Introduction to Neural Networks

Neural Networks Fundamentals

Understanding neural networks is essential for modern AI safety research.

Basic Architecture

• Neurons and activation functions
• Layers and network topology
• Forward and backward propagation
• Weight initialization and training dynamics

Common Architectures

• Feedforward networks (MLPs)
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Introduction to Transformers

Safety Considerations

• Opacity and interpretability challenges
• Vulnerability to adversarial examples
• Unpredictable failure modes
• Importance of safety-aware training