6 ms·

> just repeatedly saying "keep going" to ChatGPT For posterity, this indeed works for most problems where an agent might give up. LLMs don't inherently know so

> just repeatedly saying "keep going" to ChatGPT For posterity, this indeed works for most problems where an agent might give up. LLMs don't inherently know something is impossible. The phrase I tend to use in my harder prompts to automate this with a sane loop breaker: > **REPEAT THIS PROCESS UNTIL CONVERGENCE AND YOU ARE OUT OF OPTIMIZATION IDEAS.** You have permission to keep iterating.

markfsharp 3mo ago
What I am thinking is the way you make it 'keep going' and when you have people of the calibre of Tao doing it I kept thinking how many breakthroughs is he going to cause the LLM to find with his targetted questions :D Amazing that we have the privilege of witnessing a true expert in such a way question the LLM.
- appplication 3mo ago
  Do notice he is quite Socratic, the approach works well for LLMs they love to please so you have to be careful in how you lead them.
MikhailTal 3mo ago
this is /goal in claude code/codex. also basically a slightly improved ralph loop
paxys 3mo ago
Aka /goal
Xcelerate 3mo ago
I’m a bit surprised OpenAI isn’t finding these big results far faster than the product’s user base. With no limits on runtime, access to dev models, custom tuning, and top talent, you’d think there’d be a constantly running internal project with the goal of solving famous math problems. And who knows, perhaps there is, but it would be interesting to compare the rate of success per unit “effort” of the internal mathematics work with that of the user base.
- pdpi 3mo ago
  "OpenAI's internal team solves famous maths problem" is technically impressive but dispiriting. Non-experts solving a problem by just throwing resources at it is kind of the worst possible optics for knowledge workers. It's just disempowering. "Famous mathematician uses ChatGPT to solve famous math problem" is equally technically impressive, but now you're telling those very same knowledge workers "that famous mathematician could've been you". It puts you in the driver's seat, and provides a clear path forward — subscribe, use our product, and reap the rewards.
  - tyre 3mo ago
    I don't think they care if it's disempowering. They'd gain more in market share by indicating that this is God than missing out on a few subscriptions from math theory people. My guess is they don't do this because they don't have time. They're all trying to build a company that makes them generationally wealthy before the music stops.
    - qsera 3mo ago
      Why would they want to do it when the people paying them would do the same for them?
  - rlt 3mo ago
    Then they should give grants of tokens to famous mathematicians. EDIT: oh, they do offer grants of $1000 of API credits to researchers https://help.openai.com/en/articles/10139500-researcher-access-program-faq https://help.openai.com/en/articles/10139500-researcher-acce...
    - eru 3mo ago
      > Then they should give grants of tokens to famous mathematicians. Depends. The headline 'some rando solved a famous problem with a consumer grade subscription' might be a really good way to sell these subscriptions. "Some already famous guy with special access solved a problem" might not be as inspiring.
xyzsparetimexyz 3mo ago
I have a pi extension that just runs the same prompt in a loop 25 times. I tried giving it a loop breaker but I found that it'd give up too readily. When the task is actually complete each iteration didn't do a lot of work so it was efficient enough. I suppose another way is to call out to a separate context to check if the task is complete?
- Normal_gaussian 3mo ago
  Commands like /goal and similar are the more complex version of this; you write a prompt like it was a singular iteration, it runs one iteration, then runs an "evaluator" to determine if the goal has been reached, then runs the prompt again with a little extra to make it go again - and so on. The evaluator is just an LLM with most of the result or context looking at the original goal and the state and answering the question "has the goal been met". The interesting part of this: while some leading implementations use the same LLM and context for the evaluator, some call out to a different context, some to a tuned LLM and different context; so which is better? many blog-scale benchmarks are calling it a toss-up that is highly dependent on the primary model.
  - eru 3mo ago
    For mathematical research, you can just run until you have a computer checkable Lean proof.
    - gf000 3mo ago
      Given that it was formalized correctly, which is far from trivial in many cases (Of course LLMs can help there, get it right etc, just a caveat that people have to keep in mind)
      - eru 3mo ago
        Agreed. But also formalising the statement of a theorem, or rather understanding the formalisation that the LLM suggested to you, is often a lot easier than understand the whole proof, especially if it's a formal proof.
rubyn00bie 3mo ago
I’ll have to try this exact phrasing. I had a lot of trouble with GPT 5.5 more or less completely ignoring similar prompts and instructions and entering a sort of “doom loop” or just consistently trying to prematurely end the chat. I would love any tips for other folks who have successfully used similar approaches.
- floam 3mo ago
  You have this problem after paying for Pro?
lattalayta 3mo ago
Maybe it's just me, but does anyone else feel goofy speaking to a computer this way?
- zx8080 3mo ago
  Just relax and welcome the nondeterministic world as a non-programmer. Also, forget what you were taught in Theory of Computation, no one needs it anymore. AI will do everything for you. /s Marketing for huge bucks sounds like this. You will own nothing and will be happy (that you are still alive). Probably.

markfsharp 3mo ago

What I am thinking is the way you make it 'keep going' and when you have people of the calibre of Tao doing it I kept thinking how many breakthroughs is he going to cause the LLM to find with his targetted questions :D Amazing that we have the privilege of witnessing a true expert in such a way question the LLM.

appplication 3mo ago
Do notice he is quite Socratic, the approach works well for LLMs they love to please so you have to be careful in how you lead them.

