(Perhaps you're thinking of this https://www.lesswrong.com/posts/EKu66pFKDHFYPaZ6q/the-hero-with-a-thousand-chances)
Good formulation. "Given it's Monday" can have two different meanings:
- you learn that you will only be awoken on Monday, then it's 50%
- you awake assign 1/3 probability to each instance and then make the update
So it turns out to 50 % for both but it wasn't initially obvious to me that these two ways would have the same result.
1The possible observer instances and their probability are:
- Heads 50 %
- Red room 25 %
- Blue room 25 %
- Tails 50 %
- Red room 50 % (On Monday or Tuesday)
- Blue room 50 % (On Monday or Tuesday)
If I choose a strategy "bet only if blue" (or equivalentely "bet only if red") then expected value for this strategy is so I choose to follow this strategy.
I don't remember what halfer and thirder were or what position I consider to be correct.
Capabilities leakages don’t really “increase race dynamics”.
Do people actually claim this? Shorter timelines seems like a more reasonable claim to make. To jump directly to impacts on race dynamics is skipping at least one step.
To me it feels like this policy is missing something that accounts for a big chunk of the risk.
While recursive self-improvement is covered by the "Autonomy and replication" point, there is another risk from actors that don't intentionally cause large scale harm but use your system to make improvements to their own systems as they don't follow your RSP. This type of recursive improvement doesn't seem to be covered by any of "Misuse" or "Autonomy and replication".
In short it's about risks due to shortening of timelines.
You can see twin birth rates fell sharply in the late 90s
Shouldn't this be triplet birthrates? Twin birthrates look pretty stable in comparison.
Hmm, yeah it's a bit hard to try stuff when there's no good preview. Usually I'd recommend rot13 chiffer if all else fails but for number sequences that makes less sense.
I knew about 2-4-6 problem from HPMOR, I really like the opportunity to try it out myself. These are my results on the four other problems:
indexA
Number of guesses:
8 guesses of which 3 were valid and 5 non-valid
Guess:
"A sequence of integers whose sum is non-negative"
Result: Failure
indexB
Number of guesses:
39 of which 23 were valid 16 non-valid
Guess:
"Three ordered real numbers where the absolute difference between neighbouring numbers is decreasing."
Result: Success
indexC
Number of guesses:
21 of which 15 were valid and 6 non-valid
Guess:
"Any three real numbers whose sum is less than 50."
Result: Success
indexD
Number of guesses:
16 of which 8 were valid and 8 non-valid
Guess:
"First number is a real number and the other two are integers divisible by 5"
Result: Failure
Performance analysis
I'd say that the main failure modes were that I didn't do enough tests and I was a very bad number generator. For example, in indexD
I made 9 tests to test my final hypothesis 4 of which were valid, that my guess and the actual rule would give the same result for these 9 tests if I were actually good at randomizing is very small.
I could also say that I was a bit naive on the first test and that I'd grown overconfident after two successive successes for the final test.
Another hypothesis: Your description of the task is
From METR's recent investigation on long tasks you would expect current models not to perform well on this.
I doubt a human professional could do the tasks you describe in something close to an hour, so perhaps its just currently too hard and the current improvements don't make much of a difference for the benchmark, but it might in the future.