This, linked at “Never.” in the OP.
abstractapplic
Karma: 1,501
an alliance socialist nations
an alliance of socialist nations
I didn’t like this post, but I did very much like the “insight porn” post it linked to. (Unfortunately LW doesn’t let you simultaneously downvote and strong-upvote a post, so consider my weak-upvote as a sum-of-vibes.)
If someone says ‘What’s for supper?’ a beginner will desperately try to think up something original. He will carefully evaluate dozens of options in his mind.
“Is this funny?” “Will this not reveal something weird about myself?”
It will take him ages to come up with something and eventually he will say something “fried mermaid”.
An improv pro would simply respond “fish”.
Taken—almost verbatim, without attribution—from Impro, by Keith Johnstone. (I don’t know whether LW would consider this plagiarism, or consider that to be bad.)
taking it out early and letting it sit
What I actually usually do is move it from the freezer to the refrigerator like 15min before I eat it, so the change in temperature is more predictable and evenly distributed (instead of some parts being melted while others stay too cold).
Is the point that it’s initially too hard to scoop?
That and it being too cold to properly enjoy the taste.
(The votes on my original comment make me think most people are less concerned about their dessert-that’s-supposed-to-be-cold being too cold. Typical-mind strikes again, I guess.)
I enjoyed the exercise, thanks!
You’re welcome, and thank you for playing.
(I wrote a custom loss function for the NN)
I’m curious how you defined that. (i.e. was it “gradient = x for rows where predicted>actual, gradient = −8x for rows where actual>predicted”, or something finickier?)
I think this is because
LightGBM and its kin are tools for creating decision forests, not decision trees. If you use standard hyperparameters while creating a single-tree model then they will under-train, resulting in the “predict in a way that’s correlated with reality but ridiculously conservative in its deviations from the average” behavior you see here. Setting num_boost_round (or whatever parameter decides the number of trees) to 200 or so should go some way to fixing that problem (while giving you the new problem of having produced an incomprehensible-to-humans black-box model which can only be evaluated by its output).
(I would have said this sooner but helping a player while the challenge was still running seemed like a bad look.)
I suspect a large (possibly not dominant) part of the ice cream effect is required preptime triggering myopic discounting. If eating ice cream at home, you need to take it out of the freezer at least a few minutes before eating it; this means that if your comfort food of choice is ice cream, you’ll only eat it if it seems like a legitimately good idea (‘a moment of weakness’ becomes ‘like 10min of weakness’, a higher bar for cravings to clear).
Note: I’ll be unavoidably and unexpectedly busy at the start of next week, and so will have to delay resolution of this challenge until either Tuesday or Wednesday (probably Tuesday). I’d apologise for the inconvenience but I’m pretty sure no-one minds.
Clarifications:
The Tyrant will weigh his Precious Beasts with the same level of diligence you would: no more, no less.
You can predict weights with as fine a granularity as you like; if you want to claim a turtle has a weight of 12.345678lb, that’s fine.
“Mu”: Japanese word roughly translateable as ‘absence’.
“Kami”: Japanese word roughly translateable as ‘god’.
“-sama”: Japanese honorific for referring to someone whose status/position is much higher than yours.
Mukami-sama, the God of Atheism
I found this disproportionately charming.
I think the commentary on the state of Givewell’s evidence—in particular, that worryingly large parts of it come down to “we called a mid-ranking employee once and they claimed they were doing X and we thought they had good vibes”—was good, correct, novel and important: strong upvote for that alone.
(I disagree that you should blame Givewell for that: they’re not hiding their flaws, and AFAICT the only people other than this author who are openly discussing Givewell’s limitations are Givewell themselves. Most of their alleged sins IMO come down to the way people insist on treating them, and the bizarre dearth of competitor/successor organisations aiming for “Givewell but >10x more rigorous/demanding”.)
I think almost everything else the author says is some combination of incoherent, incorrect, mean-spirited and fnordful. But in the marketplace of ideas, one bullseye is worth any number of missed shots.
Disrecommending Slay The Spire. While it’s a great game and it fits the rest of your criteria like a glove, it has very little hidden information in a practical sense (one of the more innovative things about it is that you can almost always see what the enemy will do next turn), and as such has basically no places where explore/exploit tradeoffs and VOI calculations would be relevant (I assume that this isn’t a negotiable part of what you’re asking for; if not, yeah I also recommend StS).
Tentative recommendation of Slipways; the VOI part isn’t as central as I suspect you’d like, but sending out probes sure does cost time and money you could use for settling planets and forming trade routes; and while it’s easy enough to survive to the end of your term, it gives what you’re asking for if you choose to define ‘victory’ as ‘get 5+ stars on Tough’.
The objective of rationality is to become right instead of wrong.
I think this is technically false, in a subtle but important way. If I gained [knowledge of whether every six-digit number is prime] in exchange for [knowledge of whether wandering out into open traffic is a good idea], I’d have gleaned a net 899999 bits of right-ness, but it still wouldn’t have been a worthwhile deal, or made me more rational in any practical sense. The missing gears are becoming right about important && relevant things, bothering to apply that knowledge, and—conditional on applying it at all—applying it well.
I think this project is good (Like, unusually good! It’s a step forward! I enjoyed it, and I commend you for your service to the Cause!), but I notice a lack of emphasis on changing actions vs changing minds, both in this post and in the videos I watched, and I want to make sure you’ve noticed that too.
(And yes, I do recognize the irony of me pointing out a true thing about [pointing out true things without having an associated practical outcome] without having an associated practical outcome. Still think it’s worth saying!)
Sorry about that, reality got in the way; also, ended up scrapping my concept for the next one and my backup concept for it; no idea when it’ll end up actually made (not necessarily this month), except that I plan to release on a Friday to do the standard “10 days with a choice of weekend” thing.
Damn! Mea culpa; I’ll edit the original post so anyone going through the archives won’t have the same problem.
Also, strong-upvoted for asking “so, with X years of hindsight, how did this pan out?” on an old post. More people should do that.
Before circumstances let me answer that question, the client got bought out by a bigger company, which was (and is) a lot more cagey about both hiring contractors and sharing internal details with outsiders; last I heard, the client’s absorbed remnants are still sometimes using my modelling approach, but I have no idea how much they’re using it, how much they’re relying on it, or to what extent it’s benefiting them.
Typos:
“Al gore”->”Al Gore”
“newpaper”->”newspaper”
“south park”->”South Park”
“scott alexander”->”Scott Alexander”
“a littler deeper”->”a little deeper”
“Ai”->”AI”
(. . . I’m now really curious as to why you keep decapitalizing names and proper nouns.)
Regarding the actual content of the post: appreciated, approved, and strong-upvoted. Thank you.