Unlocking the Secrets of Deep Learning: The Residual Pathway Explained

Andrej Karpathy says the transformer's residual connections allow gradients to flow smoothly, making optimization efficient. This design lets the transformer layers act like sequential lines of code, where each layer gradually learns and contributes to the overall function, enabling the model to develop effective algorithms. #DeepLearning #GradientFlow #ResidualPathwayExplained #NeuralNetworks #OptimizationTechniques #PythonCoding #TransformerModel #ArtificialIntelligence #MachineLearning #DeepNeuralNetworks