trentmkelly/LessWrong-43k huggingface dataset:
Simplifying Board Games
by jefftk — 2020-05-31T14:10:02.578Z

A few years ago I wrote about how I'd been playing a

simplified version of Carcassonne
with Lily. We stopped for a while, but recently we've played
simplified versions of

Ticket
to Ride,

Race for the
Galaxy,

Guillotine,
and

Settlers of
Catan. My general approach here is to find a core piece of the
game that will be fun on its own, and then add to it as Lily wants
more complexity.

While the particulars of the rules don't really matter very much, some
examples to explain how we're approaching it:

In Race for the Galaxy, the core mechanic is playing cards. In our
first game you would play cards, both settlements and developments, by
discarding other cards. Something with a "2" in the corner meant
discarding two cards. At the end of each turn you would draw back up
to five, which is nothing like the original game. The winner was the
person who ended up having played cards with the greatest cost.

When she wanted to make it more complicated, we started using the
victory point value of cards instead of their cost, and each time you
played a card you read the number in the hexagonal box and placed that
many victory point chips on it. Later we'll probably be able to stop
putting the chips on it, but having physical chips to manipulate and
count makes scoring easier.

In Ticket to Ride, the core mechanic is drawing cards and playing
trains. We each got a route card of the same point value, found our
cities on the map, with the card for reference, and marked them so we
wouldn't lose them. The first time we played, on your turn you placed
a single train car. The goal was to be the first one to connect your
two cities. This went very quickly, and just taught placement and a
bit of pathfinding.

For the second game I introduced train cards. Now if you wanted to
place a train you needed to pick up an appropriately colored card.
You didn't build up a hand, just picked and placed right away. They
did need to be the right color. If no card worked for you, you could
use your turn to replace the available cards with five new ones. We
played that only kids could pick up locomotives (wild cards), which
Lily got very excited about.

In Guillotine the core mechanic is collecting nobles. Our first time
playing we would just each collect the noble at the head of the line
every time, which was not very exciting but taught the mechanic. ...
Forecasting Newsletter: May 2020.
by NunoSempere — 2020-05-31T12:35:58.063Z

A forecasting digest with a focus on experimental forecasting. The newsletter itself is experimental, but there will be at least four more iterations. Feel free to use this post as a forecasting open thread; feedback is welcome.

You can sign up here.

You can also see this post on the EA Forum here

And the post is archived here

Index

Prediction Markets & Forecasting platforms.

Augur.

Coronavirus Information Markets.

CSET: Foretell.

Epidemic forecasting (c.o.i).

Foretold. (c.o.i).

/(Good Judgement?[^]*)|(Superforecast(ing|er))/gi

Metaculus.

PredictIt & Election Betting Odds.

Replication Markets.

In the News.

Grab bag.

Negative examples.

Long Content.

Prediction Markets & Forecasting platforms.

Augur: augur.net

Augur is a decentralized prediction market. Here is a fine piece of reporting outlining how it operates and the road ahead.

Coronavirus Information Markets: coronainformationmarkets.com

For those who want to put their money where their mouth is, this is a prediction market for coronavirus related information.

Making forecasts is tricky, so would-be-bettors might be better off pooling their forecasts together with a technical friend. As of the end of this month, the total trading volume of active markets sits at $26k+ (upwards from $8k last month), and some questions have been resolved already.

Further, according to their FAQ, participation from the US is illegal: "Due to the US position on information markets, US citizens and residents, wherever located, and anyone physically present in the USA may not participate in accordance with our Terms." Nonetheless, one might take the position that the US legal framework on information markets is so dumb as to be illegitimate.

CSET: Foretell

The Center for Security and Emerging Technology is looking for (unpaid, volunteer) forecasters to predict the future to better inform policy decisions. The idea would be that as emerging technologies pose diverse challenges, forecasters and forecasting methodologies with a good track record might be a valuable source of insight and advice to policymakers.

One can sign-up on their webpage. CSET was previously funded by the Open Philanthropy Project; the grant writeup contains some more information.

