This chapter explores contemporary trends in the application of machine learning technologies in music composition and performance contexts. It argues that there is a resurgence of cybernetic approaches to music-making in response to the rapid proliferation of machine learning technologies for artificial media production in recent years. These approaches are contextualised with reference to a history of interactions between cybernetic thought and musical practices, as well as a recent rethinking of cybernetics represented in the work of Yuk Hui and N. Katherine Hayles. It considers the problem of AI slop generators designed and pushed by hegemonic tech giants, paying specific attention to the unethical and irresponsible practices used in their production as well as the algorithmic monoculture perpetuated in their outputs. The chapter then turns to key musical artists at the forefront of the cybernetic resurgence who are engaged in an ethical reappropriation of machine learning techniques away from the big tech giants, before concluding with some suggestions for how an ethically grounded cybernetics of musical machine learning might open a new space of artistic possibility beyond the algorithmic monoculture of AI slop.