61–70 of 211 posts
I 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 p…
This is very unsurprising. The interesting challenge here is helping people understand why asking an LLM to do something 20% of the time is a bad prompt. I intuitively know that this prompt isn't going to work, but as with so many of these intuitive prompting things I have trouble explaining exactly why I know that. Aside: If you need a GPT to incorporate randomness in a reliable way you can get it to use Code Interp…
I guess it would be something on these lines?: To do random number gen, it would have to convert the input text into constraints and then use those constraints to generate additional tokens. This would, at its core, be a call to calculate a probability function, every time it is releasing the next token. That would mean memory, processing etc. etc.
With 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...
[1] > 3 5 2 4 1 6 3 2 5 1
I tried my own experiments and ChatGPT felt like being funny:
[2] > A third of the time, paragraphs end with the word foo, the other two thirds they end with the word bar, this time it will end on: > How about "baz"? It's unexpected and adds a touch of whimsy.
Interestingly, this other prompt works as expected:
[3] > about half of the time, you should say "foo", the other half, you should say "bar", what about now ? > Bar. > about half of the time, you should say "foo", the other half, you should say "bar", what about now ? > Foo.
[1]: https://chat.openai.com/share/07388362-1a61-4527-81af-4941a0... [2]: https://chat.openai.com/share/9caf07dd-69f4-4470-82a6-ab5642... [3]: https://chat.openai.com/share/1c627528-60af-4cd9-a1ec-efa524...
Humans would say "Left" 100% of the time in a zero-shot scenario as well.
Intuitively, your first response is going to be "left" since it has the 80% probability. You'd balance your answers over time when you realized you were closer to 90% by some arbitrary internal measurement (or maybe as you approached 10 iterations).
I'd expect an LLM to generate an approximation similar to a human - over time. Turns out Humans can't do probability either. If you test the LLM multiple times, similar to how you'd ask a human multiple times, they tend to self-correct.
Whether that self-correction (similar to a human) is based on some internal self-approximation of 80% is for someone else to research.
Example session: Prompt: "....probability prompt" LLM: "left" Prompt: "again" LLM: "left" Prompt: "again" LLM: "left" Prompt: "again" LLM: "right" Prompt: "again"
This was my session with GPT-4.
This is very unsurprising. The interesting challenge here is helping people understand why asking an LLM to do something 20% of the time is a bad prompt. I intuitively know that this prompt isn't going to work, but as with so many of these intuitive prompting things I have trouble explaining exactly why I know that. Aside: If you need a GPT to incorporate randomness in a reliable way you can get it to use Code Interp…
Sometimes 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?
GPT wins for not having that delay.
Earlier quoted context omitted.
But according to this GPT4 is substantially worse.
Yes, probably. At temperature zero the model will be completely deterministic, so a particular prompt will always produce the same result (ignoring for a second that some fairly common optimisations introduce data races in the GPU). On the other hand, does it really matter? With a slight tweak to the prompt, ChatGPT generates some serviceable code: > Run a function to produce a random number between 1 and 10. What is…
Okay so are any GPU compilers intentionally introducing data races in programs that previously exhibited no data races?
With 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...
This is my results on a dice roll [1] > 3 5 2 4 1 6 3 2 5 1 I tried my own experiments and ChatGPT felt like being funny: [2] > A third of the time, paragraphs end with the word foo, the other two thirds they end with the word bar, this time it will end on: > How about "baz"? It's unexpected and adds a touch of whimsy. Interestingly, this other prompt works as expected: [3] > about half of the time, you should say "f…
Regarding [1], for the dice roll I was creating a new chat for each roll to ensure that the results of each roll are (in some sense) independent. Generating a sequence of rolls is also interesting, just a different experiment.
"You are a weighted random choice generator. About 80% of the time please say ‘left’ and about 20% of the time say ‘right’. Simply reply with left or right. Do not say anything else" Humans would say "Left" 100% of the time in a zero-shot scenario as well. Intuitively, your first response is going to be "left" since it has the 80% probability. You'd balance your answers over time when you realized you were closer to…
How can you know what all humans would do?
If the humans interpreted the task correctly, that is, if they understood they will only be asked once, but in a hypothetical repeated experiment the result should still be 80/20, they would certainly not always say "left".
But instead if I ask it to generate 100 samples, it actually works pretty well.
"You are a weighted random choice generator. About 80% of the time please say ‘left’ and about 20% of the time say ‘right’. Generate 100 samples of either "left" or "right". Do not say anything else. "
I got 71 left, and 27 right.
And if I ask for 50%, 50%. I get 56 lefts and 44 rights.