Too Long; Didn't Read
AI and ML applications are becoming increasingly pivotal for businesses to stay ahead of their competition. While AI holds a lot of potential, the technology is still nascent and prone to error. ML algorithms rely on historical data being fed to them, so they can learn and get better and better at predicting future data patterns. Synthetic data helps companies overcome this hurdle by helping them feed their ML algorithms with relevant, simulated data. The ability to generate random scenarios is critical when testing AI effectiveness is critical for testing it.