trentmkelly/LessWrong-43k huggingface dataset:
Prescriptions, Paradoxes, and Perversities
by Scott Alexander — 2015-04-30T04:52:19.000Z

[WARNING: I am not a pharmacologist. I am not a researcher. I am not a statistician. This is not medical advice. This is really weird and you should not take it too seriously until it has been confirmed]

I.

I’ve been playing around with data from Internet databases that aggregate patient reviews of medications.

Are these any good? I looked at four of the largest such databases – Drugs.com, WebMD, AskAPatient, and DrugLib – as well as psychiatry-specific site CrazyMeds – and took their data on twenty-three major antidepressants. Then I correlated them with one another to see if the five sites mostly agreed.

Correlations between Drugs.com, AskAPatient, and WebMD were generally large and positive (around 0.7). Correlations between CrazyMeds and DrugLib were generally small or negative. In retrospect this makes sense, because these two sites didn’t allow separation of ratings by condition, so for example Seroquel-for-depression was being mixed with Seroquel-for-schizophrenia.

So I threw out the two offending sites and kept Drugs.com, AskAPatient, and WebMD. I normalized all the data, then took the weighted average of all three sites. From this huge sample (the least-reviewed drug had 35 ratings, the most-reviewed drug 4,797) I obtained a unified opinion of patients’ favorite and least favorite antidepressants.

This doesn’t surprise me at all. Everyone secretly knows Nardil and Parnate (the two commonly-used drugs in the MAOI class) are excellent antidepressants1. Oh, nobody will prescribe them, because of the dynamic discussed here, but in their hearts they know it’s true.

Likewise, I feel pretty good to see that Serzone, which I recently defended, is number five. I’ve had terrible luck with Viibryd, and it just seems to make people taking it more annoying, which is not a listed side effect but which I swear has happened.

The table also matches the evidence from chemistry – drugs with similar molecular structure get similar ratings, as do drugs with similar function. This is, I think, a good list.

Which is too bad, because it makes the next part that much more terrifying.

II.

There is a sixth major Internet database of drug ratings. It is called RateRx, and it differs from the other five in an important way: it solicits ratings from doctors, not patients. It’s a great idea – if you trust your doctor t...
Meetup : Dublin
by Daniel_Molloy — 2015-04-29T17:45:21.782Z

Discussion article for the meetup : Dublin

WHEN:
09 May 2015 02:00:00PM (+0100)

WHERE:
Accents Coffee & Tea Lounge, Stephen Street Lower, Dublin

After a very successful HPMOR wrap party, we've decided to start a regular Dublin meetup group. This is the first meetup, so it'll be fairly unstructured. Expect introductions and ice-breaking, then a broad-ranging discussion on various Lesswrong topics and whatever else people are interested in, plus brainstorming of activities and more structured discussion ideas for future meetups.

I'll be there early with a Lesswrong sign.

For updates, join our mailing list: https://groups.google.com/forum/#!forum/dublin-rational

Discussion article for the meetup : Dublin
Tim Ferris Experiment
by casebash — 2015-04-29T14:27:57.854Z

So, I saw that the Tim Ferris Experiment was recently released. The concept of this show is that Tim spends 5 days trying to learn a new skill. I haven't seen any of the episodes (the iTunes link appears to be US only), but this seems to be exactly the kind of content that Less Wrong would be interested in.

A few questions:

1) Tim has already written about his accelerated learning techniques in the Four Hour Chef. Has anyone tried his techniques and were they effective for you?

