> Nevertheless, good human output always add something new and original to the elements that are derived from prior art. My personal opinion is that even the n

> Nevertheless, good human output always add something new and original to the elements that are derived from prior art. My personal opinion is that even the new and original elements are derivative. Once a creation derives from a sufficiently large number of sources - some unrelated, such as being inspired by music when painting - you consider it original and new, and once the space of experiences and current inputs you derive from grow sufficiently large and chaotic - including in particular that inputs and outputs become experiences, forming a feedback loop currently lacking in machine learning - you get what we consider "free thought" . That's at least the model I believe in. > Without an ability to select like a human, which from the possible random combinations is more suitable to achieve a purpose, or ... Untrained humans do not have this ability. It takes training to identify and categorize things. For example, my mother may appreciate a photo that most people would consider "good", but does not have the practice needed to either frame the scene herself or select the best framing to be deemed "good". At the same time, others might outright dislike the same picture - "good" is not exact in the first place. I see no reason to believe that our models could do this as well or better than us. If an LLM generates reasonable responses, it must already have applied a standard of "best fitting". It is just not a distinct step, just like how we are not manually filtering our thoughts as we say them.