AI Insights
Can we measure the impact of club culture influences on the record? We ask: “Is Renaissance more Chicago house or Dangerously In Love”?
Barack Obama has dropped his annual playlist and it’s a corker. But what insights can we draw with AI and how can that help with personalisation?
Metallica’s 2022 success has more in common with Kenny Loggins than any other metal act.
On a sonic level, what makes a memorable performance? We analysed some must-watch Glasto performances with AI to find out.
We’ve selected some of our favourite performances from Glastonbury and run them through our tagging AI. What can we tell about each performance based on the data?
Harry’s House, the number-one album from Harry Styles, is full of throwback influences from Prince to noughties indie, but it might be more heavily influenced by Japanese prog musician Haruomi Hosono than anyone suspected.
Kate Bush’s song has soared to fame due to its pivotal role in Netflix’s Stranger Things, but what can we learn about its success on the Billboard chart and TikTok?
What can we tell about the original score with our tagging AI? How does this correlate to the on-screen action, and what predictions can we make about the fourth season’s music?
By combining nostalgia for British rock music and respect for the Eurovision sound, Sam Ryder broke the UK’s losing streak. We dig into the data to see how his success might be replicated.
What can we learn about the 2022 Grammys through the lens of AI? And how could the tech help in future?