what is inference in ai

Inference in AI refers to the process of reasoning and making decisions based on available information or data. It is a crucial process in artificial intelligence that involves deriving new knowledge or conclusions from existing knowledge or data. In machine learning, there are two phases: training and inference. During the training phase, a machine is fed with data to develop intelligence by recording, storing, and labeling information. In the inference phase, the machine uses the intelligence gathered and stored in the training phase to understand new data. In this phase, the machine can use inference to identify and categorize new data despite having never seen it before. Inference is the essential component of artificial intelligence, and without it, a machine would not have the ability to learn. Inference is used in many AI applications, including natural language processing, computer vision, robotics, and expert systems. Inference rules are applied to derive proofs in artificial intelligence, and the proof is a sequence of the conclusion that leads to the desired goal. The demand for sophisticated AI-enabled services like image and speech recognition, and natural language processing has increased significantly in recent years, making AI inference increasingly important.