The size of the training data for evolution is immense, even if the number of parameters is not nearly so large. However, those parameters are not equivalent to ML parameters. They’re a mix of software architecture, hardware design, hyperparameters, and probably also some initial patterns of parameters as well. It doesn’t mean that you can get the same results for much less data by training some fixed design.
The size of the training data for evolution is immense, even if the number of parameters is not nearly so large. However, those parameters are not equivalent to ML parameters. They’re a mix of software architecture, hardware design, hyperparameters, and probably also some initial patterns of parameters as well. It doesn’t mean that you can get the same results for much less data by training some fixed design.