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Welch Labs explores the technical breakthrough of residual networks and how skip connections solved the shattered gradient problem in deep learning. This architectural innovation transformed neural networks, enabling unprecedented depth and shifting the fundamental understanding of how these models store and refine information during the learning process. Follow along using the transcript. Welch Labs explores the technical breakthrough of residual networks and how skip connections solved the shattered gradient problem in deep learning. This architectural innovation transformed neural networks, enabling unprecedented depth and shifting the fundamental understanding of how these models store and refine information during the learning process. Follow along using the transcript.