It'll be really interesting when they run RL training on the harness self-improvement loop. I've tried using LLMs for harness engineering, but it often creates too much bloat that weighs things down in the end. Guessing it's just not something the models are tuned to do by default. Curious if anyone's tried using RL for harness engineering? I think we're still pretty far away from the optimal harness, especially when…
Prime Agent: A self-improving RLM agent
31–40 of 81 posts
Re: Prime Agent: A self-improving RLM agent
#32https://localroger.com/prime-intellect/mopiidx.html
I vouch for this story, personally. I love it. I consider it a classic among science fiction novellas. It does include some brutal sadomasochism with graphic torture, that's true, and that's why it isn't better known. If that part bothers you, which is fair, I would skim past it. The story overall is quite worth it
It's frustrating because apart from those (awful) aspects the story is quite thoughtful and compelling. I always recommend people skip the final chapter since the resulting existential cliffhanger is far better than the bizarre last-minute swerve into gratuitous sex abuse.
Re: Prime Agent: A self-improving RLM agent
#33Re: Prime Agent: A self-improving RLM agent
#34LLM-generated code that seemingly went without much review or design is always such an interesting dive into just how bloated you can make code. In this repository, multiple files are close to 10K LOC, one file contains a switch statement that has so many case statements it spans more than 1000 lines, and lots of other fun stuff. I guess it depends on the model you're trying to use, but seems most of them prefer smal…
Re: Prime Agent: A self-improving RLM agent
#35LLM-generated code that seemingly went without much review or design is always such an interesting dive into just how bloated you can make code. In this repository, multiple files are close to 10K LOC, one file contains a switch statement that has so many case statements it spans more than 1000 lines, and lots of other fun stuff. I guess it depends on the model you're trying to use, but seems most of them prefer smal…
- 21 lines of Go
- no 3rd party dependencies
https://github.com/smol-env/smoleasier to add and customize stuff when you start from a small base
think of it as your starter dough
Re: Prime Agent: A self-improving RLM agent
#36self improvement is not a new idea but at current economics its not feasible
Re: Prime Agent: A self-improving RLM agent
#37As models get stronger, huge harnesses may become less useful. An overly opinionated harness could even constrain the model’s reasoning instead of improving it.
Re: Prime Agent: A self-improving RLM agent
#38It'll be really interesting when they run RL training on the harness self-improvement loop. I've tried using LLMs for harness engineering, but it often creates too much bloat that weighs things down in the end. Guessing it's just not something the models are tuned to do by default. Curious if anyone's tried using RL for harness engineering? I think we're still pretty far away from the optimal harness, especially when…
Re: Prime Agent: A self-improving RLM agent
#39It'll be really interesting when they run RL training on the harness self-improvement loop. I've tried using LLMs for harness engineering, but it often creates too much bloat that weighs things down in the end. Guessing it's just not something the models are tuned to do by default. Curious if anyone's tried using RL for harness engineering? I think we're still pretty far away from the optimal harness, especially when…
What policy would you use?
Re: Prime Agent: A self-improving RLM agent
#40LLM-generated code that seemingly went without much review or design is always such an interesting dive into just how bloated you can make code. In this repository, multiple files are close to 10K LOC, one file contains a switch statement that has so many case statements it spans more than 1000 lines, and lots of other fun stuff. I guess it depends on the model you're trying to use, but seems most of them prefer smal…