AI is increasingly prevalent in our daily lives, and this trend is unlikely to change anytime soon. This comes with risks, but by understanding these risks, we can build AI systems that mitigate them.
Data scarcity, privacy and bias are just a few reasons why synthetic data is becoming increasingly important. In this Q&A, Brett Wujek, Senior Manager of Product Strategy at SAS, explains why synthetic data will redefine data management and speed up the production of AI and machine learning models while cutting
Investment in AI is an obvious target for the insurance sector. Insurers have always been interested in technology that helps detect and prevent fraud and improve underwriting efficiency while speeding processes and reducing – or at least not increasing – costs. But what is the reality in this highly regulated
