models provide a good way to gather knowledge about biology. If you expand the model to include memes that hunter gatheres pass around we might also gather valuable insights about human memetics.

If we would have such an open source model, whenever someone makes a evolutionary psychology argument you could ask them whether they can specify their argument in terms of the open source model and then run an experiment to validate it.

I don't find any existing open source project for this and don't know whether that's because googling for the term evolution is hard or whether it's due to such a project not existing. Does anybody have any pointers to projects?
An Introduction to Prediction Markets
by Annapurna — 2021-06-14T16:43:14.127Z

Link to original post.
Prediction Markets, as defined by

Wikipedia

, are exchange-traded markets created for the purpose of trading the outcome of events. If you have ever placed a bet on the Super Bowl or any other sporting event, you have participated in perhaps the most common prediction market today: sports betting.

I started getting interested in the idea of prediction markets for something other than sports betting last year, when I realized that

prediction markets and prediction models for the 2020 US presidential election had serious deviations

. While analyzing the potential positive expected value opportunity, I started wondering: Is there utility in this system that could be positive for society? I believe that in the near future prediction markets will have use cases that expand beyond the current use which is entertainment / speculation.

Prediction Markets Today

There are many types of prediction markets out there. Here are the ones that I am aware of / participate in.

Sports Betting

Sports betting has been around for decades;

today it has a market size of $203 Billion and it employs almost 200,000 people.

It’s utility is to bring additional entertainment to sports fans.

PredictIt.org / Iowa Electronic Markets

PredictIt

and

IEM

are markets that focus on predicting political and financial outcomes. Due to regulation, they are limited in nature. For example in PredictIt, The max you’re allowed to wager on an outcome is $850 USD, and the maximum number of participants in an outcome is 5,000. These limitations restrict to an extent the true price discovery of an outcome, making these markets somewhat inefficient. While IEM is a non profit with no fees, PredictIt charges both trading fees and withdrawal fees, adding to the inefficiency of the market.

Metaculus

Metaculus

is a technology platform that aggregates predictions on future outcomes of all types. The big downside of Metaculus is that it does not allow you to wager real money: it has a points system and leader boards in an attempt to encourage participants to make accurate predictions. However I believe that without skin in the game, the market will always be limited.

Augur

Augur

is a peer-to-peer, decentralized, no limit, open source platform running on the Ethereum network that allows users to create their own prediction markets. I have yet to use Augur because executing smart contracts on Ethereum is sti...
Walking to School
by jefftk — 2021-06-14T15:30:02.251Z

Last week Lily (7y) decided she wanted to start walking to school by
herself. It's not very far, she knows the way, and if anything
happens she has pretty good common sense. The main problem is cars:
while we've been practicing crossing the street, she's not good enough
at it do it completely on her own. We realized, though, that if she
went a slightly longer way she would only need to cross two
streets: one right by our house and another that has a crossing guard.

We went out and practiced: she walked the route with me staying well
behind. When she got to the second crossing I pretended to be the
crossing guard. She seemed ready to do it on her own.

The next morning, after getting herself ready,
I walked her across the first street and then she set off on her own.
I stayed, watching, in case she ran into issues. When she got to where
the crossing guard should be, she turned around and came running back
crying: "the crossing guard isn't there!" It turns out that the
crossing guard was just around the corner, leaning on their car. Once
Lily saw this, I turned around, and Lily took it from there.

The remaining mornings that week I continued hanging out and watching
until I could see the crossing guard helping her across the
street. She didn't have any more problems, and this week I'm no longer
waiting.

She is quite proud of herself, and I'm glad she's able to be a bit
more independent.

Comment via: facebook
Doomsday, Sampling Assumptions, and Bayes
by Yair Halberstadt — 2021-06-14T12:41:24.259Z

Overview/TLDR

We discuss the doomsday argument, and look at various approaches taken to analyze observation selection effects, namely SSA and SIA. We conclude that the SSA is unsatisfying, and show that the SIA is isomorphic to a version of bayesianism.