Epidemic Forecasting: epidemicforecasting.org (c.o.i)

As part of their efforts, the Epidemic Forecasting group had a judgemental forecasting team that worked on a v...
Will the many protests throughout the USA prove to be good test cases for reopening?
by jmh — 2020-05-31T12:15:31.400Z

[Speculating on a hypothetical.]

Looking at some of the images in the news regarding the ongoing protests sparked by the latest death of a black person while in the hands of the police seem to suggest social distancing is not really a primary concern for the protestors or the police.

As we look at the COVID-19 statistics in the next few weeks one might expect to see a second wave originating from that event. If a second wave is not very pronounced or noticeable, what might be the implication for public health policies? A strong update on prior or some other type of response?

Not asking what the response should be but more for predictions about what they will be, given the assumption of any resulting second wave occurrence.
Anyone recommend a video course on the theory of computation?
by Eli Tyre — 2020-05-30T19:52:43.579Z

Hey all,

I'm noticing that I want to know more about the basics of theoretical computer science, subjects like the theory of computation.

This is a leisure activity for me (at least for the time being), as opposed to something that I'm going to put substantial study into. I'd like to more or less passively watch a series of videos on the topic, to get a first pass understanding of the conceptual vocabulary and how those concepts relate to each other.

There are lots of courses / series on YouTube, and I don't know which to pick. I'm currently planning to just sample from a few of them, and see which I like best, but I thought I would ask here if there was a series that folks found particularly informative, or clear, or well taught, or otherwise good.

If there was one that you liked, please share!

I'm also glad to hear suggestions about better forums or alternative methods for answering questions like this one. For that matter, I'm curious if people have heuristics for making assessments like these.

Thanks!

Eli
How to (not) do a literature review
by Katarina Slama — 2020-05-30T00:11:12.097Z
Link: https://katarinaslama.github.io/2020/05/17/OpenAI-blog5/

This is cross-posted from my personal blog, where I share thoughts on my work and learning process in the OpenAI Scholars Program. I thank Ruby Bloom for suggesting that I share the post here as well.

OpenAI Scholars: Fifth Steps - The Dreaded Literature Review

The OpenAI Scholars , and I among them, recently completed a project proposal for the second half of our program. Having recently finished a PhD, writing a proposal and doing the requisite literature review, should be second nature. But literature reviews were always my least favorite part of research.

Fortunately, I'm in good company. In a previous life as a young aspiring neuroscientist, I once attended a talk by David Hubel . When asked for tips about how to "keep up with the literature", I recall that Professor Hubel responded: "You know, at some point in your career, you have to decide if you want to be a consumer - or a producer." He elaborated that he would only really look at papers that his advisor or his long-term collaborator Torsten Wiesel pointed him to.

There's good reason to want to avoid literature reviews. To begin with, the problem formulation is intractable: "Know everything." If you've spent any amount of time around academics, it will soon become apparent that this is exactly what they expect from you. "Oh you haven't read that paper?" The assumption is that you have read every paper there is.

Of course, this is an impossible task. Last time I visited Google Scholar and searched on a few project-relevant terms, I encountered 105,000 papers. It takes me a full day to read and satisfactorily understand an academic paper. So reading 105 kilo-papers would take me 288 years. And I had hoped to also do some coding work during the Scholars program.

Now suppose you want to cook a ghormeh sabzi . To do so, you buy yourself a can of ghormeh sabzi mix , and follow the instructions on the can. There are about five steps. However, as ubiquitous an activity as the literature review is (in academic circles anyway), I am yet to encounter an honest and pragmatic recipe for how they are to be cooked. I really wish there was one.

I for one am a great fan of Thich Nhat Hanh's how-to books. Some of my favorite titles among Nhat Hanh's books are: "How to sit", "How to relax", and - perhaps the best one - "How to see...
Shutting Down RegularlyScheduled
by jefftk — 2020-05-29T22:50:04.573Z

Three years ago I created
RegularlyScheduled as a way to make it easier to coordinate events
that happened on a repeating schedule. My main motivation was to make
it easier to get together with my friends from college, but I thought
maybe it would be useful to other people as well. Several years later,
however, it doesn't seem to have been as widely useful as I'd hoped
and it's more work to maintain than I'm looking for, so I'm shutting
it down.

