![]() In addition to bootstrapping the model training, researchers can quickly generate new datasets by varying many different parameters such as location, color, object size, or lighting conditions to generate diverse data that can aid in the creation of a generalized model. Synthetic data offers an alternative to real-world data, enabling AI researchers and engineers to bootstrap AI model training. ![]() Also, the data collected may not be able to cover various corner cases, preventing the AI model from accurately predicting a wide variety of scenarios. Acquiring large sets of training data can be difficult, time-consuming, and expensive. Training AI models requires mountains of data. ![]()
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