Synthetic data training from real data.
When It Comes to AI, Can We Ditch the Datasets?
MIT News, Adam Zewe, March 15, 2022
Massachusetts Institute of Technology (MIT) researchers have demonstrated the use of a generative machine-learning model to produce synthetic data, based on real data, to train another model for image classification. Researchers showed the generative model millions of images containing objects in a specific class, after which it learned those objects' appearance in order to generate similar objects. MIT's Ali Jahanian said generative models also learn how to transform underlying training data, and connecting a pretrained generative model to a contrastive learning model enabled both models to work together automatically. The results show that a contrastive representation learning model trained only on synthetic data can learn visual representations that rival or top those learned from real data. In analyzing how the number of samples influenced the model's performance, researchers determined that, in some cases, generating larger numbers of unique samples facilitated additional enhancements. ... '
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