There are 44 registered users, most of them friends of mine, and two
events. One event is a 1st Mondays and 3rd Thursdays dinner series I
was hosting, and the other is a regular pre-dance dinner a friend
organized. That neither is running right now makes it an easier time
to make a change like this!

If there was no maintenance required I'd be happy to run it
indefinitely, but it has a database, sends email, handles
authentication, and receives commands from strangers over the
internet. Perhaps it's more surprising that it hasn't required more
work!

I've written to everyone who's signed up, given event owners a list of
their subscribed guests, and encourage them to move to other systems,
like Google calendar. While I don't know of anything that provides
exactly the same features, it's not different enough or popular enough
for me to be willing to keep it running.

I've redirected the domain name to this post for now, and I'm not
planning to renew it. It will expire in ~3y, but if anyone wants it
let me know.
Covid-19 5/29: Dumb Reopening
by Zvi — 2020-05-29T21:00:01.069Z

Previous Editions: Covid 5/14: Limbo Under, Covid-19 5/7: Fighting Limbo, Covid-19 4/30: Stuck in Limbo, My Covid-19 Thinking: 4/23 pre-Cuomo Data

I remember when people on Twitter had constant reminders that today was, indeed, only Wednesday, or whatever day it happened to be. Time moved that slowly.

Time has sped up again. It has been two weeks since my last Covid-19 post, and that’s because I didn’t feel there was much new to say. There aren’t new developments. People are acting the way you’d expect them to act, the numbers are continuing on their trend lines.

The question is, will it be good enough? Did we win? Will there be a second wave soon as we open things up?

So far, the news is mostly good. But not great. Let’s see the numbers.

The Numbers

New positive tests by region:

Date
WEST
MIDWEST
SOUTH
NE ex-NY
NY

Mar 19-Mar 25
5744
6293
7933
8354
28429

Mar 26-Apr 1
15684
20337
24224
34391
52901

Apr 2-8
19455
31148
39618
56772
65604

Apr 9-15
16291
29267
35570
61921
64463

Apr 16-22
20065
34130
33932
64669
43437

Apr 23-29
21873
42343
33773
62189
42475

Apr 30-May 6
23424
49205
37880
51693
24287

May 7-May 13
22615
43256
37591
40209
16683

May 14-May 20
22913
42762
40343
39273
13709

May 21-May 27
24104
39418
42977
28336
10595

Deaths by region:

WEST
MIDWEST
SOUTH
NE ex-NY
NY

Mar 19-Mar 25
116
67
111
84
203

Mar 26-Apr 1
347
477
502
454
1340

Apr 2-8
639
1335
1215
1783
3939

Apr 9-15
895
2106
1472
3261
5345

Apr 16-22
1008
2369
1730
5183
3994

Apr 23-29
1135
2500
1684
4285
2810

Apr 30-May 6
991
2413
1737
5349
2007

May 7-May 13
1044
2344
1679
4014
~1500

May 14-May 20
1091
2071
1448
3712
998

May 21-May 27
823
1694
1276
2430
721

Positive test rates:

Date
USA tests
Positive %
NY tests
Positive %

Mar 19-Mar 25
347,577
16.2%
88,882
32.0%

Mar 26-Apr 1
728,474
20.2%
117,401
45.1%

Apr 2-8
1,064,225
19.8%
144,273
45.5%

Apr 9-15
1,026,741
20.4%
160,859
40.1%

Apr 16-22
1,235,393
16.1%
143,970
30.2%

Apr 23-29
1,552,560
13.0%
202,499
21.0%

Apr 30-May 6
1,759,548
10.6%
183,446
13.2%

May 7-May 13
2,153,748
7.5%
202,980
8.2%

May 14-May 20
2,643,333
6.0%
246,929
5.6%

May 21-May 27
2,584,265
5.7%
305,708
3.5%

New York continues to improve. Some time in this past week, I believe New York became a safer than average place in terms of forward looking infection risk, with yesterday’s positive rate d...
An overview of 11 proposals for building safe advanced AI
by evhub — 2020-05-29T20:38:02.060Z

This is the blog post version of the paper by the same name. Special thanks to Kate Woolverton, Paul Christiano, Rohin Shah, Alex Turner, William Saunders, Beth Barnes, Abram Demski, Scott Garrabrant, Sam Eisenstat, and Tsvi Benson-Tilsen for providing helpful comments and feedback on this post and the talk that preceded it.

