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#163 - Llama 3, Grok-1.5 Vision, new Atlas robot, RHO-1, Medium ban
Last Week in AI
Optimizing Model Training with Compute Power and Data Size
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Scaling laws dictate the relationship between processing power, data set size, and model size for optimal model training. Google Deepline introduced the concept that training with more data is crucial for optimal model performance. Compute optimal models are trained based on the available compute budget, determining the data size and model size. Over-training models beyond compute optimality can enhance performance, especially with smaller models. Increasing model size allows for better utilization of additional computing power.
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