The idea is interesting but in looking at methods and github I feel the tooling leaves me wanting. I mean you are trusting LLMs here to establish, vet, and detect your various thresholds that were then used to train the classifier. I'd rather see this sort of thing done deterministically with actual code vs lossy human english prompts and a dependency on token spend to a single third party (who will probably pull the underlying model used in what a few short years probably) to replicate the results or try and use different training data.
Is the goal of this to help AI pick corn kernels out of it's own shit for the purposes of slightly raising the bar on how sloppy the slop is? Or are you trying to trick AIs into eating a higher amount of their own shit than they already are? This feels like a factory built specifically to manufacture pollution.
The idea is interesting but in looking at methods and github I feel the tooling leaves me wanting. I mean you are trusting LLMs here to establish, vet, and detect your various thresholds that were then used to train the classifier. I'd rather see this sort of thing done deterministically with actual code vs lossy human english prompts and a dependency on token spend to a single third party (who will probably pull the underlying model used in what a few short years probably) to replicate the results or try and use different training data.
Is the goal of this to help AI pick corn kernels out of it's own shit for the purposes of slightly raising the bar on how sloppy the slop is? Or are you trying to trick AIs into eating a higher amount of their own shit than they already are? This feels like a factory built specifically to manufacture pollution.