An entity undergoing a subjective experience should reason as if they are randomly selected from the distribution of all possible entities undergoing that exact same subjective experience.

We apply the principle to various scenarios, and conclude that whilst the SSA and SIA are wildly different in theory they are equivalent in practice assuming we live in a multiverse.

The Doomsday Argument

Are you gonna drop the bomb or not?

A doomsday argument attempts to predict the chance that humanity will survive a given length of time based purely on the number of people that have lived. A typical informal example might go like this.

If humanity survives thousands of years and spreads to the stars then trillions upon trillions of humans will have lived in total. Therefore if you were to pick a human at random, it would be an incredible coincidence if they happened to be among the first few billion humans to have lived. But you are essentially a human picked at random, and yet by an incredible coincidence you are among the first few billion humans!

If on the other hand humanity will die off in the next 100 years, and in total 100 billion humans will ever live, then it wouldn't be at all surprising to pick someone who happens to be around the 50 billion person mark.

Hence, it seems more likely that only a small number of humans will ever live than that a large number will love.

Now obviously we have lots of other sources of information we can use to predict how long humanity will survive, but the doomsday argument, if we accept it, will shift these probabilities downwards via a Bayesian update.

The doomsday argument seems crazy at first glance. Predicting the future is common, but that's usually based on extrapolating from information that's available now and determines the future - fast forwarding the universe in our minds. He're we're not doing that - instead we're saying that if in the future trillions of humans will live, that somehow affects the chances that we'll see what we'll see in the present. It would definitely be nice to put this Doomsday argument on a more formal footing so we can wrestle with it more directly.

Self Sa

...
A lateral way of thinking about Cause X: barely visible but potentially enormous categories of value
by Writer — 2021-06-14T11:44:04.628Z

EA Forum cross-post

Disclaimer: I don't know if this idea is an original way of thinking about Cause X. If it is not, I haven't seen it discussed much. In any case, it is not original outside of the Cause X discussion. Everything here is tentative, and the thing I'm pointing at might even be non-existent, but this line of thought might be promising.
Two concise and complementary ways to describe the search of Cause X might be:
1. Find X, where X is a barely visible but vast tragedy.
2. Find X, where X is a barely visible way to create a vast amount of value.

These are the main ideas relating to Cause X discussed in the introductory articles on effectivealtruism.org. The first idea relates to moral progress and asks if today there are tragedies that, by enlarge, current humans still don't recognize as such. One such past example is slavery. The second idea also considers the upside: There have been ways of creating huge amounts of value in the past, mainly thanks to scientific progress. What other ways to create huge value do we have today that we are not seeing?
Here, I want to introduce a third way to approach the question of Cause X:
3. Find X, where X is a barely visible but potentially vast new category of value.
Discovering a new vast category of value might be important in itself, but it's also important in relation to the two other questions: an answer might enable ways to prevent tragedies happening on the new axis of value discovered, or ways to create huge amounts of value on that axis.
This thought has occurred to me while reading the first chapter of The Precipice, by Toby Ord. He writes:

Our descendants could have eons to explore these heights, with new means of exploration. And it's not just wellbeing. Whatever you value—beauty, understanding, culture, consciousness, freedom, adventure, discovery, art—our descendants would be able to take these so much further, perhaps even discovering entirely new categories of value, completely unknown to us. Music we lack the ears to hear.

The obvious next question occurred to me: "what is this music that we lack the ears to hear?" and then the obvious next-next question occurred to me: "what are examples of new categories of value that arose in the past but weren't always there?" Much in the same way that now we see tragedies that weren't considered as such before, we now see value where perhaps we didn't ...
Coronavirus crash vs history
by bfinn — 2021-06-14T10:55:44.779Z

HOW has the coronavirus stock market crash compared with earlier ones? Is there a pattern?