This post is a collection of 11 different proposals for building safe advanced AI under the current machine learning paradigm. There's a lot of literature out there laying out various different approaches such as amplification, debate, or recursive reward modeling, but a lot of that literature focuses primarily on outer alignment at the expense of inner alignment and doesn't provide direct comparisons between approaches. The goal of this post is to help solve that problem by providing a single collection of 11 different proposals for building safe advanced AI—each including both inner and outer alignment components. That being said, not only does this post not cover all existing proposals, I strongly expect that there will be lots of additional new proposals to come in the future. Nevertheless, I think it is quite useful to at least take a broad look at what we have now and compare and contrast some of the current leading candidates.

It is important for me to note before I begin that the way I describe the 11 approaches presented here is not meant to be an accurate representation of how anyone else would represent them. Rather, you should treat all the approaches I describe here as my version of that approach rather than any sort of canonical version that their various creators/proponents would endorse.

Furthermore, this post only includes approaches that intend to directly build advanced AI systems via machine learning. Thus, this post doesn't include other possible approaches for solving the broader AI existential risk problem such as:

finding a fundamentally different way of approaching AI than the current machine learning paradigm that makes it easier to build safe advanced AI,

developing some advanced technology that produces a decisive strategic advantage without using advanced AI, or

achieving global coordination around not building advanced AI via (for example) a persuasive demonstration that any advanced AI is likely to be unsafe.

For each of the proposals that I consider, I will try to evaluate them on the following four basic c...
GPT-3: a disappointing paper
by nostalgebraist — 2020-05-29T19:06:27.589Z

[Note: I wrote this post in late May 2020, immediately after the GPT-3 paper was released.]

This post is a compilation of two posts I recently made on tumblr.

For context: I have been an enthusiastic user of GPT-2, and have written a lot about it and transformer models more generally. My other writing on this topic includes human psycholinguists: a critical appraisal and "the transformer ... "explained?" See also my tumblr bot, which uses GPT-2 as a core component.

Part 1

argumate said:

@nostalgebraist, give us the goss on how GPT-3 compares with GPT-2!

I haven’t read the paper super carefully yet, but I am pretty sure of the following:

1.1: On GPT-3's mundanity

“GPT-3″ is just a bigger GPT-2. In other words, it’s a straightforward generalization of the “just make the transformers bigger” approach that has been popular across multiple research groups since GPT-2.

This excerpt captures this pretty clearly:

Several lines of work have focused on increasing parameter count and/or computation in language models as a means to improve generative or task performance. […] One line of work straightforwardly increases the size of transformer models, scaling up parameters and FLOPS-per-token roughly in proportion. Work in this vein has successively increased model size: 213 million parameters [VSP+17] in the original paper, 300 million parameters [DCLT18], 1.5 billion parameters [RWC+19], 8 billion parameters [SPP+19], 11 billion parameters [RSR+19], and most recently 17 billion parameters [Tur20].

The first two papers mentioned here are the original transformer for machine translation (VSP+17) and BERT (DCLT18). The parameter count doesn’t actually increase that much between those two.

The third one (RWC+19) is GPT-2. The parameter counts jumps up 5x there. Arguably the point of the GPT-2 paper was “it sounds dumb and too easy, but amazing things happen if you just make a transformer bigger” – and this “GPT-3″ paper is making the same point with bigger numbers.

"GPT-3" is a transformer with 175 billion parameters. It's another big jump in the number, but the underlying architecture hasn't changed much.

In one way this is a fair thing to call “GPT-3″: it’s another step in the new biggenin...
Should we stop using the term 'Rationalist'?
by B Jacobs — 2020-05-29T15:11:18.329Z

This might be an unpopular opinion, but I really dislike the term 'rationalist' for four reasons:

1) It makes you sound self-aggrandizing. The term gives the impression that you think you are already rational and therefore smarter-than-thou.

2) It's already a term used to describe a different group. In fact, that way of using the term is not only way older, but also way more common.

