Presented by iMerit.
In AI development, success or failure lies significantly in a data science team’s ability to handle edge cases, or those rare occurrences in how an ML model reacts to data that cause inconsistencies and interrupt the usability of an AI tool. This is especially crucial now as generative AI, now newly-democratized, takes center stage. Along with increased awareness comes new AI strategy demands from business leaders who now see it as both a competitive advantage and as a game changer.
