Datagen emerges from stealth to create synthetic datasets for computer vision models

Datagen, a Tel Aviv, Israel-based startup offering a platform to create synthetic computer vision system training data, today emerged from stealth with $18.5 million in funding from TLV Partners and Viola Ventures. The company says the proceeds will be put toward growing its R&D lab while it expands into new markets globally. Datagen, which Ofir Chakon and Gil Elbaz founded in 2018, leverages computer graphics and data generation to simulate the real world with datasets that include 2D and 3D annotations. By combining generative adversarial networks (GANs) with reinforcement learning-driven humanoid motion algorithms within a physical simulator, Datagen says it can deliver photorealistic, scalable datasets suitable for augmented and virtual reality, internet of things, smart store, robotics, and smart car use cases. GANs are two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples.