David Scott, CEO & Founder at Synetic, makes the case for synthetic training data as the most practical solution to edge case coverage in computer vision at the 2025 Embedded Vision Summit. Real-world data collection is slow, expensive, and structurally unable to capture the rare but critical scenarios — adverse lighting, unusual occlusions, extreme environments — that determine whether a model succeeds in production.
David demonstrates how Synetic’s synthetic data platform generates photorealistic, fully annotated training examples at scale, targeting exactly the distribution gaps that cause models to fail. The result: more robust models, faster, without the cost or safety risk of capturing dangerous edge cases in the field.
