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Developers typically use the 10x rule to determine an ideal size for the training dataset to train an AI/ML model. This means that if your model has 10 features/parameters, you’d require at least 100 data points to train effectively. You can only imagine extending this rule to models with billions or trillions of parameters, such as OpenAI’s GPT-4; the world-famous AI model rumored to be trained on 1.76 trillions of…