{
  "id": 1501498,
  "title": "Machine learning of artistic fingerprints in jazz",
  "url": "https://urgent.news/2026/08/17/machine-learning-of-artistic-fingerprints-in-jazz",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-17T00:00:00.000Z",
  "source": {
    "name": "Nature Machine Intelligence",
    "slug": "nature-machine-intelligence",
    "url": "https://www.nature.com/articles/s42256-026-01279-9"
  },
  "original_language": "en",
  "account": null,
  "summary": "Nature Machine Intelligence, Published online: 17 August 2026; doi:10.1038/s42256-026-01279-9 Cheston et al. develop a machine learning pipeline that identifies 20 iconic jazz pianists from audio recordings with up to 94% accuracy, revealing how melody, harmony, rhythm and dynamics shape each performer’s individual musical fingerprint.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}