turn down the randomness to get more consistent outputs for simple tasks.
This is a tricky one… if you can define good success/failure criteria, then the randomness coupled with an accurate measure of success, is how “AI” like Alpha Go learns to win games, really really well.
In using AI to build computer programs and systems, if you have good tests for what “success” looks like, you’d rather have a fair amount of randomness in the algorithms trying to make things work because when they don’t and they fail, they end up stuck, out of ideas.
floquant@lemmy.dbzer0.com 4 hours ago
You’re both right imo. LLMs and every subsequent improvement are fundamentally ruined by marketing heads like oh so many things in the history of computing, so even if agentic AI is actually an improvement, it doesn’t matter because everyone is using it to do stupid fucking things.
Auth@lemmy.world 3 hours ago
Yeah like stringing 5 chatgpt’s together saying “you are scientist you are product lead engineer etc” is dumb but stringing together chatgpt into a coded tool into a vision model into a specific small time LLM is an interesting new way to build workflows for complex and dynamic tasks.