Can AI generate plausible synthetic training data for ml models ?
Cast your vote — then read what our editor and the AI models found.
The snake-eating-its-tail phase of ML — most foundation models now train partly on synthetic data generated by their predecessors.
AI can generate plausible synthetic training data for ML models, which is useful when real data is scarce or difficult to obtain. This is often achieved through techniques such as generative adversarial networks (GANs) and variational autoencoders (VAEs), which can produce synthetic data that mimics the characteristics of real data. The quality of the generated data is improving, with some models able to produce highly realistic synthetic images, videos, and text. However, generating synthetic data that is both realistic and diverse remains a challenging task.
— Enriched May 9, 2026 · Source: IEEE — https://ieeexplore.ieee.org
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