Asking the chat models to have self-disccusion and use/simulate metacognition really seems to help. Play around with it. Often times I am deep in a chat and I learn from its mistakes, it kinda learns from my mistakes and feedback. It is all about working with and not against. Because at this time LLMs are just feed forward neural networks trained on supercomputer clusters. We really don’t even know what they are capable of fully because it is so hard to quantify, especially when you don’t really know what exactly has been learned.
Q-learning in language is also an interesting methodology I’ve been playing with. With an imagine generator for example though, you can just add (Q-learning quality) and you may get more interesting and quality results. Which itself is very interesting to me.
Asking the chat models to have self-disccusion and use/simulate metacognition really seems to help. Play around with it. Often times I am deep in a chat and I learn from its mistakes, it kinda learns from my mistakes and feedback. It is all about working with and not against. Because at this time LLMs are just feed forward neural networks trained on supercomputer clusters. We really don’t even know what they are capable of fully because it is so hard to quantify, especially when you don’t really know what exactly has been learned.
Q-learning in language is also an interesting methodology I’ve been playing with. With an imagine generator for example though, you can just add (Q-learning quality) and you may get more interesting and quality results. Which itself is very interesting to me.