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

In the new paper Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?, a research team from Google and DeepMind posits that understanding the connections between neural network architectures and scaling laws is essential for designing and evaluating new models. The team pretrains and finetunes over 100 models to reveal useful insights on the scaling behaviours of ten diverse model architectures.

ai artificial intelligence deepmind deep-neural-networks google interactions laws machine learning machine learning & data science ml network neural network research scaling scaling law study technology