Why Deep Neural Networks Don't Break (Residual Connections Explained)

Why Deep Neural Networks Don't Break (Residual Connections Explained) Why can AI models stack 96+ layers without losing information? The answer isn't complex math — it's a simple shortcut called a residual connection. In this video, we break down what residual connections are, why Transformers need them, and how one basic addition operation solves the vanishing gradient problem and makes today's massive AI models possible. #ResidualConnections #DeepLearning #TransformerArchitecture #MachineLearning #NeuralNetworks #AIExplained #LLM #ArtificialIntelligence #DataScience #DeepLearningExplained