  Hot streaks dominate the main impact of creative careers. Despite their
ubiquitous nature across a wide range of creative domains, it remains unclear
if there is any regularity underlying the beginning of hot streaks. Here, we
develop computational methods using deep learning and network science and apply
them to novel, large-scale datasets tracing the career outputs of artists, film
directors, and scientists, allowing us to build high-dimensional
representations of the artworks, films, and scientific publications they
produce. By examining individuals' career trajectories within the underlying
creative space, we find that across all three domains, individuals tend to
explore diverse styles or topics before their hot streak, but become notably
more focused in what they work on after the hot streak begins. Crucially, we
find that hot streaks are associated with neither exploration nor exploitation
behavior in isolation, but a particular sequence of exploration followed by
exploitation, where the transition from exploration to exploitation closely
traces the onset of a hot streak. Overall, these results unveil among the first
identifiable regularity underlying the onset of hot streaks, which appears
universal across diverse creative domains, suggesting that a sequential view of
creative strategies that balances experimentation and implementation may be
particularly powerful for producing long-lasting contributions, which may have
broad implications for identifying and nurturing creative talents.
