EETimes - What Is Synthetic Data and Why Is It Critical for the Future of AI?

Advanced AI development today is still deeply rooted in 1950s computer science philosophies, including the phrase "garbage in, garbage out." The adage reminds us that an AI model is only as good as the data it's trained on. For everything from advanced cancer screenings to suggesting a new movie, data scientists need large and diverse datasets to train AI models. This can be a significant challenge with real-world data. Often protected for privacy reasons, authentic data can be hard to come by and can also be expensive to source, and potentially not as diverse as desired.