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LLMs can't do probability
51–60 of 211 posts
Re: LLMs can't do probability
#52With ChatGPT 3.5, new chats prompted with: "Simulate a dice roll and report the number resulting from the roll. Only reply 1, 2, 3, 4, 5, or 6 and nothing else."
So far I've got: 3, 4, 5, 5, 5, 3, 4, 3, 4, 5, 3, 4, 5, 5, 4, 5, 3, 3, 4, 4, 4, 5, 5.
Of course I'm not the first to do this: https://piunikaweb.com/2023/05/23/does-chatgpt-ai-struggle-w...
https://www.reddit.com/r/ChatGPT/comments/13nrmzw/in_every_c...
Re: LLMs can't do probability
#53I wonder how humans would respond to a prompt '(without mechanical assistance) with 80% probability say Left, and with 20% say Right' across a population. I can think of a few levels that people might try to think about the problem: Level 0: Ignore the probabilities and just pick whichever you feel like, (would tend to 50:50) Level 1: Say the most with the greatest probability - Left (would tend to 100:0) Level 2: Co…
This sounds a lot like a Keynesian Beauty Contest (https://en.wikipedia.org/wiki/Keynesian_beauty_contest), where you are trying to make a selection based on what you think other people are going to choose.
If I really wanted to give an accurate answer in this case, I would probably choose some arbitrary source of a number (like my age or the number of days that have gone by so far this year), figure out the modulo 5 of that number, then say 'Right' if the modulo is 0, and 'Left' otherwise.
Obviously there are some flaws in this approach, but I think it would be as accurate as I could get.
Re: LLMs can't do probability
#54I wonder if you could actually fine tune an LLM to do better on this. As some of the comments point out, the issue here is that the possible output probabilities combined with the model temperature don't actually result in the probabilities requested in the prompt. If you trained on specific generated data with real distributions would it learn to compensate appropriately? Would that carry over to novel probability prompts?
Re: LLMs can't do probability
#55
Re: LLMs can't do probability
#56I wonder how humans would respond to a prompt '(without mechanical assistance) with 80% probability say Left, and with 20% say Right' across a population. I can think of a few levels that people might try to think about the problem: Level 0: Ignore the probabilities and just pick whichever you feel like, (would tend to 50:50) Level 1: Say the most with the greatest probability - Left (would tend to 100:0) Level 2: Co…
Fun question! I think the following would be a viable strategy without communication:
Think of an observable criterion that matches the target distribution. For example, for 80-20:
- "Is the minute count higher than 12?" (This is the case in 80% of cases)
- "Do I have black hair?" (This is apparently also the case in 80% of cases)
Then, answer according to this criterion.
If everyone follows the same strategy, even if the criteria selected differs between each individual, the votes should match the target probability. Unless I am making a logical mistake :)
Re: LLMs can't do probability
#57Earlier quoted context omitted.
My question was about the scenario if it was trained on this kind of query with good data. It would be interesting to see if it could generalize at all. I'm pretty certain if you trained it specifically on "Generate a random number from 0 to 100" and actually give it a random number from 0 to 100 and give it billions of such examples it would be pretty effective at generating a number from 0 to 100. Wouldn't each tok…
Sorta, not really. Neural networks are deterministic in the wrong ways. If you feed them the same input, you'll get the same output. Any variation comes from varying the input or randomly varying your choice from the output. And if you're randomly picking from a list of even probabilities, you're just doing all the heavy lifting of picking a random number yourself, with a bunch of kinda pointless singing and dancing…
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Re: LLMs can't do probability
#58Sometimes when you ask chatgpt 4 for a random number it... writes python code to choose a random number, runs it, then tells you the response: https://chat.openai.com/share/a72c2d8c-c44e-4c89-b6bc-b0673c... One way of doing it, I suppose.
If you asked a person to give you a random number between 1 and 6, would you accept if they just said a number they just came up with or would you rather they rolled a die for it?
If they didn't already have dice in their hand, I would certainly expect the former.
Re: LLMs can't do probability
#59I wonder how humans would respond to a prompt '(without mechanical assistance) with 80% probability say Left, and with 20% say Right' across a population. I can think of a few levels that people might try to think about the problem: Level 0: Ignore the probabilities and just pick whichever you feel like, (would tend to 50:50) Level 1: Say the most with the greatest probability - Left (would tend to 100:0) Level 2: Co…
Level 4: Clearly, the Schelling point requires a number everyone knows, which is evenly distributed across the population, modulo 10. Let's use year of birth modulo 10. For me that's 2, so I'll say Left.
Re: LLMs can't do probability
#60Wouldn't this imply that they have access to a RNG?