A year ago I

looked at

all previous US and UK meltdowns throughout history. Now we can include the 2020 crash too:

Each coloured line shows a crash and its one-year aftermath, in the S&P 500 index (solid lines) and FTSE All-Share (dashed).[1]

The red lines show that last year stocks plummeted unusually far, particularly in the UK, where prices fell more than 30%. They then quickly rebounded, giving the US the strongest market recovery in history; and the UK, while not so stellar, fared better than average.

But earlier crashes show how easily prices could have kept falling. The spaghetti-like range of aftermaths illustrates that anything can happen after a crash, with no visible pattern.

However, there’s a striking bit of order lurking in the data. If we average all crashes over the last century[2], this is what we get:

The black line shows that just after crashing, on average prices neither fall further nor rebound, but are nearly flat, rising slowly for a year. Moreover, they closely match an average normal (non-crash) year, shown by the thick grey line, both in shape and slope.[3]

It’s remarkable that the wide variation and high volatility after a big fall produces no unusual behaviour overall. You’d have thought traders might either be spooked into selling unnecessarily, or hold out when they should cut their losses. But it seems overreactions from some are exactly cancelled by underreactions from others.[4] Crash aftermaths form no abnormal pattern, and the lack of one is strangely exact.

(That said, if we divide the crashes up by country or time period, they are inconsistent: the US has generally performed better than normal after a crash, the UK worse, and recent falls recovered faster than earlier ones. But with so few datapoints, those may well just be random variation; averaging all crashes together tells us the most.)

The black line fits a wider theory, the weak-form

Efficient-Market Hypothesis

, which says that you can’t predict future prices from past ones. Even after a crash, on average they should carry on just like normal. As indeed they do.

(P.S. Though off the right of these charts, more than a year after a crash, stocks

seem to rise faster than normal

, perhaps due to government stimulus measures.)

[1] Real total returns, treating a crash as a fall of at...
Which rationalists faced significant side-effects from COVID-19 vaccination?
by ChristianKl — 2021-06-14T09:39:29.218Z

While I want to believe the vaccines to be safe, Gendlin's litany tells me that it's more important that whether they actually are and the ability to change one's mind is a key feature of a rationalist. Another

thread

links to a discussion on the

Dark Horse Podcast

between Steve Kirsch, Robert Malone and Bret Weinstein about issues with vaccine safety. My prior for Steve Kirsch before that video was that he was one of the people in the world who thought most effectively about how to deal with COVID-19 in 2020. I hold that belief because of his project, the COVID-19 Early Treatment Fund.

The Fund describes it's

guiding principles

as:

The world has to take a multipronged approach to tackling COVID-19. We should work to identify effective repurposed drugs, validate experimental drugs, develop new drugs, test early treatments, test late treatments, try convalescent serums and invest in vaccines. We must do all of this in parallel to end the pandemic.

The guiding principles document goes into more detail about their principles and is well worth reading. When I first read it I thought, this is actually a sensible plan compared to what governments are doing. It seemed to me also better than what various EA groups managed to come up with. When someone who run a non-profit that tells the world that it's important to invest in vaccines in its guiding principles tells you about vaccine side-effects and who managed to put their money into a sane COVID-19 response, that's to be taken a lot more seriously than most other possible people who might say something about vaccine side-effects.

If the thesis is true, it's very important to know as soon as possible, because the thesis is about issues that are particular to the spike protein. If the thesis is true a step that's as simple as putting domains of the spike protein seperately into a vaccine or targeting a different protein for the third vaccination shoot might completely mitigate the side-effects.

Given that many rationalists are vaccinated and the thesis of Kirsch is that adverse effects to the vaccine are common, we would expect that if the thesis is true there are rationalists who face significant side-effects. While that still isn't a full proof of the thesis, it would increase our knowledge to know whether that's the case.

For a definition of significant side-effects where significant side-effects means effe...