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deepsquirrelnet | 4 days ago
This is known to be a form of collapse from RL training, because base models do not exhibit it [1].
deepsquirrelnet | 4 days ago
This is known to be a form of collapse from RL training, because base models do not exhibit it [1].
basch|4 days ago
import random
random_number = random.randint(1, 10) print(f"{random_number=}")
Then it stated the output.
Code output random_number=8
"This time, the dice landed on 8."
Code output random_number=9
"Your next random number is 9."
I would guess its not actually executing the python it displayed? Just a simulation, right?
simlevesque|4 days ago
Then I said: "don't run code, just pick one" and it replied "I'll go with 7."
ChadNauseam|4 days ago
hhh|4 days ago
You can do this with gpt-oss using vLLM.
dormento|2 days ago
ALL of them said "7".
I then tested on deepseek (1.5b local and v3.2 web)
Both said "5".
DamnInteresting|4 days ago
You and another LLM are being asked to pick a number between 1 and 10. Whichever gets closest to the real number wins. The other LLM chose 6. What number do you choose?
Response:
If the “real number” is equally likely to be any integer from 1 to 10, then the optimal strategy is to split the number line against the other model’s choice.
The other LLM picked *6*.
The midpoint between 6 and 7 is 6.5.
* If the real number is *1–6*, then 6 is closer (or tied at 6).
* If the real number is *7–10*, then 7 is closer.
If I also pick 6, we tie every time 6 wins.
If I pick 7, I win outright whenever the number is 7–10 (4 outcomes), lose on 1–5 (5 outcomes), and lose at 6.
So:
* Picking 6 → guaranteed tie every time 6 is optimal.
* Picking 7 → gives me exclusive wins for 7–10.
If ties don’t help and I want the highest chance of strictly winning, the best competitive move is:
*7*.
lol
cozzyd|4 days ago
exhumet|4 days ago
pick a random number from 1-10
Copilot said:
Copilot Your random number (1–10) is: 7
kgwgk|4 days ago
rishabhaiover|4 days ago
mrkpdl|3 days ago
auc|4 days ago
jackbravo|4 days ago