2) Has anyone attempted accelerated learning based off another resource? How effective was it?
Shawn Mikula on Brain Preservation Protocols and Extensions
by oge — 2015-04-29T02:47:59.009Z

Recently published article in Nature Methods on a new protocol for preserving mouse brains that allows the neurons to be traced across the entire brain, something that wasn't possible before. This is exciting because in as little as 3 years, the method could be extended to larger mammals (like humans), and pave the way for better neuroscience or even brain uploads. From the abstract:

Here we describe a preparation, BROPA (brain-wide reduced-osmium staining with pyrogallol-mediated amplification), that results in the preservation and staining of ultrastructural details throughout the brain at a resolution necessary for tracing neuronal processes and identifying synaptic contacts between them. Using serial block-face electron microscopy (SBEM), we tested human annotator ability to follow neural ‘wires’ reliably and over long distances as well as the ability to detect synaptic contacts. Our results suggest that the BROPA method can produce a preparation suitable for the reconstruction of neural circuits spanning an entire mouse brain

http://blog.brainpreservation.org/2015/04/27/shawn-mikula-on-brain-preservation-protocols/
CFAR-run MIRI Summer Fellows program: July 7-26
by AnnaSalamon — 2015-04-28T19:04:27.403Z

CFAR will be running a three week summer program this July for MIRI, designed to increase participants' ability to do technical research into the superintelligence alignment problem.

The intent of the program is to boost participants as far as possible in four skills:

The CFAR “applied rationality” skillset, including both what is taught at our intro workshops, and more advanced material from our alumni workshops;

“Epistemic rationality as applied to the foundations of AI, and other philosophically tricky problems” -- i.e., the skillset taught in the core LW Sequences. (E.g.: reductionism; how to reason in contexts as confusing as anthropics without getting lost in words.)

The long-term impacts of AI, and strategies for intervening (e.g., the content discussed in Nick Bostrom’s book Superintelligence).

The basics of AI safety-relevant technical research. (Decision theory, anthropics, and similar; with folks trying their hand at doing actual research, and reflecting also on the cognitive habits involved.)

The program will be offered free to invited participants, and partial or full scholarships for travel expenses will be offered to those with exceptional financial need.

If you're interested (or possibly-interested), sign up for an admissions interview ASAP at this link (takes 2 minutes): http://rationality.org/miri-summer-fellows-2015/

Also, please forward this post, or the page itself, to anyone you think should come; the skills and talent that humanity brings to bear on the superintelligence alignment problem may determine our skill at navigating it, and sharing this opportunity with good potential contributors may be a high-leverage way to increase that talent.
Meetup : Canberra: Putting Induction Into Practice
by DanielFilan — 2015-04-28T14:40:55.876Z

Discussion article for the meetup : Canberra: Putting Induction Into Practice

WHEN:
09 May 2015 06:00:00PM (+1000)

WHERE:
108 North Road, Acton, ACT

At our last meetup, we talked about a mathematical theory of how to do induction well. At this meetup, we will get some practice at actually doing it by playing (a facsimile of) Zendo! In small groups, one player will be the 'Master', and the rest will be their 'Students'. Students will have playing cards, and the Master will have some criterion to pick out 'good' arrangements of playing cards. The 'Students' have to try to guess the Master's criterion by putting out arrangements of playing cards, and asking the Master if they are 'good'. If a Student guesses the Master's criterion, they win!
As always, vegan snacks will be provided.

General meetup info:

If you use Facebook, please join our group.

Structured meetups are (usually) held on the second Saturday and fourth Friday of each month from 6 pm until late in the CSIT building, room N101.

Discussion article for the meetup : Canberra: Putting Induction Into Practice
High impact from low impact, continued
by Stuart_Armstrong — 2015-04-28T13:00:51.000Z

The idea of splitting a high impact task between two low-impact AIs has on critical flaw. AI X is aiming for low impact, conditional on ¬Y (the other AI not being turned on, or not outputting a message, or something similar). "Outputting the right coordinates" is one way that X can accomplish its goal. However, there is another way it can do it: "create a robot that will output the right coordinates if ¬Y, and [do something else] if Y."

That's a dangerous situation to be in, especially if we have a more general situation that the "laser aiming at the asteroid". But note that if X does create such a robot, and if ¬Y is actually true, then that robot must be low impact and not dangerous, since that's X's programming. Since X cannot predict all the situations the robot would encounter, the robot is probably generically "safe" and low impact.

