Big data has been a growing obsession in science, government, and business for over a decade now. Global networks, billions of mobile devices, and a new “internet of things” have produced unprecedented amounts of data that humans alone could never hope to analyze or understand. Artificial intelligence, which enables computers to analyze and make use of this data, has exploded as a result.
The subfield of artificial intelligence research known as “machine learning” has been a key enabler in the continued growth of behavioral biometrics.
Machines that learn are able to astutely refine or enhance their own capabilities as they perform key tasks or encounter data related to these tasks—just what’s needed for behavioral biometrics technologies to “learn about” user behavior and gradually evolve with it over time.
The advances in machine learning that have occurred over the last decade have thus resulted in a seismic shift in behavioral biometrics—taking it from a largely research-oriented field to a portfolio of market-ready technologies ideal for use in industry.