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Advancements in AI and Music Analysis
This chapter explores the introduction of Lark, a foundational model for music analysis that utilizes audio and language inputs for insightful outputs such as tempo and emotion. It also discusses the partnership between a prominent audio platform and the University of Washington, and dives into recent advancements in AI models for time series predictions and the challenges of reasoning in large language models. The implications of Reinforcement Learning from Human Feedback (RLHF) on model performance and diversity are highlighted, underscoring the significance of ongoing collaboration between academia and industry.