Therefore, if the robot behaves the same way under Y and ¬Y, we're good.

How could we achieve that? Well, we could adapt my idea from "restrictions that are hard to hack". If a hypothetical superintelligent AI C observed the output stream from X, could it deduce that Y vs ¬Y was something important in it? If C knew that X was conditioning on ¬Z, but didn't know Z=Y, could it deduce that? That seems like a restriction that we could program into X, as a third component of its utility (the first being the "do what we want" component, the second being the "have a reduced impact conditional on ¬Z" one).

And if we have a "safe" robot, given ¬Y, and the programming of that robot does not (explicitly or implicitly) mention Y or its features, we probably have a safe robot.

The idea still needs to be developed and some of the holes patched, but I feel it has potential.
High impact from low impact, continued
by Stuart_Armstrong — 2015-04-28T12:58:44.341Z

A putative new idea for AI control; index here.

The idea of splitting a high impact task between two low-impact AIs has on critical flaw. AI X is aiming for low impact, conditional on ¬Y (the other AI not being turned on, or not outputting a message, or something similar). "Outputting the right coordinates" is one way that X can accomplish its goal. However, there is another way it can do it: "create a robot that will output the right coordinates if ¬Y, and [do something else] if Y."

That's a dangerous situation to be in, especially if we have a more general situation that the "laser aiming at the asteroid". But note that if X does create such a robot, and if ¬Y is actually true, then that robot must be low impact and not dangerous, since that's X's programming. Since X cannot predict all the situations the robot would encounter, the robot is probably generically "safe" and low impact.

Therefore, if the robot behaves the same way under Y and ¬Y, we're good.

How could we achieve that? Well, we could adapt my idea from "restrictions that are hard to hack". If a hypothetical superintelligent AI C observed the output stream from X, could it deduce that Y vs ¬Y was something important in it? If C knew that X was conditioning on ¬Z, but didn't know Z=Y, could it deduce that? That seems like a restriction that we could program into X, as a third component of its utility (the first being the "do what we want" component, the second being the "have a reduced impact conditional on ¬Z" one).

And if we have a "safe" robot, given ¬Y, and the programming of that robot does not (explicitly or implicitly) mention Y or its features, we probably have a safe robot.

The idea still needs to be developed and some of the holes patched, but I feel it has potential.
Learning a concept using only positive examples
by jessicata — 2015-04-28T03:57:24.000Z

Summary: it is sometimes desirable to create systems that avoid edge cases. This post presents a partial solution to this problem, which works by comparing the system's behavior to a "natural" distribution.

Introduction

Learning a concept from both positive and negative examples is a well-studied
problem in machine learning. However, if we learn a concept from training data
(say, using human judgments as the gold standard),
then the learned concept might not generalize well; it could differ from human
judgments on any number of edge cases. There is a sense in which these edge cases
are "outside the domain" of the training data; that is, the training data seems
to naturally define some domain where we can make judgments
confidently, with edge cases lying outside this domain.

Therefore, we will be ignoring 2-class classification and defining a form
of "classification" that uses only positive examples. We could use this
"classifier" to positively identify regions that do not contain edge cases.

As a running example, consider a system that is supposed to create burritos using
a nanofactory.
It will have as training data some training burrito configuration files, which
specify the exact arrangement of atoms in each training burrito. The task will
be to create burritos that are similar to the training burritos, without necessarily being
identical to them.

Suppose this system has access to a hypercomputer. Then it could use a variant
of Solomonoff induction to learn a generative model over burrito configuration
files, b. With some caveats, this may learn the distribution of training burritos.

We could instruct the system to sample a burrito configuration file from this distribution,
and then print it out using the nanofactory. If the induced distribution
reflects the distribution of training burritos, then this should not be significantly
different from creating a new training burrito in the usual fashion.

