Many AI startups that received substantial funding from ambitious venture capital firms in response to the significant hype around generative AI, a French startup specializing in algorithm compression and AI-backed image analysis, as well as Canadian machine vision and smart manufacturing company DarwinAI. Leveraging DarwinAI’s latest deep learning tool for visual inspection is particularly compelling given the current generative AI ecosystem.
Synthetic data could help in cases where collecting real-world data is either difficult due to its rarity or cost. Bank fraud, for example,a relatively rare event in the real world, meaning that collecting sufficient data points to train AI systems to flag fraudulent transactions is difficult without recourse to synthetic data.
Another obvious concern is the possibility of synthetic data eventually becoming a closed system. Concretely, this would mean that the systems would be trained on not only potentially biased but also repetitive datasets that would in turn produce a restricted set of predictions.