3) The people it describes are not only interested in 'rationality', but also talk at length about things like AI, Bayes-theorem, Utilitarianism, etc.

4) We don't even agree on what it means anymore. I'm not sure we ever did, but post-rationality has put the nail in the coffin.

I've toyed with introducing the term 'Aspirationalist', but maybe we should just split it into 'Lesswrongers', 'SSCers', 'Effective Altruist' etc?
On the construction of the self
by Kaj_Sotala — 2020-05-29T13:04:30.071Z

This is the fifth post of the "a non-mystical explanation of the three characteristics of existence" series.

On the construction of the self

In his essay

The Self as a Center of Narrative Gravity

, Daniel Dennett offers the thought experiment of a robot that moves around the world. The robot also happens to have a module writing a novel about someone named Gilbert. When we look at the story the novel-writing module is writing, we notice that its events bear a striking similarity to what the rest of the robot is doing:

If you hit the robot with a baseball bat, very shortly thereafter the story of Gilbert includes his being hit with a baseball bat by somebody who looks like you. Every now and then the robot gets locked in the closet and then says "Help me!" Help whom? Well, help Gilbert, presumably. But who is Gilbert? Is Gilbert the robot, or merely the fictional self created by the robot? If we go and help the robot out of the closet, it sends us a note: "Thank you. Love, Gilbert." At this point we will be unable to ignore the fact that the fictional career of the fictional Gilbert bears an interesting resemblance to the "career" of this mere robot moving through the world. We can still maintain that the robot's brain, the robot's computer, really knows nothing about the world; it's not a self. It's just a clanky computer. It doesn't know what it's doing. It doesn't even know that it's creating a fictional character. (The same is just as true of your brain; it doesn't know what it's doing either.) Nevertheless, the patterns in the behavior that is being controlled by the computer are interpretable, by us, as accreting biography--telling the narrative of a self.

As Dennett suggests, something similar seems to be going on in the brain. Whenever you are awake, there is a constant distributed decision-making process going on, where different subsystems swap in and out of control. While you are eating breakfast, subsystem #42 might be running things, and while you are having an argument with your spouse, subsystem #1138 may be driving your behavior. As this takes place, a special subsystem that we might call the “self-narrative subsystem” creates a story of how all of these actions were taken by “the self”, and writes that story into consciousness.

The ...
Our Need for Need
by  — 2020-05-29T11:12:40.284Z

[I wrote this in 2017, well before I had a LessWrong account. The style isn't necessarily what I would have chosen if I'd known I was going to share it here, but I think the topic might be of some interest anyway, so I'm reposting it with light edits. Originally on Grand, Unified, Crazy.]

It is a trite, well-established truth that people like being useful. But there’s more to it than that, or rather, there’s also a stronger version of that claim. People do like being useful, but useful is a very broad term. Stocking shelves at a Walmart is useful, in that it’s a thing with a use, which needs to be done. And it’s true that some people may in fact actively like a job stocking shelves at a Walmart. But on the whole, it’s not something most people would consider particularly enjoyable, and it’s certainly not something that most people would consider "fulfilling".

Let us then upgrade the word “useful” to the word “needed”: people like to be needed. While stocking shelves at a Walmart is useful, the person doing it is fundamentally replaceable. There are millions of others around the world perfectly capable of doing the same job, and there are probably thousands of them just within the immediate town or city. If our fictional stocker were to suddenly vanish one day, management would have no trouble hiring somebody else to fill their shoes. The world would go on. Walmart would survive.

Now this is all well and good, but I would argue that there is an even stronger version of this claim: people don’t just like to be needed, people actively need to be needed. Over a decade ago, Paul Graham wrote an essay called Why Nerds are Unpopular; it’s a long essay with a number of different points, but there is one thread running through it that in my opinion has gotten far too little attention: “[Teenagers’] craziness is the craziness of the idle everywhere”.

The important thing to note about this (and Graham does so, in a roundabout sort of way) is that teenagers in a modern western high school are not exactly idle. They have class, and homework, and soccer practice or band practice or chess club; they play games and listen to music and do all the sort of things that teenagers do. They just don’t have a purpose. They are literally unneeded,...