The video tutorial explains the concept of predicted and actual values in a model, highlighting the importance of minimizing the error or cost function for accuracy. It introduces backpropagation as a key algorithm for adjusting weights in neural networks to enhance output accuracy. The tutorial concludes with a brief transition to the next lecture.

Why is it important to reduce error in a model for accurate predictions?

What role does backpropagation play in artificial intelligence?