Explain CNN, Genetic Algorithms, and Backpropagation

Question: Explain Convolutional Neural Networks (CNN), Genetic Algorithms, and Backpropagation. Key points: CNN uses convolutional filters over input grids to extract spatial features, pooling for downsampling, and dense layers for final prediction. Genetic algorithms are population-based optimization methods inspired by natural selection - candidate solutions are scored by fitness, then combined/mutated across generations to search a solution space. Backpropagation computes gradients of the loss with respect to each network weight via the chain rule, propagating error signal backward from output to input layers so weights can be updated via gradient descent. Interviewers expected exact formulas, not just conceptual explanations.