👉 Uncertainty computing is a branch of artificial intelligence that focuses on quantifying and managing the uncertainty inherent in predictions and decisions. Unlike traditional computing, which often provides deterministic outputs, uncertainty computing acknowledges that many real-world systems are inherently probabilistic and unpredictable. It involves techniques to estimate the confidence or reliability of a model's predictions, often through probabilistic models or Bayesian methods. This approach helps decision-makers understand the range of possible outcomes and their likelihoods, enabling more robust and informed decisions in the face of uncertainty. By explicitly modeling uncertainty, uncertainty computing enhances the transparency and trustworthiness of AI systems, particularly in critical applications like healthcare, finance, and autonomous systems.
