RJ-AI: A Radio Jockey Agent developed using Markov Models and Personality Fine-tuning

This paper investigates the potential of Probabilistic Models combined with Generative Artificial Intelligence (GenAI) in mass media and entertainment, with a specific focus on its application in radio broadcasting. We present a methodology that applies Markov models to develop an Agentic framework capable of generating engaging radio show segments. The proposed system aims to produce engaging audio commentary, recommend and play relevant music, and integrate demographically contextual daily news and weather updates, ensuring both content coherence and the organic structure of the generated programme.