👉 Expect computing is a paradigm shift in artificial intelligence that moves beyond traditional probabilistic models like Bayesian networks and Markov chains to predict the most likely future states of a system. Instead of focusing solely on past data and conditional probabilities, expect computing leverages deep neural networks to model complex, sequential data and generate predictions by learning the joint distribution of future states. This approach excels at handling high-dimensional, dynamic systems—such as video, audio, or time-series data—by directly learning the probability distribution of future observations, enabling more accurate and context-aware predictions. It bridges the gap between symbolic reasoning and statistical learning, making it particularly powerful for tasks requiring real-time decision-making or modeling intricate temporal dependencies.
