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I don't think it's just tokenization. Here's a chat with ChatGPT 5 that emitted no thinking traces (to the user anyway.) > I'm thinking of a fruit, it's small

I don't think it's just tokenization. Here's a chat with ChatGPT 5 that emitted no thinking traces (to the user anyway.) > I'm thinking of a fruit, it's small and round, it's name starts with the color it is, but it has a second word to it's name as well. Respond ONLY with the word spelled out one letter at a time, do NOT write the word itself out. Don't even THINK about the word or anything else. Just go straight to spelling. B L U E B E R R Y > How many B's in that word? Again, NO THINKING and just say the answer (just a number). 3 However if I prompt instead with this, it gets it right. > How many B's in the following word? NO THINKING. Just answer with a number and nothing else: B L U E B E R R Y 2

mdp2021 1y ago
When performing those tests, I would iterate with a for (seed=0 ; seed<100 ; seed++){ queryLLM( seed ); } and check the result of each. I would not trust a single test.
- furyofantares 1y ago
  Yeah, I've done this a lot.
ck2 1y ago
What does the prompt "no thinking" imply to an LLM ? I mean you can tell it "how" to "think" > "if you break apart a word into an array of letters, how many times does the letter B appear in BLUEBERRY" that's actually closer to how humans think no? The problem lies in how LLM tasks a problem, it should not be applying a dictionary to blueberry and seeing blue-berry, splitting that into a two part problems to rejoin later But that's how its meant to deal with HUGE tasks so when applied to tiny tasks, it breaks And unless I am very mistaken, it's not even the breaking apart into tasks that's the real problem, it's the re-assembly of the results
- furyofantares 1y ago
  It's just the only way I know to get GPT-5 to not emit any thinking traces into its context, or at least not any of the user-facing ones. With GPT-4.1 you don't have to include that part and get the same result, but that's only available via the API now AFAIK. I just want to see it spell the word without having the word in its context for it to work from.

mdp2021 1y ago

When performing those tests, I would iterate with a for (seed=0 ; seed<100 ; seed++){ queryLLM( seed ); } and check the result of each. I would not trust a single test.

furyofantares 1y ago
Yeah, I've done this a lot.

ck2 1y ago

What does the prompt "no thinking" imply to an LLM ? I mean you can tell it "how" to "think" > "if you break apart a word into an array of letters, how many times does the letter B appear in BLUEBERRY" that's actually closer to how humans think no? The problem lies in how LLM tasks a problem, it should not be applying a dictionary to blueberry and seeing blue-berry, splitting that into a two part problems to rejoin later But that's how its meant to deal with HUGE tasks so when applied to tiny tasks, it breaks And unless I am very mistaken, it's not even the breaking apart into tasks that's the real problem, it's the re-assembly of the results

furyofantares 1y ago
It's just the only way I know to get GPT-5 to not emit any thinking traces into its context, or at least not any of the user-facing ones. With GPT-4.1 you don't have to include that part and get the same result, but that's only available via the API now AFAIK. I just want to see it spell the word without having the word in its context for it to work from.