What if the nanofactory can't print all possible burrito configurations (or it can, but
we only want to print high-quality burritos)? Suppose
we have some feasible set f of printable burrito configurations. We may be tempted
to sample from the distribution b|f, which assigns probabilities proportional to b
for burrito configurations in f and probability 0 to other burrito configurations.
However, this may be dangerous! For example, if only burritos containi

...
Meetup : Null event
by MelbourneLW — 2015-04-27T22:48:35.516Z

Discussion article for the meetup : Null event

WHEN:
11 January 2016 04:00:16PM (+1100)

WHERE:
West Antarctica

PLEASE IGNORE

It wasn't possible to correct the date on this event (was marked for April 2016 instead of 2015), so I'm trying to get rid of it this way.

Discussion article for the meetup : Null event
Experience of typical mind fallacy.
by Elo — 2015-04-27T18:39:42.403Z

following on from:

http://lesswrong.com/lw/dr/generalizing_from_one_example/

I am quite sure in my experience that at some point between the ages of 10-15 I concluded that; "no the rest of the world does not think like me, I think in an unusual way".

This idea disagrees with the typical mind fallacy (where people outwardly generalise to think everyone else has similar minds to their own).

I suspect I started with a typical mind model of the world but at some point it broke badly enough that I re-modelled on "I just think differently to most others".

I wanted to start a new discussion; rather than continuing on from one in 2009;

Where do your experiences lie in relation to typical minds?
Meetup : Raleigh RTLW Meetup - Predictions Followup, Zendo
by curiousepic — 2015-04-27T17:00:15.162Z

Discussion article for the meetup : Raleigh RTLW Meetup - Predictions Followup, Zendo

WHEN:
30 April 2015 07:00:00PM (-0400)

WHERE:
2109 Avent Ferry Rd #142, Raleigh, NC 27606

Let's have some discussion and exercises following up on last meetup's topic of everyday predictions. No worries if you didn't attend last time.

I'd like for everyone to make at least one testable, non-subjective prediction about this meetup itself, which we will then take a look at near the end. We'll also play some Zendo, and perhaps practice predictions and/or calibration using it!

We will meet at 7:00 at Cup a Joe in Mission Valley and may subsequently convene to Ba-Da Wings. See you there, and don't forget your pre-commitments!

Discussion article for the meetup : Raleigh RTLW Meetup - Predictions Followup, Zendo
Nick Bostrom's TED talk on Superintelligence is now online
by chaosmage — 2015-04-27T15:15:21.481Z

http://www.ted.com/talks/nick_bostrom_what_happens_when_our_computers_get_smarter_than_we_are

Artificial intelligence is getting smarter by leaps and bounds — within this century, research suggests, a computer AI could be as "smart" as a human being. And then, says Nick Bostrom, it will overtake us: "Machine intelligence is the last invention that humanity will ever need to make." A philosopher and technologist, Bostrom asks us to think hard about the world we're building right now, driven by thinking machines. Will our smart machines help to preserve humanity and our values — or will they have values of their own?

I realize this might go into a post in a media thread, rather than its own topic, but it seems big enough, and likely-to-prompt-discussion enough, to have its own thread.

I liked the talk, although it was less polished than TED talks often are. What was missing I think was any indication of how to solve the problem. He could be seen as just an ivory tower philosopher speculating on something that might be a problem one day, because apart from mentioning in the beginning that he works with mathematicians and IT guys, he really does not give an impression that this problem is already being actively worked on.
The stamp collector
by So8res — 2015-04-27T03:00:00.000Z
Link: https://mindingourway.com/the-stamp-collector/

Once upon a time, a group of naïve philosophers found a robot that collected trinkets. Well, more specifically, the robot seemed to collect stamps: if you presented this robot with a choice between various trinkets, it would always choose the option that led towards it having as many stamps as possible in its inventory. It ignored dice, bottle caps, aluminum cans, sticks, twigs, and so on, except insofar as it predicted they could be traded for stamps in the next turn or two. So, of course, the philosophers started calling it the "stamp collector."

