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Google & DeepMind Study the Interactions Between Scaling Laws and Neural Network Architectures

State-of-the-art AI models have ballooned to billions of parameters in recent years. Although the machine learning (ML) community has shown keen interest in the scaling properties of transformer-based models, there has been relatively little research on scaling effects with regard to the inductive biases imposed by different model…

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