Uncertainty in AI refers to the unpredictability or lack of full knowledge about a situation or outcome. AI models often encounter uncertainties due to incomplete or noisy data. Techniques such as Bayesian Inference and Probabilistic Graphical Models are used to quantify and manage uncertainty in AI.
Adversarial machine learning involves studying and defending AI models against attacks or adversarial examples designed to deceive the system. By understanding vulnerabilities and deploying…