CS50's Fundamentals of AI - Lecture 0 - Playing (live, unedited)

This podcast introduces CS50's Fundamentals of Artificial Intelligence course, differentiating it from the existing Python-based CS50 AI course by focusing on the principles behind AI rather than programming. The initial lecture explores AI's application in playing games, starting with tic-tac-toe to illustrate basic AI strategies. The discussion moves to the Minimax algorithm, which helps computers determine optimal moves by assigning numerical values to game outcomes. Chess is used as an example to highlight the computational challenges due to its vast possibilities, leading to more efficient strategies like alpha-beta pruning and depth-limited minimax with evaluation functions. The lecture concludes with reinforcement learning, using the game Snake to demonstrate how AI can learn through rewards and punishments, emphasizing the importance of aligning AI goals with desired outcomes.