The Andromeda network being LALAL's sixth-generation AI engine is the architecture claim worth understanding
Trained on years of data for human-like voice replication is the training foundation claim. Unmatched precision in vocal nuances, diction subtleties and tonal qualities is the quality output claim. Real-time processing is the performance claim. These three together define the Andromeda proposition: better quality and faster than previous generations.
The practical test of any vocal separation engine is on the specific types of audio that your workflow produces. Studio recordings with clean separation between tracks respond well to most modern engines. Live recordings with bleed between microphones, heavily processed vocals sitting close to instrumental frequencies, and complex arrangements with many simultaneous elements are where the generation improvements matter and where you can actually perceive the quality difference.
The human-like voice replication specifically being emphasised for the Andromeda engine tells you the primary improvement is on the vocal side rather than across all stem types. That means the quality gains are most pronounced on the use cases that depend on clean vocal isolation: remixing, stem creation for live performance, voiceover extraction and the like.
On what specific type of audio have you noticed the most meaningful quality improvement between LALAL.AI versions?