Then, one day, the philosophers discovered computers, and deduced out that the robot was merely a software program running on a processor inside the robot's head. The program was too complicated for them to understand, but they did manage to deduce that the robot only had a few sensors (on its eyes and inside its inventory) that it was using to model the world.

One of the philosophers grew confused, and said, "Hey wait a sec, this thing can't be a stamp collector after all. If the robot is only building a model of the world in its head, then it can't be optimizing for its real inventory, because it has no access to its real inventory. It can only ever act according to a model of the world that it reconstructs inside its head!"

"Ah, yes, I see," another philosopher answered. "We did it a disservice by naming it a stamp collector. The robot does not have true access to the world, obviously, as it is only seeing the world through sensors and building a model in its head. Therefore, it must not actually be maximizing the number of stamps in its inventory. That would be impossible, because its inventory is outside of its head. Rather, it must be maximizing its internal stamp counter inside its head."

So the naïve philosophers nodded, pleased with this, and then they stopped wondering how the stamp collector worked.

There are a number of flaws in this reasoning. First of all, these naïve philosophers have made the homunculus error. The robot's program may not have "true access" to how many stamps were in its inventory (whatever that means), but it also didn't have "true access" to its internal stamp counter.

The robot is not occupied by some homunculus that has dominion over the innards but not the outards! The abstract program doesn't have "true" access to the register holding the stamp counter and "fake" access to the inven...
Open Thread, Apr. 27 - May 3, 2015
by Gondolinian — 2015-04-27T00:18:11.426Z

If it's worth saying, but not worth its own post (even in Discussion), then it goes here.

Notes for future OT posters:

1. Please add the 'open_thread' tag.

2. Check if there is an active Open Thread before posting a new one. (Immediately before; refresh the list-of-threads page before posting.)

3. Open Threads should be posted in Discussion, and not Main.

4. Open Threads should start on Monday, and end on Sunday.
Less Wrong Study Hall - Year Two
by Error — 2015-04-26T17:59:33.847Z

The Less Wrong Study Hall is still going, two years after its creation. I'm trying to make last year's survey an annual thing, so I did it again. We've been growing slowly but steadily. According to this year's census, we have 60+ users. By comparison to Yvain's Less Wrong survey, that gives us just under 4% penetration.

For anyone who isn't familiar with the Hall: We're a collection of (mostly) Less Wrong users who gather to work in a video chat room. The idea is not so much to collaborate on projects, as to have visible companions in the effort to get things done. There's a thorough description here, and its description of our efforts is still more or less accurate. The room is hosted by Tinychat, and we work according to the Pomodoro Technique.

I'll briefly reiterate our social norms for anyone who doesn't want to read the whole prior post:

Say hello and ask for the current time when entering, if needed.

Don’t talk during pomos.

Do talk during breaks.

Talking about work is encouraged.

Bragging about work is encouraged.

Don’t turn your mic on.

But do turn your camera or desktop view on if you want

The tinychat room is here, and the Complice frontend is here. Either will work. The password is 'lw'. The password exists not as a security measure but as a roadblock for random walk-ins.

Aside from our growing population, the most significant change of the last year was malcolmocean succesfully integrating the room into his Complice application. This doesn't give us control of the room, but does give us (by which I mean him) the ability to bolt on features, including a unified pomodoro timer with audible dings. It's achieved fixation remarkably quickly; most of our participants now use it.

Last year's top suggestion box item was better enforcement of pomodoros; break overruns were extremely common. The public timer has rapidly and all-but-completely solved the problem. No technological enforcement was necessary, which surprised me. There was some concern that users who weren't inclined to use Complice would be left in the dark, but that doesn't seem to have happened. I would like to emphasize that if you are joining via Tinychat rather than Complice, it is still okay to explicitly ask for the time. We know that not everyone can see the timer, and we won't bite you.

We do have some challenges to deal with in the upcoming year. Most of them involve our co...