A Markov Chain is a mathematical model that describes a sequence of events where the probability of each future event depends only on the current state, not on the history of how you got there. This "memoryless" property means that to predict what happens next, you only need to know where you are now, not the entire path you took. Common examples include predicting weather patterns (today's weather influences tomorrow's, but not last week's), autocomplete suggestions, board game movements, and modeling customer behavior in marketing.
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As AI technologies rapidly evolve, Professor Kochenderfer leads the charge in developing effective validation mechanisms to ensure safety in autonomous systems like vehicles and drones.
As AI technologies rapidly evolve, Professor Kochenderfer leads the charge in developing effective validation mechanisms to ensure safety in autonomous systems like vehicles and drones.
