The reason AI appears to “understand” lies in its ability to apply what it has learned to new situations—this is known as “generalization.” This skill is key to enhancing AI’s adaptability and usefulness across different contexts.
Reinforcement learning in AI is a mechanism through which optimal actions are learned by trial and error. It resembles the way humans grow through experience, gradually improving by trying different approaches and learning from the outcomes.
Swisscom’s AI-powered Network Assistant simplifies network management for engineers, enhancing efficiency and decision-making while ensuring data security.
