Artificial intelligence has made real contributions to aging research, but the field often collapses distinct layers of progress into one exaggerated timeline.
The useful separation is between discovery compression and therapeutic closure. AI can improve target ranking, structural reasoning, chemistry generation, and signal triage without solving indication design, endpoint validity, or human translational uncertainty.
This cluster assembles the articles that keep those layers distinct. They examine digital twins, age clocks, and AI-designed drugs as real tools with bounded value rather than as substitutes for downstream biological proof.
That approach matters for readers because almost every major AI-longevity claim becomes more credible when narrowed. The technology is most useful when it sharpens decisions inside a stack that still depends on measurement quality, mechanism, and clinical validation.