MikhailTal 3mo ago

this is /goal in claude code/codex. also basically a slightly improved ralph loop

paxys 3mo ago

Aka /goal

Xcelerate 3mo ago

I’m a bit surprised OpenAI isn’t finding these big results far faster than the product’s user base. With no limits on runtime, access to dev models, custom tuning, and top talent, you’d think there’d be a constantly running internal project with the goal of solving famous math problems. And who knows, perhaps there is, but it would be interesting to compare the rate of success per unit “effort” of the internal mathematics work with that of the user base.

pdpi 3mo ago
"OpenAI's internal team solves famous maths problem" is technically impressive but dispiriting. Non-experts solving a problem by just throwing resources at it is kind of the worst possible optics for knowledge workers. It's just disempowering. "Famous mathematician uses ChatGPT to solve famous math problem" is equally technically impressive, but now you're telling those very same knowledge workers "that famous mathematician could've been you". It puts you in the driver's seat, and provides a clear path forward — subscribe, use our product, and reap the rewards.
- tyre 3mo ago
  I don't think they care if it's disempowering. They'd gain more in market share by indicating that this is God than missing out on a few subscriptions from math theory people. My guess is they don't do this because they don't have time. They're all trying to build a company that makes them generationally wealthy before the music stops.
  - qsera 3mo ago
    Why would they want to do it when the people paying them would do the same for them?
- rlt 3mo ago
  Then they should give grants of tokens to famous mathematicians. EDIT: oh, they do offer grants of $1000 of API credits to researchers https://help.openai.com/en/articles/10139500-researcher-access-program-faq https://help.openai.com/en/articles/10139500-researcher-acce...
  - eru 3mo ago
    > Then they should give grants of tokens to famous mathematicians. Depends. The headline 'some rando solved a famous problem with a consumer grade subscription' might be a really good way to sell these subscriptions. "Some already famous guy with special access solved a problem" might not be as inspiring.

xyzsparetimexyz 3mo ago

I have a pi extension that just runs the same prompt in a loop 25 times. I tried giving it a loop breaker but I found that it'd give up too readily. When the task is actually complete each iteration didn't do a lot of work so it was efficient enough. I suppose another way is to call out to a separate context to check if the task is complete?

Normal_gaussian 3mo ago
Commands like /goal and similar are the more complex version of this; you write a prompt like it was a singular iteration, it runs one iteration, then runs an "evaluator" to determine if the goal has been reached, then runs the prompt again with a little extra to make it go again - and so on. The evaluator is just an LLM with most of the result or context looking at the original goal and the state and answering the question "has the goal been met". The interesting part of this: while some leading implementations use the same LLM and context for the evaluator, some call out to a different context, some to a tuned LLM and different context; so which is better? many blog-scale benchmarks are calling it a toss-up that is highly dependent on the primary model.
- eru 3mo ago
  For mathematical research, you can just run until you have a computer checkable Lean proof.
  - gf000 3mo ago
    Given that it was formalized correctly, which is far from trivial in many cases (Of course LLMs can help there, get it right etc, just a caveat that people have to keep in mind)
    - eru 3mo ago
      Agreed. But also formalising the statement of a theorem, or rather understanding the formalisation that the LLM suggested to you, is often a lot easier than understand the whole proof, especially if it's a formal proof.

rubyn00bie 3mo ago

I’ll have to try this exact phrasing. I had a lot of trouble with GPT 5.5 more or less completely ignoring similar prompts and instructions and entering a sort of “doom loop” or just consistently trying to prematurely end the chat. I would love any tips for other folks who have successfully used similar approaches.

floam 3mo ago
You have this problem after paying for Pro?

lattalayta 3mo ago

Maybe it's just me, but does anyone else feel goofy speaking to a computer this way?

zx8080 3mo ago
Just relax and welcome the nondeterministic world as a non-programmer. Also, forget what you were taught in Theory of Computation, no one needs it anymore. AI will do everything for you. /s Marketing for huge bucks sounds like this. You will own nothing and will be happy (that you are still alive). Probably.