CS50's Fundamentals of AI - Lecture 1 - Predicting (live, unedited)

This podcast introduces the fundamentals of AI, distinguishing itself from CS50's existing AI course by targeting beginners without prior programming experience. The discussion centers on using machine learning for predictions, transitioning AI from game environments to real-world applications like plant growth. A core concept explored is the "loss function," which evaluates the accuracy of AI predictions, particularly within regression problems aimed at predicting numerical values. The podcast further discusses classification problems, such as predicting rainfall, using algorithms like nearest neighbor and k-nearest neighbor classification. Neural networks, inspired by the human brain, are introduced as versatile tools for classification, with a focus on perceptrons and their application to datasets like the iris dataset, demonstrating how neural networks learn through adjusting weights and biases.