Neural Networks

Neat things about neural networks:

• Interesting model of parallel computation unlike orthodox parallel computation
• Degrade gracefully under extreme conditions
• Potential for combining brain-like parallelism with silicon switching speeds

What's important for our purposes is that neural networks:

• Can be viewed as incremental function approximators
• Can be trained using supervised learning via gradient descent