Speaking of Beats In Space, this is a trove of mix history that I need to dive into:
Beats In Space is a radio show that started in 1999 on WNYU 89.1FM in New York City and is now broadcasting every week on Apple Music.
Beats In Space is brought to you by New York DJ Tim Sweeney.
Not only does Sweeney have a guest mix, often he also does a mix, and an interview with the guest dj:
I’m excited to share that all Beats In Space interviews are now available for FREE on Apple Podcasts! Whether you’re a long-time listener or just discovering the show, you can now dive into in-depth conversations with some of the most influential DJs and producers in electronic music—no paywall, just pure music talk. Subscribe and leave us a comment!
Great backgrounder at the fifteen year mark on Sweeney and the show. Now currently at twenty five plus years and counting 😮, with a only a single hiatus!
Previously I have spoken about the notion of a retrocast for spoken word podcasts, but the same could be done for music podcasts / mix series, tracing their evolution over time. I chatted up Gemini about this during some background research on Carlita and asked “Are there any such tools that look at longitudinal track trends, DJ relations and history, and/or track genealogy”. There’s a whole bunch more to the thread but this kicks off a lot of intellectual provocation.
You’re asking about a fascinating and cutting-edge area of AI in music, moving beyond simple track identification to deeper, more interconnected analysis. While the precise, all-in-one tools for “longitudinal track trends, DJ relations and history, and/or track genealogy” aren’t yet widely available as off-the-shelf consumer products, the underlying AI and research are certainly advancing in these directions.
Mixes, episodes, data integration and AI 🤔. Feels like a great rabbit hole to get stuck into.