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For this purpose, abstract synthetic data refers to data generated by an algorithm that can be stored in less than 100MB, such as an algorithm that randomly generates programs and runs them.
- Neural network models can learn the same task through different methods:
- Pre-training: 10^7-10^8 samples
- Fine-tuning: 500-50000 samples
- Few-shot learning: 5-10 samples
- Initially, most models were directly pre-trained on the required task, such as digit classification.