Explore the critical topic of adversarial attacks on deep learning models in this 23-minute Launchpad video. Delve into the paper "Towards Deep Learning Models Resistant to Adversarial Attacks" and understand the process of generating adversarial attacks, their implications, and underlying causes. Examine the problem definition, attack methodology, and experimental results using various datasets and dimensions. Analyze the effects of network capacity and training data on model vulnerability. Compare accuracy across different training methods and sources. Gain valuable insights into developing more robust deep learning models that can withstand adversarial attacks.