Hello! I work at Lightcone and like LessWrong :-). I have made some confidentiality agreements I can’t leak much metadata about (like who they are with). I have made no non-disparagement agreements.
kave
Karma: 2,705
This seems unlikely to satisfy linearity, as A/B + C/D is not equal to (A+C)/(B+D)
I don’t feel particularly uncertain. This EA Forum comment and its parents inform my view quite a bit.
Maybe sometimes a team will die in the dungeon?
<details>blah blah</details>
So I did some super dumb modelling.
I was like: let’s assume that there aren’t interaction effects between the encounters either in the difficulty along a path or in the tendency to co-occur. And let’s assume position doesn’t matter. Let’s also assume that the adventurers choose the minimally difficult path, only moving across room edges.
To estimate the value of an encounter, let’s look at how the dungeons where it occurs in one of the two unavoidable locations (1 and 9) differ on average from the overall average.
Assuming ChatGPT did all the implementation correctly, this predictor never overestimates the score by much. Though it frequently, and sometimes egregiously, underestimates the score.
Anyway, using this model and this pathing assumption, we have DBN/OWH/NOC
We skip the goblins and put our fairly rubbish trap in the middle to stop adventurers picking and choosing which parts of the outside paths they take. The optimal path for the adventurers is DONOC, which has a predicted score of 30.29, which ChatGPT tells me is ~95th percentile.
I’d love to come at this with saner modelling (especially of adventurer behaviour), but I somewhat doubt I will.
I’m guessing encounter 4 (rather than encounter 6) follows encounter 3?
You can simulate a future by short-selling the underlying security and buying a bond with the revenue. You can simulate short-selling the same future by borrowing money (selling a bond) and using the money to buy the underlying security.
I think these are backwards. At the end of your simulated future, you end up with one less of the stock, but you have k extra cash. At the end of your simulated short sell, you end up with one extra of the stock and k less cash.
A neat stylised fact, if it’s true. It would be cool to see people checking it in more domains.
I appreciate that Ege included all of examples, theory, and predictions of the theory. I think there’s lots of room for criticism of this model, which it would be cool to see tried. In particular, as far as I understand the formalism, it doesn’t seem like it is obviously discussing the costs of the investments, as opposed to their returns.
But I still like this as a rule of thumb (open to revision).
I still think this post is cool. Ultimately, I don’t think the evidence presented here bares that strongly on the underlying question: “can humans get AIs to do their alignment homework?”. But I think it bares on it at all, and was conducted quickly and competently.
I would like to live in a world where lots of people gather lots of weak pieces of evidence on important questions.
Yep, if the first vote takes the score to ≤ 0, then the post will be dropped off the latest list. This is somewhat ameliorated by:
(a) a fair number of people browsing https://lesswrong.com/allPosts
(b) https://greaterwrong.com having chronological sort by default
(c) posts appearing in recent discussion in order that they’re posted (though I do wonder if we filter out negative karma posts from recent discussion)
I often play around with different karma / sorting mechanisms, and I do think it would be nice to have a more Bayesian approach that started with a stronger prior. My guess is the effect you’re talking about isn’t a big issue in practice, though probably worth a bit of my time to sample some negative karma posts.
I had a quick look in the database, and you do have some tag filters set, which could cause the behaviour you describe
Because it’s a number and a vector, you’re unlikely to see anyone (other than programmers) trying to use i as a variable.
I think it’s quite common to use i as index variable (for example, in a sum)
(edit: whoops, I see several people have mentioned this)
In this case sitting down with someone doing similar tasks but getting more use out of LMs would likely help.
I would contribute to a bounty for y’all to do this. I would like to know whether the slow progress is prompting-induced or not.
Click on the gear icon next to the feed selector
A quick question re: your list: do you have any tag filters set?
I think “unacceptable reputational costs” here basically means the conjunction of “Dustin doesn’t like the work” and “incurs reputational costs for Dustin”. Because of the first conjunct, I don’t think this suggestion would help Lightcone, sadly.
The “latest” tab works via the hacker news algorithm. Ruby has a footnote about it here. I think we set the “starting age” to 2 hours, and the power for the decay rate to 1.15.
mod note: this post used to say “LessWrong doesn’t seem to support the
<details>element, otherwise I would put this code block in it”.
We do now support it, so I’ve edited the post to put the code block in such an element
Robin Hanson is one of the intellectual fathers of LessWrong, and I’m very glad there’s a curated, organised list of some of his main themes.
He’s the first thinker I remember reading and thinking “what? that’s completely wrong”, who went on to have a big influence on my thought. Apparently I’m not an isolated case (paragraph 3 page 94).
Thanks, Arjun and Richard.
I do feel like it would be good to start with a more optimistic prior on new posts. Over the last year, the mean post karma was a little over 13, and the median was 5.